Category Archives: Human Behavior

Human Behavior

Understanding human behavior as part of the IPM process – Pest Management Professional – Pest Management Professional magazine

PHOTO: KAMELEON007/ISTOCK / GETTY IMAGES PLUS/GETTY IMAGES

There are lots of ways to practice integrated pest management (IPM), but many pest management professionals (PMPs) would agree that IPM includes sanitation, exclusion and chemical control elements as part of a multifaceted approach to managing pest populations.

Many PMPs also would agree that one of the biggest hurdles to implementing a successful IPM program for clients are the clients themselves.

A commonly recommended IPM tactic is to keep doors and windows closed to keep flying insects from entering a building. Yet, why do we find this suggestion so often ignored? Here are a few questions to consider that could help get to the root cause:

Certainly, budget limitations can affect how quickly (and effectively) your exclusion recommendations are executed. And operational constraints can make sanitation tricky. But the biggest hurdle almost always is people.

By taking a closer look and understanding the underlying behaviors that are making effective pest management more difficult, the root cause can be addressed. Everybody wins.

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Understanding human behavior as part of the IPM process - Pest Management Professional - Pest Management Professional magazine

Human Behavior

The Office Teaches Human Behavior to AI. Is That Really a Good Thing? – DesignNews

Humans know how to interact with each other using body language and communication, but robots developed to work alongside people dont have this innate sensibility.

Artificial intelligence (AI) is helping collaborative robots predict how a person likely will behave so it can respond accordingly. That is one reason why researchers have been using movies, popular TVs shows, and sports to train the system on human behavior.

Related: Will Advanced Artificial Skin Raise Hope in Restoring a Sense of Touch?

Researchers from Columbia Engineering developed a computer-vision technique for giving machines a more intuitive sense for patterns of human behavior by using higher-level associations between people, animals, and objects. They also leveraged an ancient form of geometry in their mathematical framework for how the AI functions.

The algorithm, the most accurate method to date for predicting video action events up to several minutes in the future, analyzed thousands of hours of movies, sporting events, and TV shows like The Office. In this way, it learned to predict hundreds of human interactions and activities, such as handshakes or fist bumps.

Related: Can New Materials Discovery get a Boost From Artificial Intelligence?

When the system cant predict the specific action, it finds a higher-level concept that is related to the action, such as, in the case of handshakes or fist bumps, the word greeting, researchers said.

Our algorithm is a step toward machines being able to make better predictions about human behavior, and thus better coordinate their actions with ours, said Carl Vondrick, assistant professor of computer science at Columbia, who directed the study. Our results open several possibilities for human-robot collaboration, autonomous vehicles, and assistive technology.

The team is no stranger to predictive machine learning. However, in the past, its efforts, like those of other scientists, included predicting just one action at a time. In this scenario, the algorithms must decide how to classify an actsuch as a hug, high five, or even someones lack of response, which would be classified as ignore.

However, when algorithms couldnt with high certainty identify an action, most couldnt find common threads between following potential options for action, researchers said.

To find a new way to develop long-range prediction models, Columbia Engineering Ph.D. students Didac Suris and Ruoshi Liu took a different approach based on the idea that not everything in the future is predictable, Suris said in a press statement.

When a person cannot foresee exactly what will happen, they play it safe and predict at a higher level of abstraction, he said in the statement. Our algorithm is the first to learn this capability to reason abstractly about future events.

In other words, the new AI model can recognize when it cant predict a future action with certainty and, like people do all the time, can make a guess as to what it will be by relating it to a concept.

To develop the model based on this idea, Suris and Liu used unusual geometries that arent commonly taught in high-school mathematics; instead, they date back to the time of ancient Greeks. These geometries have counter-intuitive properties in which the straight lines of typical geometry can bend, and triangles dont have three even sides but instead bulge, researchers said.

Using principles of this unusual type of geometry, researchers constructed AI models that could organize high-level concepts to predict future human behavior based on how predictable events are in the future, they said.

For example, humans know that swimming and running are both types of exercise. The system can categorize such related activities on its while also being aware of uncertainty. The latter instance provides more specific actions when there is a certainty and more generic predictions when there is not, researchers said.

Human behavior is often surprising, Vondrick said in a press statement. Our algorithms enable machines to anticipate better what they are going to do next.

Researchers wrote a paper on their work and presented the study at the International Conference on Computer Vision and Pattern Recognition on June 24.

