#environmental api

[rederiswrites]

I'd love to have the time and energy to synthesize all my Master Gardeners' class materials into good posts, but I don't, so here's a couple things from my entomology presentation, which I'm watching the recording of (honestly guys their online class system is slick as hell).

One: the lady beetles (lady bugs, colloquially) that you can order online are the Asian variety. They're not the native variety. They're still good generalist predators, and they're pretty thoroughly naturalized in North America now. (Naturalized: successfully established and reproducing in their non-native environment.) That said, the Extension Services still doesn't recommend buying them, because the conditions in which they were raised might introduce diseases, which might then be passed on to the native populations in your environment.

More generally, expert advice on encouraging animals ranging from insects up through quail and pheasants is increasingly to create and maintain habitat so that the critters show up on their own, rather than to introduce captive-raised animals. I know that introducing the animal feels like doing more, but the evidence is against it being effective. I know, it annoys me too. I know for quail and pheasants, there were big programs aimed at raising and releasing the birds, because they're popular game birds, and those programs are now winding down and shifting focus, because captive raised birds just don't survive to raise the next generation. So at best what you're actually encouraging is your target animal's predators.

Anyway. We were talking about insects.

Two: Yes, several species of non-native mantis insects are naturalized in North America now. It's fine to leave them alone and be happy about them. They're good generalist predators, and there's no evidence so far that they negatively impact the native mantises. As above, they don't suggest buying mantises to introduce, but the ones that are already in your environment are fine.

I guess both tie into a broader point, which is that invasive species have two criteria. They must be non-native, but they must also be detrimental to the native species in an area. A non-native that doesn't negatively impact the environment, such as dandelions, say, is not invasive. It may not have many ties in the food web of the area, like for example only being of use to generalist pollinators, but that doesn't mean it's harmful. A plant that is native but can outcompete other plants in an area is aggressive, not invasive.

Whether non-native plants and animals can have a positive role in environments is a topic that even the experts are still hotly debating, but certainly non-native does not automatically mean invasive.

Oh. In case it needs to be said, generalist: able to make use of a variety of resources. I.E. Apis mellifera, the European honey bee, that can get nectar and pollen from many different plants. MOST native insects are specialists, meaning they can only survive using one variety of plant. For example, the Monarch butterfly, whose caterpillars are specialized to feed on milkweed.

And THAT, my friends, is why native plants matter. Not for a nice idea, not for looks, not for some impossible ideal of a single state of environmental being. But because they are the base of the food web, and native plants are what has a relationship with native insects.

This post could be reordered a lot for clarity but I ent gonna do that, so good luck and you know where my inbox is I guess.

[mbti-notes]

Anon wrote: hello! thank you for running this blog. i hope your vacation was well-spent!

i am an enfp in the third year of my engineering degree. i had initially wanted to do literature and become an author. however, due to the job security associated with this field, my parents got me to do computer science, specialising in artificial intelligence. i did think it was the end of my life at the time, but eventually convinced myself otherwise. after all, i could still continue reading and writing as hobbies.

now, three years in, i am having the same thoughts again. i've been feeling disillusioned from the whole gen-ai thing due to art theft issues and people using it to bypass - dare i say, outsource - creative work. also, the environmental impact of this technology is astounding. yet, every instructor tells us to use ai to get information that could easily be looked up in textbooks or google. what makes it worse is that i recently lost an essay competition to a guy who i know for a fact used chatgpt.

i can't help feeling that by working in this industry, i am becoming a part of the problem. at the same time, i feel like a conservative old person who is rejecting modern technology and griping about 'the good old days'.

another thing is that college work is just so all-consuming and tiring that i've barely read or written anything non-academic in the past few years. quitting my job and becoming a writer a few years down the road is seeming more and more like a doomed possibility.

i've been trying to do what i can at my level. i write articles about ethical considerations in ai for the college newsletter. i am in a technical events club, and am planning out an artificial intelligence introductory workshop for juniors where i will include these topics, if approved by the superiors.

from what i've read on your blog, it doesn't seem like you have a very high opinion of ai, either, but i've only seen you address it in terms of writing. i'd like to know, are there any ai applications that you find beneficial? i think that now that i am here, i could try to make a difference by working on projects that actually help people, rather than use some chatgpt api to do the same things, repackaged. i just felt like i need the perspective of someone who thinks differently than all those around me. not in a 'feed my tunnel-vision' way, but in a 'tell me i'm not stupid' way.

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

It's kind of interesting (in the "isn't life whacky?" sort of way) you chose the one field that has the potential to decimate the field that you actually wanted to be in. I certainly understand your inner conflict and I'll give you my personal views, but I don't know how much they will help your decision making.

I'm of course concerned about the ramifications on writing not just because I'm a writer but because, from the perspective of education and personal growth, I understand the enormous value of writing skills. Learning to write analytically is challenging. I've witnessed many people meet that challenge bravely, and in the process, they became much more intelligent and thoughtful human beings, better able to contribute positively to society. So, it pains me to see the attitude of "don't have to learn it cuz the machine does it". However, writing doesn't encompass my full view on AI.

I wouldn't necessarily stereotype people who are against new technology as "old and conservative", though some of them are. My parents taught me to be an early adopter of new tech, but it doesn't mean I don't have reservations about it. I think, psychologically, the main reason people resist is because of the real threat it poses. Historically, we like to gloss over the real human suffering that results from technological advancement. But it is a reasonable and legitimate response to resist something that threatens your livelihood and even your very existence.

