#semantic fields n that

[torotits]

tell me something interesting about your day

umm i got a poetry essay back and i got 29/30 bc im the smartest boy in the whole wide world!!!!! my teacher was like there’s some really great ideas here and i was like ‼️‼️ i know i thought them in my brain ‼️

[goodmode]

scholarly bug digifake! pulling together several of my favourite themes and tropes to hopefully settle on a digimon partner after all these years :^) info + name origins below the cut!

LARMON

Level: In-Training/Baby II | Attribute: Vaccine | Field: Virus Busters | Type: Larva

A Larva Digimon that hides in its cloth-like outer garment, using its long antennae to listen to the world around it. This Digimon's movement is limited, so it hitches rides by quietly attaching itself to the backs of larger creatures, which can cause an ominous feeling to come over the host as they mistake it for a haunting. This effect seems completely accidental, however, as Larmon themselves tend to be quite sweet-natured and encouraging if they can overcome their shy nature. Overwhelming situations can cause them to give a nasty bite.

Attacks

Phantom Nip - Gives a nasty pinch from its small mandibles.

Night Light - Produces a soft golden glow from its marking and tail that gently repels those of violent spirit.

Namesake

larva(n.) - 1630s, "a ghost, specter, disembodied spirit" (earlier as larve, c. 1600), from Latin larva (plural larvae), earlier larua "ghost, evil spirit, demon," also "mask," a word from Roman mythology, of unknown origin; de Vaan finds a possible derivation from Lar "tutelary god" (see Lares) "quite attractive semantically." Crowded out in its original sense by the zoological use (1768) which began with Linnaeus, who applied the word to immature forms of animals that do not resemble, and thus "mask," the adult forms. [source]

Lares(n.) - Roman tutelary gods and household deities, worshipped in primitive cult rites, Latin, plural of Lar, a word of unknown origin. Infernal, protective of the state and the family, they could be potently evil if offended. Their shrine in the home was a lararium. [source]

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PUERMON

Level: Rookie/Child | Attribute: Vaccine | Field: Virus Busters | Type: Insect

An Insect Digimon with the self-imposed task of infiltrating Virus type groups and strongholds, and using its unique undercover position to learn everything it can, training itself to be able to restore peace and defend the just. In this way, Puermon is sometimes considered a "pest" infesting the networks of Virus Digimon. Highly industrious, Puermon takes its work very seriously, and can lose its temper with anyone who interferes or risks blowing its cover. Its crystalline sceptre is made of all the data Puermon has absorbed, its helix shape slowly building towards Evolution.

Attacks

Lucidate - Holds its staff high, casting a bright golden light that makes evil Digimon lose their fighting spirit and want to move away, and gives focus and sharpness of mind to those with good intentions. The light from this staff can also help make sense of such things as computer code and Digimoji. Puermon may also call out the name of this attack before simply giving someone a punishing bop on the head.

Namesake

pupil(n.1) [student], late 14c., "orphan child, ward, person under the care of a guardian," from Old French pupille (14c.) and directly from Latin pupillus (fem. pupilla) "orphan child, ward, minor," diminutive of pupus "boy" (fem. pupa "girl"), probably related to puer "child" (and thus probably from a suffixed form of PIE root *pau- (1) "few, little"). Meaning "disciple, student youth or any person of either sex under the care of an instructor or tutor" is recorded by 1560s. [source]

puerile(adj.) 1660s, "youthful, boyish," a back-formation from puerility (q.v.), or else from French puéril (15c.), from Latin puerilis "boyish; childish," from puer "boy, child." The depreciative sense of "merely juvenile, immature, lacking intellectual force" is from 1680s. [source]

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AXLAMON

Level: Champion/Adult | Attribute: Vaccine | Field: Virus Busters/Wind Guardians | Type: Insect

An advanced Insect Digimon that has picked up some high-level programming language. Though lacking the formal training of Witchelny, it reached this level of sorcery through necessity and instinct. Because of this, its reflexes and quick thinking put it almost equivalent with the likes of its Witchelny peers, and it spun itself a similar outfit to lend itself credibility as a sorcerer and to hide its true face beneath its cloak.

Its staff has hardened into the shape of an insect's horns, the light of its gathered knowledge kept between them and giving it strength. This staff can be ridden like a broomstick, letting Axlamon hide its new wings inside the sleeves of its cloak.

Despite its outwardly solitary and ascetic temperament, it appears this is simply a mask over the same shyness it had as a Child-level Digimon, and its secretly-passionate heart can be counted on to uplift others and balance the odds at any cost when things look grim.

Attacks

Kindle - Raises its staff to shine a brilliant light. Allies find their best strengths amplified and their wounds healed, and blackhearted foes are weakened and driven back from the holy beacon. This attack can also make sense of computer code, Digimoji, and sometimes things spoken or written in code.

Sacrosanctuary - Stands its ground and casts an illuminated shield of immutable truths and promises around itself and its allies. Its commitment is equal to the strength of its shield.

Opine Flare - Burns off some of its absorbed information data, converting it to a missile of pure energy to strike with. Some data is lost in the conversion, making direct attacks costly.

Namesake

In entomology, "alate" usually refers to the winged form of a social insect, especially ants[2] [source]

alate(adj.) "having wings, winged," 1660s, from Latin alatus, from ala "wing, armpit, wing of an army," from *axla, originally "joint of the wing or arm;" from PIE *aks- "axis" (see axis). [source]

axis (plural axes or (rare) axiis) - (geometry) An imaginary line around which an object spins (an axis of rotation) or is symmetrically arranged (an axis of symmetry). / The centre of attention within a process (e.g. the axis of investigation). [source]

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uhhh if you read this far thank you for the interest! maybe someday i'll do their Perfect/Ultimate form or beyond but for now i ran out of steam so this lil guy's future is mysterious...

please don't use this fakie without permission, but if you do wanna borrow him for a roleplay or something please don't be shy of asking at least, i'm pretty chill

[dumber-alek]

Polish words English desperately needs (or that may exist I just can't think of a close equivalent idk):

- ogarniętość (n) : a trait that is a combination of common sense, street-smarts, and the ability to kinda... Deal with whatever task is thrown at you. It's usually a kind of inherent trait, but you can be ogarnięty in some areas, but not others (work, social life, personal life, etc.) If you're a sensible person who is able to identify a problem, think about what you need to do next, and do it, then congrats! You can call yourself ogarnięty. The closest equivalent I could think of is 'someone who has their shit together' but aside from it being a bit of a mouthful, it doesn't quite communicate the same thing (as it's more general and associated less with being smart than 'ogarnietosc').

- kombinować (v) : it can literally mean to fiddle with something in a more physical sense, but as an abstract concept it could be translated to many different things : to be up to something, to scheme, to work something out, or to lie. Generally, to try to find a way to solve an issue, through either non-straightforward or dishonest means. I think the uniqueness of this term comes from its' ambiguity and versatility : it can mean you're going to try really hard to figure a way out of a situation, it can also mean you try to get out of a situation by lying, cheating, or taking advantage of someone or something.

cwaniak (n) : kind of connected to kombinować, as a cwaniak is often a person that kombinuje. Some suggestions of translations I found are dodger and con man which I guess could be close, but they only capture a narrow part of the semantic field that the word cwaniak describes. It's the type of person that's is a combination of dishonest, untrustworthy, sly, and trying to find the best ways to benefit themselves, usually at the cost of others, and with a mocking attitude towards the notion of fairness. All that while they dodge personal or social responsibility - I would rather call them shifty, cause a con man or a swindler implies a particular operation or a goal someone is trying to achieve. A cwaniak, however, is a way of life.

[najia-cooks]

[ID: The first image is of four stuffed artichoke hearts on a plate with a mound of rice and fried vermicelli; the second is a close-up on one artichoke, showing fried ground 'beef' and golden pine nuts. End ID]

أرضي شوكي باللحم / Ardiyy-shawkiyy b-al-lahm (Stuffed artichoke hearts)

Artichoke hearts stuffed with spiced meat make a common dish throughout West Asia and North Africa, with variations on the recipe eaten in Lebanon, Syria, Palestine, Algeria, and Morocco. In Palestine, the dish is usually served on special occasions, either as an appetizer, or as a main course alongside rice. The artichokes are sometimes paired with cored potatoes, which are stuffed and cooked in the same manner. Stuffed artichokes do not appear in Medieval Arab cookbooks (though artichokes do), but the dish's distribution indicates that its origin may be Ottoman-era, as many other maḥshis (stuffed dishes) are.⁩

The creation of this dish is easy enough once the artichoke hearts have been excavated (or, as the case may be, purchased frozen and thawed): they are briefly deep-fried, stuffed with ground meat and perhaps pine nuts, then stewed in water, or water and tomato purée, or stock, until incredibly tender.

While simple, the dish is flavorful and well-rounded. A squeeze of lemon complements the bright, subtle earthiness of the artichoke and cuts through the richness of the meat; the fried pine nuts provide a play of textures, and pick up on the slight nutty taste that artichokes are known for.

Terminology and etymology

Artichokes prepared in this way may be called "ardiyy-shawkiyy b-al-lahm." "Ardiyy-shawkiyy" of course means "artichoke"; "ب" ("b") means "with"; "ال" ("al") is the determiner "the"; and "لَحْم" ("laḥm") is "meat" (via a process of semantic narrowing from Proto-Semitic *laḥm, "food"). Other Palestinian Arabic names for the same dish include "أرضي شوكي محشي" ("ardiyy-shawkiyy maḥshi," "stuffed artichokes"), and "أرضي شوكي على ادامه" ("ardiyy-shawkiyy 'ala adama," "artichokes cooked in their own juice").

The etymology of the Levantine dialectical phrase meaning "artichoke" is interestingly circular. The English "artichoke" is itself ultimately from Arabic "الخُرْشُوف" ("al-khurshūf"); it was borrowed into Spanish (as "alcarchofa") during the Islamic conquest of the Iberian peninsula, and thence into English via the northern Italian "articiocco." The English form was probably influenced by the word "choke" via a process of phono-semantic matching—a type of borrowing wherein native words are found that sound similar to the foreign word ("phonetics"), and communicate qualities associated with the object ("semantics").

"Artichoke" then returned to Levantine Arabic, undergoing another process of phono-semantic matching to become "ardiyy-shawkiyy": أَرْضِيّ ("ʔarḍiyy") "earthly," from أَرْض‎ ("ʔarḍ"), "Earth, land"; and شَوْكِيّ ("shawkiyy") "prickly," from شَوْك‎ ("shawk"), "thorn."

Artichokes in Palestine

Artichoke is considered to be very healthful by Palestinian cooks, and it is recommended to also consume the water it is boiled in (which becomes delightfully savory and earthy, suitable as a broth for soup). In addition to being stuffed, the hearts may be chopped and cooked with meat or potatoes into a rich soup. These soups are enjoyed especially during Ramadan, when hot soup is popular regardless of the season—but the best season for artichokes in the Levant is definitively spring. Stuffed artichokes are thus often served by Jewish people in North Africa and West Asia during Passover.

