#objects: laboratory

[simsbeshoppin]

Soloriya's Little Chemist from TSR

[simdertalia]

🧬⚗️ ACNH Bug Museum - Part 5 🔬🧪

Sims 4, base game compatible, the steam versions of 3 items requires Cats & Dogs for the animation to show up | 51 items 💗

This part focuses on the laboratory room. I've added extra swatches to many of the items.Plants are in Part 1. More objects in Part 2. Butterfly exhibit room in Part 3. In-wall cages and other decor in Part 4. At last, the final set for the bug museum collection is finished! 🥳

I hope you enjoy! ☺️💗 *Remember to pay attention to poly numbers if you have an older computer.

Always suggested: bb.objects ON, it makes placing items much easier. For further placement tweaking, check out the TOOL mod.

Use the 0,9 keyboard feature to raise items or lower them

Use the scale up & down feature on your keyboard to make the items larger or smaller to your liking. If you have a non-US keyboard, it may be different keys depending on which alphabet it uses.

Set contains: Buy: -Beaker | 4 swatches | 230 poly -Cabinet | 2 swatches | 1002 poly -Cabinet Light (glows in the dark) | 1 swatch | 354 poly -Computer 1 (decor) | 1 swatch | 1334 poly -Computer 2 (decor) | 1 swatch | 1202 poly -Container | 1 swatch | 550 poly -Containers 1 | 6 swatches | 1932 poly each -Containers 2 | 1 swatch | 1658 poly -Counter Corner (many slots) | 2 swatches | 1762 poly -Counter Right (many slots) | 1 swatch | 1860 poly -Cup of Coffee (2 items: steam & non-steam versions) | 6 swatches | 582 poly -DNA (glows in the dark) | 4 swatches | 1057 poly -Electrical Outlet | 1 swatch | 1016 poly -Experiment Set (2 items: steam & non-steam versions) | 2 swatches each | 2408 poly each -Flea | 1 swatch | 410 poly -Floor Lamp (glows in the dark) | 1 swatch | 3618 poly -Fly | 1 swatch | 554 poly -Fly Swatter | 4 swatches | 446 poly -Glass Cage Fleas (slotted) | 1 swatch | 4774 poly -Glass Cage Fly (slotted) | 1 swatch | 562 poly -Glass Cage Mosquito (slotted) | 1 swatch | 2712 poly -Glass Cage Paper Kite Butterfly | 1 swatch | 3110 poly -Info Sign | 1 swatch | 466 poly -Jar Single 1-3 (3 items) | 4, 1, & 4 swatches | 116, 166, & 274 poly -Jars 1-4 (4 items) | 1, 4, 4, & 1 swatches | 444, 572, 2178, & 2462 poly -Jars Box | 4 swatches | 1054 poly -Jars Tray | 4 swatch | 736 poly -Microscope | 5 swatches | 1180 poly -Mortar and Pestle | 1 swatch | 146 poly -Mosquito | 1 swatch | 586 poly -Papers | 2 swatches | 106 poly -Petri Dish | 1 swatch | 62 poly -Plant Flytrap | 3 swatches | 1978 poly -Scale (slotted) | 3 swatches | 430 poly -Screen | 1 swatch | 4614 poly -Spray Bottles | 1 swatch | 2918 poly -Spray Bottle Single | 2 swatches | 974 poly -Stool | 3 swatches | 658 poly -Test Tubes | 2 swatches | 332 poly -Tissue | 1 swatch | 402 poly -Wall Pipe | 1 swatch | 836 poly -Wooden Bug Cage | 1 swatch | 2719 poly

Build: -Floor Rubber | 3 swatches | Misc -Walls | 1 swatch | Misc / Masonry

Type “acnh bug museum part 5" into the search query in build mode to find  quickly. You can always find items like this, just begin typing  the title and it will appear.