For example, it is already difficult enough to make a living in the arts, and AI just might make it impossible. Even if you do come up with something genuinely creative and valuable, how are you going to make a living with it? As soon as creative products are digitized, they just get scraped up, regurgitated, and disseminated to the masses with no credit or compensation given to the original creator. It's cannibalism. Cannibalism isn't sustainable.

I wonder if people can seriously imagine a society where human creativity in the arts has been made obsolete and people only have exposure to AI creation. There are plenty of people who don't fully grasp the value of human creativity, so they wouldn't mind it, but I would personally consider it to be a kind of hell.

I occasionally mention that my true passion is researching "meaning" and how people come to imbue their life with a sense of meaning. Creativity has a major role to play in 1) almost everything that makes life/living feel worthwhile, 2) generating a culture that is worth honoring and preserving, and 3) building a society that is worthy of devoting our efforts to.

Living in a capitalist society that treats people as mere tools of productivity and treats education as a mere means to a paycheck already robs us of so much meaning. In many ways, AI is a logical result of that mindset, of trying to "extract" whatever value humans have left to offer, until we are nothing but empty shells.

I don't think it's a coincidence that AI comes out of a society that devalues humanity to the point where a troubling portion of the population suffers marginalization, mental disorder, and/or feels existentially empty. Many of the arguments I've heard from AI proponents about how it can improve life sound to me like they're actually going to accelerate spiritual starvation.

Existential concerns are serious enough, before we even get to the environmental concerns. For me, environment is the biggest reason to be suspicious of AI and its true cost. I think too many people are unaware of the environmental impact of computing and networking in general, let alone running AI systems. I recently read about how much energy it takes to store all the forgotten chats, memes, and posts on social media. AI ramps up carbon emissions dramatically and wastes an already dwindling supply of fresh water.

Can we really afford a mass experiment with AI at a time when we are already hurtling toward climate catastrophe? When you think about how much AI is used for trivial entertainment or pointless busywork, it doesn't seem worth the environmental cost. I care about this enough that I try to reduce my digital footprint. But I'm just one person and most of the population is trending the other way.

With respect to integrating AI into personal life or everyday living, I struggle to see the value, often because those who might benefit the most are the ones who don't have access. Yes, I've seen some people have success with using AI to plan and organize, but I also always secretly wonder at how their life got to the point of needing that much outside help. Sure, AI may help with certain disadvantages such as learning or physical disabilities, but this segment of the population is usually the last to reap the benefits of technology.

More often than not, I see people using AI to lie, cheat, steal, and protect their own privilege. It's particularly sad for me to see people lying to themselves, e.g., believing that they're smart for using AI when they're actually making themselves stupider, or thinking that an AI companion can replace real human relationship.

I continue to believe that releasing AI into the wild, without developing proper safeguards, was the biggest mistake made so far. The revolts at OpenAI prove, once again, that companies cannot be trusted to regulate themselves. Tech companies need a constant stream of data to feed the beast and they're willing to sacrifice our well-being to do it. It seems the only thing we can do as individuals is stop offering up our data, but that's not going to happen en masse.

Even though you're aware of these issues, I want to mention them for those who aren't, and for the sake of emphasizing just how important it is to regulate AI and limit its use to the things that are most likely to produce a benefit to humanity, in terms of actually improving quality of human life in concrete terms.

In my opinion, the most worthwhile place to use AI is medicine and medical research. For example, aggregating and analyzing information for doctors, assisting surgeons with difficult procedures, and coming up with new possibilities for vaccines, treatments, and cures is where I'd like to see AI shine. I'd also love to see AI applied to:

scientific research, to help scientists sort, manage, and process huge amounts of information

educational resources, to help learners find quality information more efficiently, rather than feeding them misinformation

engineering and design, to build more sustainable infrastructure

space exploration, to find better ways of traveling through space or surviving on other planets

statistical analysis, to help policymakers take a more objective look at whether solutions are actually working as intended, as opposed to being blinded by wishful thinking, bias, hubris, or ideology (I recognize this point is controversial since AI can be biased as well)

Even though you work in the field, you're still only one person, so you don't have that much more power than anyone else to change its direction. There's no putting the worms back in the can at this point. I agree with you that, for the sake of your well-being, staying in the field means choosing your work carefully. However, if you want to work for an organization that doesn't sacrifice people at the altar of profit, it might be slim pickings and the pay might not be great. Staying true to your values can be costly too.

[fuckyeahecco]

Here's the interview where Ed confirms the remasters and new game, as well as reflecting on some of his inspiration for the series!

[rjzimmerman]

Excerpt from this story from the Union of Concerned Scientists:

The U.S. oil and gas industry has sounded its mating call to the incoming Presidential administration with a policy wish list remarkable for its unabated pursuit of profits and defiance of climate science and economic trends. 

The American Petroleum Institute (API) released a “policy roadmap” addressed to President-elect Donald Trump on November 12 outlining five “actions” he can take to bolster their agenda. However, the “actions”—given euphemistic titles like “protect consumer choice”—actually aim to roll back science-based environmental protections in order to maximize already massive profits. The policy details within each action roughly correspond with recommendations in Project 2025, the infamous policy agenda penned in part by figures from the first Trump administration and supported by several anti-climate organizations.  

Here’s a breakdown of the roadmap’s requests along with an explanation of how they would roll back environmental progress. 