Artichokes grow wild in Palestine, sometimes in fields adjacent to cultivated crops such as cereals and olives. Swiss traveler Johann Ludwig Burckhardt, writing in 1822, referred to the abundant wild artichoke plants (presumably Cynara syriaca) near لُوبْيا ("lūbyā"), a large village of stone buildings on a hilly landscape just west of طبريا ("ṭabariyya," Tiberias):

About half an hour to the N. E. [of Kefer Sebt (كفر سبط)] is the spring Ain Dhamy (عين ظامي), in a deep valley, from hence a wide plain extends to the foot of Djebel Tor; in crossing it, we saw on our right, about three quarters of an hour from the road, the village Louby (لوبي), and a little further on, the village Shedjare (شجره). The plain was covered with the wild artichoke, called khob (خُب); it bears a thorny violet coloured flower, in the shape of an artichoke, upon a stem five feet in height.

(Despite resistance from local militia and the Arab Liberation Army, Zionist military groups ethnically cleansed Lubya of its nearly 3,000 Palestinian Arab inhabitants in July of 1948, before reducing its buildings and wells to rubble, The Jewish National Fund later planted the Lavi pine forest over the ruins.)

Artichokes are also cultivated and marketed. Elihu Grant, nearly a century after Burckhardt's writing, noted that Palestinian villages with sufficient irrigation "[went] into gardening extensively," and marketed their goods in crop-poor villages or in city markets:

Squash, pumpkin, cabbage, cauliflower, lettuce, turnip, beet, parsnip, bean, pea, chick-pea, onion, garlic, leek, radish, mallow and eggplant are common varieties [of vegetable]. The buds of the artichoke when boiled make a delicious dish. Potatoes are getting to be quite common now. Most of them are still imported, but probably more and more success will be met in raising a native crop.

Either wild artichokes (C. syriaca) or cardoons (C. cardunculus, later domesticated to yield modern commerical artichokes) were being harvested and eaten by Jewish Palestinians in the 1st to the 3rd centuries AD (the Meshnaic Hebrew is "עַכָּבִיּוֹת", sg. "עַכָּבִית", "'aqubit"; related to the Arabic "⁧عَكُوب⁩" "'akūb," which refers to a different plant). The Tosefta Shebiit discusses how farmers should treat the sprouting of artichokes ("קינרסי," "qinrasi") during the shmita year (when fields are allowed to lie fallow), indicating that Jews were also cultivating artichokes at this time.

Though artichokes were persistently associated with wealth and the feast table (perhaps, Susan Weingarten speculates, because of the time they took to prepare), trimming cardoons and artichokes during festivals, when other work was prohibited, was within the reach of common Jewish people. Those in the "upper echelons of Palestinian Jewish society," on the other hand, had access to artichokes year-round, including (through expensive marvels of preservation and transport) when they were out of season.

Jewish life and cuisine

Claudia Roden writes that stuffed artichoke, which she refers to as "Kharshouf Mahshi" (خرشوف محشي), is "famous as one of the grand old Jerusalem dishes" among Palestinian Jews. According to her, the stuffed artichokes used to be dipped in egg and then bread crumbs and deep-fried. This breading and frying is still referenced, though eschewed, in modern Sephardi recipes.

Prior to the beginning of the first Aliyah (עלייה, wave of immigration) in 1881, an estimated 3% of the overall population of Palestine, or 15,011 people, were Jewish. This Jewish presence was not the result of political Zionist settler-colonialism of the kind facilitated by Britain and Zionist organizations; rather, it consisted of ancestrally Palestinian Jewish groups, and of refugees and religious immigrants who had been naturalized over the preceding decades or centuries.

One such Jewish community were the Arabic-speaking Jews whom the Sephardim later came to call "מוּסְתערבים" or "مستعربين" ("Musta'ravim" or "Musta'ribīn"; from the Arabic "مُسْتَعْرِب⁩" "musta'rib," "Arabized"), because they seemed indifferentiable from their Muslim neighbors. A small number of them were descendants of Jews from Galilee, which had had a significant Jewish population in the mid-1st century BC; others were "מגרבים" ("Maghrebim"), or "مغربية" ("Mughariba"): descendents of Jews from Northwest Africa.

Another major Jewish community in pre-mandate Palestine were Ladino-speaking descendents of Sephardi Jews, who had migrated to Palestine in the decades following their expulsion from Spain and then Portugal in the late 15th century. Though initially seen as foreign by the 'indigenous' Mista'avim, this community became dominant in terms of population and political influence, coming to define themselves as Ottoman subjects and as the representatives of Jews in Palestine.

A third, Yiddish- and German-speaking, Askenazi Jewish population also existed in Palestine, the result of immigration over the preceding centuries (including a large wave in 1700).

These various groups of Jewish Palestinians lived as neighbors in urban centers, differentiating themselves from each other partly by the language they spoke and partly by their dress (though Sephardim and Ashkenazim quickly learned Arabic, and many Askenazim and Muslims learned Ladino). Ashkenazi women also learned from Sephardim how to prepare their dishes. These groups' interfamiliarity with each other's cuisine is further evidenced by the fact that Arabic words for Palestinian dishes entered Ladino and Yiddish (e.g. "كُفْتَة" / "kufta," rissole; "مَزَّة⁩" "mazza," appetizer); and words entered Arabic from Ladino (e.g. "דונסי" "donsi," sweet jams and fruit leather; "בוריק" "burek," meat and cheese pastries; "המים" "hamim," from "haminados," braised eggs) and Yiddish (e.g. "לעקעך‎" "lakach," honey cake).

In addition to these 'native' Jews were another two waves of Ashkenazi migration in the late 18th and early-to-mid 19th centuries (sometimes called the "היישוב הישן," "ha-yishuv ha-yashan," "old settlement," though the term is often used more broadly); and throughout the previous centuries there had also been a steady trickle of religious immigration, including elderly immigrants who wished to die in Jerusalem in order to be present at the appointed place on the day of Resurrection. Recent elderly women immigrants unable to receive help from charitable institutions would rely on the community for support, in exchange helping the young married women of the neighborhood with childcare and with the shaping of pastries ("מיני מאפה").

In the first few centuries AD, the Jewish population of Palestine were largely farmers and agricultural workers in rural areas. By the 16th century, however, most of the Jewish population resided in the Jewish Holy Cities of Jerusalem (القُدس / al-quds), Hebron (الخليل / al-khalil), Safed (صفد), and Tiberias (طبريا / ṭabariyya). In the 19th century, the Jewish population lived entirely in these four cities and in expanding urban centers Jaffa and Haifa, alongside Muslims and Christians. Jerusalem in particular was majority Jewish by 1880.

In the 19th century, Jewish women in Jerusalem, like their Christian and Muslim neighbors, used communal ovens to bake the bread, cakes, matzah, cholent, and challah which they prepared at home. One woman recalls that bread would be sent to the baker on Mondays and Thursdays—but bribes could be offered in exchange for fresh bread on Shabbat. Charges would be by the item, or else a fixed monthly payment.

Trips to the ovens became social events, as women of various ages—while watching the bakers, who might not put a dish in or take it out in time—sent up a "clatter" of talking. During religious feast days, with women busy in the kitchen, some families might send young boys in their stead.

Markets and bakeries in Jerusalem sold bread of different 'grades' based on the proportion of white and wheat flour they contained; as well as flatbread (خبز مفرود / חובז מפרוד / khobbiz mafroud), Moroccan מאווי' / ماوي / meloui, and semolina breads (כומאש / كماج / kmaj) which Maghrebim especially purchased for the Sabbath.

On the Sabbath, those who had brick ovens in their sculleries would keep food, and water for tea and coffee, warm from the day before (since religious law prohibits performing work, including lighting fires, on Shabbat); those who did not would bring their food to the oven of a neighbor who did.

Palestinian Jewish men worked in a variety of professions: they were goldsmiths, writers, doctors, merchants, scientists, linguists, carpenters, and religious scholars. Jewish women, ignoring prohibitions, engaged in business, bringing baked goods and extra dairy to markets in Jerusalem, grinding and selling flour, spinning yarn, and making clothing (usually from materials purchased from Muslims); they were also shopkeepers and sellers of souvenirs and wine. Muslims, Jews, and Christians shared residential courtyards, pastimes, commercial enterprises, and even holidays and other religious practices.

Zionism and Jewish Palestinians

Eastern European Zionists in the 1880s and 90s were ambivalent towards existing Jewish communities in Palestine, often viewing them as overly traditional and religious, backwards-thinking, and lacking initiative. Jewish Palestinians did not seem to conform with the land-based, agricultural, and productivist ideals of political Zionist thinkers; they were integrated into the Palestinian economy (rather than seeking to create their own, segregated one); they were not working to create a Jewish ethnostate in Palestine, and seemed largely uninterested in nationalist concerns. Thus they were identified with Diaspora Jewish culture, which was seen as a remnant of exile and oppression to be eschewed, reformed, or overthrown.

These attitudes were applied especially to Sephardim and Mista'arevim, who were frequently denigrated in early Zionist literature. In 1926, Revisionist Zionist leader Vladimir Jabotinsky wrote that the "Jews, thank God, have nothing in common with the East. We must put an end to any trace of the Oriental spirit in the Jews of Palestine." The governance of Jewish communities was, indeed, changed with the advent of the British Mandate (colonial rule which allowed the British to facilitate political Zionist settling), as European political and "socialist" Zionists promoted Ashkenazi over Sephardi leadership.

Under the Ottomans, the millet system had allowed a degree of Jewish and Christian autonomy in matters of religious study and leadership, cultural and legal affairs, and the minting of currency. The religious authority of all Jewish people in Palestine had been the Sephardi Rabbi of Jerusalem, and his authority on matters of Jewish law (like the authority of the Armenian Patriarchate on matters of Christian law) extended outside of Palestine.

But British and European funding allowed newer waves of Ashkenazi settlers (sometimes called "היישוב החדש," "ha-yishuv ha-khadash," "new settlement")—who, at least if they were to live out the ideals of their sponsors, were more secular and nationalist-minded than the prior waves of Ashkenazi immigration—to be de facto independent of Sephardi governance. Several factors lead to the drying up of halaka (donated funds intended to be used for communal works and the support of the poor in Sephardi communities), which harmed Sephardim economically.

Zionist ideas continued to dominate newly formed committees and programs, and Palestinian and Sephardi Jews reported experiences of racial discrimination, including job discrimination, leading to widespread poverty. The "Hebrew labor" movement, which promoted a boycott of Palestinian labor and produce, in fact marginalized all workers racialized as Arab, and promises of work in Jewish labor unions were divided in favor of Ashkenazim to the detriment of Sephardim and Mizrahim. This economic marginalization coincided with the "social elimination of shared indigenous [Palestinian] life" in the Zionist approach to indigenous Jews and Muslims.

