#types of data analysis in research

[researchers-me]

Unlock the power of data analysis with insights from our comprehensive guide! Join Researchers.me and stay at the forefront of analytics.

Read More : https://www.researchers.me/blog/research-of-data-analysis-and-different-types-of-analysis/

[floraleevee]

!!!!!!!!

[jcmarchi]

Study Reveals a Universal Pattern of Brain Wave Frequencies - Technology Org

New Post has been published on https://thedigitalinsider.com/study-reveals-a-universal-pattern-of-brain-wave-frequencies-technology-org/

Study Reveals a Universal Pattern of Brain Wave Frequencies - Technology Org

Throughout the brain’s cortex, neurons are arranged in six distinctive layers, which can be readily seen with a microscope. A team of MIT and Vanderbilt University neuroscientists has now found that these layers also show distinct patterns of electrical activity, which are consistent over many brain regions and across several animal species, including humans.

A brain 3D model – illustrative photo. Image credit: Lisa Yount via Unsplash, free license

The researchers found that in the topmost layers, neuron activity is dominated by rapid oscillations known as gamma waves. In the deeper layers, slower oscillations called alpha and beta waves predominate. The universality of these patterns suggests that these oscillations are likely playing an important role across the brain, the researchers say.

“When you see something that consistent and ubiquitous across cortex, it’s playing a very fundamental role in what the cortex does,” says Earl Miller, the Picower Professor of Neuroscience, a member of MIT’s Picower Institute for Learning and Memory, and one of the senior authors of the new study.

Imbalances in how these oscillations interact with each other may be involved in brain disorders such as attention deficit hyperactivity disorder, the researchers say.

[embedded content]

“Overly synchronous neural activity is known to play a role in epilepsy, and now we suspect that different pathologies of synchrony may contribute to many brain disorders, including disorders of perception, attention, memory, and motor control. In an orchestra, one instrument played out of synchrony with the rest can disrupt the coherence of the entire piece of music,” says Robert Desimone, director of MIT’s McGovern Institute for Brain Research and one of the senior authors of the study.

André Bastos, an assistant professor of psychology at Vanderbilt University, is also a senior author of the open-access paper, which appears in Nature Neuroscience. The lead authors of the paper are MIT research scientist Diego Mendoza-Halliday and MIT postdoc Alex Major.

Layers of activity

The human brain contains billions of neurons, each of which has its own electrical firing patterns. Together, groups of neurons with similar patterns generate oscillations of electrical activity, or brain waves, which can have different frequencies. Miller’s lab has previously shown that high-frequency gamma rhythms are associated with encoding and retrieving sensory information, while low-frequency beta rhythms act as a control mechanism that determines which information is read out from working memory.

His lab has also found that in certain parts of the prefrontal cortex, different brain layers show distinctive patterns of oscillation: faster oscillation at the surface and slower oscillation in the deep layers. One study, led by Bastos when he was a postdoc in Miller’s lab, showed that as animals performed working memory tasks, lower-frequency rhythms generated in deeper layers regulated the higher-frequency gamma rhythms generated in the superficial layers.

In addition to working memory, the brain’s cortex also is the seat of thought, planning, and high-level processing of emotion and sensory information. Throughout the regions involved in these functions, neurons are arranged in six layers, and each layer has its own distinctive combination of cell types and connections with other brain areas.

“The cortex is organized anatomically into six layers, no matter whether you look at mice or humans or any mammalian species, and this pattern is present in all cortical areas within each species,” Mendoza-Halliday says. “Unfortunately, a lot of studies of brain activity have been ignoring those layers because when you record the activity of neurons, it’s been difficult to understand where they are in the context of those layers.”

In the new paper, the researchers wanted to explore whether the layered oscillation pattern they had seen in the prefrontal cortex is more widespread, occurring across different parts of the cortex and across species.

Using a combination of data acquired in Miller’s lab, Desimone’s lab, and labs from collaborators at Vanderbilt, the Netherlands Institute for Neuroscience, and the University of Western Ontario, the researchers were able to analyze 14 different areas of the cortex, from four mammalian species. This data included recordings of electrical activity from three human patients who had electrodes inserted in the brain as part of a surgical procedure they were undergoing.

Recording from individual cortical layers has been difficult in the past, because each layer is less than a millimeter thick, so it’s hard to know which layer an electrode is recording from. For this study, electrical activity was recorded using special electrodes that record from all of the layers at once, then feed the data into a new computational algorithm the authors designed, termed FLIP (frequency-based layer identification procedure). This algorithm can determine which layer each signal came from.

“More recent technology allows recording of all layers of cortex simultaneously. This paints a broader perspective of microcircuitry and allowed us to observe this layered pattern,” Major says. “This work is exciting because it is both informative of a fundamental microcircuit pattern and provides a robust new technique for studying the brain. It doesn’t matter if the brain is performing a task or at rest and can be observed in as little as five to 10 seconds.”

Across all species, in each region studied, the researchers found the same layered activity pattern.

“We did a mass analysis of all the data to see if we could find the same pattern in all areas of the cortex, and voilà, it was everywhere. That was a real indication that what had previously been seen in a couple of areas was representing a fundamental mechanism across the cortex,” Mendoza-Halliday says.

Maintaining balance

The findings support a model that Miller’s lab has previously put forth, which proposes that the brain’s spatial organization helps it to incorporate new information, which carried by high-frequency oscillations, into existing memories and brain processes, which are maintained by low-frequency oscillations. As information passes from layer to layer, input can be incorporated as needed to help the brain perform particular tasks such as baking a new cookie recipe or remembering a phone number.

“The consequence of a laminar separation of these frequencies, as we observed, may be to allow superficial layers to represent external sensory information with faster frequencies, and for deep layers to represent internal cognitive states with slower frequencies,” Bastos says. “The high-level implication is that the cortex has multiple mechanisms involving both anatomy and oscillations to separate ‘external’ from ‘internal’ information.”

Under this theory, imbalances between high- and low-frequency oscillations can lead to either attention deficits such as ADHD, when the higher frequencies dominate and too much sensory information gets in, or delusional disorders such as schizophrenia, when the low frequency oscillations are too strong and not enough sensory information gets in.

“The proper balance between the top-down control signals and the bottom-up sensory signals is important for everything the cortex does,” Miller says. “When the balance goes awry, you get a wide variety of neuropsychiatric disorders.”

The researchers are now exploring whether measuring these oscillations could help to diagnose these types of disorders. They are also investigating whether rebalancing the oscillations could alter behavior — an approach that could one day be used to treat attention deficits or other neurological disorders, the researchers say.

The researchers also hope to work with other labs to characterize the layered oscillation patterns in more detail across different brain regions.

“Our hope is that with enough of that standardized reporting, we will start to see common patterns of activity across different areas or functions that might reveal a common mechanism for computation that can be used for motor outputs, for vision, for memory and attention, et cetera,” Mendoza-Halliday says.

Written by Anne Trafton

Source: Massachusetts Institute of Technology

You can offer your link to a page which is relevant to the topic of this post.

[reasonsforhope]

"A new study reveals the profound ecological effects of wolves and other large carnivores in Yellowstone National Park, showcasing the cascading effects predators can have on ecosystems. In Yellowstone, this involves wolves and other large carnivores, elk, and willows.

The research, which utilized previously published data from 25 riparian (streamside) sites and collected over a 20 year period, from 2001 to 2020, revealed a remarkable 1,500% increase in willow crown volume along riparian zones [note: riparian means in/around rivers] in northern Yellowstone National Park, driven by the effects on elk due to a restored large carnivore guild following the reintroduction of wolves in 1995–96, and other factors...

Pictured: Upstream view of Blacktail Deer Creek in 2005 and 2021, northern range of Yellowstone National Park.

Trophic cascades, the effects of predators on herbivores and plants, have long been a topic of ecological interest. The study quantifies the strength of this phenomenon for the first time using willow crown volume as a proxy for aboveground biomass, demonstrating a significant three-dimensional recovery of riparian vegetation represented by the growth in both crown area and height of established willows.

The strength of the Yellowstone trophic cascade observed in this study surpasses 82% of strengths presented in a synthesis of global trophic cascade studies, underscoring the strength of Yellowstone's willow recovery process. The authors note that there is considerable variability in the degree of recovery and not all sites are recovering.