API’s anti-environment entreaties 

Fight clean cars. API’s first policy proposal is repealing rules designed to support the shift to electric vehicles that the oil and gas industry has fought for decades. API specifically targets Environmental Protection Agency (EPA) rules to reduce carbon emissions from automobile tailpipes and fuel economy standards established by the National Highway Traffic Safety Administration. API also targets an EPA waiver for a 2022 California rule that would reduce pollution from new gasoline-powered cars while increasing sales requirements for zero-emission vehicles.

Pump up gas. The second policy proposal is to reinstate permitting of liquified natural gas (LNG), also known as methane, a fossil fuel that is a potent source of global warming emissions. The Biden administration temporarily paused pending approvals for new LNG export authorizations in January 2024, citing the need to update the review process to best reflect impacts on climate, domestic energy prices, and health—especially as borne by frontline communities.

Reverse protections for public land and health. The third policy proposal focuses on federal lands that API believes should be opened up to drilling, both onshore and offshore. It recommends repealing a Bureau of Land Management rule that would put conservation on equal footing with drilling and ranching as a legal use of public lands, in addition to adding more leasing opportunities from the Bureau of Ocean Energy Management’s offshore leasing program. But the most blatantly anti-climate demand in this area would repeal a Congressionally approved fee on every metric ton of methane that high-emitting oil and gas facilities produce above specific levels. The oil and gas industry is responsible for 30 percent of human-caused methane emissions.

Muzzle environmental reviews. The fourth policy proposal involves the federal permitting process, a perennial enemy of the fossil fuel industry. The statute in their crosshairs is the National Environmental Protection Act (NEPA), which the industry has fought since it was signed into law by Republican President Richard Nixon in the 1970s. API and Project 2025 sing from the same sheet in their NEPA-related demands, which would curtail scientific and environmental reviews, limit public notice and comment, and block access to the courts. 

Preserve industry giveaways. API finishes off its wish list with requests to preserve fossil fuel industry tax breaks that cost taxpayers some $3 billion each year, regardless of how much they’re currently paying at the pump.

[acuvate-updates]

How Agentic AI & RAG Revolutionize Autonomous Decision-Making

In the swiftly advancing realm of artificial intelligence, the integration of Agentic AI and Retrieval-Augmented Generation (RAG) is revolutionizing autonomous decision-making across various sectors. Agentic AI endows systems with the ability to operate independently, while RAG enhances these systems by incorporating real-time data retrieval, leading to more informed and adaptable decisions. This article delves into the synergistic relationship between Agentic AI and RAG, exploring their combined impact on autonomous decision-making.

Overview

Agentic AI refers to AI systems capable of autonomous operation, making decisions based on environmental inputs and predefined goals without continuous human oversight. These systems utilize advanced machine learning and natural language processing techniques to emulate human-like decision-making processes. Retrieval-Augmented Generation (RAG), on the other hand, merges generative AI models with information retrieval capabilities, enabling access to and incorporation of external data in real-time. This integration allows AI systems to leverage both internal knowledge and external data sources, resulting in more accurate and contextually relevant decisions.

Read more about Agentic AI in Manufacturing: Use Cases & Key Benefits

What is Agentic AI and RAG?

Agentic AI: This form of artificial intelligence empowers systems to achieve specific objectives with minimal supervision. It comprises AI agents—machine learning models that replicate human decision-making to address problems in real-time. Agentic AI exhibits autonomy, goal-oriented behavior, and adaptability, enabling independent and purposeful actions.

Retrieval-Augmented Generation (RAG): RAG is an AI methodology that integrates a generative AI model with an external knowledge base. It dynamically retrieves current information from sources like APIs or databases, allowing AI models to generate contextually accurate and pertinent responses without necessitating extensive fine-tuning.

Know more on Why Businesses Are Embracing RAG for Smarter AI

Capabilities

When combined, Agentic AI and RAG offer several key capabilities:

Autonomous Decision-Making: Agentic AI can independently analyze complex scenarios and select effective actions based on real-time data and predefined objectives.

Contextual Understanding: It interprets situations dynamically, adapting actions based on evolving goals and real-time inputs.

Integration with External Data: RAG enables Agentic AI to access external databases, ensuring decisions are based on the most current and relevant information available.

Enhanced Accuracy: By incorporating external data, RAG helps Agentic AI systems avoid relying solely on internal models, which may be outdated or incomplete.

How Agentic AI and RAG Work Together

The integration of Agentic AI and RAG creates a robust system capable of autonomous decision-making with real-time adaptability:

Dynamic Perception: Agentic AI utilizes RAG to retrieve up-to-date information from external sources, enhancing its perception capabilities. For instance, an Agentic AI tasked with financial analysis can use RAG to access real-time stock market data.

Enhanced Reasoning: RAG augments the reasoning process by providing external context that complements the AI's internal knowledge. This enables Agentic AI to make better-informed decisions, such as recommending personalized solutions in customer service scenarios.

Autonomous Execution: The combined system can autonomously execute tasks based on retrieved data. For example, an Agentic AI chatbot enhanced with RAG can not only answer questions but also initiate actions like placing orders or scheduling appointments.

Continuous Learning: Feedback from executed tasks helps refine both the agent's decision-making process and RAG's retrieval mechanisms, ensuring the system becomes more accurate and efficient over time.