Despite the adversarial, disdainful, and sometimes abusive relationship which the European Zionist movement had with "Oriental" Jews, their presence is frequently used in Zionist food and travel writing to present Israel as a multicultural and pluralist state. Dishes such as stuffed artichokes are claimed as "Israeli"—though they were eaten by Jews in Palestine prior to the existence of the modern state of Israel, and though Sephardi and Mizrahi diets were once the target of a civilizing, correcting mission by Zionist nutritionists. The deep-frying that stuffed artichokes call for brings to mind European Zionists' half-fascinated, half-disgusted attitudes towards falafel. The point is not to claim a dish for any one national or ethnic group—which is, more often than not, an exercise in futility and even absurdity—but to pay attention to how the rhetoric of food writing can obscure political realities and promote the colonizer's version of history. The sinking of Jewish Palestinian life prior to the advent of modern political Zionism, and the corresponding insistence that it was Israel that brought "Jewish cuisine" to Palestine, allow for such false dichotomies as "Jewish-Palestinian relations" or "Jewish-Arab relations"; these descriptors further Zionist rhetoric by making a clear situation of ethnic cleansing and settler-colonialism sound like a complex and delicate issue of inter-ethnic conflict. To boot, the presentation of these communities as having merely paved the way to Zionist nationalism ignores their existence as groups with their own political, social, and cultural lives and histories.

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Ingredients:

Serves 4 (as a main dish).

For the artichokes:

6 fresh, very large artichokes; or frozen (not canned) whole artichoke hearts

1 lemon, quartered (if using fresh artichokes)

250g (1 1/2 cups) vegetarian ground beef substitute; or 3/4 cup TVP hydrated with 3/4 cup vegetarian 'beef' stock from concentrate

1 yellow onion, minced

Scant 1/2 tsp kosher salt

1/2 tsp ground black pepper

1 pinch ground cardamom (optional)

1/4 tsp ground allspice or seb'a baharat (optional)

1 Tbsp pine nuts (optional)

Water, to simmer

Oil, to fry

2 tsp vegetarian 'beef' stock concentrate, to simmer (optional)

Lemon, to serve

Larger artichokes are best, to yield hearts 3-4 inches in width once all leaves are removed. If you only have access to smaller artichokes, you may need to use 10-12 to use up all the filling; you might also consider leaving some of the edible internal leaves on.

The meat may be spiced to taste. Sometimes only salt and black pepper are used; some Palestinian cooks prefer to include seb'a baharat, white pepper, allspice, nutmeg, cardamom, and/or cinnamon.

Medieval Arab cookbooks sometimes call for vegetables to be deep-fried in olive oil (see Fiḍālat al-Khiwān fī Ṭayyibāt al-Ṭaʿām wa-l-Alwān, chapter 6, recipe no. 373, which instructs the reader to treat artichoke hearts this way). You may use olive oil, or a neutral oil such as canola or sunflower (as is more commonly done in Palestine today).

Elihu Grant noted in 1921 that lemon juice was often served with stuffed vegetable dishes; today stuffed artichokes are sometimes served with lemon.

For the rice:

200g Egyptian rice (or substitute any medium-grained white rice)

2 tsp broken semolina vermicelli (شعيريه) (optional)

1 tsp olive oil (optional)

Large pinch salt

520g water, or as needed

Broken semolina vermicelli (not rice vermicelli!) can be found in plastic bags at halal grocery stores.

Instructions:

For the stuffed artichokes:

1. Prepare the artichoke hearts. Cut off about 2/3 of the top of the artichoke (I find that leaving at least some of the stem on for now makes it easier to hollow out the base of the artichoke heart without puncturing it).

2. Pull or cut away the tough outer bracts ("leaves") of the artichoke until you get to the tender inner leaves, which will appear light yellow all the way through. As you work, rub a lemon quarter over the sides of the artichoke to prevent browning.

3. If you see a sharp indentation an inch or so above the base of the artichoke, use kitchen shears or a sharp knife to trim off the leaves above it and form the desired bowl shape. Set aside trimmings for a soup or stew.

4. Use a small spoon to remove the purple leaves and fibers from the center of the artichoke. Make sure to scrape the spoon all along the bottom and sides of the artichoke and get all of the fibrous material out.

5. Use a paring knife to remove any remaining tough bases of removed bracts and smooth out the base of the artichoke heart. Cut off the entire stem, so that the heart can sit flat, like a bowl.

6. Place the prepared artichoke heart in a large bowl of water with some lemon juice squeezed into it. Repeat with each artichoke.

7. Drain artichoke hearts and pat dry. Heat a few inches of oil in a pot or wok on medium and fry artichoke hearts, turning over occasionally, for a couple minutes until lightly browned. If you don't want to deep-fry, you can pan-fry in 1 cm or so of oil, flipping once. Remove with a slotted spoon and drain.

8. Prepare the filling. Heat 1 tsp of olive oil in a large skillet on medium-high and fry onions, agitating often, until translucent.

Tip: Some people add the pine nuts and brown them at this point, to save a step later. If you do this, they will of course be mixed throughout the filling rather than being a garnish on top.

9. Add spices, salt, and meat substitute and fry, stirring occasionally, until meat is browned. (If using TVP, brown it by allowing it to sit in a single layer undisturbed for 3-4 minutes, then stir and repeat.) Taste and adjust spices and salt.

10. Heat 1 Tbsp of olive oil or margarine in a small pan on medium-low. Add pine nuts and fry, stirring constantly, until they are a light golden brown, then remove with a slotted spoon. Note that, once they start taking on color, they will brown very quickly and must be carefully watched. They will continue to darken after they are removed from the oil, so remove them when they are a shade lighter than desired.

11. Stuff the artichoke hearts. Fill the bowl of each heart with meat filling, pressing into the bottom and sides to fill completely. Top with fried pine nuts.

12. Cook the artichoke hearts. Place the stuffed artichoke hearts in a single layer at the bottom of a large stock pot, along with any extra filling (or save extra filling to stuff peppers, eggplant, zucchini, or grape leaves).

13. Whisk stock concentrate into several cups of just-boiled water, if using—if not, whisk in about a half teaspoon of salt. Pour hot salted water or stock into the pot to cover just the bottoms of the stuffed artichokes.

14. Simmer, covered, for 15-20 minutes, until the artichokes are tender. Simmer uncovered for another 5-10 minutes to thicken the sauce.

For the rice:

1. Rinse your rice once by placing it in a sieve, putting the sieve in a closely fitting bowl, then filling the bowl with water; rub the rice between your fingers to wash, and remove the sieve from the bowl to strain.

2. Place a bowl on a kitchen scale and tare. Add the rice, then add water until the total weight is 520g. (This will account for the amount of water stuck to the rice from rinsing.)

3. (Optional.) In a small pot with a close-fitting lid, heat 1 tsp olive oil. Add broken vermicelli and fry, agitating often, until golden brown.

4. Add the rice and water to the pot and stir. Increase heat to high and allow water to come to a boil. Cover the pot and lower heat to a simmer. Cook the rice for 15 minutes. Remove from heat and steam for 10 minutes.

To serve:

1. Plate artichoke hearts on a serving plate alongside rice and lemon wedges; or, place artichoke hearts in a shallow serving dish, pour some of their cooking water in the base of the dish, and serve rice on a separate plate.

Tip: The white flesh at the base of the bracts (or "leaves") that you removed from the artichokes for this recipe is also edible. Try simmering removed leaves in water, salt, and a squeeze of lemon for 15 minutes, then scraping the bract between your teeth to eat the flesh.

[justanotherfanwriter]

a/n: i just wanted to write something short and sweet for one of my lil comfort pairings :)

----------------------------------------------------

"Okay, so that's flyer derby in a nutshell," Willow Park nodded, handing him a green jersey. "Do you think you've kind of got it?"

"Get the flags on the tree," Hunter huffed, pulling the jersey over his head. He carded his fingers through and slightly shook his head to fluff out his hair before fixing Willow Park with a look, "Not too difficult."

Willow laughed, "Listen, I'm just making sure, not insulting your intelligence."

He sat down to re-lace his boots and didn't respond. His ego was already bruised enough after underestimating the rest of her team. He didn't want her to do the same with him. He'd get the job done.

Willow didn't take the hint and continued talking. Bouncing slightly on the tips of her toes, she threw a nervous look over at the rest of the team before turning her gaze back on him, "I'm so jittery right now. Like game day nerves—" she shook her hands out, "—I mean, I was expecting game day jitters, but not literally on the first day. Do you think they can tell?"

He blinked, sneaking a look at Gus, Skara, and Viney, as they pilfered through a box of lost junk, trying to find things to wear. When he looked back at Willow, she was waiting expectantly for his answer. It dawned on him that she wasn't asking some asinine hypothetical, but confiding in him—someone she had just met (like she actually thought his opinion mattered). Aside from his Uncle (even then, that was like pulling teeth), he wasn't anyone's go-to confidant at the Castle. He didn't have many if any . . . allies. 

"I, uh—" He stared at her, watching how she chewed on her bottom lip, before forcing his focus back on his boots, "—no, I don't. Well, maybe Gus. You two are close."

Willow sighed, sinking onto the bleachers beside him, "I really want us to do well."

"You should want us to win," he sniffed, finishing his laces and sitting up straight. "Well isn't enough. There's no more of this—" he gestured around, "—if we don't win."

That was a semi-lie. If all went well and Willow's team proved themselves worthy, these four would be in the Emperor's Coven by nightfall. They wouldn't have time to play any more games (unless it was on their one day off, but eugh, semantics).

"Right, yeah," She nodded sharply before her face fell slightly, "right. Without a single practice. Yep."

"I think we have a good shot." He said truthfully with a one-shoulder shrug. The annoying professor across the field looked easily puntable. He smirked, "Come on, what happened to the whole 'don't underestimate us' spiel from like ten minutes ago? Remember? When you were rubbing my nose in the dirt?"

She offered him a sheepish smile, "You know, it's no fun if you use my words against me."

"Pick your audiences more carefully," He shot back, adjusting the straps of his gloves.

"It's just, this is something I've wanted for a while now. For it to be right in my grasp—" Willow blew the bangs off her forehead, "—that's a lot of pressure. And this professor? Not my biggest fan. I don't know how they do it in the Toes, but Hexside isn't as . . . forgiving as it seems."

Unbidden, he thought of his Uncle. He thought of the throne room, and the Titan's blood, and the key. He tried picturing Willow in that position. He couldn't.

"I was homeschooled, actually." He admitted. "Private tutors."

She briefly considered him, then nodded, "Yeah, that makes sense."

He furrowed his eyebrows together, "what does that mean?"

Willow's eyes widened as her gaze flickered from side to side, resting everywhere but his face. "Oh, nothing! Just, you know—" she gestured vaguely in his direction, and no, he did not know. "Totally nothing."

"Right. Sure," Hunter glared before tacking on, "I mean, you're stuck in school for what? Another three or four years? I've practically graduated, but whatever."

"I didn't mean anything by it." Willow threw up her hands in surrender, fighting off a smile. "I promise." Her face fell a second later, "wait, did you say you'll be graduating soon?"

"I have a few credits left," he said dismissively, which was probably true if he went to a regular school.

"Aw, no," She pouted, "now we definitely have to win! We need you on the team for as long as we still have you!"