While computers currently take action based on preprogramming, the model developed by the team can help give collaborative robots more spontaneity, just as humans do in their interactions, Liu said. This can help humans who in the future work closely with robots form a type of relationship, he said.

Trust comes from the feeling that the robot understands people, Liu explained in a press statement. If machines can understand and anticipate our behaviors, computers will be able to seamlessly assist people in daily activity.

Researchers plan to continue their work by verifying how the algorithm works outside of the lab in diverse settings rather than merely testing it on benchmark tasks, they said. If its successful, the model can develop and eventually use robots that can work alongside humans to improve our safety, health, and security, researchers said.

The team also plans to continue to improve the algorithms performance with larger datasets and computers, and other forms of geometry.

Stills from The Cider House Rules (top) and Mumford (bottom).

Elizabeth Montalbano is a freelance writer who has written about technology and culture for more than 20 years. She has lived and worked as a professional journalist in Phoenix, San Francisco, and New York City. In her free time, Elizabeth enjoys surfing, traveling, music, yoga, and cooking. She currently resides in a village on the southwest coast of Portugal.

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The Office Teaches Human Behavior to AI. Is That Really a Good Thing? - DesignNews

Human Behavior

Don’t rely too much on social media to understand human behavior – The Next Web

Since the early days of social media, there has been a lot ofexcitement about how data traces left behind by users can be exploited for the study of human behavior. Nowadays, researchers who were once restricted to surveys or experiments in laboratory settings have access to huge amounts of real-world data from social media.

The research opportunities enabled by social media data are undeniable. However, researchers often analyze this data with tools that were not designed to manage the kind of large, noisy observational sets of data you find on social media.

We explored problems that researchers might encounter due to this mismatch between data and methods.

What we found is that the methods and statistics commonly used to provide evidence for seemingly significant scientific findings can also seem to support nonsensical claims.

The motivation for our paper comes from a series of research studies that deliberately present absurd scientific results.

One brain imaging study appeared to show the neural activity of a dead salmon tasked with identifying emotions in photos. An analysis of longitudinal statistics from public health records suggested that acne, height, and headaches are contagious. And an analysis of human decision-making seemingly indicated people can accurately judge the population size of different cities by ranking them in alphabetical order.

Why would a researcher go out of their way to explore such ridiculous ideas? The value of these studies is not in presenting a new substantive finding. No serious researcher would argue, for example, that a dead salmon has a perspective on emotions in photos.

Rather, the nonsensical results highlight problems with the methods used to achieve them. Our research explores whether the same problems can afflict studies that use data from social media. And we discovered that indeed they do.

When a researcher seeks to address a research question, the method they use should be able to do two things:

For example, imagine you have chronic back pain and you take a medical test to find its cause. The test identifies a misaligned disc in your spine. This finding might be important and inform a treatment plan.

However, if you then discover the same test identifies this misaligned disc in a large proportion of the population who do not have chronic back pain, the finding becomes far less informative for you.

The fact the test fails to identify a relevant, distinguishing feature of negative cases (no back pain) from positive cases (back pain) does not mean the misaligned disc in your spine is non-existent. This part of the finding is as real as any finding. Yet the failure means the result is not useful: evidence that is as likely to be found when there is a meaningful effect (in this case, back pain) as when there is none is simply not diagnostic, and, as result, such evidence is uninformative.

Using the same rationale, we evaluated commonly used methods for analyzing social media data called null hypothesis significance testing and correlational statistics by asking an absurd research question.

Past and current studies have tried to identify what factors influence Twitter users decisions to retweet other tweets. This is interesting both as a window into human thought and because resharing posts is a key mechanism by which messages are amplified or spread on social media.

So we decided to analyze Twitter data using the above standard methods to see whether a nonsensical effect we call XYZ contagion influences retweets. Specifically, we asked

Does the number of Xs, Ys, and Zs in a tweet increase the probability of it being spread?

Upon analyzing six datasets containing hundreds of thousands of tweets, the answer we found was yes. For example, in a dataset of 172,697 tweets about COVID-19, the presence of an X, Y, or Z in a tweet appeared to increase the messages reach by a factor of 8%.

Needless to say, we do not believe the presence of Xs, Ys, and Zs is a central factor in whether people choose to retweet a message on Twitter.