Read more about Multi-Meta-RAG: Enhancing RAG for Complex Multi-Hop Queries

Example Use Case: Customer Service

Customer Support Automation Scenario: A user inquiries about their account balance via a chatbot.

How It Works: The Agentic AI interprets the query, determines that external data is required, and employs RAG to retrieve real-time account information from a database. The enriched prompt allows the chatbot to provide an accurate response while suggesting payment options. If prompted, it can autonomously complete the transaction.

Benefits: Faster query resolution, personalized responses, and reduced need for human intervention.

Example: Acuvate's implementation of Agentic AI demonstrates how autonomous decision-making and real-time data integration can enhance customer service experiences.

2. Sales Assistance

Scenario: A sales representative needs to create a custom quote for a client.

How It Works: Agentic RAG retrieves pricing data, templates, and CRM details. It autonomously drafts a quote, applies discounts as instructed, and adjusts fields like baseline costs using the latest price book.

Benefits: Automates multi-step processes, reduces errors, and accelerates deal closures.

3. Healthcare Diagnostics

Scenario: A doctor seeks assistance in diagnosing a rare medical condition.

How It Works: Agentic AI uses RAG to retrieve relevant medical literature, clinical trial data, and patient history. It synthesizes this information to suggest potential diagnoses and treatment options.

Benefits: Enhances diagnostic accuracy, saves time, and provides evidence-based recommendations.

Example: Xenonstack highlights healthcare as a major application area for agentic AI systems in diagnosis and treatment planning.

4. Market Research and Consumer Insights

Scenario: A business wants to identify emerging market trends.

How It Works: Agentic RAG analyzes consumer data from multiple sources, retrieves relevant insights, and generates predictive analytics reports. It also gathers customer feedback from surveys or social media.

Benefits: Improves strategic decision-making with real-time intelligence.

Example: Companies use Agentic RAG for trend analysis and predictive analytics to optimize marketing strategies.

5. Supply Chain Optimization

Scenario: A logistics manager needs to predict demand fluctuations during peak seasons.

How It Works: The system retrieves historical sales data, current market trends, and weather forecasts using RAG. Agentic AI then predicts demand patterns and suggests inventory adjustments in real-time.

Benefits: Prevents stockouts or overstocking, reduces costs, and improves efficiency.

Example: Acuvate’s supply chain solutions leverage predictive analytics powered by Agentic AI to enhance logistics operations

How Acuvate Can Help

Acuvate specializes in implementing Agentic AI and RAG technologies to transform business operations. By integrating these advanced AI solutions, Acuvate enables organizations to enhance autonomous decision-making, improve customer experiences, and optimize operational efficiency. Their expertise in deploying AI-driven systems ensures that businesses can effectively leverage real-time data and intelligent automation to stay competitive in a rapidly evolving market.

Future Scope

The future of Agentic AI and RAG involves the development of multi-agent systems where multiple AI agents collaborate to tackle complex tasks. Continuous improvement and governance will be crucial, with ongoing updates and audits necessary to maintain safety and accountability. As technology advances, these systems are expected to become more pervasive across industries, transforming business processes and customer interactions.

In conclusion, the convergence of Agentic AI and RAG represents a significant advancement in autonomous decision-making. By combining autonomous agents with real-time data retrieval, organizations can achieve greater efficiency, accuracy, and adaptability in their operations. As these technologies continue to evolve, their impact across various sectors is poised to expand, ushering in a new era of intelligent automation.

[notwiselybuttoowell]

President Joe Biden is expected to permanently ban future offshore oil and gas development in parts of the Atlantic and Pacific oceans in a way that could be especially difficult for the incoming Trump administration to undo.

Biden’s planned executive order will invoke the 1953 Outer Continental Shelf Lands Act, a law that gives presidents broad authority to withdraw federal waters from future oil and gas leasing and development, according to an administration source familiar with the plans.

The law does not give presidents explicit authority to revoke the action and place federal waters back into development, meaning President-elect Donald Trump would have to get Congress to change it before he could reverse Biden’s move.

As Biden’s presidency draws to a close, environmental and climate groups have advocated for him to withdraw areas off the Eastern Gulf of Mexico, as well as other parts of the Atlantic and Pacific oceans – giving the areas permanent protections from future drilling. The move would guard against future oil spills and adding more planet-warming pollution from fossil fuels to the atmosphere.

“We hope it will be part of a very vast area,” Oceana campaign director Joseph Gordon told CNN, adding Biden’s actions “would extend and make permanent those protections.”

Despite a friendly posture towards the oil and gas industry, Trump also moved to ban offshore drilling while president. After proposing a major expansion in offshore drilling early in his first term, Trump in 2020 extended a ban on future oil drilling in the Eastern Gulf and expanded it to include the Atlantic coasts of three states: Florida, Georgia and South Carolina.

“Every president this century has recognized that some areas of the ocean are just too risky or too sensitive to drill,” Earthjustice vice president of litigation for lands, wildlife and oceans Drew Caputo said in a statement.

The White House declined to comment. Biden’s move was first reported by Bloomberg.

Energy analysts told CNN the move won’t make much of a difference in US oil production, which has set new records under Biden.

It’s “not particularly consequential for US exploration and production going forward,” said Tom Kloza, global head of energy analysis at the Oil Price Information Service. Kloza noted there’s plenty of existing offshore rigs pumping oil in the Gulf of Mexico and added that offshore projects typically take 6-8 years to come online.

“I don’t see it as having any real impact on US supply, exports, imports,” Kloza said.