Another awkward feeling washed over him. Obviously (pending approval and then basic training), they would be interacting with each other (on a strictly professional level) to some degree in the Emperor's Coven. But Willow didn't know that yet. Willow still thought he was some guy named Caleb (who she wanted, for whatever reason, without even really knowing him, on her flyer derby team for as long as possible).

"Oh, um, yeah, bummer." He mumbled, playing like he was genuinely disappointed (and there was a brief millisecond where he was, actually, kind of disappointed).

"You're amazing with a Palisman staff, seriously. You graduating is going to be a real loss. Where did you even learn to fly like that?"

"Ohhh, you know, private tutors, soo…" He trailed off, pursing his lips.

"And did you carve Flapjack or adopt? I adopted Clover. Well, personally, adoption isn't the right word. It's more like she chose me, but what about you and Flapjack? I swear, I remember a red bird when the Bat Queen came to our school for an adoption event."

Flapjack landed on Hunter's shoulder at the sound of their names, and Clover came bumbling behind him to plop down onto Willow's lap.

Hunter looked off, trying to concoct an excuse, and at Flap's suggestion, said, "He's been in the family for a few generations, so, uh, no to both, and obviously, it follows that he couldn't be the same bird you saw at whatever event you are describing because he was with me . . . and I lived in the toes, so yep?"

"That makes sense." Willow chirped, wiggling a finger in Flap's direction, "Birds are popular, after all."

"Mmhm." The following beat of silence made him break out into a thin line of sweat (did Willow know, Luz?). He stood awkwardly, "Well, I guess we should—"   

"Wait," Her hand shot out, capturing his wrist, "where do you think you're going?"

He stared at her, "the field?"

She shook her head with a wide grin, pulling him back onto the bleachers, "Not without face paint, dude, come on."

"Yeah, I don't know how to put that stuff on without it looking like finger paint, soo—"

"Don't worry. I'll help." She grabbed the tub of green paint and popped open the lid, "Face me."

Reluctantly, he angled his body toward her.

"No, like, here, sit like this," She straddled the bench, gesturing for him to mimic her.

Something inside him seized up like an eruption of fire ants swarming in his stomach, and he did what she said. They were suddenly close. Physically, it was way more intimate than he was used to, and admittedly, he wasn't used to much. She leaned in with a smile, two fingers coated in thick green paint, "Okay, this is going to be a little cold."

"That's fine," His voice came out low, unsure.

Her paint-free hand cupped one side of his face gently, tilting his head into a more favorable position but restricting his ability to look anywhere but her face. He stayed quiet as her fingers traced down his face, starting at the top of his forehead and working down his jaw.

"Let's do a lightning bolt, yeah?" She hummed thoughtfully, her mouth opened slightly in concentration. He stared at the tip of her tongue, and the intensity of the fire ants mulling around his stomach intensified. He forced his gaze to the side and discreetly wet his lips.

"Sure."

She smiled, "I promise it will look good."

"Okay," He agreed because he didn't know what else to say. Willow's fingers were soft against his skin. The paint was cold. Her hand was warm. Their knees knocked together more than once until her left rested against his right.

"Now, wait, I'm gonna fix this—" She gently smudged her thumb across his cheek, leaning in even closer.

He shot a nervous glance at her, worried suddenly about his breath. She didn't seem offended, and, of course, he had brushed his teeth that morning, but he still made sure to keep his mouth shut. He didn't look away, though. This close, the color of her eyes was too hard to ignore, and she had a slight splattering of sun freckles across the bridge of her button nose.

"Almost done," she said with a smile, eyes flickering to meet his.

He nodded again, more interested in how her eyelashes fanned across her cheeks before realizing, belatedly, that she had a dimple on her right cheek.

Her thumb tickled the corner of his mouth, and his breath hitched. He repressed the pleasant shiver running down his spine as she laughed, "Sorry. Like I said, cold."

Hunter didn't feel cold. He felt quite the opposite.

"Alright," She nodded with some finality and sat back. Hunter sucked in a quick breath, remembering right then to breathe. "Let me look at you." She cupped his chin, again, gently, tilting his face to the left than the right.

"Lookin' good," She winked, and an annoying, high-pitched peel of obnoxious laughter ripped out of him. His face grew hotter by the second.

Her smile shrunk, eyebrows furrowing together as her thumb gently swiped the scar on his cheek, "oh, thorns, Caleb, what happened here?"

It took him half a second longer than it should have to remember he was Caleb.

"Oh, uh—"

"—if you don't mind me asking, of course," She quickly interrupted, waving her hands in front of her, "sorry, that was rude!"

"No, I, uh," He flat out couldn't remember, like anything right then, let alone where one stupid scar came from (which was a lie, he remembered, but he couldn't get the words in the proper order in his head). He was still thinking about her thumb on the corner of his mouth, the green of her eyes, and her bottom lip.

"I fell," he croaked out, eventually, which was a partial truth. He had fallen. If the fall had caused the scar, that was up for debate (it wasn't). He cringed at his own words, forcing his gaze away again.

"Of course," She nodded, "and like I said, I'm sorry if that question was too forward. I tend to be a worrywart, especially when it comes to my friends." She stood up and stretched her hand to him, "Ready to win?"

Willow's smile was infectious; her dimple only helped her cause. He took her hand, almost shyly, "Duh, Captain." 

Willow giggled, beaming, almost preening at the title. His face warmed all over again.

He really needed this to go well.

[jezabelle9299]

Rise and Shine S.R x FEM! Reader

Overture- This is a part 2 of Morning Sunshine, which if you'd like to read you could do Here, but if you don't feel like doing that the gist is that these two are roommates on a long case (separate beds they're awkward enough without being under the same comforter), and when Spencer wakes up Reader is already up getting ready, so they decide to get breakfast together. But Spencer is very sleepy, and starts drifting off again.

CWs-Spencer falls down, but he's fine.

A/N- Someone actually requested this! It made me very happy and I would like to give that person a very small kiss on the nose. Also it's technically Halloween, so happy Halloween! I'm beginning to think I may not finish all of these before the end of the month (but I may die trying) Anyway, this is day 23, and if you'd like to read the other things I did this month you can do that here: October Writing Master List

You let Spencer sleep in an extra 15 minutes, long enough for you to finish your makeup– before trying to wake him up again. You agreed to get breakfast and coffee before the morning briefing, and if you were going to make it in time, he needed to start getting ready. 

“Hey Spencer?” You called out to him, and although you were only a few feet away, he didn’t respond. 

“Spence?” This time he only turned over in response, so you leaned over his bed to gently shake his shoulder, lowering your voice a little bit so as to not startle him. 

“Hey, come on, we gotta go if we’re going to make it to the briefing on time and still get breakfast on the way.” He turned his head towards you, sleepily grumbling a little bit. 

“5 more minutes Sunshine?” That he’d never called you before. He wasn’t very into nicknames outside of occasionally calling you and your colleagues by their last names. And you could see the very moment he recognized it in himself, his eyes shooting open, and him immediately sitting back up in bed. He registered your slightly shocked expression and threw the blankets off of himself. 

“Ah— I mean I— I’ll get ready now.”  He stumbled to get out of that bed so quickly, he didn’t even notice his leg caught in the sheets until he went tumbling to the floor. 

“Oh my god Spencer are you ok?” You rushed over to him, trying to pull the rest of the bedding off of him.

“Yeah-yep, I’m fine. How about I meet you in the lobby in like 10 minutes?” He spoke while still collecting himself from the floor. 

“Sure, I’ll see you then.” You gently closed the door behind you, and made your way down to the lobby to wait. Spencer however, spent the first minute screaming into a pillow because he was so mad at himself that he not only let the nickname he preferred to keep confined to his thoughts slip in front of you, but that he immediately fell down after. Like a baby deer learning to walk. 

When he came down to the lobby, his face was still as red as could be. But you didn’t say a word about what happened earlier, leading him with his cute little message bag to the cute little cafe down the street. You got your food and coffees, and then after the waitress made sure everything was ok, you decided you could now tease him just a little bit.

“So Sunshine, huh?” He almost choked on his coffee, and you felt just a little bit bad for bringing it up. 

“I’m so sorry about that, I wasn’t thinking– I didn’t mean to call you–that.”

“I didn’t think you liked nicknames.”

“Generally I don’t.”

“So what got me the honor of such a flattering one?”

“I don’t know, you’re just so warm? I guess?” Warm, bright, the light of his life— it was all semantics really.

“Aww, thank you. That’s really sweet, Spencer.” 

You took a glance at the clock on the wall, and realized you needed to be at the briefing in less than 20 minutes. Everyone on the team knew you were sharing a room so if you both turned up late, they’d have a field day. You could make it on time, but you raised your hand when the waitress walked by so you could get the check. 

“Oh the two people at that table already paid your tab. They said you were a very cute couple.” She said it in a way that was so sweet and genuine, you really weren’t sure who you were picturing when you looked towards the door, where the waitress had pointed. 

Yet there they were, Derek and Emily, smug as ever. Spencer followed your line of sight and all of the color drained from his face. They each gave you small waves before putting their sunglasses back on and walking out. 

“Alright, we’re getting made fun of this morning anyway, you might as well finish your coffee.” Spencer grumbled while picking up his own mug again.

[compneuropapers]

Interesting Papers for Week 13, 2025

Representational drift in barrel cortex is receptive field dependent. Ahmed, A., Voelcker, B., & Peron, S. (2024). Current Biology, 34(24), 5623-5634.e4.

Monkeys engage in visual simulation to solve complex problems. Ahuja, A., Yusif Rodriguez, N., Ashok, A. K., Serre, T., Desrochers, T. M., & Sheinberg, D. L. (2024). Current Biology, 34(24), 5635-5645.e3.

Theta oscillations optimize a speed-precision trade-off in phase coding neurons. Amil, A. F., Albesa-González, A., & Verschure, P. F. M. J. (2024). PLOS Computational Biology, 20(12), e1012628.

Semantic relatedness proactively benefits learning, memory, and interdependence across episodes. Bennion, K. A., Phong, J., Le, M., Cheng, K., Wahlheim, C. N., & Antony, J. W. (2024). eLife, 13, e95480.3.

Efficient value synthesis in the orbitofrontal cortex explains how loss aversion adapts to the ranges of gain and loss prospects. Brochard, J., & Daunizeau, J. (2024). eLife, 13, e80979.

Prediction-based false memory: Unconfirmed prediction can result in robust false memories. Bulatova, O., & Fukuda, K. (2025). Cognition, 255, 106013.

Perceptual constancy for an odor is acquired through changes in primary sensory neurons. Conway, M., Oncul, M., Allen, K., Zhang, Z., & Johnston, J. (2024). Science Advances, 10(50).

Exploring the hierarchical structure of human plans via program generation. Correa, C. G., Sanborn, S., Ho, M. K., Callaway, F., Daw, N. D., & Griffiths, T. L. (2025). Cognition, 255, 105990.

Discrete Synaptic Events Induce Global Oscillations in Balanced Neural Networks. Goldobin, D. S., di Volo, M., & Torcini, A. (2024). Physical Review Letters, 133(23), 238401.