However, like the medical test for diagnosing back pain, our finding shows that sometimes, methods for social media data analysis can reveal effects where there should be none. This raises questions about how meaningful and informative results obtained by applying current social science methods to social media data really are.

As researchers continue to analyze social media data and identify factors that shape the evolution of public opinion, hijack our attention, or otherwise explain our behavior, we should think critically about the methods underlying such findings and reconsider what we can learn from them.

The issues raised in our paper are not new, and there are indeed many research practices that have been developed to ensure results are meaningful and robust.

For example, researchers are encouraged to pre-register their hypotheses and analysis plans before starting a study to prevent a kind of data cherry-picking called p-hacking. Another helpful practice is to check whether results are stable after removing outliers and controlling for covariates. Also important are replication studies, which assess whether the results obtained in an experiment can be found again when the experiment is repeated under similar conditions.

These practices are important, but they alone are not sufficient to deal with the problem we identify. While developing standardized research practices is needed, the research community must first think critically about what makes a finding in social media data meaningful.

Article by Jason Burton, PhD researcher, Birkbeck, University of London; Nicole Cruz, Postdoctoral Research Associate, UNSW, and Ulrike Hahn, Professor of Psychology, Birkbeck, University of London

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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Don't rely too much on social media to understand human behavior - The Next Web

Human Behavior

Dont hike so close to me: How the presence of humans can disturb wildlife up to half a mile away – The Current GA

Millions of Americans are traveling this summer as pandemic restrictions wind down. Rental bookings and crowds in national parks show that many people are headed for the great outdoors.

This story also appeared in The Conversation

Seeing animals and birds is one of the main draws of spending time in nature. But as researchers who study conservation, wildlife and human impacts on wild places, we believe its important to know that you can have major effects on wildlife just by being nearby.

In a recent review of hundreds of studies covering many species, we found that the presence of humans can alter wild animal and bird behavior patterns at much greater distances than most people may think. Small mammals and birds may change their behavior when hikers or birders come within 300 feet (100 meters) the length of a football field. Large birds like eagles and hawks can be affected when humans are over 1,300 feet (400 meters) away roughly a quarter of a mile. And large mammals like elk and moose can be affected by humans up to 3,300 feet (1,000 meters) away more than half a mile.

Many recent studies and reports have shown that the world is facing a biodiversity crisis. Over the past 50 years, Earth has lost so many species that many scientists believe the planet is experiencing its sixth mass extinction due mainly to human activities.

Protected areas, from local open spaces to national parks, are vital for conserving plants and animals. They also are places where people like to spend time in nature. We believe that everyone who uses the outdoors should understand and respect this balance between outdoor recreation, sustainable use and conservation.

Pandemic lockdowns in 2020 confined many people indoors and wildlife responded. In Istanbul, dolphins ventured much closer to shore than usual. Penguins explored quiet South African Streets. Nubian ibex grazed on Israeli playgrounds. The fact that animals moved so freely without people present shows how wild species change their behavior in response to human activities.

Decades of research have shown that outdoor recreation, whether its hiking, cross-country skiing or riding all-terrain vehicles, has negative effects on wildlife. The most obvious signs are behavioral changes: Animals may flee from nearby people, decrease the time they feed and abandon nests or dens.

Other effects are harder to see, but can have serious consequences for animals health and survival. Wild animals that detect humans can experience physiological changes, such as increased heart rates and elevated levels of stress hormones.

And humans outdoor activities can degrade habitat that wild species depend on for food, shelter and reproduction. Human voices, off-leash dogs and campsite overuse all have harmful effects that make habitat unusable for many wild species. Disturbing shorebirds can cause them to stop eating, stop feeding their young or flee their nests, leaving chicks vulnerable.

For our study we examined 330 peer-reviewed articles spanning 38 years to locate thresholds at which recreation activities negatively affected wild animals and birds. The main thresholds we found were related to distances between wildlife and people or trails. But we also found other important factors, including the number of daily park visitors and the decibel levels of peoples conversations.

The studies that we reviewed covered over a dozen different types of motorized and nonmotorized recreation. While it might seem that motorized activities would have a bigger impact, some studies have found that dispersed quiet activities, such as day hiking, biking and wildlife viewing, can also affect which wild species will use a protected area.