Still, the American Petroleum Institute blasted Biden’s decision, calling it a “misguided approach.”

“We look forward to working with the incoming administration to bring the benefits offshore oil and natural gas production provides to the United States through jobs, investment and domestic energy security,” API senior vice president of policy, economics and regulatory affairs Dustin Meyer said in a statement.

In a separate coming announcement, the Biden administration is also expected to declare two new national monuments in California in the coming week, a source familiar with the planning told CNN.

Biden will establish the Chuckwalla National Monument in Southern California near Joshua Tree National Park and the Sáttítla National Monument in Northern California, the source said. Native tribes have been actively pushing the administration to protect the land from energy development.

This ban has now gone ahead

[deepalitechnovalue]

Polludrone

Polludrone is a Continuous Ambient Air Quality Monitoring System (CAAQMS). It is capable of monitoring various environmental parameters related to Air Quality, Noise, Odour, Meteorology, and Radiation. Polludrone measures the particulate matter and gaseous concentrations in the ambient air in real-time. Using external probes, it can also monitor other auxiliary parameters like traffic, disaster, and weather. Polludrone is an ideal choice for real-time monitoring applications such as Industries, Smart Cities, Airports, Construction, Seaports, Campuses, Schools, Highways, Tunnels, and Roadside monitoring. It is the perfect ambient air quality monitoring system to understand a premise's environmental health.

Product Features:

Patented Technology: Utilizes innovative e-breathing technology for higher data accuracy.

Retrofit Design: Plug-and-play design for ease of implementation.

Compact: Lightweight and compact system that can be easily installed on poles or walls.

Internal Storage: Internal data storage capacity of up to 8 GB or 90 days of data.

On-device Calibration: On-site device calibration capability using built-in calibration software.

Identity and Configuration: Geo-tagging for accurate location (latitude and longitude) of the device.

Tamper-Proof: IP 66 grade certified secure system to avoid tampering, malfunction, or sabotage.

Over-the-Air Update: Automatically upgradeable from a central server without the need for an onsite visit.

Network Agnostic: Supports a wide range of connectivity options, including GSM, GPRS, Wi-Fi, LoRa, NBIoT, Ethernet, Modbus, Relay, and Satellite.

Real-Time Data: Continuous monitoring with real-time data transfer at configurable intervals.

Weather Resistant: Durable IP 66 enclosure designed to withstand extreme weather conditions.

Fully Solar Powered: 100% solar-powered system, ideal for off-grid locations.

Key Benefits:

Robust and Rugged: Designed with a durable enclosure to withstand extreme climatic conditions.

Secure Cloud Platform: A secure platform for visualizing and analyzing data, with easy API integration for immediate action.

Accurate Data: Provides real-time, accurate readings to detect concentrations in ambient air.

Easy to Install: Effortless installation with versatile mounting options.

Polludrone Usecases:

Industrial Fenceline: Monitoring pollution at the industry fenceline ensures compliance with policies and safety regulations, and helps monitor air quality levels.

Smart City and Campuses: Pollution monitoring in smart cities and campuses provides authorities with actionable insights for pollution control and enhances citizen welfare.

Roads, Highways, and Tunnels: Pollution monitoring in roads and tunnels supports the creation of mitigation action plans to control vehicular emissions.

Airports: Pollution and noise monitoring at taxiways and hangars helps analyze the impact on travelers and surrounding neighborhoods. Visit www.technovalue.in for more info.

[allthebrazilianpolitics]

Fully protected marine areas in Brazil are contaminated by microplastics

Researchers from the Federal University of São Paulo used oysters and mussels as sentinel organisms to assess the presence of these pollutants. The results show that even the most restrictive sites for human presence have significant contamination.

Despite being considered sanctuaries for biodiversity, Brazil’s marine protected areas (MPAs) are not immune to microplastic contamination. A recent study has shown that even MPAs classified as integral protection areas (APIs), which are the most restrictive to human intervention, are contaminated by this material. The research, which involved Brazilian and Australian scientists, used bivalve mollusks (oysters and mussels) as sentinel organisms to assess contamination. The results were published in the journal Environmental Research.

“Our study showed that microplastic contamination occurs even in the most restrictive environmental protection areas. For example, in Atol das Rocas, where there’s no economic activity and tourists aren’t allowed to visit. Microplastics can reach places like this by being carried by the wind or ocean currents,” Ítalo Braga, coordinator of the research funded by FAPESP and professor at the Institute of Marine Science of the Federal University of São Paulo (IMar-UNIFESP) in Brazil, told Agência FAPESP. 

Microplastics are particles ranging in size from 1 micron (1 μm) to 5 millimeters (5 mm) that result from the fragmentation of larger plastics or are directly manufactured in this format for industrial or cosmetic use. Those detected in the study showed consistent patterns along the Brazilian coast: predominantly black, white or transparent, and less than 1 millimeter in size.

Continue reading.

[jcmarchi]

Top 5 areas in the data pipeline with the least responsiveness

New Post has been published on https://thedigitalinsider.com/top-5-areas-in-the-data-pipeline-with-the-least-responsiveness/

Top 5 areas in the data pipeline with the least responsiveness

Data pipelines are critical for organizations handling vast amounts of data, yet many practitioners report challenges with responsiveness, especially in data analysis and storage.

Our latest generative AI report revealed that various elements within the pipeline significantly affect performance and usability. We wanted to investigate what could be affecting the responsiveness of the practitioners who reported issues. 