Sculpting new visual categories into the human brain. Iordan, C. R., Ritvo, V. J. H., Norman, K. A., Turk-Browne, N. B., & Cohen, J. D. (2024). Proceedings of the National Academy of Sciences, 121(50), e2410445121.

Rapid, systematic updating of movement by accumulated decision evidence. Molano-Mazón, M., Garcia-Duran, A., Pastor-Ciurana, J., Hernández-Navarro, L., Bektic, L., Lombardo, D., de la Rocha, J., & Hyafil, A. (2024). Nature Communications, 15, 10583.

A computational approach to the N-back task. Ni, L., & Ma, W. J. (2024). Scientific Reports, 14, 30211.

Social conformity is a heuristic when individual risky decision-making is disrupted. Orloff, M. A., Chung, D., Gu, X., Wang, X., Gao, Z., Song, G., Tatineni, C., Xu, S., Casas, B., & Chiu, P. H. (2024). PLOS Computational Biology, 20(12), e1012602.

Parallel development of object recognition in newborn chicks and deep neural networks. Pandey, L., Lee, D., Wood, S. M. W., & Wood, J. N. (2024). PLOS Computational Biology, 20(12), e1012600.

Intermittent rate coding and cue-specific ensembles support working memory. Panichello, M. F., Jonikaitis, D., Oh, Y. J., Zhu, S., Trepka, E. B., & Moore, T. (2024). Nature, 636(8042), 422–429.

Memory reactivation generates new, adaptive behaviours that reach beyond direct experience. Rawson, A. B., Nalluru, S., O’Reilly, J. X., & Barron, H. C. (2024). Scientific Reports, 14, 30097.

Neuronal circuit mechanisms of competitive interaction between action-based and coincidence learning. Rozenfeld, E., & Parnas, M. (2024). Science Advances, 10(49).

Representation of a perceptual bias in the prefrontal cortex. Serrano-Fernández, L., Beirán, M., Romo, R., & Parga, N. (2024). Proceedings of the National Academy of Sciences, 121(50), e2312831121.

Vector coding and place coding in hippocampus share a common directional signal. Zhou, Y.-Q., Puliyadi, V., Chen, X., Lee, J. L., Zhang, L.-Y., & Knierim, J. J. (2024). Nature Communications, 15, 10630.

Value construction through sequential sampling explains serial dependencies in decision making. Zylberberg, A., Bakkour, A., Shohamy, D., & Shadlen, M. N. (2024). eLife, 13, e96997.3.

[foreverisntenough]

Is there anything you can tell us about the kyky series I’m soooo curious!!! Like what will it be about?? Will it be set when kyky is at real or psg??? Anything you can say??? I CANT WAIT😭😔🫶🫶🫶🫶

Hmmmm... what do I want to share about it....

I don't want to pile up on myself here because I'm still writing 'Movie Night,' and begining 'Aperture' but for my Kyks girlies.....

Title will be 'Slow Burn' Here is a little sneak peak at a draft of the cover art....

Kyks in the fic is at least in France... I haven't gotten into the semantics of where he is playing during it but at least the way it starts he is physically in the country of France lol....

The Y/N character is also French and miss girl is a very chic chef.

a first attempt at a synopsis for you as well

'Hidden in Provence, surrounded by fields of lavender and the golden haze of early summer, you leave behind Paris to take a job as a private chef at a secluded chateau, craving nothing more than the quiet comfort of your craft working for a non disclosed athlete. But when the door opens, it’s not just any athlete—it’s Kylian, his presence as magnetic as the heat rolling off the stove. You tell yourself to stay composed, to keep your heart steady, but feelings bubble over like water left too long to boil. He’s nothing like you expected—beneath the charm and fame are delicate layers, soft and surprising, much like the croissants you make him each morning. And as storms sweep across the countryside, trapping you in the warm glow of candlelight, you realize some fires aren’t meant to be controlled—they’re meant to consume you.'

Vibes wise using music - I'd say it's like a cross between like Diana and a song like (Dream) if you can wrap your head around that lol.

[innovatexblog]

How Large Language Models (LLMs) are Transforming Data Cleaning in 2024

Data is the new oil, and just like crude oil, it needs refining before it can be utilized effectively. Data cleaning, a crucial part of data preprocessing, is one of the most time-consuming and tedious tasks in data analytics. With the advent of Artificial Intelligence, particularly Large Language Models (LLMs), the landscape of data cleaning has started to shift dramatically. This blog delves into how LLMs are revolutionizing data cleaning in 2024 and what this means for businesses and data scientists.

The Growing Importance of Data Cleaning

Data cleaning involves identifying and rectifying errors, missing values, outliers, duplicates, and inconsistencies within datasets to ensure that data is accurate and usable. This step can take up to 80% of a data scientist's time. Inaccurate data can lead to flawed analysis, costing businesses both time and money. Hence, automating the data cleaning process without compromising data quality is essential. This is where LLMs come into play.

What are Large Language Models (LLMs)?

LLMs, like OpenAI's GPT-4 and Google's BERT, are deep learning models that have been trained on vast amounts of text data. These models are capable of understanding and generating human-like text, answering complex queries, and even writing code. With millions (sometimes billions) of parameters, LLMs can capture context, semantics, and nuances from data, making them ideal candidates for tasks beyond text generation—such as data cleaning.

To see how LLMs are also transforming other domains, like Business Intelligence (BI) and Analytics, check out our blog How LLMs are Transforming Business Intelligence (BI) and Analytics.

Traditional Data Cleaning Methods vs. LLM-Driven Approaches

Traditionally, data cleaning has relied heavily on rule-based systems and manual intervention. Common methods include:

Handling missing values: Methods like mean imputation or simply removing rows with missing data are used.

Detecting outliers: Outliers are identified using statistical methods, such as standard deviation or the Interquartile Range (IQR).

Deduplication: Exact or fuzzy matching algorithms identify and remove duplicates in datasets.

However, these traditional approaches come with significant limitations. For instance, rule-based systems often fail when dealing with unstructured data or context-specific errors. They also require constant updates to account for new data patterns.

LLM-driven approaches offer a more dynamic, context-aware solution to these problems.

How LLMs are Transforming Data Cleaning

1. Understanding Contextual Data Anomalies

LLMs excel in natural language understanding, which allows them to detect context-specific anomalies that rule-based systems might overlook. For example, an LLM can be trained to recognize that “N/A” in a field might mean "Not Available" in some contexts and "Not Applicable" in others. This contextual awareness ensures that data anomalies are corrected more accurately.

2. Data Imputation Using Natural Language Understanding

Missing data is one of the most common issues in data cleaning. LLMs, thanks to their vast training on text data, can fill in missing data points intelligently. For example, if a dataset contains customer reviews with missing ratings, an LLM could predict the likely rating based on the review's sentiment and content.

A recent study conducted by researchers at MIT (2023) demonstrated that LLMs could improve imputation accuracy by up to 30% compared to traditional statistical methods. These models were trained to understand patterns in missing data and generate contextually accurate predictions, which proved to be especially useful in cases where human oversight was traditionally required.

3. Automating Deduplication and Data Normalization

LLMs can handle text-based duplication much more effectively than traditional fuzzy matching algorithms. Since these models understand the nuances of language, they can identify duplicate entries even when the text is not an exact match. For example, consider two entries: "Apple Inc." and "Apple Incorporated." Traditional algorithms might not catch this as a duplicate, but an LLM can easily detect that both refer to the same entity.

Similarly, data normalization—ensuring that data is formatted uniformly across a dataset—can be automated with LLMs. These models can normalize everything from addresses to company names based on their understanding of common patterns and formats.

4. Handling Unstructured Data

One of the greatest strengths of LLMs is their ability to work with unstructured data, which is often neglected in traditional data cleaning processes. While rule-based systems struggle to clean unstructured text, such as customer feedback or social media comments, LLMs excel in this domain. For instance, they can classify, summarize, and extract insights from large volumes of unstructured text, converting it into a more analyzable format.

For businesses dealing with social media data, LLMs can be used to clean and organize comments by detecting sentiment, identifying spam or irrelevant information, and removing outliers from the dataset. This is an area where LLMs offer significant advantages over traditional data cleaning methods.

For those interested in leveraging both LLMs and DevOps for data cleaning, see our blog Leveraging LLMs and DevOps for Effective Data Cleaning: A Modern Approach.

Real-World Applications

1. Healthcare Sector

Data quality in healthcare is critical for effective treatment, patient safety, and research. LLMs have proven useful in cleaning messy medical data such as patient records, diagnostic reports, and treatment plans. For example, the use of LLMs has enabled hospitals to automate the cleaning of Electronic Health Records (EHRs) by understanding the medical context of missing or inconsistent information.

2. Financial Services

Financial institutions deal with massive datasets, ranging from customer transactions to market data. In the past, cleaning this data required extensive manual work and rule-based algorithms that often missed nuances. LLMs can assist in identifying fraudulent transactions, cleaning duplicate financial records, and even predicting market movements by analyzing unstructured market reports or news articles.

3. E-commerce

In e-commerce, product listings often contain inconsistent data due to manual entry or differing data formats across platforms. LLMs are helping e-commerce giants like Amazon clean and standardize product data more efficiently by detecting duplicates and filling in missing information based on customer reviews or product descriptions.

Challenges and Limitations

While LLMs have shown significant potential in data cleaning, they are not without challenges.

Training Data Quality: The effectiveness of an LLM depends on the quality of the data it was trained on. Poorly trained models might perpetuate errors in data cleaning.

Resource-Intensive: LLMs require substantial computational resources to function, which can be a limitation for small to medium-sized enterprises.

Data Privacy: Since LLMs are often cloud-based, using them to clean sensitive datasets, such as financial or healthcare data, raises concerns about data privacy and security.

The Future of Data Cleaning with LLMs

The advancements in LLMs represent a paradigm shift in how data cleaning will be conducted moving forward. As these models become more efficient and accessible, businesses will increasingly rely on them to automate data preprocessing tasks. We can expect further improvements in imputation techniques, anomaly detection, and the handling of unstructured data, all driven by the power of LLMs.

By integrating LLMs into data pipelines, organizations can not only save time but also improve the accuracy and reliability of their data, resulting in more informed decision-making and enhanced business outcomes. As we move further into 2024, the role of LLMs in data cleaning is set to expand, making this an exciting space to watch.

Large Language Models are poised to revolutionize the field of data cleaning by automating and enhancing key processes. Their ability to understand context, handle unstructured data, and perform intelligent imputation offers a glimpse into the future of data preprocessing. While challenges remain, the potential benefits of LLMs in transforming data cleaning processes are undeniable, and businesses that harness this technology are likely to gain a competitive edge in the era of big data.

[bookishtheaterlover7]

The AI article is nice and all but major issues of this were legit….

The “divorce” would prove this was a legit relationship and marriage which it’s not. Team real would have a field day with this.

Mackie is Captain America and if Chris reprised anything it would show he’s selfish because again….Mackie is Cap now and it would also show Chris needed Marvel to survive and anything promised in this PR mess failed and wasn’t nor isn’t worth this shitshow.