As always, please let me know if you have any issues! Happy Simming! 💗

📁 SimFileShare (no ads): HERE

📁 Alt Mega Download (still no ads): HERE

🌻 Download on Patreon

Will be public on May 7th, 2025 💗 Midnight CET

Happy Simming! ✨ Some of my CC is early access. If you like my work, please consider supporting me (all support helps me with managing my chronic pain/illness & things have been rough as of late) My flare-ups have been more frequent and intense on top of it all:

★ Patreon  🎉 ❤️ |★ Ko-Fi  ☕️  ❤️ ★ Instagram📷

Thank you for reblogging ❤️ ❤️ ❤️

@sssvitlanz  @maxismatchccworld @mmoutfitters  @coffee-cc-finds  @itsjessicaccfinds  @gamommypeach  @stargazer-sims-finds  @khelga68  @suricringe  @vaporwavesims  @mystictrance15 @moonglitchccfinds @xlost-in-wonderlandx @jbthedisabledvet @fischottersims

Other CC Pictured: The seamless windows that I have used in the preview are the Ava Windows by Mincsims. Heads up that this download is unfortunately on TSR, which I don't jump to share links to due to all of their ads and overall history (nothing against the creators, they are great), but seamless windows are quite hard to find so I have to leave you with a link to t-s-blargh.

The rest of my CC

[thepastisalreadywritten]

[brokenrefraction]

lore meme that literally nobody else will get it except me and my brother

[wayti-blog]

A scientist in his laboratory is not a mere technician: he is also a child confronting natural phenomena that impress him as though they were fairy tales.

― Marie Curie, a Polish and naturalised-French physicist and chemist who conducted pioneering research on radioactivity. She was the first woman to win a Nobel Prize, the first person to win a Nobel Prize twice, and the only person to win a Nobel Prize in two scientific fields. Her husband, Pierre Curie, was a co-winner of her first Nobel Prize, making them the first married couple to win the Nobel Prize (x)

[hysterialabarchive]

Watch out!

-M.A.L.A

[egnolab]

HEY CLIPBOARD umm out of all of your employees, who’s your favorite (if you have one) and your least favorite?

[upsurgecomic]

[atomic-freezer]

Turn around we did for a class. Hoping to model this guy one of these days

[quotelr]

Stopping in the 1970s, "Hybridity" as the fifth and final chapter is less of an end point than a certain realization of the artifice, plasticity, and technology that Wells and Loeb envisioned as the future of the human relationship to living matter as well as of the "catastrophic" situation that Georges Canghuilhem (following Kurt Goldstein) saw in life subjected to the milieu of the laboratory.

Hannah Landecker, Culturing Life: How Cells Became Technologies

[jcmarchi]

A new way to create realistic 3D shapes using generative AI

New Post has been published on https://thedigitalinsider.com/a-new-way-to-create-realistic-3d-shapes-using-generative-ai/

A new way to create realistic 3D shapes using generative AI

Creating realistic 3D models for applications like virtual reality, filmmaking, and engineering design can be a cumbersome process requiring lots of manual trial and error.

While generative artificial intelligence models for images can streamline artistic processes by enabling creators to produce lifelike 2D images from text prompts, these models are not designed to generate 3D shapes. To bridge the gap, a recently developed technique called Score Distillation leverages 2D image generation models to create 3D shapes, but its output often ends up blurry or cartoonish.

MIT researchers explored the relationships and differences between the algorithms used to generate 2D images and 3D shapes, identifying the root cause of lower-quality 3D models. From there, they crafted a simple fix to Score Distillation, which enables the generation of sharp, high-quality 3D shapes that are closer in quality to the best model-generated 2D images.  

     These examples show two different 3D rotating objects: a robotic bee and a strawberry. Researchers used text-based generative AI and their new technique to create the 3D objects.

Image: Courtesy of the researchers; MIT News

Some other methods try to fix this problem by retraining or fine-tuning the generative AI model, which can be expensive and time-consuming.

By contrast, the MIT researchers’ technique achieves 3D shape quality on par with or better than these approaches without additional training or complex postprocessing.

Moreover, by identifying the cause of the problem, the researchers have improved mathematical understanding of Score Distillation and related techniques, enabling future work to further improve performance.

“Now we know where we should be heading, which allows us to find more efficient solutions that are faster and higher-quality,” says Artem Lukoianov, an electrical engineering and computer science (EECS) graduate student who is lead author of a paper on this technique. “In the long run, our work can help facilitate the process to be a co-pilot for designers, making it easier to create more realistic 3D shapes.”

Lukoianov’s co-authors are Haitz Sáez de Ocáriz Borde, a graduate student at Oxford University; Kristjan Greenewald, a research scientist in the MIT-IBM Watson AI Lab; Vitor Campagnolo Guizilini, a scientist at the Toyota Research Institute; Timur Bagautdinov, a research scientist at Meta; and senior authors Vincent Sitzmann, an assistant professor of EECS at MIT who leads the Scene Representation Group in the Computer Science and Artificial Intelligence Laboratory (CSAIL) and Justin Solomon, an associate professor of EECS and leader of the CSAIL Geometric Data Processing Group. The research will be presented at the Conference on Neural Information Processing Systems.