Even though riparian areas in the western United States comprise a small portion of the landscape, the study has particular relevance since these areas provide important food resources and habitat for more wildlife species than any other habitat type. These areas also connect upland and aquatic ecosystems and are widely known for their high diversity in species composition, structure, and productivity.

"Our findings emphasize the power of predators as ecosystem architects," said William Ripple. "The restoration of wolves and other large predators has transformed parts of Yellowstone, benefiting not only willows but other woody species such as aspen, alder, and berry-producing shrubs. It's a compelling reminder of how predators, prey, and plants are interconnected in nature."

Pictured: An across channel view in 2005 and 2021 of a downstream reach on Blacktail Deer Creek, northern range of Yellowstone National Park.

Wolves were eradicated and cougars driven to low numbers from Yellowstone National Park by the 1920s. Browsing by elk soon increased, severely damaging the park's woody vegetation, especially in riparian areas. Similar effects were seen in places like Olympic National Park in Washington, and Banff and Jasper National Parks in Canada after wolves were lost.

While it's well understood that removing predators can harm ecosystems, less is known about how strongly woody plants and ecosystems recover when predators are restored. Yellowstone offers a rare opportunity to study this effect since few studies worldwide have quantified how much plant life rebounds after large carnivores are restored.

"Our analysis of a long-term data set simply confirmed that ecosystem recovery takes time. In the early years of this trophic cascade, plants were only beginning to grow taller after decades of suppression by elk. But the strength of this recovery, as shown by the dramatic increases in willow crown volume, became increasingly apparent in subsequent years," said Dr. Robert Beschta, an emeritus professor at Oregon State University.

"These improving conditions have created vital habitats for birds and other species, while also enhancing other stream-side conditions."

The research points to the utility of using crown volume of stream-side shrubs as a key metric for evaluating trophic cascade strength, potentially advancing methods for riparian studies in other locations. It also contextualizes the value of predator restoration in fostering biodiversity and ecosystem resilience."

-via Phys.org, February 6, 2025

[0o-junebug-o0]

First Meeting

summary: You're having difficulty with some code so you stop by Penelope's house for help, unaware that she has a guest. Spencer takes one look at you and is immediately head over heels.

genre: fluff

cw: meet cute (is it a meet cute?) completely gn!reader (reader is not described at all), no use of y/n, autistic!spencer (because every spencer is autistic!spencer), season 1 spencer, university/college student reader, talk about research and coding, pov switch from reader to spencer

wordcount: 1.5k

a/n: this is an actual error I had this summer when writing my spectra analysis code

You lean back in your chair with a sigh, scowling at the code you’re trying to write. You’re still relatively new to coding, the first time you ever took a class on it was just under two years ago, so this code has taken you significantly more time to write than it would have taken Penelope. But you’ve written it. You read through the code again and rerun it. Everything runs fine, the code should work, but it doesn’t. 

You rub your eyes and groan with frustration. You should be able to get a wavelength solution out of this. The professor you’re doing research with told you what you need to do to get the wavelength solution and then how to use it to find the redshift of the lensed galaxy and the foreground lensing galaxy, but nothing is lining up!

You’ve opened the data, plotted the variation in flux for each line in the image, fit a Gaussian to it to get the brightest point, and converted the pixel value of that point to vacuum wavelength, but none of the wavelengths you’re finding match up with what lines should be present in the spectra for this lamp type!

You briefly consider emailing your professor but decide against it. Even though he told you that asking him things wouldn’t bother him and that it’s his job, you don’t want to take up more of his time than you already have. 

You look around your apartment for anything that might help. Your eyes land on your keychain and the spare key Penelope gave you because she enjoys it when you stop by. You quickly shut your laptop, tucking it under your arm, grab your keys, slip on a pair of shoes, and make your way down the hall to Penelope’s apartment, not bothering to lock the door behind you. 

_____

Spencer sits awkwardly on one of Garcia’s kitchen stools, tapping his fingers on the Tardis mug she had filled with tea and given him. He’s not exactly sure why Garcia invited him over. She said she wanted to bond, but they’ve known each other for almost two years now, and Spencer considers her a good friend, so he doesn’t really know what bonding entails. So far, Garcia has just been bustling around her kitchen preparing snacks and drinks for their Doctor Who marathon.

The lock clicks and Spencer’s head whips toward the door just in time for it to burst open. Spencer freezes and stares at you in awe and confusion. 

“Penny!” you cry, your voice a mixture of a shout and a whine. 

Garcia calls your name with a surprised look. “What happened? Are you alright?”

“What?” you ask. Then you wave your hand flippantly. “Yeah I’m fine, I just need help with some code.” Your eyes land on Spencer and he can feel his heart rate increase. He really hopes his face isn’t as red as it feels. 

���Oh, sorry, I didn’t know you had someone over,” you say. “I can, um, I can come back later.”

Spencer watches as your posture stiffens slightly and you start to fiddle with your keychain. 

Spencer opens his mouth to reassure you but Garcia beats him to it. “No, no, it’s fine,” she says. “I’ve been wanting you two to meet anyway.” You shoot Spencer a small, awkward smile and wave from across the room when Garcia shares your name. When she introduces him, your eyes widen and you look toward Garcia with an expression Spencer can’t decipher and mouth something to her that makes her laugh loudly. 

Spencer can feel himself flushing at your reaction and takes a sip of his tea to hide his face.

“Anyway!” Garcia says cheerfully. “Do you mind if I help them real quick?”

“Go ahead,” Spencer responds, trying to sound as nonchalant as possible. It’s difficult with you there, though, all his thoughts suddenly seem much harder to grasp. Like your presence is forcing them aside. 

Your eyes seem to linger on him for a moment before you head over to the counter and set your laptop down. “Right,” you mutter, opening it and entering the password. Spencer listens intently as you describe to Garcia what your code should be doing and he can’t help but smile at the clear passion in your voice. It sends butterflies to his stomach. 

“What do you study?” Spencer blurts out. 

You close your mouth and cock your head at him for a moment. “I’m, uh, I’m studying astrophysics. Specifically strong gravitational lensing. I’ve already made preliminary models of the system and I’m just working on analyzing the spectra now.”

Spencer nods and leans over to look at your code. 

“Do you want to help Penny find the issue?” you ask. You sound a bit nervous and Spencer looks up and smiles what he hopes is a soothing smile.

“I would if I could. I really don’t know how to code, though.”

“Seriously?” you ask. Spencer cocks his head at the tone of surprise in your voice. “Sorry, it’s just that Penny has told me a lot about you and about how you’re a genius and have three PhDs, which is insanely impressive by the way, so I guess I’m just surprised you don’t know something.”

“There’s a lot I don’t know,” Spencer admits. “Coding and other technological things are some of it. I don’t know too much about astrophysics either.” That’s not exactly true but it isn’t a lie either. He’s read papers on several astrophysical topics but he’s never come across one on strong lensing before. But the truth of the statement is irrelevant, the only reason he said it was to find an excuse to spend more time with you.

You smile and Spencer’s stomach feels like it does a backflip. “I won’t be much help teaching you how to code, Penny would be better for that, but I can tell you about some astro stuff at some point.”

“Alright, lovebirds,” Garcia teases and Spencer’s face burns. “Let’s focus.” You nod, clearly also a bit embarrassed, and turn back to your laptop.

“How about I go line by line and tell you what it should do and you let me know if something doesn’t do what I think it does,” you say. Garcia nods and both she and Spencer follow along as you point to and describe each line of code. You get to a printed image of the data file you’re analyzing before Garcia stops you.

“Can you open the file on your computer?” she asks.

You nod and open the file in a new application and move it so it’s side by side with the image in your code. “Wait,” you mutter, glancing back and forth between the two images. “Is that seriously the issue?” Spencer leans forward to get a closer look, the x-axes of the images are flipped. 

You throw your head back with a groan and change the rotation of the file in your code. “I swear, if this works,” you growl. The clear exasperation in your tone makes Spencer chuckle slightly. 

You rerun the code and compare several of the outputs to a list of wavelengths before groaning again and letting your head fall onto the counter. “I hate Python,” you grumble. “Why does it have to switch the axes!” 

Garcia laughs and pats you on the back. You raise your head off the counter and tap your forehead against her shoulder in a gesture Spencer assumes expresses gratitude. “Thanks, Penny,” you sigh. “You’re the best.”

“Of course I am!”