The fans are painted as “crazy” because it reads like we’re delusional and how her friends being racist doesn’t mean she is….yes unfortunately people would use that as an argument and label us all collectively as crazy.

Basically, for the article to really hit home head need to basically admit the fans were right and this is 100% PR and then list chris taking time to recover and his sincerity in apologizing for putting his fans through this bs and him taking time for therapy and then working in new projects when he returns.

Also all the more reason for him to keep his love life and personal life private after this mess.

So if his team is reading, don’t follow that ai generated mess, reread my points above and then MAKE IT HAPPEN! 👏 😂

Semantics, An🫶n...

Let's just step into Delulu Land for a bit, and imagine that the whole PR bullshit is done! 😆 That honestly would be nice.

But in all seriousness though, yeah, they shouldn't copy-paste this thing. They should point out that after everything, we were right, and certain things need to be done by Chris, in order to convince the Fandom, shit like this won't happen again.

And mean it 😁

[cant-get-no-worse]

Ciene ur French so maybe u can help: what's 'Chemin du Roi' on twitter?? ive seen a lot of these guys around and understood its smth abt Neymar.

Jjajajajaaa so you have stumbled upon the Chemin du Roi... peace and prayers to you. 🙏

Let's be serious. The « Chemin du Roi » is an unavoidable piece of Football French Twitter (hereby referred to as FFT) lore. It's like a piece of furniture you're used to by now. Let's rant about it.

« Chemin du Roi » is the denomination of fan collective in the same manner « Factos FC » or « Messi FC » are used to name fans of specific world-renowned players. They're a bit different than these, though, because Messi and Ronaldo weren't playing in Ligue 1 (until 2021 for Messi) while Neymar had been in France since 2017. So unlike Ronaldo FC or Messi FC who are more global, the « Chemin du Roi » (Way of the King in English. Yes, it reeks a bit of dramatism. One would say, very on brand with the object of their affection.) is an exclusively French-originated community of Neymar fans who hold the reputation of being a bid mad, extreme or idolatrous on FFT. Which is kind of funny, given that those critics partly come from Ronaldo FC/« Mbobutu FC »/ (like Factos FC, derogatory French Twitter nickname for Mbappé, specifically playing on the dictator notion) known for their equal idolatry towards their star, or from the Ultras, PSG's collective with a formidable reputation of turning on their players faster than a windmill.

It goes back all the way to 2017. You have to put it into context: Neymar has just been sold from Barça to PSG for the exorbitant amount of 222M, setting a precedent and completely disrupting the players' market, at 25 years old, fresh off a specatular Remontada of which he was the principal instigator, and at the peak of his art. I have to stress this: in 2017, Neymar isn't just an excellent player. He's considered to be the next brand of football super-stars, set to conquer football by his talent, marketing appeal, image and brand. This transfer is supposed to make him take on the costume of successor to Messi and Ronaldo as the face of modern world football: Neymar, in 2017, IS the future of the sport.

That's how he arrives to the Parc des Princes (Prince's Park, PSG's stadium) at least. Thus, it's not unusual to hear the same phrases employed in the French news and some PSG supporters at that time, playing on the whole royalty semantic field. Neymar is the Parc's Prince, set to become a King by crowning himself with the Champion's League, ever-lacking from PSG's trophy cabinet.

The Chemin du Roi itself, though, doesn't take form until 2019. Summer 2019 is, for Paris, one messy, messy mercato. Rumors are flying around. Neymar is said to be on the verge of returning to Barcelona. Some PSG supporters are incredibly frustrated at this, call for treason, ask for his departure, and all around write incendiary diatribes against their N°10. Following this, a number of Neymar fans/sympathizers rallied their troups in a public show of support to Neymar, refuting all notion of « treason », and making #LECHEMINDUROI trend on FFT.

"The train is still on the platform. Hurry up to board, after that, it'll be too late. #LECHEMINDUROI" Note that the word « train » is broadly used on FFT to designate, more than the enthusiasm, an agenda that one will make on a player, generally: - A young prospect (15 - 21) you think will prove himself, - A new player who came in your club during a transfer window, - A kind of second chance given to a player on your team who sucked but who you think, following recent performances for example, that « the train is going to start again » (meaning: the player's going to be good again) so « get back on the train » (meaning: publicly declare in the very silly Football Twitter sphere that you're betting/will do the praises of this player — at least until he disappoints you so you « jump off the train » — so that later on, you can claim you've always said so. Once again. Extremely silly behaviour but that's Twitter for you.).

On August 21, 2019, a journalist for a French outlet writes, regarding the situation:

“Contacted by us, the Tweeps who started the movement answered “Dunno” (sic) when asked the real meaning of this fight. Powerful words, which sum up the importance of this hashtag #LeCheminDuRoi… Absolute nonsense."

If by August 2019, the Chemin du Roi was effectively nothing more than a cry of protest against those who dared speaking ill of Neymar amidst Mercato rumors, the movement, in lieu of vanishing like all Twitter infatuation, instead cimented itself into FFT. One could say it was only a matter of time, after all, before Neymar had a similarly cult-like following to the very idols he was set to surpass. Ronaldo and Messi FC's reputation was at the time unprecedented, and enough to make a grown man cry.

Thus the Chemin du Roi seemed to be just one natural step to the modern crowned super-star fate that awaited him. The only step left to this fate, though, was a problematic one: winning the UCL. This problem proved itself to give the Chemin du Roi the very purpose lots accused them of missing: now, upon being asked "So what is at the end of the way? What's the goal of it all?" the Chemin du Roi could now answer "Winning the UCL."

By the beginning of 2020, this was clear as crystal. These supporters had already forged themselves a strong reputation on FFT — some very eerie and sexuals tweets that FFT obviously couldn't wait to blow out of proportion and make a mockery of, but also all that a cult-fanbase following entails: propaganda of the player to the last degree, utter obsession, blaming of others for each bad game, etc.

In Summer 2020 though, as PSG went on to beat each one of their opponents in a Covid-rigged UCL, the Chemin du Roi and the PSG supporters seemed to have found the Promised Land: a neutral common ground. The club was doing well; PSG supporters were happy. Neymar was doing well, CheminduRoi were happy. Overall, all praised the team, having the same objective in mind: the trophy that was missing. See below, on August 11, 2020, a PSG news account:

"The Chemin du Roi Neymar must lead us at Europe's summit. First stopover on this journey: Atalanta. We count on him to galvanize the whole team. The pressure, he deals with it. Hoping that the speaker is well loaded for the pre-game. 🔥"

All is well and good in the City of Light eh? Well, it is, until it isn't. PSG famously fucks up the final. Since that, it's been pretty much a complete fall-off from both sides. Most PSG supporters on FFT can't bear the Chemin du Roi, described as being lunatics, fanatics, unbearable (funnily enough, that's the words I would use to describe most of them. How the turn tables.) . The "immature" adjective often used to describe Neymar has, by mirror effect, been passed on to the Chemin du Roi apologists, who are seen by lots of FFT as blind, weird fan boys. A beef largely reciprocated by the Chemin du Roi.

Their reputation goes beyond the PSG FFT though, since, since there's been heavy rumors of Neymar going back to Barça in the summer of 2023, Barça FFT accounts start to complain about having to endure a Chemin du Roi mass migration.

So yeah. That's the Chemin du Roi for you. Just a fancy way of saying French Neymar FC, really. But a bit weirder even by Messi and Ronaldo's standards. Funny stuff.

[renatoferreiradasilva]

\documentclass[11pt]{article} \usepackage{amsmath, amssymb, amsfonts} \usepackage{geometry} \usepackage{graphicx} \usepackage{hyperref} \geometry{margin=1in} \title{Spectral Foundations for Hybrid Optoelectronic Computing Architectures: From Riemann Zeros to Physical AI Hardware} \author{Renato Ferreira da Silva \ \texttt{renatoferreiradasilva1980@yahoo.com} \ ORCID: \href{https://orcid.org/0009-0003-8908-481X}{0009-0003-8908-481X}} \date{\today}

\begin{document}

\maketitle

\begin{abstract} This article establishes a theoretical bridge between spectral models of the Riemann zeta zeros and the design principles of hybrid optoelectronic computing architectures. By interpreting data flow and signal processing as spectral phenomena, we draw on Schr\"odinger operators with machine-learned potentials to inform the structural logic of neuromorphic chips. Our approach uses the Gaussian Unitary Ensemble (GUE) as a universal benchmark for both numerical accuracy and hardware robustness. We argue that such architectures are not merely computational devices, but physical realizations of spectral operators whose eigenvalues encode semantic and functional states. This spectral paradigm enables scalable, reconfigurable, and energetically efficient AI hardware that emulates fundamental structures from number theory and quantum mechanics. \end{abstract}

\section{Introduction} The convergence of high-performance computing, artificial intelligence, and photonics demands a foundational rethinking of how computation is physically realized. While Moore's Law slows, spectral methods rooted in mathematical physics offer a new direction. In particular, the Hilbert--P\'olya conjecture---which suggests that the nontrivial zeros of the Riemann zeta function correspond to the eigenvalues of a self-adjoint operator---invites a reinterpretation of computation as a spectral phenomenon. This work connects spectral operator modeling with hardware design, offering a principled framework for constructing optoelectronic systems whose logic is derived from eigenvalue dynamics.

\section{Spectral Operator Framework} We consider operators of the form: [ \mathcal{L} = -\frac{d^2}{dx^2} + V(x), ] with Dirichlet boundary conditions and potentials of the form: [ V(x) = \sum_{n=0}^K c_n H_n(x) e^{-x^2/2}, ] where $H_n(x)$ are Hermite polynomials and $c_n$ are trainable parameters. The eigenvalues of $\mathcal{L}$, computed numerically, align with the statistical properties of the nontrivial zeros of the Riemann zeta function. We leverage neural networks to learn mappings $c_n \mapsto \lambda_j$, interpreting these as functional transformations from hardware configurations to observable spectral states.

\section{GUE as Design Metric} The Gaussian Unitary Ensemble provides a statistical benchmark for spectral rigidity and eigenvalue spacing. In our context, it serves dual roles: \begin{itemize} \item In simulation: to validate the fidelity of the learned operator. \item In hardware: to ensure robust optical communication, minimal crosstalk, and consistent signal coherence across filaments. \end{itemize} Designing hardware whose delay paths, optical resonances, and thermal fluctuations approximate GUE behavior results in physical stability under computational load.

\section{Hardware Realization of Spectral Paradigms} Each computational unit (UC) in the hybrid optoelectronic architecture is interpreted as a physical realization of a node in a spectral graph: \begin{itemize} \item Optical interconnects act as eigenmode couplings. \item Modulation depths and frequencies correspond to potential configurations. \item Thermal gradients and electromagnetic fields define boundary conditions. \end{itemize} Hence, computation is no longer symbolic but spectral---defined by eigenvalue distributions and dynamic wave propagation.

\section{Spectral Learning and Inference} Using physics-informed neural networks (PINNs), we train the system to infer potential shapes from target spectral outputs. This establishes a feedback loop where: \begin{enumerate} \item Input data modulates physical parameters. \item Spectral output is measured optically. \item Machine learning adjusts the configuration for optimal response. \end{enumerate} This feedback aligns with biological principles of neural plasticity, offering a pathway to hardware-level learning.