The main area of data workflow or pipeline where practitioners find the least responsiveness is data analysis (28.6%), followed by data storage (14.3%) and other reasons (14.3%), such as API calls, which generally take a significant amount of time.

What factors have an impact on that portion of the data pipeline?

We also asked practitioners about the factors impacting that portion of the pipeline. The majority (58.3%) cited the efficiency of the pipeline tool as the key factor. This could point to a pressing need for improvements in the performance and speed of these tools, which are essential for maintaining productivity and ensuring fast processing times in environments where quick decision-making is key.

With 25% of practitioners pointing to storage as a significant bottleneck after the efficiency of the pipeline tool, inadequate or inefficient storage solutions can impact the ability to process and manage large volumes of data effectively. 

16.7% of practitioners highlighted that code quality disrupts the smooth operation of AI pipelines. This can lead to errors, increased downtime, and complicated maintenance and updates. 

Code quality

The quality of the code in the data pipeline is key to its overall performance and reliability. High-quality code often leads to fewer errors and disruptions, translating to smoother data flows and more reliable outputs. 

Examples of how high code quality can enhance responsiveness:

1. Error handling and recovery

2. Optimized algorithms 

3. Scalability

4. Maintainability and extensibility

5. Parallel processing and multithreading

6. Effective resource management 

7. Testing and quality assurance

Efficiency of pipeline tool

Efficient tools can quickly handle large volumes of data, helping to support complex data operations without performance issues. This is an essential factor when dealing with big data or real-time processing needs, where delays can lead to outdated or irrelevant insights. 

Examples of how the efficiency of pipeline tools can enhance responsiveness:

Data processing speed 

Resource utilization

Minimized latency

Caching and state management

Load balancing

Automation and orchestration

Adaptability to data volume and variety

Storage

Storage solutions in a data pipeline impact the cost-effectiveness and performance of data handling. Effective storage solutions must offer enough space to store data while being accessible and secure. 

Examples of how storage can enhance responsiveness:

Data retrieval speed

Data redundancy and backup

Scalability

Data integrity and security

Cost efficiency

Automation and management tools

Integration capabilities

What use cases are driving your data pipeline?

What use cases are driving your data pipeline?

We also asked respondents to identify the specific scenarios or business needs that drive their data pipelines’ design, implementation, and operation to understand the primary purposes for which the data pipeline is being utilized within their organizations.

Natural language processing, or NLP, was highlighted as the main use case (42.8%), with an even distribution across the other use cases. This could be due to businesses increasing their operations in digital spaces, which generate vast amounts of textual data from sources like emails, social media, customer service chats, and more.

NLP

NLP applications require processing and analyzing text data to complete tasks like sentiment analysis, language translation, and chatbot interactions. Effective data pipelines for NLP need to manage diverse data sources like social media posts, customer feedback, and technical documents.

Examples of how NLP drives data pipelines:

Extracting key information from text data

Categorizing and tagging content automatically

Analyzing sentiment in customer feedback

Enhancing search and discovery through semantic analysis

Automating data entry from unstructured sources

Generating summaries from large text datasets

Enabling advanced question-answering systems

Image recognition

Image recognition analyzes visual data to identify objects, faces, scenes, and activities. Data pipelines for image recognition have to handle large volumes of image data efficiently, which requires significant storage and powerful processing capabilities. 

Examples of how image recognition drives data pipelines:

Automating quality control in manufacturing

Categorizing and tagging digital images for easier retrieval

Enhancing security systems with facial recognition

Enabling autonomous vehicle navigation

Analyzing medical images for diagnostic purposes

Monitoring retail spaces for inventory control

Processing satellite imagery for environmental monitoring

Image/visual generation

Data pipelines are designed to support the generation process when generative models are used to create new images or visual content, such as in graphic design or virtual reality. 

Examples of how image/visual generation drives data pipelines:

Creating virtual models for fashion design

Generating realistic game environments and characters

Simulating architectural visualizations for construction planning

Producing visual content for marketing and advertising

Developing educational tools with custom illustrations

Enhancing film and video production with CGI effects

Creating personalized avatars for social media platforms

Recommender systems

Recommender systems are useful in a wide variety of applications, from e-commerce to content streaming services, where personalized suggestions improve user experience and engagement. 

Examples of how recommender systems drive data pipelines:

Personalizing content recommendations on streaming platforms

Suggesting products to users on e-commerce sites

Tailoring news feeds on social media

Recommending music based on listening habits

Suggesting connections on professional networks

Customizing advertising to user preferences

Proposing travel destinations and activities based on past behavior

[canmom]

so there's a widely used tool called ReShade which intercepts the DirectX API calls of a game to add additional post-processing effects using the game's frame and depth buffers. basically gives you access to various deferred techniques, with certain technical caveats. common effects include bloom, depth of field, tonemapping, and screen space ambient occlusion.

one of the more ambitious effects is Screen Space Realtime Global Illumination (SSRTGI, or just RTGI), implemented in Marty's Mods. this attempts to simulate diffuse-diffuse interreflection, i.e. how the light from a brightly lit object will spill onto surrounding objects. it's a very important part of rendering bright, colourful scenes.