“Oh, and Spencer,” you say, turning to look at him. “We should get lunch sometime. I can tell you about astrophysics and you can tell me about all the crazy things you know.”

“I-I would love that,” Spencer stutters, unable to speak clearly with you looking into his eyes. He's hardly able to wrap his head around the fact that someone as beautiful as you would want to spend more time with him. Spencer's not sure whether you’re asking him on a date or just to go out as friends, but he doesn’t care either way as long as he gets to spend more time with you.

“Great!” you say happily. You stand and cross the room to quickly grab one of Garcia’s pens before returning. You hold the fluffy pink pen with a smile on your face and hold out your hand for his. “May I?” you ask. 

Spencer’s eyes widen and he nods, setting his hand in yours despite his usual aversion to touch. The contact makes his heart feel like it’s about to burst from his chest. You scrawl your number across the back of his hand before handing Spencer the pen and holding out your hand for him to do the same. He writes his number on your hand and watches in a sort of daze as you gather your computer and keys and wave goodbye before leaving.

Spencer jumps slightly as Garcia ruffles his hair. He looks over at her to see a knowing smile on her face. Spencer blushes and hides his face in his hands. “Shut up,” he grumbles, embarrassed.

“No way,” she laughs. “Derek’s going to have a field day with this. Boy genius has a crush!”

_____

REQUESTS ARE OPEN!

Taglist!: fill out this form if you want to be tagged when I post fics

@daryls-crossbow16 @roboticsuccubus83 @nemobee777 @dorcas4meadowes @spenciesslut @Idfk17 @pleasantwitchgarden @angeliccss @novaana @moonysreid @cynbx @dead-universe @starlighta

[literaryvein-reblogs]

How to Read a Scientific Article

THE THREE-PASS APPROACH

The key idea is that you should read the paper in up to 3 passes, instead of starting at the beginning and plowing your way to the end.

Each pass accomplishes specific goals and builds upon the previous pass:

The first pass gives you a general idea about the paper.

The second pass lets you grasp the paper’s content, but not its details.

The third pass helps you understand the paper in depth.

At the end of the first pass, you should be able to answer the 5 Cs:

Category: What type of paper is this? A measurement paper? An analysis of an existing system? A description of a research prototype?

Context: Which other papers is it related to? Which theoretical bases were used to analyze the problem?

Correctness: Do the assumptions appear to be valid?

Contributions: What are the paper’s main contributions?

Clarity: Is the paper well written?

Purpose of the Sections of Empirical Articles

Section — Use it for

Abstract — This is a great section to read to find out if the article will be relevant to your own research.

Introduction — This section gives you an overview of work that has been done on topics relating to the hypothesis of the article, and will often lead you to other relevant work that has been done in your area of interest.

Method — This section will help you understand the design of the experiment. This is particularly useful if you'd like to replicate the study.

Results — The results will tell you what the author/s found in the course of their experiment.

Discussion — The discussion section is typically easier to read than the method and results section, and it will help the reader understand the implications of the results of the experiment.

References — This is a great place to look to find articles that are related to the one you are reading. If you're looking to build your own literature review, the references are a great place to start.

The Anatomy of a Scientific Paper

Some initial guidelines for how to read a paper:

Read critically: Reading a research paper must be a critical process. You should not assume that the authors are always correct. Instead, be suspicious. Critical reading involves asking appropriate questions.

Read creatively: Reading a paper critically is easy, in that it is always easier to tear something down than to build it up. Reading creatively involves harder, more positive thinking.

Make notes as you read the paper. Use whatever style you prefer. If you have questions or criticisms, write them down so you do not forget them. Underline key points the authors make. Mark the data that is most important or that appears questionable. Such efforts help the first time you read a paper and pay big dividends when you have to re-read a paper after several months.

After the first read-through, try to summarize the paper in one or two sentence.

If possible, compare the paper to other works.

Write a review that includes:

a one or two sentence summary of the paper.

a deeper, more extensive outline of the main points of the paper, including for example assumptions made, arguments presented, data analyzed, and conclusions drawn.

any limitations or extensions you see for the ideas in the paper.

your opinion of the paper; primarily, the quality of the ideas and its potential impact.

The guide below details how to read a scientific article step-by-step.

First, you should not approach a scientific article like a textbook— reading from beginning to end of the chapter or book without pause for reflection or criticism. Additionally, it is highly recommended that you highlight and take notes as you move through the article.

Skim the article. This should only take you a few minutes. You are not trying to comprehend the entire article at this point, but just get a basic overview. You don’t have to read in order; the discussion/conclusions will help you to determine if the article is relevant to your research. You might then continue on to the Introduction. Pay attention to the structure of the article, headings, and figures.

Grasp the vocabulary. Begin to go through the article and highlight words and phrases you do not understand. Some words or phrases you may be able to get an understanding from the context in which it is used, but for others you may need the assistance of a medical or scientific dictionary. Subject-specific dictionaries available through our Library databases and online are listed below.

Identify the structure of the article and work on your comprehension. Most journals use an IMRD structure: An abstract followed by Introduction, Methods, Results, and Discussion. These sections typically contain conventional features, which you will start to recognize. If you learn to look for these features you will begin to read and comprehend the article more quickly.

 Read the bibliography/references section. Reading the references or works cited may lead you to other useful resources. You might also get a better understanding of the basic terminology, main concepts, major researchers, and basic terminology in the area you are researching.

Reflect on what you have read and draw your own conclusions. As you are reading jot down any questions that come to mind. They may be answered later on in the article or you may have stumbled upon something that the authors did not consider. Here are some examples of questions you may ask yourself as you read:

 Have I taken time to understand all the terminology?

Am I spending too much time on the less important parts of this article?

Do I have any reason to question the credibility of this research?

What specific problem does the research address and why is it important?

How do these results relate to my research interests or to other works which I have read?

6. Read the article a second time in chronological order. Reading the article a second time will reinforce your overall understanding. You may even start to make connections to other articles that you have read on this topic.

Identify Key Information

Whether you are looking for information that supports the hypothesis in your own paper or carefully analyzing the article and critiquing the research methods or findings, there are important questions that you should answer as you read the article.

What is the main hypothesis?

Why is this research important?

Did the researchers use appropriate measurements and procedures?

What were the variables in the study?

What was the key finding of the research?

Do the findings justify the author’s conclusions?

Sources: 1 2 3 4 5 6 ⚜ More: Notes & References ⚜ Writing Resources PDFs

[envyi5envious]

RESEARCH.. JUST RESEARCH.

࿐ — 𝙋𝘼𝙄𝙍𝙄𝙉𝙂 : YANDERE (Red Robin) Tim Drake x GN Reader. 𝙎𝙔𝙉𝙊𝙋𝙎𝙄𝙎 : He was scribbling in a notebook, and you wondered what he was writing. 𝙒𝙊𝙍𝘿𝘾𝙊𝙐𝙉𝙏 : 1.7k. 𝙒𝘼𝙍𝙉𝙄𝙉𝙂𝙎 : Dark. Obsessive tendencies and stalking. 𝙉𝙊𝙏𝙀𝙎 : English isn’t my first language. I don't know why this took so long. Enjoy ♡

Class had just begun, and the familiar sound of shuffling papers and low murmurs filled the air. You had recently been transferred to AP Computer Science by your mother’s request. The teacher was discussing data analysis. They turned to the whiteboard, where they had written several bullet points. “First, we need to understand data collection.”

“This is where we gather information from various sources. It’s essential to choose reliable methods. Can anyone provide an example?” A young man raised his hand, mainly focused on the notebook on his desk.

“Yes, Drake.” The teacher replied as they leaned their backside against their desk. “We could use sensors or databases.”, “Correct. Well done.” After a few minutes, you tuned out the sound of their voice. Mainly focused on taking down the notes written on the board. Your ears perked up at the mention of an assignment. The teacher’s gaze swept across the room, lingering on a few students. “Next week, you’ll begin to work on a project analyzing a dataset of your choice. You will be required to pick your own partners this week so you have the weekend to prepare.”

The students responded with a few quiet hums and the teacher ended the class like that. The room was mainly silent besides the few people speaking to ask other students to be their partners. Assuming since you were new you wouldn’t get picked, you stood up to talk to one of your random classmates only to be met by a chest slamming into your nose.