\section{Conclusion and Outlook} We propose a new paradigm in AI hardware design rooted in spectral operator theory. By grounding hardware architectures in the spectral behavior of Schr\"odinger-type systems, validated through GUE statistics and machine learning, we lay the foundation for scalable, efficient, and intelligent photonic computing. Future work will explore: \begin{itemize} \item Topological extensions to noncommutative geometries. \item Quantum analogs with entangled photonic states. \item Integration with health diagnostics and real-time physical simulation. \end{itemize}

\end{document}

[fromdevcom]

C Programming: String Copy Functions Compared - strcpy, strncpy, and strlcpy Tutorial Buffer overflows have long been one of the most notorious security vulnerabilities in C programming. At the heart of many such issues lies string manipulation, particularly string copying operations. Understanding the differences between strcpy, strncpy, and strlcpy isn't just about writing better code – it's about writing secure code. The Evolution of String Copying in C When C was first developed, string manipulation seemed straightforward. The standard library provided strcpy(), a simple function to copy strings. However, as security concerns grew and buffer overflows became a significant threat, newer alternatives emerged: strncpy() and later, strlcpy(). Each function has its own strengths and pitfalls, making the choice between them crucial for developers. Understanding strcpy() The simplest and oldest of the three functions, strcpy() copies a string from source to destination, including the null terminator. Its prototype looks like this: cCopychar *strcpy(char *dest, const char *src); Advantages of strcpy() Simple to use and understand Guaranteed null termination Efficient performance Part of the standard C library Disadvantages of strcpy() No buffer overflow protection Requires pre-validated input Can cause security vulnerabilities Unsafe for untrusted data Consider this example: cCopychar small_buffer[5]; char *long_string = "This string is too long"; strcpy(small_buffer, long_string); // Buffer overflow! This code will write beyond small_buffer's bounds, potentially corrupting memory or causing a crash. Enter strncpy() To address strcpy()'s security issues, strncpy() was introduced. It allows specifying a maximum number of characters to copy: cCopychar *strncpy(char *dest, const char *src, size_t n); Advantages of strncpy() Prevents buffer overflows Part of the standard C library Allows precise control over copy length Suitable for fixed-width fields Disadvantages of strncpy() Doesn't guarantee null termination May leave destination unterminated Inefficient for large buffers Fills remaining space with null bytes Here's a proper usage example: cCopychar dest[10]; strncpy(dest, "Hello", 9); dest[9] = '\0'; // Explicit null termination The Modern Solution: strlcpy() Developed for OpenBSD, strlcpy() aims to combine safety with ease of use: cCopysize_t strlcpy(char *dest, const char *src, size_t size); Advantages of strlcpy() Always null terminates Returns intended string length More efficient than strncpy() Clearer semantics Disadvantages of strlcpy() Not part of standard C library Limited platform availability Requires external implementation May need portability wrapper Example usage: cCopychar dest[10]; size_t result = strlcpy(dest, "Hello, World!", sizeof(dest)); if (result >= sizeof(dest)) // String was truncated Performance Considerations When it comes to performance, these functions show interesting characteristics: strcpy() is fastest but unsafe strncpy() can be slower due to null padding strlcpy() offers good performance without padding Best Practices for String Copying When to Use Each Function Use strcpy() when: Source string length is known Destination buffer size is verified Performance is critical Working with trusted data Use strncpy() when: Working with fixed-width fields Null padding is desired Standard C compliance is required Buffer size is known Use strlcpy() when: Security is paramount Platform supports it Clear error handling is needed Working with unknown data Security Guidelines Always validate input lengths Check function return values Ensure proper buffer sizing Consider using string libraries Modern Alternatives While these traditional functions remain widely used, modern C programming often employs alternatives:

String Classes Safe String Libraries Buffer Management Systems String View Types Common Pitfalls to Avoid strcpy() Pitfalls Assuming source fits destination Not checking for NULL pointers Overlapping memory regions Trusting user input strncpy() Pitfalls Forgetting manual null termination Incorrect size calculations Assuming automatic null termination Inefficient null padding strlcpy() Pitfalls Platform dependency issues Ignoring return values Assuming universal availability Incorrect size parameter Conclusion Choosing between strcpy(), strncpy(), and strlcpy() involves balancing security, performance, and portability. While strcpy() offers simplicity and speed, its security risks make it suitable only for carefully controlled scenarios. strncpy() provides better safety but requires careful handling of null termination. strlcpy() represents the most modern approach, combining safety and usability, though its limited availability can be a constraint. For modern C programming, strlcpy() is often the best choice when available. Otherwise, carefully used strncpy() with explicit null termination provides a good balance of safety and portability. Remember: in string manipulation, the extra effort spent on safety always pays off in the long run.

[reallyhappyyouth]

PiLog Preferred Record: Delivering a Single Source of Truth for Master Data

n today's complex and fast-paced business environment, organizations are increasingly recognizing the critical role that accurate and consistent data plays in achieving operational efficiency and informed decision-making. Yet, one of the most persistent challenges companies face is the presence of duplicate, inconsistent, and unstructured data across various systems and departments. This data chaos can lead to procurement errors, inflated inventory costs, compliance risks, and a lack of trust in business intelligence. To address this fundamental problem, PiLog introduces a powerful concept known as the Preferred Record.

The PiLog Preferred Record is a golden master data entry, carefully created by consolidating and standardizing the most accurate, complete, and relevant information from multiple data sources. Rather than relying on fragmented records scattered across disparate systems, the Preferred Record provides a single version of the truth — a trusted and validated data object that can be shared and used across the entire enterprise. It becomes the authoritative source of information for materials, vendors, equipment, services, and more.

What sets the Preferred Record apart is its foundation in internationally recognized standards such as ISO 8000, UNSPSC, and eClass. This ensures that data is not only accurate but also semantically consistent and ready for integration into enterprise resource planning systems like SAP, Oracle, and others. Through advanced data governance rules, artificial intelligence, and deep industry-specific expertise, PiLog identifies duplicate entries, cleanses inconsistent fields, and enriches the data with structured attributes to form a complete and reliable master record.

The value of the Preferred Record extends far beyond technical accuracy. It directly contributes to business performance. Procurement teams are empowered to negotiate better with suppliers when they have clear visibility into standardized material and vendor data. Inventory managers can optimize stock levels and eliminate redundancy. Compliance teams can ensure that reporting is aligned with regulatory expectations, and decision-makers gain the confidence to act on insights drawn from clean and trustworthy data.

PiLog’s Preferred Record is not just a tool; it is a strategic enabler for digital transformation. It helps organizations transition from reactive data correction to proactive data governance. It provides a scalable, sustainable approach to master data management that adapts to business growth, system changes, and evolving market demands. Ultimately, it allows businesses to shift from simply managing data to actually leveraging it as a competitive advantage.

#Golden Master Data #Data Cleansing #Data Governance #Master Data Standardization

[park-jaechan]

Jaechan: "I Realized That I Had to Take Acting Seriously" [N Interview]②

Last year, you appeared in three consecutive projects. How do you feel about that?

I was really lucky. I think I was chosen because I understood the characters well and showed improvement. Personally, I’m satisfied that I was able to show growth with each project, and I want to keep working even harder in the future.

Were you always interested in acting?

When I debuted as a singer, I didn’t have any thoughts about acting. Then, I got a great opportunity to appear in the drama My YouTube Diary, and after that, I started receiving more web drama offers. As my acting projects increased, I began finding it more enjoyable. These days, you need to be good at everything to survive in the industry. As my passion for acting grew, I realized I needed to take it seriously.

To be honest, at first, I saw acting as just a side job while singing was my main focus. But after Semantic Error received so much love and I worked on Bitter Sweet Hell, I started approaching acting more seriously. Watching experienced actors, I strongly felt that I couldn’t just do this half-heartedly—I had to do it properly.

You started with web dramas, then moved to OTT series, and now you’re on major broadcasting channels. What has changed?

I started acting in web dramas, then moved to OTT series, and now I’m doing mainstream dramas on major networks. Because of that, I feel like more people who didn’t know me before are recognizing me. In the past, people would ask, "Aren't you Jaechan?" But now, more people say, "I’m enjoying your drama." That’s when I really feel that I’m reaching a new audience.

Are there any genres or roles you’d like to try in the future?

So far, I’ve mostly played kind and gentle characters, so I want to challenge myself with a completely different role. Also, in Check in Hanyang, there were royal family storylines, and seeing that made me want to try a traditional historical drama. I once wore a crown prince’s outfit, and it suited me so well. My personal color is ‘crown prince.’ (Laughs)

Do you have a role model?

My role model is D.O. sunbaenim, who is both an actor and a singer. He’s incredibly active in both fields, and watching him made me realize, "You can excel at both singing and acting." I want to follow that path. When I’m working as a singer, I’ll focus on music, and when I’m acting, I want to show my best performances, dedicating myself fully to each moment.

Do the DKZ members support your acting career?

I sometimes feel guilty about not being able to be as active with the group because of my acting projects, but my members always support me. They cheer me on whenever I take on a new project and give me space to focus on my solo activities, which I’m really grateful for. This time, they even contacted me after watching my drama and participated in the OST. I appreciate them so much. Everyone is working hard on their own paths as well, which makes me proud.

Is there something you want to achieve as a singer?

Since debut, my goal has always been for DKZ’s song to rank in the top 10. Also, I’d love to perform our legendary songs like Crazy Night and Lupin again. Because of COVID-19, we had to perform without audiences many times, so I really want to feel the energy of performing with fans in a live concert setting.

Have any of your fellow artists reached out after watching Check in Hanyang?

Seoham hyung also contacts me whenever a new project comes out, saying he’s enjoying watching it. Also, THE BOYZ’s Q hyung and ONEUS’s Keonhee reached out, telling me they were really enjoying the drama, which I was very thankful for.

What are your goals and resolutions for this year?

I’m currently preparing my solo album, and my goal is to present songs of even higher quality than my first album. If the opportunity arises, I’d also love to challenge myself with a movie role. My constant goal is to make each year better than the last, and I want to look back on this year feeling that I’ve grown and improved once again.