From 2D images to 3D shapes

Diffusion models, such as DALL-E, are a type of generative AI model that can produce lifelike images from random noise. To train these models, researchers add noise to images and then teach the model to reverse the process and remove the noise. The models use this learned “denoising” process to create images based on a user’s text prompts.

But diffusion models underperform at directly generating realistic 3D shapes because there are not enough 3D data to train them. To get around this problem, researchers developed a technique called Score Distillation Sampling (SDS) in 2022 that uses a pretrained diffusion model to combine 2D images into a 3D representation.

The technique involves starting with a random 3D representation, rendering a 2D view of a desired object from a random camera angle, adding noise to that image, denoising it with a diffusion model, then optimizing the random 3D representation so it matches the denoised image. These steps are repeated until the desired 3D object is generated.

However, 3D shapes produced this way tend to look blurry or oversaturated.

“This has been a bottleneck for a while. We know the underlying model is capable of doing better, but people didn’t know why this is happening with 3D shapes,” Lukoianov says.

The MIT researchers explored the steps of SDS and identified a mismatch between a formula that forms a key part of the process and its counterpart in 2D diffusion models. The formula tells the model how to update the random representation by adding and removing noise, one step at a time, to make it look more like the desired image.

Since part of this formula involves an equation that is too complex to be solved efficiently, SDS replaces it with randomly sampled noise at each step. The MIT researchers found that this noise leads to blurry or cartoonish 3D shapes.

An approximate answer

Instead of trying to solve this cumbersome formula precisely, the researchers tested approximation techniques until they identified the best one. Rather than randomly sampling the noise term, their approximation technique infers the missing term from the current 3D shape rendering.

“By doing this, as the analysis in the paper predicts, it generates 3D shapes that look sharp and realistic,” he says.

In addition, the researchers increased the resolution of the image rendering and adjusted some model parameters to further boost 3D shape quality.

In the end, they were able to use an off-the-shelf, pretrained image diffusion model to create smooth, realistic-looking 3D shapes without the need for costly retraining. The 3D objects are similarly sharp to those produced using other methods that rely on ad hoc solutions.

“Trying to blindly experiment with different parameters, sometimes it works and sometimes it doesn’t, but you don’t know why. We know this is the equation we need to solve. Now, this allows us to think of more efficient ways to solve it,” he says.

Because their method relies on a pretrained diffusion model, it inherits the biases and shortcomings of that model, making it prone to hallucinations and other failures. Improving the underlying diffusion model would enhance their process.

In addition to studying the formula to see how they could solve it more effectively, the researchers are interested in exploring how these insights could improve image editing techniques.

This work is funded, in part, by the Toyota Research Institute, the U.S. National Science Foundation, the Singapore Defense Science and Technology Agency, the U.S. Intelligence Advanced Research Projects Activity, the Amazon Science Hub, IBM, the U.S. Army Research Office, the CSAIL Future of Data program, the Wistron Corporation, and the MIT-IBM Watson AI Laboratory.

[literaryvein-reblogs]

some words for worldbuilding (pt. 1)

Air

billow, breath, bubble, draft, effervescence, fumes, puff, vapor

Arena

aquarium, bazaar, coliseum, field, hall, mecca, stage

Building

abbey, architecture, armory, asylum, bakery, bar, booth, cathedral, club, construction, court, department store, dock, edifice, emergency room, factory, food court, fort/fortress, framework, garrison, greasy spoon, hacienda, hangout, headquarters, hotel, inn, institute/institution, jetty, laboratory, mansion, mental hospital, monastery, mosque, museum, nursing home, office, pavilion, penitentiary, plant, prison, rampart, repository, ruins, sanctuary, shrine, skyscraper, stockade, storeroom, structure, temple, theater/theatre, treasury, warehouse, wharf

City

capital, metropolis, town, village

Furniture

altar, banister, bench, booth, bunk, cabinet, chair, couch, crib, davenport, dresser, furnishings, futon, jetty, lectern, partition, perch, platform, pulpit, rail/railing, screen, secretary, stand, wardrobe