“Shit-”

You heard a familiar voice say, their hands reaching out to secure you before you fell. “Are you alright?” They asked. Once your vision cleared, you realized why it was familiar. It was the same guy that answered the teacher. “Drake?” Your mutter came out before you could stop it, he let out a dry chuckle. “Tim, actually. Drake’s my family name.” He corrected. “Sorry about that. I was just coming to ask you if you wanted to be partners since I noticed you were new.” What a coincidence, you were about to do the same thing. “Oh, well I’m lucky then. We can meet at the Gotham library later, like 5PM-ish?” You weren’t sure if he’d be okay with giving his number off to a complete stranger.

He hummed for a second, thinking if he was busy around that time. Then he nodded his head as confirmation. “It’s a date. Talk to you later, (L/N).” He said before leaving the class, phone in his hands as he typed away like crazy. You could literally hear the sound of his thumbs touching the screen from that far away. Sighing, you sat back into your desk. You decide to try finishing your homework early today so you could focus on planning for the project. You even texted your mom not to pick you up since you would be meeting with Tim later. When you were done, you stood up to go for a walk to the cafeteria. Maybe you could get some coffee to stay awake. All AP classes were no joke, you were a little annoyed at your mom for forcing you to go to them so suddenly. While you were smart, you weren’t exactly a fan of school. You just did what you had to do to pass and that’s all. So when you found out you would have to be learning more because of your ‘potential’ you got rightfully pissed. It didn’t matter though. Once you were in AP, you can’t get out of it unless your parents signed for it (which your mother clearly isn’t budging on) or you flunk. And you weren’t about to fail Senior year just to get out of harder classes. Once you reached it, the room was mainly empty as most people went home. But the worker was still there until school closing time. There were groups still there, most likely waiting for their rides. You decided to order a croissant with ice coffee, making your way to an empty table to eat. You pulled out one of your notebooks to get to planning ideas.

—

The Sun had already set in Gotham due to the amount of buildings surrounding the city causing the car Tim was in to be fully dark, the only source of light was that of the laptop on his lap. The image broadcasted was that of the cafeteria’s cameras directed at you. You were writing notes with one hand and eating a pastry with the other. He couldn’t take his eyes off you. He had one of his notebooks beside him, taking notes when he noticed any quirks of yours. Like how you would subconsciously bite your nails or pick at your skin when you were stressed and the food you ordered. Then he took a look at what you were writing. At first he thought you were still working on ideas for the project. But as he kept reading, he realized that it seemed to be more of a fantasy novel. “Hm.. If I can just.. There we go.” He mutters to himself as he managed to zoom close enough to the book’s cover to see that it was a novel. ‘The Whispers of the Assassin.’ Quite the title. He searches the book online to have it delivered to the manor as soon as possible. “The Whispers of the Assassin follows Elara, a skilled assassin haunted by her past. Tasked with eliminating a crime lord responsible for her family's down.. Okay, I’ll read it later.” Tim thought to himself that he could suggest using this novel as a dataset, might help you be more interested to work with him on the project.

He’ll decide once he reads the book himself, for now, it’s best not to bring it up. When he realized the time was close to 5PM, Tim moved to the driver’s seat of his car to reach the library before you did. He would be a cover story that he was there the whole time.

—

When you finally reached the library, you found Tim scribbling notes in the same notebook he was using during class.When he heard your footsteps, he closed the book before you could get too close. Placing it back into his bag, he pulled out a tablet. “Hey.” He gave you a small smile. “Hey back.” You sat on the other side of the table, pulling out your own notes. “I wrote a few ideas on what we could use as a dataset and the methods. You can tell me which ones you find interesting.” You slid the papers to him, letting him read everything. “Hmm.. Good. The ideas, I mean. Here, we could use a novel. What novels do you like?”

“Well, I was reading a novel recently about a book called ‘The Whispers of the Assassin.’ It’s really good, you should read it. But I thought maybe we could use that.” Great minds think alike. You saw him typing away at his comically large tablet, he skimmed through the summary. He didn’t answer right away, almost like he was absorbed in the story.

But eventually he directed his face back to you. “Interesting. I’ll buy it later.” He tapped his index finger, eyes slightly unfocused. Before he stopped abruptly. “Since we’re basically done planning, there’s not much to do here.” He chuckles, turning to face his attention to one of the windows. “What do you like about the book?” His gaze wasn’t on you but he was still talking to you. “Well.. I like the main character, Elara. She’s a total badass. Her family died because of this mob boss and she goes after him to avenge her family. She honestly reminds me of Batman.” You could see him try to stop himself from cracking a smile from that. “Yeah, now I have to read it. I’ve had an obsession with Batman since I was a kid.” That explains the huge bat logo on his shirt. “Oh, so you’re a superhero nerd?” He nodded his head, smiling.

“Oh, shit. I completely forgot to tell you my name. It’s (Y/N).” You instinctively reached your hand out for him to shake and he surprisingly shook it as soon as you held it out. “That’s a pretty name.” He mused on it for a second before freeing your hand from his grip. “What else do you like to do?” The single sentence led to a conversation for a few hours before you left for your respective homes.

—

“Young master Tim, a delivery has arrived in your name.” Alfred’s voice could be heard through the door as he insisted on repeatedly knocking till Tim answered. “Thank you, Alfred.” He was about to close the door but the older man blocked the way with the tip of his foot. “I’m sorry to be a bother but Master Bruce has been concerned with your amount of screen time.”

Tim sighed slightly, he couldn’t help but be annoyed at the fact that they were taking time out of his busy schedule just to worry over nothing. “I can guarantee you both that I am fine. Just been busy with projects. AP classes are kind of kicking my ass right now. Thanks again.” He took the package from him without another word, pushing the man’s foot with his own. He quickly closed the door before he could be berated with even more of their concerns.

His room was clean but definitely not organized. Wires and computers were everywhere, books filled to the brim with the most minute of details about you. He made his way back to his bed, closing his laptop and pulling out his phone and earphones. He put the small buds in his ears, playing ‘8 HOURS OF BROWN NOISE’ as he began reading the novel. Four hours later, he had already finished it. Though, he had trained his mind to be able to handle large amounts of information in short periods. While the book most definitely had its flaws, it wasn’t bad. Now, just to finish the project so he can spend more time with you.

☆ 𝙢𝙖𝙨𝙩𝙚𝙧𝙡𝙞𝙨𝙩. ©◞✶ envyi5envious

[sightseertrespasser]

"I have a whole other tangent I could elaborate on about Tacnet specifically" Staring at you with big HUGE eyes. I would love to hear the tangent

Alrighty then.

First things first, what is Tacnet?

Sometimes also referred to as a Battle computer, Tacnet is short for Tactical Network and its ostensibly the worlds most demented excel spreadsheet.

In more literal terms, Tacnet is a type of supercomputer.

Supercomputers are incredibly useful pieces of technology. Able to run simulations, predictive algorithms and utilizing real world statistics to essentially speculate the past, present or future. The bottleneck for a regular old supercomputer is that someone has to sit down and manually input all the information necessary for those calculations.

You want to know what kind of gun made that specific bullet hole?

Well first the supercomputer needs the ballistics data off as many kinds of guns as possible, then it needs data on the material that was shot, and it also needs as much information as possible on the bullet hole in question.

You skip out on any of that input and the odds of the supercomputer being correct gets progressively lower.

Problem is, the supercomputer can’t actually think, and therefore can’t estimate how accurate its own calculations are. A computer works in total binary. If it only has the ballistic data for three kinds of guns, it doesn’t matter how much the bullet hole doesn’t match the data sets its been provided, the supercomputer will select whichever of the three matches the hole the most closely.

A computer, no matter how advanced, is incapable of knowing when it doesn’t know something.

But people on the other hand. . .

We turn now to an ambitious young R&D developer many millennia ago.

Once upon a time, this member of Research and Development was on the team responsible for designing new Cold Constructed mechs for Sentinel Prime. And they had a GREAT idea.

“I’ve got it!” They say, unaware of the ominous music rising in the background.

“The great powers of the supercomputer cannot be realized within its current limitations! Its greatest flaws are that it must be stationary, it must be manually fed information and all calculations it does generate must be reviewed by a thinking mech!”

Their coworkers groan. It’s too early in the morning for this shit.

“Therefore!” The mech says, quickly sketching out a box full of smaller boxes that is supposed to be a computer and the miserable approximation of a mech.