Source: 재찬 "연기, 제대로 하지 않으면 안 되겠다 느꼈죠" [N인터뷰]② - 뉴스1 Translated by Park Jaechan Updates

[drmikewatts]

Complex & Intelligent Systems. Volume 10, Issue 6, December 2024

1) PD-DETR: towards efficient parallel hybrid matching with transformer for photovoltaic cell defects detection

Author(s): Langyue Zhao, Yiquan Wu, Yubin Yuan

Pages: 7421 - 7434

2) Intelligent bulk cargo terminal scheduling based on a novel chaotic-optimal thermodynamic evolutionary algorithm

Author(s): Shida Liu, Qingsheng Liu, Xianlong Chen

Pages: 7435 - 7450

3) Smart calibration and monitoring: leveraging artificial intelligence to improve MEMS-based inertial sensor calibration

Author(s): Itilekha Podder, Tamas Fischl, Udo Bub

Pages: 7451 - 7474

4) Identification of switched gated recurrent unit neural networks with a generalized Gaussian distribution

Author(s): Wentao Bai, Fan Guo, Haoyu Zhang

Pages: 7475 - 7485

5) Attention-guided mask learning for self-supervised 3D action recognition

Author(s): Haoyuan Zhang

Pages: 7487 - 7496

6) Bi-HS-RRT: an efficient sampling-based motion planning algorithm for unknown dynamic environments

Author(s): Longjie Liao, Qimin Xu, Xixiang Liu

Pages: 7497 - 7512

7) Predictive air combat decision model with segmented reward allocation

Author(s): Yundi Li, Yinlong Yuan, Liang Hua

Pages: 7513 - 7530

8) Feature selection for hybrid information systems based on fuzzy covering and fuzzy evidence theory

Author(s): Xiaoqin Ma, Huanhuan Hu, Yi Xu

Pages: 7531 - 7552

9) MPOCSR: optical chemical structure recognition based on multi-path Vision Transformer

Author(s): Fan Lin, Jianhua Li

Pages: 7553 - 7563

10) TCohPrompt: task-coherent prompt-oriented fine-tuning for relation extraction

Author(s): Jun Long, Zhuoying Yin, Wenti Huang

Pages: 7565 - 7575

11) nHi-SEGA: n-Hierarchy SEmantic Guided Attention for few-shot learning

Author(s): Xinpan Yuan, Shaojun Xie, Luda Wang

Pages: 7577 - 7589

12) Incorporating long-tail data in complex backgrounds for visual surface defect detection in PCBs

Author(s): Liying Zhu, Sen Wang, Xuangang Li

Pages: 7591 - 7604

13) Leveraging hybrid 1D-CNN and RNN approach for classification of brain cancer gene expression

Author(s): Heba M. Afify, Kamel K. Mohammed, Aboul Ella Hassanien

Pages: 7605 - 7617

14) Rdfinet: reference-guided directional diverse face inpainting network

Author(s): Qingyang Chen, Zhengping Qiang, Fei Dai

Pages: 7619 - 7630

15) A counterfactual explanation method based on modified group influence function for recommendation

Author(s): Yupu Guo, Fei Cai, Xin Zhang

Pages: 7631 - 7643

16) PPSO and Bayesian game for intrusion detection in WSN from a macro perspective

Author(s): Ning Liu, Shangkun Liu, Wei-Min Zheng

Pages: 7645 - 7659

17) Incomplete multi-view partial multi-label classification via deep semantic structure preservation

Author(s): Chaoran Li, Xiyin Wu, Xiaohuan Lu

Pages: 7661 - 7679

18) CL-fusionBEV: 3D object detection method with camera-LiDAR fusion in Bird’s Eye View

Author(s): Peicheng Shi, Zhiqiang Liu, Aixi Yang

Pages: 7681 - 7696

19) Negation of permutation mass function in random permutation sets theory for uncertain information modeling

Author(s): Yongchuan Tang, Rongfei Li, Yubo Huang

Pages: 7697 - 7709

20) Adaptive multi-stage evolutionary search for constrained multi-objective optimization

Author(s): Huiting Li, Yaochu Jin, Ran Cheng

Pages: 7711 - 7740

21) A FDA-based multi-robot cooperation algorithm for multi-target searching in unknown environments

Author(s): Wenwen Ye, Jia Cai, Shengping Li

Pages: 7741 - 7764

22) Latent-SDE: guiding stochastic differential equations in latent space for unpaired image-to-image translation

Author(s): Xianjie Zhang, Min Li, Yusen Zhang

Pages: 7765 - 7775

23) Self-selective receptive field network for person re-identification

Author(s): Shaoqi Hou, Xueting liu, Zhiguo Wang

Pages: 7777 - 7797

24) HSC: a multi-hierarchy descriptor for loop closure detection in overhead occlusion scenes

Author(s): Weilong Lv, Wei Zhou, Gang Wang

Pages: 7799 - 7823

25) HRDLNet: a semantic segmentation network with high resolution representation for urban street view images

Author(s): Wenyi Chen, Zongcheng Miao, Guokai Shi

Pages: 7825 - 7844

26) A learning-based model predictive control scheme for injection speed tracking in injection molding process

Author(s): Zhigang Ren, Jianpu Cai, Zongze Wu

Pages: 7845 - 7861

27) A novel iteration scheme with conjugate gradient for faster pruning on transformer models

Author(s): Jun Li, Yuchen Zhu, Kexue Sun

Pages: 7863 - 7875

28) An improved cross-domain sequential recommendation model based on intra-domain and inter-domain contrastive learning

Author(s): Jianjun Ni, Tong Shen, Yang Gu

Pages: 7877 - 7892

29) Segmentation-aware relational graph convolutional network with multi-layer CRF for nested named entity recognition

Author(s): Daojun Han, Zemin Wang, Juntao Zhang

Pages: 7893 - 7905

30) DCASAM: advancing aspect-based sentiment analysis through a deep context-aware sentiment analysis model

Author(s): Xiangkui Jiang, Binglong Ren, Hong Li

Pages: 7907 - 7926

31) Repmono: a lightweight self-supervised monocular depth estimation architecture for high-speed inference

Author(s): Guowei Zhang, Xincheng Tang, Shangfeng Jiang

Pages: 7927 - 7941

32) Generalized spatial–temporal regression graph convolutional transformer for traffic forecasting

Author(s): Lang Xiong, Liyun Su, Feng Zhao

Pages: 7943 - 7964

33) Integration of attention mechanism and CNN-BiGRU for TDOA/FDOA collaborative mobile underwater multi-scene localization algorithm

Author(s): Duo Peng, Ming Shuo Liu, Kun Xie

Pages: 7965 - 7986

34) Optimizing long-short term memory neural networks for electroencephalogram anomaly detection using variable neighborhood search with dynamic strategy change

Author(s): Branislav Radomirovic, Nebojsa Bacanin, Miodrag Zivkovic

Pages: 7987 - 8009

35) A teacher-guided early-learning method for medical image segmentation from noisy labels

Author(s): Shangkun Liu, Minghao Zou, Weimin Zheng

Pages: 8011 - 8026

36) Online optimal tracking control of unknown nonlinear singularly perturbed systems using single network adaptive critic with improved learning

Author(s): Zhijun Fu, Bao Ma, Yuming Yin

Pages: 8027 - 8041

37) A multi-level collaborative self-distillation learning for improving adaptive inference efficiency

Author(s): Likun Zhang, Jinbao Li, Yahong Guo

Pages: 8043 - 8061

38) Swarm mutual learning

Author(s): Kang Haiyan, Wang Jiakang

Pages: 8063 - 8077

39) Real-time vision-inertial landing navigation for fixed-wing aircraft with CFC-CKF

Author(s): Guanfeng Yu, Lei Zhang, Zhengjun Zhai

Pages: 8079 - 8093

40) MFPIDet: improved YOLOV7 architecture based on multi-scale feature fusion for prohibited item detection in complex environment

Author(s): Lang Zhang, Zhan Ao Huang, Xi Wu

Pages: 8095 - 8108

41) A novel local feature fusion architecture for wind turbine pitch fault diagnosis with redundant feature screening

Author(s): Chuanbo Wen, Xianbin Wu, Junjie Yang

Pages: 8109 - 8125

42) Location-routing optimization of UAV collaborative blood delivery vehicle distribution on complex roads

Author(s): Zhiyi Meng, Ke Yu, Rui Qiu

Pages: 8127 - 8141

43) SDGSA: a lightweight shallow dual-group symmetric attention network for micro-expression recognition

Author(s): Zhengyang Yu, Xiaojuan Chen, Chang Qu

Pages: 8143 - 8162

44) POI recommendation by deep neural matrix factorization integrated attention-aware meta-paths

Author(s): Xiaoyan Li, Shenghua Xu, Xuan He

Pages: 8163 - 8177

45) TARGCN: temporal attention recurrent graph convolutional neural network for traffic prediction

Author(s): He Yang, Cong Jiang, Xinke Bai

Pages: 8179 - 8196

46) Molecular subgraph representation learning based on spatial structure transformer

Author(s): Shaoguang Zhang, Jianguang Lu, Xianghong Tang

Pages: 8197 - 8212

47) TSKPD: twin structure key point detection in point cloud

Author(s): Yangyue Feng, Xiaokang Yang, Jinfang Jin

Pages: 8213 - 8231

48) A hybrid neural combinatorial optimization framework assisted by automated algorithm design

Author(s): Liang Ma, Xingxing Hao, Li Chen

Pages: 8233 - 8247

49) Hybrid attentive prototypical network for few-shot action recognition

Author(s): Zanxi Ruan, Yingmei Wei, Yuxiang Xie

Pages: 8249 - 8272

50) GVP-RRT: a grid based variable probability Rapidly-exploring Random Tree algorithm for AGV path planning

Author(s): Yaozhe Zhou, Yujun Lu, Liye Lv

Pages: 8273 - 8286

51) A general supply-inspect cost framework to regulate the reliability-usability trade-offs for few-shot inference

Author(s): Fernando Martínez-Plumed, Gonzalo Jaimovitch-López, José Hernández-Orallo

Pages: 8287 - 8317

52) A DQN based approach for large-scale EVs charging scheduling

Author(s): Yingnan Han, Tianyang Li, Qingzhu Wang

Pages: 8319 - 8339

53) Adaptive dynamic programming-based multi-fault tolerant control of reconfigurable manipulator with input constraint

Author(s): Zhenguo Zhang, Tianhao Ma, Fan Zhou

Pages: 8341 - 8353

54) Accuracy is not enough: a heterogeneous ensemble model versus FGSM attack

Author(s): Reham A. Elsheikh, M. A. Mohamed, Mohamed Maher Ata

Pages: 8355 - 8382

55) Graph convolutional networks with the self-attention mechanism for adaptive influence maximization in social networks

Author(s): Jianxin Tang, Shihui Song, Jitao Qu

Pages: 8383 - 8401

56) Enhanced EDAS methodology for multiple-criteria group decision analysis utilizing linguistic q-rung orthopair fuzzy hamacher aggregation operators

Author(s): Jawad Ali, Waqas Ali, Muhammad I. Syam

Pages: 8403 - 8432

57) Integration of a novel 3D chaotic map with ELSS and novel cross-border pixel exchange strategy for secure image communication

Author(s): Sajid Khan, Hao Peng, Namra Mukhtar

Pages: 8433 - 8465

58) SAGB: self-attention with gate and BiGRU network for intrusion detection

Author(s): Zhanhui Hu, Guangzhong Liu, Siqing Zhuang

Pages: 8467 - 8479

59) A collision-free transition path planning method for placement robots in complex environments

Author(s): Yanzhe Wang, Qian Yang, Weiwei Qu

Pages: 8481 - 8500

60) A spherical Z-number multi-attribute group decision making model based on the prospect theory and GLDS method

Author(s): Meiqin Wu, Sining Ma, Jianping Fan

Pages: 8501 - 8524