Geographic division

area, county, desert, dynasty, kingdom, outskirts, quarter, sector, suburb, territory, tract, zone

Habitat

abode, ecosystem, environmentalist, habitat/habitation, harbor, home, land, nest, paradise, premises, refuge, settlement, tent

Habitat, human: accommodations, apartment, barracks, cabin, castle, condominium, convent, domesticity, dungeon, element, encampment, estate, grange, hacienda, home, house, housing, hut, jail, lodging, madhouse, monastery, neighborhood, old country, palace, prison, reservation, resort, sanctuary, shanty, suite, vacancy, villa

Habitat, rural: barn, burrow, conservatory, desert, farm, forest, grange, jungle, sanctuary, wilderness/wilds, wood/woods

Land

abyss, avalanche, bank, bay, bed, bluff, campus, cape, cavern, cliff, compost, cove, crevice/crevasse, dirt, downgrade, dune, elevation, estuary, expanse, field, fossil, garden, glacier, gorge, green, ground, gulf, harbor, hillock, inlet, knoll, landscape, lawn, lot, marshy, menagerie, mine, moat, mound, mountainous, nature, outlook, park, patio, pit, plateau, plaza, porch, prairie, projection, property, quagmire, ravine, ridge, savanna, shelf, soil, stack, table, trench, tundra, valley, well, wood/woods, yard

Nation

country, home, land, nationality, soil, state

Personal item

adornment, amulet, beads, best-seller, briefcase, cache, cargo, charm, contraceptive, disguise, effects, equipment, favorite, gem, glasses, handbag, jewelry, knickknack, luggage, marionette, memorabilia, necklace, novelty, object d’art, odds-on-favorite, paraphernalia, pledge, possession, pride, puppet, purse, resources, ring, souvenir, stuff, supplies, sustenance, thing/things, trappings, trifle, valuable

Planet

cosmos, Earth, galaxy, moon, planet, sphere, world

Region

capital, commonwealth, quarter, region, settlement, suburb

Room

alcove, attic, bath, bedroom, boutique, cellar, den, enclosure, foyer, gin mill, hall, lavatory, loft, outhouse, parlor, restaurant, saloon, shop, stage, store, tenement, theater/theatre, vestibule

Shape

angular, beaten, billowy, checkered, concave, conical/conic, crescent, curly, deformed, elliptical, flat, gnarled, kinky, misshapen, obtuse, round, shapeless, spiral, straight

Vehicle

camper, conveyance, motorcade, transport

Vehicle, air: aircraft, armada, blimp, dirigible, helicopter, shuttle, UFO

Vehicle, land: ambulance, bicycle, car, cherry-picker, dolly, excavator, model, traffic, truck

Vehicle, water: armada, boat, craft, fleet, sailboat, yacht

Water

abyss, aqueduct, basin, beach, blackball, brook, cape, channel, condensation, creek, deep, estuary, fountain, gulf, heading, inlet, lake, oasis, pond, promontory, reservoir, sea, spray, strait, tide, wash, wave, whirlpool

NOTE

The above are concepts classified according to subject and usage. It not only helps writers and thinkers to organize their ideas but leads them from those very ideas to the words that can best express them.

It was, in part, created to turn an idea into a specific word. By linking together the main entries that share similar concepts, the index makes possible creative semantic connections between words in our language, stimulating thought and broadening vocabulary. Writing Resources PDFs

Source ⚜ Writing Basics & Refreshers ⚜ On Vocabulary

[ancientcharm]

Pompeii. New discoveries

A bird of prey stands out in the upper part of the lararium. The raptor, which can probably be identified as an eagle, holds a palm branch in its claws. In the lower part, the scene consists of two snakes facing each other which frame an altar with a fluted circular shaft on which offerings are placed. From the left, it is possible to distinguish the following features:  a pine cone, a raised element that supports an egg, and what appear to be a fig and a date. The background of the scene is filled with two bushes with lanceolate leaves and red and yellow berries on which three sparrows move about. Several interesting finds were discovered inside the niche: ritual objects, left as part of a last offering before the eruption that destroyed Pompeii in AD 79: an incense burner in achromatic clay with missing pieces dating from antiquity and a lamp, both displaying clear signs of burning. Laboratory analyses have made it possible to identify the remains of twigs of aromatic plants, while two parts of a dried fig were found behind the two objects. Two strips of coloured marble were discovered on the flat top of the altar together with a third element, presumably made of red marble, with the depiction of a face ascribable to the Dionysian world, probably a Silenus.