Put another way, many species may be disturbed by humans nearby, even if those people are not using motorboats or all-terrain vehicles. Its harder for animals to detect quiet humans, so theres a better chance that theyll be surprised by a cross-country skier than a snowmobile, for instance. In addition, some species that have been historically hunted are more likely to recognize and flee from a person walking than a person in a motorized vehicle.

Generally, larger animals need more distance, though the relationship is clearer for birds than mammals. We found that for birds, as bird size increased, so did the threshold distance. The smallest birds could tolerate humans within 65 feet (20 meters), while the largest birds had thresholds of roughly 2,000 feet (600 meters). Previous research has found a similar relationship. We did not find that this relationship existed as clearly for mammals.

We found little research on impact thresholds for amphibians and reptiles, such as lizards, frogs, turtles and snakes. A growing body of evidence shows that amphibians and reptiles are disturbed and negatively affected by recreation. So far, however, its unclear whether those effects reflect mainly the distance to people, the number of visitors or other factors.

While theres much still to learn, we know enough to identify some simple actions people can take to minimize their impacts on wildlife. First, keep your distance. Although some species or individual animals will become used to human presence at close range, many others wont. And it can be hard to tell when you are stressing an animal and potentially endangering both it and yourself.

Second, respect closed areas and stay on trails. For example, in Jackson Hole, Wyoming, wildlife managers seasonally close some backcountry ski areas to protect critical habitat for bighorn sheep and reduce stress on other species like moose, elk and mule deer. And rangers in Maines Acadia National Park close several trails annually near peregrine falcon nests. This reduces stress to nesting birds and has helped this formerly endangered species recover.

Getting involved with educational or volunteer programs is a great way to learn about wildlife and help maintain undisturbed areas. As our research shows, balancing recreation with conservation means opening some areas to human use and keeping others entirely or mostly undisturbed.

As development fragments wild habitat and climate change forces many species to shift their ranges, movement corridors between protected areas become even more important. Our research suggests that creating recreation-free wildlife corridors of at least 3,300 feet (1,000 meters) wide can enable most species to move between protected areas without disturbance. Seeing wildlife can be part of a fun outdoor experience but for the animals sake, you may need binoculars or a zoom lens for your camera.

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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Dont hike so close to me: How the presence of humans can disturb wildlife up to half a mile away - The Current GA

Human Behavior

Getting dressed with help from robots – MIT News

Basic safety needs in the paleolithic era have largely evolved with the onset of the industrial and cognitive revolutions. We interact a little less with raw materials, and interface a little more with machines.

Robots dont have the same hardwired behavioral awareness and control, so secure collaboration with humans requires methodical planning and coordination. You can likely assume your friend can fill up your morning coffee cup without spilling on you, but for a robot, this seemingly simple task requires careful observation and comprehension of human behavior.

Scientists from MITs Computer Science and Artificial Intelligence Laboratory (CSAIL) have recently created a new algorithm to help a robot find efficient motion plans to ensure physical safety of its human counterpart. In this case, the bot helped put a jacket on a human, which could potentially prove to be a powerful tool in expanding assistance for those with disabilities or limited mobility.

Developing algorithms to prevent physical harm without unnecessarily impacting the task efficiency is a critical challenge, says MIT PhD student Shen Li, a lead author on a new paper about the research. By allowing robots to make non-harmful impact with humans, our method can find efficient robot trajectories to dress the human with a safety guarantee.

Robot-assisted dressing could aid those with limited mobility or disabilities.

Human modeling, safety, and efficiency

Proper human modeling how the human moves, reacts, and responds is necessary to enable successful robot motion planning in human-robot interactive tasks. A robot can achieve fluent interaction if the human model is perfect, but in many cases, theres no flawless blueprint.

A robot shipped to a person at home, for example, would have a very narrow, default model of how a human could interact with it during an assisted dressing task. It wouldnt account for the vast variability in human reactions, dependent on myriad variables such as personality and habits. A screaming toddler would react differently to putting on a coat or shirt than a frail elderly person, or those with disabilities who might have rapid fatigue or decreased dexterity.

If that robot is tasked with dressing, and plans a trajectory solely based on that default model, the robot could clumsily bump into the human, resulting in an uncomfortable experience or even possible injury. However, if its too conservative in ensuring safety, it might pessimistically assume that all space nearby is unsafe, and then fail to move, something known as the "freezing robot" problem.