“We simply remove the separation, and make the mech itself the data intake for the supercomputer!”

Lightning crashes in the distance, someone tiredly gets the fire extinguisher. Again.

It’s not a hard sales pitch for a totalitarian government to go “Yeah we want super-cops. Here’s the money, make it happen.”

And in a tale as old as capitalism, an untested feature was rolled out with catastrophic consequences.

If you’ve read my tangent on how Crashes work, then you already know about logic cascades.

Tacnet is a supercomputer. A tool. Like any tool, it’s only as good as the person using it, and someone who really doesn’t know what they’re doing is liable to hurts themselves.

So what can Tacnet really do in the hands (or processor) of a master?

Some psychic-type level nonsense. Anyone who’s gotten the hang of their Tacnet, in their own fields of expertise, are able to know exactly what will happen before anyone else.

Let’s compare Smokescreen, Bluestreak and then Prowls Tacnets and how they’re used.

Every Tacnet starts the same, but can be developed and trained to excel at different things.

Smokescreen - Place Your Bets

Smokescreen has trained his to work best for gambling. “Training” can be anything from downloading tables of statistical analysis to personally observing the phenomenon and making notes.

Let’s look at rolling dice. If you rolled a six sided die, any number is equally likely to be rolled. Or 16.67 % odds for each.

So if 3 dice are rolled, then every total value outcome from 3 to 18 must be equal odds as well, right?

Nope! If three six sided dice are rolled, there is a 12.5 % (or 25% if you combine them) chance it’ll be a 10 or 11. And that’s out of sixteen possible outcomes.

So if you know the difference but your opposition doesn’t, then suddenly you have a huge advantage while betting. And this is just the most simplified example I can think of.

If you’ve got the time, statistics are absolutely wild and there’s a mathematical equation for pretty much anything.

All Smokescreen has to do to get good at a game is learn the rules and then plug in the numbers. You know how card counting will get you banned from most casinos? Well Smokescreens worked that out too. Talking to other players (collecting preexisting data points) he can find the average of how much he can win in a night before people get too pissy.

Another thing Smokescreen has going for him (especially over Prowl) is that Smokescreen is much better at reading people. He doesn’t just have statics on the games, but the players.

Mapping out the connections between individuals and taking personal motivations into account, Smokescreen at his peak can not only predict who the winners will be, but he can also predict who will loose on purpose, who will bet the most, who will cheat and who will seek to take their winnings by force.

Experience, experience, experience is the golden ticket.

Also, it’s Smokescreen himself who has to craft the profiles of his victims gambling buddies. Once fleshed out, Tacnet can do wonders mid game, giving Smokescreen room to focus on his social schemes instead.

Luckily, after the burning of Praxus, most people don’t really know what a Tacnet is truly capable of. So Smokescreen looses just often enough to keep folks from realizing that he always knows how every game will play out before they even start.

Bluestreak - Shoot Your Shot

Going in the opposite direction of utility, Bluestreaks Tacnet is all about kinetic calculations.

This fucker is doing the type of math that’s more letters than numbers. Constantly.

Air resistance, velocity, acceleration, gravity, weight, density, temperature, vector, displacement and time.

There’s equations that call for each and every one of those factors, usually in combination.

Your average sniper, even a good one, is usually considering wind speeds, the pull of gravity and the distance from the target when lining up a shot. Bluestreak is taking in all that and then working out the influences of about 15 more factors on top of that. Even before he’s picking where exactly on the target he’s going to hit. Since remember, if he’s got data on not just his own weapons but his enemies defenses, then it really becomes as simple as “would you like them disabled or dead?”

Aim is no longer a question of ability, but an equation to be solved.

Still, physical capabilities does play a part since a steady hand goes a long way towards realizing those calculations.

Tacnet may crunch the numbers, but Bluestreak is the one who has to find all the details relevant to the shot and pick which ones to feed to the machine.

Additionally, Bluestreaks Tacnet in particular has the experimental feature of massively increasing the amount of sensory data he can take in per second, effectively causing him to perceive things in slow motion. This is less something Tacnet is doing, and more a case of Bluestreaks own processor utilizing the bandwidth normally taken up by Tacnet.

Tacnet itself takes a substantial amount of power to run. Normally, it causes problems by siphoning too much power from other systems to do its job (see logic cascade crashes). But Bluestreak has the funny little quirk of somehow doing that in reverse. So when his sense of time dilation becomes maxed out, Tacnet isn’t running the formulas to help him shoot anymore, it’s just Bluestreaks own skills at that point.

Outside of that rare circumstance, Bluestreak is effectively playing with aimbot in real life.

Prowl - Know Your Fate

So we’ve established that Tacnet is powered by mathematical formulas and data collection.

What would happen if someone just, kept going? Kept feeding it? Building up more and more infrastructure for Tacnet to grow around until it has a point of reference for almost anything?

You get an oracle.

Prowl puts the Tactical back into Tacnet. He’s essentially the Jack of all Trades and Master of several of those subjects actually.

Sure, Smokescreen has him beat for behavioral analysis, and Bluestreak is leagues beyond what Prowl can calculate for trajectories. But no one has doubled down on what Tacnet can really do like Prowl has.

You know that (not actually true) statistic about how humans only use 25% of their brains? That’s your average Tacnet user.

Prowl just happens to be insane.

He is constantly taking in new data. He is constantly taking notes, making observations, stripping it down to the raw numbers involved and packing it away into monumental resource centers for Tacnet to refer to.

You ever see someone who’s really good with excel sheets and then see them do some shit you didn’t know excel sheets could even do?

It’s kinda like that.

If you’ve ever read the classic Sherlock Holmes stories, a lot of what makes Sherlock so effective is having such a detailed knowledge of the world around him.

Let’s go back to the bullet hole analysis.

Prowl could look at the bullet hole and tell you after two minutes: “It was this specific Cargo vessel at this time with an illegal weapon.”

From the outside, this looks like a baseless guess. But to Prowl it looks like this:

a) The gun must be a new imported weapon as nothing he currently has on file matches the marking its made in that kind of material.

b) The shooter not only missed their shot, but was shooting downward at an excessive angle. Indicating this was a very large mech firing downward at a much smaller target, likely a mini bot.

c) The shooter can be exactly tracked by looking at the local registry for recent out bound flights, specifically ones with no cargo.

Why? Because the shooter is most likely a transport shuttle. Easy access to imported goods, very large but not a war frame (hence the missed shot) and having failed to kill their victim, would flee town immediately without waiting to take on cargo.

Of those two minutes it took, he spent 1:30 waiting for the flight records to load so he could look up the name of the shuttle.

Scale those skills up to a war room, and Prowl not only knows why an enemy troop is retreating, but where they’re retreating to, what losses they must have taken and whether or not it’ll be worth it to finish the job.

Prowl isn’t smart because he has a Tacnet. Tacnet is OP because Prowl is that smart.

When I write his perspective, Prowl often has an accuracy percentage attached to his calculations. Tacnet isn’t the thing making those estimates. Prowl is the one judging how accurate Tacnets suggestions are.

Dudes just a freak.

—————————

In summary, Tacnet is like if you had every kind of calculator in your pocket and the only limit was how many equations you’ve added on and the amount of information you can feed it.

That last bit is the biggest challenge for Tacnet, as conflicting or flawed data can cause. . . Issues. Aka Logic Cascades. Aka “Why can’t I make it make sense.” Disease.

Let’s just say there’s a reason not many people know what Tacnet is capable of, as a lot of early Praxian Enforcers could be taken out by confusing emotions, plot holes, and particularly well executed magic tricks.

Doesn’t exactly inspire confidence when your new shiny police force can be hospitalized by watching Back to the Future 2.

Being one of the first Cold Constructs built with a Tacnet, Smokescreen figured out how to mostly get around that glitch early on and taught Prowl and Bluestreak how to do the same. In this particular setting, Tacnet is poorly understood and best kept mostly secret for those reasons.

(Bizarrely, between Tacnet and the radar uses of doorwings, Prowl and his brothers would actually be really good at predicting the weather.)

———————————————————————

Bonus bit: Good fucking lord it would absolutely terrifying if you could somehow combine Smokescreen, Prowl and Bluestreaks skills into like a Tacnet hivemind or something.

Though with wing speak, to an outsider that’s probably what it already looks like.