Text from the article by pompeiisites.org (October 2024) Photos provided by pompeiisites.org

[stealingyourbones]

Zeta Beams are a very finicky and powerful technology that require specific conditions to work properly.

Being shot with an unknown ray from one of Lex Luthors guns mid zeta was not one of those conditions.

Superboy, reappearing out of the zeta beam, now dazed and confused, stumbles and leans against the closest solid object and takes in his surroundings.

He’s in a lab of some sort, and whoever used it knew a wide variety of sciences. Chemistry equipment consolidated to one corner of the room while a mildly cluttered bench of mechanisms, welding equipment, and doohickeys take over another corner of the room. The entire workplace was bathed in a toxic green light coming from…

Kon turned and gawked at the massive swirling green vortex and pushed off the metal edge of the tear in reality that he had been leaning on.

His mind was running miles a minute. He was meant to be at the Watchtower and he’s here in some windowless laboratory and a portal that looks like something straight out of science fiction. He doesn’t know what to do but all of his scrambling thoughts screeched to a halt the moment he heard footsteps and an unknown heartbeat coming down a set of stairs he hadn’t noticed on his quick scan of the room.

He should have flown to the ceiling and hid or used his X-Ray vision to identify the threat but he was reeling so badly he just stood frozen in place, a foot or two away from the portal casting a long shadow that cut through the violently green glow.

A man in an orange jumpsuit barrels down the stairs with- is that a bazooka?

The orange wall of a human man whipped around the barrel to face him. “DIE GHOST!”.

“I’m sorry what?”

Kon didn’t get a verbal answer but he sure as hell got a physical one. The man pulled the trigger and a glowing green bullet of *something* shot towards him. Kon momentarily debated dodging out of the way with his super speed but thought better of it. Robin would tell him to stay still and show the threat that he couldn’t be harmed to shut down the fight before it could escalate any further.

Blocking his face from debris, Kon closes his eyes and lets the projectile make contact.

He expected to be thrown back into the strange vortex portal thing or feel the impact, but to his surprise he felt absolutely nothing. Whatever glowing green and white metallic stuff he was hit with, he was completely invulnerable to as a half Kryptonian.

(It is at this point where I sped the writing along to bullet point outlines)

- Kon goes hey wtf man I’m not a ghost

- Jack doesn’t buy it it might be a ghost trick.

- Jack slowly walks up to Kon with a Fenton bat.

- Kon stares at him arms crossed. He knows now he can’t be hurt

- Jack, making full eye contact with Kon and goes ‘you can’t fool me ghost’ or something and hits him over the head with the bat.

- Bat shatters over Kon’s head as Kon stares at him and does a “are you done?”

- as he says this Jack Fenton slowly raises a lipstick lazer

- Jack turns on lazer and Kon glares at Jack exasperatedly.

- Kon’s patience runs out. He grabs the lazer from jacks hands and crushes it in his palm.

- I’m not a ghost man. I was trying to zeta to the watchtower and now I’m here now can you stop??

- Jack doesn’t understand what those words mean. Mutters that this might be a fascinating new discovery and goes over to the tech corner

- Grabs a tsa metal detector wand looking thing and waves it over Kon, who hasnt moved and is now curious to see what this man will do knowing now that he can’t be hurt. (Later found that this universe boosts his powers a tad which is making him More Invulnerable)

- It beeps and jack looks at it and his face of confusion turns to a massive grin. He turns towards the stairs and shouts to Maddie that they have a extradimensional non ghost guest and to move the ghost gear out of the guest room.

- Kon is like what the shit why did this mans attitude chanhe so much

- kon is then temporarily housed by the Fentons whilst they are delighted to start on a new big project. they plan to make an addition onto the ghost zone portal to find the frequency of other dimensions and make a gateway between them using Kon as the tuning fork to find his dimension.

[hysterialabarchive]

Shambler

This slow moving creature was pretty easy to capture, seeing as we caught it out in the open. Being an ambush predator, the extraction team was lucky catching it off guard. This one is a more recent capture, so we have limited biological information.

--MALA

[egnolab]

Does anyone here hate paper

Clipboard does

(Old doodle. There’s also one of Paper jumping him. But I don’t like it..)