Global Illumination is usually handled in offline rendering by raytracing, and there's been a lot of excitement in the last few years about the new realtime raytracing acceleration hardware in graphics cards. SSRTGI doesn't use this at all: it knows nothing about the scene geometry beyond the depth buffer. instead it uses raymarching, which steps a ray forward a fixed distance at a time until it discovers an intersection with the depth buffer. Since we're using the depth buffer, the algorithm only knows about the near sides of objects.

This video is a bit rambling but it shows some of the limitations of SSRTGI:

So this has been a fun new toy to play with now my computer can handle it. For example, here's a scene with a bright dancefloor in FFXIV's default renderer, which by default has a strong green tint and desaturated colours.

The Alive preset's colour grade improves matters a lot (this scene doesn't necessarily show the best of it, but removing the green tint and desaturation is a night and day difference throughout the game)...

...but my character's legs should be affected by the bright floor. Enter SSRTGI. I can actually isolate the exact RTGI contribution:

I've turned up the ray length a fair bit compared to the Alive preset's default, since it was a bit too subtle to be worth the performance hit otherwise.

You can see that the SSRTGI models both ambient occlusion and indirect light from bright surfaces. Essentially, each pixel traces a ray in a random direction until it hits a surface visible to the camera. Then, it samples the brightness of that pixel and calculates a light contribution and AO amount. I assume it does some kind of average over neighbouring pixels to smooth out the noise.

The effect is a little subtle, but it makes the scene look more integrated...

...at the cost of a hefty framerate hit (using a 4070Ti; unmodded FFXIV runs at an 1440p ultrawide on an easy 144fps (the monitor refresh rate), without RTGI I can get into the mid 90s, with RTGI it's pretty resolutely locked at 72), and heating my graphics card up to 70-80°C (well within tolerances but it's rare to see a game push it that hard).

The effect may be a little subtle in this scene, which has a lot of high frequency detail and darker materials. It really pops in the Fall Guys crossover, which is a very bright scene.

Note the bright green reflected light on the green cube as a particularly obvious RTGI effect (although the shadow it casts is kinda janky ngl). I should really get a screenshot of the exact RTGI contribution in this area, and create a suite of comparisons like the above.

The RTGI also stands out on bright days in Ul'dah, it does a lot for the Gold Saucer, and generally it makes certain environmental light sources a bit prettier. If you turn it up too much it starts to look a bit silly, since brightly lit floors turn into brilliant torches lighting up nearby walls. But there's a comfy middle ground where it's noticeable without being too extreme. I'm looking forward to seeing how it fares in the colourful areas of the expansions, but this character isn't out of ARR yet.

So, that's cool and all, but toying around with SSRTGI, you really start to feel its limits compared to true raytracing. For example, objects will cast shadows in the indirect lighting, but the specular light contributions are not properly affected by the base game's shadowmaps, so you see speculars in places that you shouldn't. A decent number of surfaces in FFXIV have planar reflections (using the usual technique of rendering the scene inverted through the mirror to a rendertexture), which is nice, but there's no middle ground between 'perfect mirror' and 'rough specular that still reflects the scene'. And of course the other usual limitations of SSRTGI, e.g. a brightly lit surface must be visible to the camera to contribute light.

No, this is nice and all, but the people want real raytracing. Which leads me to wonder is there a way to intercept all the draw calls issued by an application, extract the geometry from them, reformat it for raytracing and feed it into the raytracing hardware - basically replace the game's entire render pipeline with raytracing?

This is going to take some research. It very likely isn't possible, or performant if it was possible, because a lot of smart tech artists have already been working hard to push the limits of ENBSeries, Reshade, etc. (Acerola has a solid video on implementing various effects in Reshade.) But the imp of the perverse in me wants to figure out if it can be done. After all, RenderDoc is capable of intercepting and analysing all the draw calls issued by an application. The question is, how severe is the overhead of on-the-fly translating rasterisation calls into raytracing calls? Most likely absolutely hideous! That's not how you're supposed to use a graphics card!

Since the hardware I develop for very definitely does not support raytracing, I have relatively little idea how you actually write a shader with raytracing. But now I kind of want to find out. If I ever get anywhere beyond idle thoughts, I'll let you know what I find out.

[shinelikethunder]

looooool i'm already seeing people in the notes of that open-source post get catty about the quality of tumblr's software development practices, to which all i have to say is. you fools. you sweet summer children. i was messing around with tumblr's API long before the porn ban & the sale to automattic, and i've seen environmental-storytelling horrors in the legacy data that you people wouldn't believe. this? this shit is fucking PRISTINE. i had to pinch myself poking through the github repo. make your peace with the intrinsic messy-ass-bitchdom of having to code in the real world where your predecessors + yesteryear's corporate overlords sure have made some decisions, lest god afflict you with visions of all the CakeWrecks Dot Com bullshit that powers the united states department of defense.

[fishcemetery]

By @colourswirlcannibal 's request, here's a list of environmental/atmospheric/biome Minecraft mods I use:

Abundant Atmosphere

Additional Structures

Alex's Mobs

Biome Makeover

Biomes O' Plenty

Ecologics

Endless Biomes

End's Phantasm

Explorify

Friends & Foes

Galosphere

Gardens of the Dead

Geophilic

Good Ending

Nether Depths Upgrade

Sculked

Windswept

Team Abnormals:

Atmospheric

Autumnity

Buzzier Bees

Environmental

Quark

Upgrade Aquatic

+ Stay True Texture Pack

+ Complementary Reimagined Shaders

(read the descriptions carefully and remember to get all necessary libraries/APIs/so on)

[chemicalresearchupdates]

Exploring the Global Aldehydes Market: Key Players and Market Dynamics

The aldehydes market is a segment of the chemical industry that deals with the production and distribution of a class of organic compounds known as aldehydes. These compounds are characterized by the presence of a carbonyl group (C=O) bonded to a hydrogen atom and a carbon atom in their chemical structure. Aldehydes find widespread applications in various industries, thanks to their unique properties and versatile reactivity.