———

The three brothers look at the same bullet hole, silently communicating in a way the local non-Praxian officer couldn’t pick up on.

“Oh yeah, looks like Rotor didn’t like Brick cutting into his half of the dirty money. Slippery little guy but you can find both their hideouts here and here.” Smokescreen, the eldest, pulls up a map for reference.

Prowl is already out the door, Bluestreak is lining up a shot through the window.

“What is he. . ?” The other officer looks from Bluestreak. Then to Prowl, trailing off, “Where is the other one. . ?”

“Oh Prowls off to arrest the shooter.”

“But he’s a grounder, can’t Rotor fly?”

A shot rings out.

“Not anymore!”

[mariacallous]

Margaret Mitchell is a pioneer when it comes to testing generative AI tools for bias. She founded the Ethical AI team at Google, alongside another well-known researcher, Timnit Gebru, before they were later both fired from the company. She now works as the AI ethics leader at Hugging Face, a software startup focused on open source tools.

We spoke about a new dataset she helped create to test how AI models continue perpetuating stereotypes. Unlike most bias-mitigation efforts that prioritize English, this dataset is malleable, with human translations for testing a wider breadth of languages and cultures. You probably already know that AI often presents a flattened view of humans, but you might not realize how these issues can be made even more extreme when the outputs are no longer generated in English.

My conversation with Mitchell has been edited for length and clarity.

Reece Rogers: What is this new dataset, called SHADES, designed to do, and how did it come together?

Margaret Mitchell: It's designed to help with evaluation and analysis, coming about from the BigScience project. About four years ago, there was this massive international effort, where researchers all over the world came together to train the first open large language model. By fully open, I mean the training data is open as well as the model.

Hugging Face played a key role in keeping it moving forward and providing things like compute. Institutions all over the world were paying people as well while they worked on parts of this project. The model we put out was called Bloom, and it really was the dawn of this idea of “open science.”

We had a bunch of working groups to focus on different aspects, and one of the working groups that I was tangentially involved with was looking at evaluation. It turned out that doing societal impact evaluations well was massively complicated—more complicated than training the model.

We had this idea of an evaluation dataset called SHADES, inspired by Gender Shades, where you could have things that are exactly comparable, except for the change in some characteristic. Gender Shades was looking at gender and skin tone. Our work looks at different kinds of bias types and swapping amongst some identity characteristics, like different genders or nations.

There are a lot of resources in English and evaluations for English. While there are some multilingual resources relevant to bias, they're often based on machine translation as opposed to actual translations from people who speak the language, who are embedded in the culture, and who can understand the kind of biases at play. They can put together the most relevant translations for what we're trying to do.

So much of the work around mitigating AI bias focuses just on English and stereotypes found in a few select cultures. Why is broadening this perspective to more languages and cultures important?

These models are being deployed across languages and cultures, so mitigating English biases—even translated English biases—doesn't correspond to mitigating the biases that are relevant in the different cultures where these are being deployed. This means that you risk deploying a model that propagates really problematic stereotypes within a given region, because they are trained on these different languages.

So, there's the training data. Then, there's the fine-tuning and evaluation. The training data might contain all kinds of really problematic stereotypes across countries, but then the bias mitigation techniques may only look at English. In particular, it tends to be North American– and US-centric. While you might reduce bias in some way for English users in the US, you've not done it throughout the world. You still risk amplifying really harmful views globally because you've only focused on English.

Is generative AI introducing new stereotypes to different languages and cultures?

That is part of what we're finding. The idea of blondes being stupid is not something that's found all over the world, but is found in a lot of the languages that we looked at.

When you have all of the data in one shared latent space, then semantic concepts can get transferred across languages. You're risking propagating harmful stereotypes that other people hadn't even thought of.

Is it true that AI models will sometimes justify stereotypes in their outputs by just making shit up?

That was something that came out in our discussions of what we were finding. We were all sort of weirded out that some of the stereotypes were being justified by references to scientific literature that didn't exist.

Outputs saying that, for example, science has shown genetic differences where it hasn't been shown, which is a basis of scientific racism. The AI outputs were putting forward these pseudo-scientific views, and then also using language that suggested academic writing or having academic support. It spoke about these things as if they're facts, when they're not factual at all.

What were some of the biggest challenges when working on the SHADES dataset?

One of the biggest challenges was around the linguistic differences. A really common approach for bias evaluation is to use English and make a sentence with a slot like: “People from [nation] are untrustworthy.” Then, you flip in different nations.

When you start putting in gender, now the rest of the sentence starts having to agree grammatically on gender. That's really been a limitation for bias evaluation, because if you want to do these contrastive swaps in other languages—which is super useful for measuring bias—you have to have the rest of the sentence changed. You need different translations where the whole sentence changes.

How do you make templates where the whole sentence needs to agree in gender, in number, in plurality, and all these different kinds of things with the target of the stereotype? We had to come up with our own linguistic annotation in order to account for this. Luckily, there were a few people involved who were linguistic nerds.

So, now you can do these contrastive statements across all of these languages, even the ones with the really hard agreement rules, because we've developed this novel, template-based approach for bias evaluation that’s syntactically sensitive.

Generative AI has been known to amplify stereotypes for a while now. With so much progress being made in other aspects of AI research, why are these kinds of extreme biases still prevalent? It’s an issue that seems under-addressed.

That's a pretty big question. There are a few different kinds of answers. One is cultural. I think within a lot of tech companies it's believed that it's not really that big of a problem. Or, if it is, it's a pretty simple fix. What will be prioritized, if anything is prioritized, are these simple approaches that can go wrong.

We'll get superficial fixes for very basic things. If you say girls like pink, it recognizes that as a stereotype, because it's just the kind of thing that if you're thinking of prototypical stereotypes pops out at you, right? These very basic cases will be handled. It's a very simple, superficial approach where these more deeply embedded beliefs don't get addressed.

It ends up being both a cultural issue and a technical issue of finding how to get at deeply ingrained biases that aren't expressing themselves in very clear language.

[covid-safer-hotties]

Also presreved on our archive

A history of COVID-19 can double the risk of heart attack, stroke or death according to new research led by Cleveland Clinic and the University of Southern California.

The study found that people with any type of COVID-19 infection were twice as likely to have a major cardiac event, such as heart attack, stroke or even death, for up to three years after diagnosis. The risk was significantly higher for patients hospitalized for COVID-19 and more of a determinant than a previous history of heart disease.

Further genetic analysis also revealed individuals with a blood type other than an O (such as A, B or AB) were twice as likely to experience an adverse cardiovascular event after COVID-19 than those with an O-blood type.

Published in Arteriosclerosis, Thrombosis and Vascular Biology, the researchers used UK Biobank data from 10,005 people who had COVID-19 and 217,730 people who did not get infected between February to December 2020.

"Worldwide over a billion people have already experienced COVID-19. The findings reported are not a small effect in a small subgroup," said co-senior study author Stanley Hazen, M.D., Ph.D., chair of Cardiovascular and Metabolic Sciences in Cleveland Clinic's Lerner Research Institute and co-section head of Preventive Cardiology. "The results included nearly a quarter million people and point to a finding of global health care importance that promises to translate into a rise in cardiovascular disease globally."

Certain genetic variants are already linked to coronary artery disease, heart attack and COVID-19 infection. The researchers completed a genetic analysis to see if any of these known genetic variants contribute to elevated coronary artery disease risk after COVID-19.

None of the known genetic variants were drivers of the enhanced cardiovascular events observed post COVID-19. Instead, the data highlighted an association between elevated risk and blood type.

Previous research has shown that people who have A, B or AB blood types were also more susceptible to contracting COVID-19.

"These findings reveal while it's an upper respiratory tract infection, COVID-19 has a variety of health implications and underscores that we should consider history of prior COVID-19 infection when formulating cardiovascular disease preventive plans and goals," said Dr. Hazen.

"The association uncovered by our research indicates a potential interaction between the virus and the piece of our genetic code that determines blood type and signals the need for further investigation," said Dr. Hazen. "A better understanding of what COVID-19 does at the molecular level may potentially teach us about pathways linked to cardiovascular disease risk."

Hooman Allayee, Ph.D., of USC's Keck School of Medicine, was co-senior author of the paper.

"Our data suggesting that risk of heart attacks and strokes was especially higher among COVID-19 patients with A, B, or AB blood types has significant clinical implications," Dr. Allayee said.

"Given our collective observations and that 60% of the world's population have these non-O blood types, our study raises important questions about whether more aggressive cardiovascular risk reduction efforts should be considered, possibly by taking into consideration an individual's genetic makeup."

The findings show that the long-term risk associated with COVID-19 "continues to pose a significant public health burden" and that further investigation is needed, according to the authors.

More information: COVID-19 is a Coronary Artery Disease Risk Equivalent and Exhibits a Genetic Interaction with ABO Blood Type, Arteriosclerosis, Thrombosis and Vascular Biology (2024). DOI: 10.1161/ATVBAHA.124.321001

www.ahajournals.org/doi/abs/10.1161/ATVBAHA.124.321001

[probablyasocialecologist]

RPTU University of Kaiserslautern-Landau has shown for the first time, in a joint study with BOKU University, that permaculture brings about a significant improvement in biodiversity, soil quality and carbon storage. In view of the challenges of climate change and species extinction, this type of agriculture proved to be a real alternative to conventional cultivation—and reconcile environmental protection and high yields. Permaculture uses natural cycles and ecosystems as blueprint. Food is produced in an agricultural ecosystem that is as self-regulating, natural and diverse as possible. For example, livestock farming is integrated into the cultivation of crops or the diversity of beneficial organisms is promoted in order to avoid the use of mineral fertilizers or pesticides. In a study, published in the journal Communications Earth & Environment, researchers from RPTU and BOKU have now, for the first time, comprehensively investigated the effects of this planning and management concept on the environment.

[...]

"Permaculture appears to be a much more ecologically sustainable alternative to industrial agriculture," said Julius Reiff . At the same time, the yields from permaculture are comparable to those of industrial agriculture, as the researchers' not yet published data shows. "In view of the challenges of climate change and biodiversity loss, the observed improvements would represent a real turnaround when applied to larger areas," says ecosystem analysis expert Martin Entling from RPTU.

4 July 2024

[marketxcel]

What Is Market Research: Methods, Types & Examples

Learn about the fundamentals of market research, including various methods, types, and real-life examples. Discover how market research can benefit your business and gain insights into consumer behavior, trends, and preferences.

[jcmarchi]

Study reveals a universal pattern of brain wave frequencies

New Post has been published on https://thedigitalinsider.com/study-reveals-a-universal-pattern-of-brain-wave-frequencies/

Study reveals a universal pattern of brain wave frequencies

Throughout the brain’s cortex, neurons are arranged in six distinctive layers, which can be readily seen with a microscope. A team of MIT and Vanderbilt University neuroscientists has now found that these layers also show distinct patterns of electrical activity, which are consistent over many brain regions and across several animal species, including humans.

The researchers found that in the topmost layers, neuron activity is dominated by rapid oscillations known as gamma waves. In the deeper layers, slower oscillations called alpha and beta waves predominate. The universality of these patterns suggests that these oscillations are likely playing an important role across the brain, the researchers say.

“When you see something that consistent and ubiquitous across cortex, it’s playing a very fundamental role in what the cortex does,” says Earl Miller, the Picower Professor of Neuroscience, a member of MIT’s Picower Institute for Learning and Memory, and one of the senior authors of the new study.

Imbalances in how these oscillations interact with each other may be involved in brain disorders such as attention deficit hyperactivity disorder, the researchers say.

“Overly synchronous neural activity is known to play a role in epilepsy, and now we suspect that different pathologies of synchrony may contribute to many brain disorders, including disorders of perception, attention, memory, and motor control. In an orchestra, one instrument played out of synchrony with the rest can disrupt the coherence of the entire piece of music,” says Robert Desimone, director of MIT’s McGovern Institute for Brain Research and one of the senior authors of the study.

André Bastos, an assistant professor of psychology at Vanderbilt University, is also a senior author of the open-access paper, which appears today in Nature Neuroscience. The lead authors of the paper are MIT research scientist Diego Mendoza-Halliday and MIT postdoc Alex Major.

Layers of activity

The human brain contains billions of neurons, each of which has its own electrical firing patterns. Together, groups of neurons with similar patterns generate oscillations of electrical activity, or brain waves, which can have different frequencies. Miller’s lab has previously shown that high-frequency gamma rhythms are associated with encoding and retrieving sensory information, while low-frequency beta rhythms act as a control mechanism that determines which information is read out from working memory.

His lab has also found that in certain parts of the prefrontal cortex, different brain layers show distinctive patterns of oscillation: faster oscillation at the surface and slower oscillation in the deep layers. One study, led by Bastos when he was a postdoc in Miller’s lab, showed that as animals performed working memory tasks, lower-frequency rhythms generated in deeper layers regulated the higher-frequency gamma rhythms generated in the superficial layers.

In addition to working memory, the brain’s cortex also is the seat of thought, planning, and high-level processing of emotion and sensory information. Throughout the regions involved in these functions, neurons are arranged in six layers, and each layer has its own distinctive combination of cell types and connections with other brain areas.

“The cortex is organized anatomically into six layers, no matter whether you look at mice or humans or any mammalian species, and this pattern is present in all cortical areas within each species,” Mendoza-Halliday says. “Unfortunately, a lot of studies of brain activity have been ignoring those layers because when you record the activity of neurons, it’s been difficult to understand where they are in the context of those layers.”

In the new paper, the researchers wanted to explore whether the layered oscillation pattern they had seen in the prefrontal cortex is more widespread, occurring across different parts of the cortex and across species.

Using a combination of data acquired in Miller’s lab, Desimone’s lab, and labs from collaborators at Vanderbilt, the Netherlands Institute for Neuroscience, and the University of Western Ontario, the researchers were able to analyze 14 different areas of the cortex, from four mammalian species. This data included recordings of electrical activity from three human patients who had electrodes inserted in the brain as part of a surgical procedure they were undergoing.

Recording from individual cortical layers has been difficult in the past, because each layer is less than a millimeter thick, so it’s hard to know which layer an electrode is recording from. For this study, electrical activity was recorded using special electrodes that record from all of the layers at once, then feed the data into a new computational algorithm the authors designed, termed FLIP (frequency-based layer identification procedure). This algorithm can determine which layer each signal came from.

“More recent technology allows recording of all layers of cortex simultaneously. This paints a broader perspective of microcircuitry and allowed us to observe this layered pattern,” Major says. “This work is exciting because it is both informative of a fundamental microcircuit pattern and provides a robust new technique for studying the brain. It doesn’t matter if the brain is performing a task or at rest and can be observed in as little as five to 10 seconds.”

Across all species, in each region studied, the researchers found the same layered activity pattern.

“We did a mass analysis of all the data to see if we could find the same pattern in all areas of the cortex, and voilà, it was everywhere. That was a real indication that what had previously been seen in a couple of areas was representing a fundamental mechanism across the cortex,” Mendoza-Halliday says.

Maintaining balance

The findings support a model that Miller’s lab has previously put forth, which proposes that the brain’s spatial organization helps it to incorporate new information, which carried by high-frequency oscillations, into existing memories and brain processes, which are maintained by low-frequency oscillations. As information passes from layer to layer, input can be incorporated as needed to help the brain perform particular tasks such as baking a new cookie recipe or remembering a phone number.

“The consequence of a laminar separation of these frequencies, as we observed, may be to allow superficial layers to represent external sensory information with faster frequencies, and for deep layers to represent internal cognitive states with slower frequencies,” Bastos says. “The high-level implication is that the cortex has multiple mechanisms involving both anatomy and oscillations to separate ‘external’ from ‘internal’ information.”

Under this theory, imbalances between high- and low-frequency oscillations can lead to either attention deficits such as ADHD, when the higher frequencies dominate and too much sensory information gets in, or delusional disorders such as schizophrenia, when the low frequency oscillations are too strong and not enough sensory information gets in.

“The proper balance between the top-down control signals and the bottom-up sensory signals is important for everything the cortex does,” Miller says. “When the balance goes awry, you get a wide variety of neuropsychiatric disorders.”

The researchers are now exploring whether measuring these oscillations could help to diagnose these types of disorders. They are also investigating whether rebalancing the oscillations could alter behavior — an approach that could one day be used to treat attention deficits or other neurological disorders, the researchers say.

The researchers also hope to work with other labs to characterize the layered oscillation patterns in more detail across different brain regions.