In terms of market overview, the aldehydes market has been experiencing steady growth in recent years. This growth can be attributed to the increasing demand for aldehydes in industries such as pharmaceuticals, agriculture, food and beverages, and cosmetics. Aldehydes serve as crucial intermediates in the synthesis of various chemicals and are essential in the production of fragrances, flavor enhancers, and pharmaceuticals.

The growth in the aldehydes market industry can be primarily attributed to the expansion of these end-user industries. For instance, the pharmaceutical industry relies heavily on aldehydes for the synthesis of a wide range of drugs and active pharmaceutical ingredients (APIs). Additionally, the food and beverage industry utilizes aldehydes for flavor enhancement and preservation purposes, further driving market growth.

The aldehydes market is also influenced by evolving industry trends. One significant trend is the increasing emphasis on green chemistry and sustainable practices. Many companies in the aldehydes sector are adopting environmentally friendly production processes, such as catalytic hydrogenation, to reduce the environmental impact of their operations. This trend aligns with the growing awareness of environmental issues and the need for more eco-friendly chemical manufacturing.

Another noteworthy trend is the constant innovation and development of novel aldehyde derivatives with enhanced properties. This innovation is driven by the demand for higher-quality products in various industries. Researchers and manufacturers are continuously exploring new applications and synthesizing aldehydes tailored to meet specific industry requirements, which contributes to market expansion.

In conclusion, the aldehydes market is a dynamic segment within the chemical industry, driven by the increasing demand from various end-user industries. As industries continue to grow and evolve, the market is expected to witness further advancements, particularly in sustainable production methods and novel aldehyde derivatives, to meet the changing needs of consumers and businesses alike.

[vanauviet]

Tiêu chuẩn và quy định liên quan đến van 2 ngã

Việc sử dụng và vận hành van 2 ngã trong các ứng dụng công nghiệp và hệ thống cấp nước cần tuân thủ các tiêu chuẩn và quy định để đảm bảo an toàn và hiệu quả. Dưới đây là một số tiêu chuẩn và quy định quan trọng liên quan đến van 2 ngã: Tiêu chuẩn sản xuất và chất lượng: Mỗi quốc gia có thể có các tiêu chuẩn sản xuất và chất lượng riêng để đảm bảo rằng van 2 ngã đáp ứng các yêu cầu kỹ thuật và an toàn. Ví dụ: tiêu chuẩn ASTM (American Society for Testing and Materials) và tiêu chuẩn ISO (International Organization for Standardization) cung cấp các hướng dẫn về yêu cầu chất lượng và thử nghiệm cho van 2 ngã. Tiêu chuẩn kỹ thuật: Các tiêu chuẩn kỹ thuật quy định các thông số kỹ thuật cụ thể cho van 2 ngã, bao gồm kích thước, áp suất làm việc, dải nhiệt độ, độ chính xác và độ bền. Ví dụ: tiêu chuẩn ANSI (American National Standards Institute) và tiêu chuẩn API (American Petroleum Institute) cung cấp các hướng dẫn về tiêu chuẩn kỹ thuật cho van công nghiệp. Quy định an toàn: Các quy định an toàn quy định các yêu cầu và tiêu chuẩn an toàn cho van 2 ngã, đảm bảo rằng nó hoạt động một cách an toàn và không gây nguy hiểm cho môi trường và con người. Ví dụ: quy định của OSHA (Occupational Safety and Health Administration) và các quy định an toàn quốc gia có thể yêu cầu việc sử dụng van 2 ngã đạt các tiêu chuẩn an toàn nhất định. Quy định môi trường: Trong một số ứng dụng, van 2 ngã cần tuân thủ các quy định về môi trường để đảm bảo không gây ô nhiễm và tuân thủ các tiêu chuẩn về bảo vệ môi trường. Ví dụ: quy định của EPA (Environmental Protection Agency) và các quy định quốc gia có thể áp dụng cho van 2 ngã trong các ứng dụng liên quan đến xử lý nước thải và bảo vệ môi trường. Quy định vận hành và bảo trì: Để đảm bảo hoạt động đúng cách và an toàn của van 2 ngã, cần tuân thủ các quy định và hướng dẫn vận hành và bảo trì cung cấp bởi nhà sản xuất và các c�� quan quản lý. Các hướng dẫn này bao gồm các biện pháp bảo trì định kỳ, kiểm tra áp suất, bôi trơn và thay thế bộ phận hỏng. Tóm lại, việc tuân thủ tiêu chuẩn và quy định liên quan đến van 2 ngã là rất quan trọng để đảm bảo hoạt động an toàn và hiệu quả của hệ thống. Các tiêu chuẩn và quy định này đảm bảo rằng van đáp ứng các yêu cầu kỹ thuật, an toàn và môi trường.

Tìm Hiểu Thêm: Van 2 ngã - van bi vi sinh điều khiển khí nén hàng chính hãng giá ưu đãi

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#auvietco-com-vn, #vannuoc1chieu, #vandientu