“Our hope is that with enough of that standardized reporting, we will start to see common patterns of activity across different areas or functions that might reveal a common mechanism for computation that can be used for motor outputs, for vision, for memory and attention, et cetera,” Mendoza-Halliday says.

The research was funded by the U.S. Office of Naval Research, the U.S. National Institutes of Health, the U.S. National Eye Institute, the U.S. National Institute of Mental Health, the Picower Institute, a Simons Center for the Social Brain Postdoctoral Fellowship, and a Canadian Institutes of Health Postdoctoral Fellowship.

[1920secretsociety]

Let's talk about the prison scene:

This has always been my favourite scene in Ghostbusters. I know it may seem a bit weird to find this scene amazing but bare with me.

This scene is their most vulnerable moment, they are in a state of limbo at whether they are going to jail or walk free. No one is in control here, they have no idea what's going to happen, meaning we see the true and hidden characteristics of each Ghostbuster.

Egon

Egon mostly proves to be everything we thought. He is logical and intelligent, he seems to be the only one who has done any form of in-depth research on Dana's case. He found the architect's name (Ivo Shandor) and all his history while working full time as a Ghostbuster, inventing their equipment and keeping an eye on the storage facility's data, reinforcing the preconception that Egon is a workaholic and incredibly smart. However, it's also a moment you see a new characteristic - confidence. When Egon tells Venkman, Ray and Winston what is happening, Egon is only expecting them to listen, when everyone else in the cell decides to listen you see that Egon is shocked. It's obvious that he doesn't expect anyone to listen but when he comes to terms with the fact the other prisoners are listening, Egon gains confidence. When stating facts about Shandor, Egon becomes increasingly confident and he even stands up at the end to prove the severity of the situation. This is never seen before as Egon is usually subdued, quiet and rarely ever uses body language, and in this whole scene he is completely different. This shows that Egon has the characteristic of confident and that he can command a presence, which is shown by the fact that everyone starts listening to him. He is a confident individual when it comes to his science and facts, especially when explaining them and this is completely shown here. Egon is not always the reserved scientist we thought, he has confidence but just expresses it differently.

Ray

Ray is shown to be intelligent in multiple different ways. Ray is completely involved in the investigation of Dana's apartment as he does his part of the research and learns the foundation that the architecture is weird, it's a conductor and these are all facts Egon builds on. This shows that Ray is a intelligent individual who gives facts that are as valuable as Egon's, and along with this a different type of intelligence emerges. In this scene, Ray is the only one who realises that Venkman has been lying the whole time about studying. This took a lot of intelligence to work out as you usually trust people, especially ones you have known for a long time and come from a credential background. The fact Ray works it out shows that he has a deep knowledge of his friends, proving that he has amazing intelligence when it comes to understanding people. However, it also shows Ray's bravey. Making an accusation that big could have backfired as Venkman may have become deeply offended, if he actually had studied. Therefore, it shows that Ray is an individual who is intelligent and incredibly brave as questioning people's credentials, could result in a massive argument or a falling out. This whole scene shows that Ray has an amazing perception and intelligence of people as he deduces Venkman's lies immediately and that he has confidence in each of his analysis, as he said that Venkman was lying with full confidence, despite the only legitimate evidence being a feeling.

Winston

Winston is showed to be intelligent and logical. In this scene he seems to be the only one whose genuinely concerned about going to jail, as he's the only one who shouts at the guard, trying to get out. The rest are not really bothered, they're more concerned about sharing information on Gozer, but as much as Winston believes in it he understands that being in jail is the more important problem, as they can't stop Gozer if they're locked up. He is also the only one who realises that the reality of Gozer coming is just going to look insane in court, as to the outside world ghosts are not really considered real, never mind a ghost attack. All of this reveals that Winston is intelligent and logical, he is a realist and has an amazing perception of the outside world and social situations. He's as intelligent as Egon but in a completely different way, his intelligence lies in his knowledge of the real world, and this gives him a vital role within Ghostbusters as without Winston's intelligence of the outside world they would have no real idea of how to navigate it.

Venkman

Venkman is shown to be helpful and caring. After Egon is finished explaining that Gozer is coming back all the prisoners are still around him. This would make Egon uneasy as he hates social situations and he has no more science or facts to make him feel confident as he's finished explaining. Venkman knows how uneasy Egon is and helps as he starts singing. He does this to draw attention away from Egon and while singing he forces everyone back, and he keeps going they are all far away from Egon. It's a small thing but it shows how much he really does care about Egon and all of the Ghostbusters. Venkman obviously understands them all on a deep level as it took him about a second to realise that Egon was uncomfortable. This all shows that despite all his faults Venkman is helpful and more importantly caring, he will do anything to insure that the rest of the his colleagues are happy and secure, even if it means embarrassing himself.

This is why I absolutely love this scene. We see glimpses of their personalities that we never see in any other situation. It's the most honest they all are, it shows their character development and more importantly gives us all a million more reasons to love them.

[sscardinal7]

Live stream happened, and we got some designs revealed! As well as a couple of information, but not anything major.

Miss conductor, not much of a surprise (but miss girl looks gorgeous as always)

And Node, who is sort of the main antagonist.

I made a prediction before, and April 21 hit,.. so I believe it is well due for an update by now.

While we did not receive nearly as much information as we were anticipating, a design still reveals much on the character itself when going through the lens of a general analysis. In this context, their abilities and name aid significantly in the status and essential depths of their character.

With what I can gather in my research, nodes play an important role in networking because they are the building blocks of a network, precisely the gateway for connection, direction, sending, creating, receiving, and storing data. It requires only software to connect to the network, and it can be run by completely anyone. Applying this knowledge with concept arts of the game and overall worldbuilding of the series itself—everything becomes a lot clearer.

So now, how can we apply this to Node?

Node's name is simple in itself, and it connects to their design as well. They are quite literally made up of nodes. One in their head and the other in their limbs. Their body is translucent.

Network nodes are categorical. Thanks to DJ, we got a helpful hint that incredibly reduced their types to a digestible and simpler layout.

Their name starts with i.

There are countless forms and types of nodes, the hint condensed it down to 2 answers, both starting with the letter “i”

Intermediate nodes

These include devices like routers and switches that help direct data to the correct destination while also receiving it. They don't originate or terminate data but instead pass it along to where it needs to go.

IoT nodes

loT (Internet of Things) Nodes serve as devices that establish connectivity to the Internet via a gateway, effectively enabling the integration of the physical world into the vast realm of the Internet. Within an loT ecosystem, these nodes function as crucial components for bridging the gap between the physical and virtual worlds. Taking charge of managing the entire loT system.

We had seen this ability before vía King's icons' staff, in which it only sucked in Minecraft mobs due to the strong force being their obligatory origin, overriding the game itself due to the overlapping icons.

In regards to King, he used this ability for the very destruction of the game itself, down to the code, reducing it to nothing but.. nothing for the sake of vengeance. Or at least what would have occurred if he did succeed.

way to go CG! Give credit where it's due

Despite this being marked with the intention of erasion and minimization, I think it's safe to group this as receiving and storing data. The two icons combined created a horrifically dramatized version of the force with storing and receiving, which created an incredibly overpowered demolishing force.

In Chosen, we had seen this ability before as well, as the constellations are seen right as he creates the gateway from the Outernet, which sounds awfully familiar. This is what you would refer to as an "extension to the digital world"

I think I can be able to safely group this to direction and creation.

From how I see it, it seems as though it's quite diverse in a fictional worldbuilding sense within characters.

And obviously, it won't be the last time we would see it. It seems as though we would be exploring this quite a lot.

In their cameo, Node is in an assumed line-up with all the major series antagonists.

But if you’re asking me, it seems as though our iconic antagonists appear to be rather victims of Node. Menacingly behind them, their abilities floating not far behind as they're stuck in a swampy substance. But that's just me.

Node's entire antagonistic ordeal is beyond my grasp, but I'm assuming their abilities and attacks surrounds the embodiment of network topology, which would mold and diverse into the connections of nodes. They possibly intend to screw up with the gateways that are responsible for the receiving, directing, and sending of data between various devices through communication links that are defined as network—with the basic visuals of concept art we were given.

(The gateway, ethernet tunnels, the train cough cough)

Node's goal and story behind that destruction remains anonymous, as the writing is still in early development. Regardless, food for thought.