To provide a theoretical guarantee of human safety, the team's algorithm reasons about the uncertainty in the human model. Instead of having a single, default model where the robot only understands one potential reaction, the team gave the machine an understanding of many possible models, to more closely mimic how a human can understand other humans. As the robot gathers more data, it will reduce uncertainty and refine those models.

To resolve the freezing robot problem, the team redefined safety for human-aware motion planners as either collision avoidance or safe impact in the event of a collision. Often, especially in robot-assisted tasks of activities of daily living, collisions cannot be fully avoided. This allowed the robot to make non-harmful contact with the human to make progress, so long as the robot's impact on the human is low. With this two-pronged definition of safety, the robot could safely complete the dressing task in a shorter period of time.

For example, lets say there are two possible models of how a human could react to dressing. Model One is that the human will move up during dressing, and Model Two is that the human will move down during dressing. With the teams algorithm, when the robot is planning its motion, instead of selecting one model, it will try to ensure safety for both models. No matter if the person is moving up or down, the trajectory found by the robot will be safe.

To paint a more holistic picture of these interactions, future efforts will focus on investigating the subjective feelings of safety in addition to the physical during the robot-assisted dressing task.

This multifaceted approach combines set theory, human-aware safety constraints, human motion prediction, and feedback control for safe human-robot interaction, says assistant professor in The Robotics Institute at Carnegie Mellon University Zackory Erickson. This research could potentially be applied to a wide variety of assistive robotics scenarios, towards the ultimate goal of enabling robots to provide safer physical assistance to people with disabilities.

Li wrote the paper alongside CSAIL postdoc Nadia Figueroa, MIT PhD student Ankit Shah, and MIT Professor Julie A. Shah. They will present the paper virtually at the 2021 Robotics: Science and Systems conference. The work was supported by the Office of Naval Research.

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Getting dressed with help from robots - MIT News

Human Behavior

This startup aims to improve workplace conversations with empathy-as-a-service software – GeekWire

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Most of us have had the experience of sending a text or email that came across sounding insensitive or angry, even though that wasnt our intent.

Unfortunately, the lack of social cues in such messaging makes it much easier to be misinterpreted. Depending on the communication, this can lead to misunderstandings, hurt feelings or worse. Thats a shortcoming Bellevue, Wash.-based mpathic wants to correct using empathic AI.

Drawing on insights and datasets assembled over the past decade, mpathic has set out to promote human connection and understanding in the workplace.

To do this, theyve created plugins that tie into their cloud-based empathy-as-a-service, or EaaS, to help humans talk to humans using real-time text corrections. This way, texts and emails can be reviewed and changes can be suggested prior to hitting Send. By adding these capabilities into platforms like Slack, or Gmail, mpathic hopes to bring more empathy to the corporate communication landscape.

We realized this could all be mediated with an AI empathy engine, almost like Grammarly for empathy, said co-founder Grin Lord. Weve had amazing developments in AI that allow us to do this now in real time, making this is the first time in human history that we can get real-time empathy correction thats dynamic.

In an example from a recent pitch, the service suggested replacing an inflammatory message like, Why does Nic schedule these meetings always at the last minute? Am I right? with a more open question: How do you feel about the meeting change?

Based on years of research on human interaction, mpathic offers a unique approach to guiding users. Lord, who has a Doctor of Psychology degree, initially based mpathics dataset on insights she gained doing research in the early 2000s at Harborview Medical Center in Seattle, the only Level I trauma center in Washington state.

During that time, Lord was part of a group doing research on empathic listening. Following a car crash, DUI drivers would frequently be brought into Harborview. Rather than giving the driver pamphlets or telling them what to do or shaming them, the researchers would listen to them, perhaps for 15 or 20 minutes, following specific protocols. In a randomized controlled trial, they saw a measurable drop in drinking by those drivers that lasted for up to three years, as well as a 48% reduction in hospital readmissions. Not only did this help the subject toward recovery, it led to significant cost reductions, as well as greater public safety.

Since then, Lord has been involved with other startups including Lyssn, a platform for assessing behavioral health provider empathy and engagement during clinical sessions.

Prior to its launch, the team behind mpathic started Empathy Rocks, which builds human connection using empathic AI through a gamified platform. The platform allows practitioners to improve their empathic listening skills while earning continuing education credits.

But it was during the early seed funding stage for Empathy Rocks that Lord and co-founder Nic Bertagnolli became aware they already had a viable product in the underlying empathy engine for that platform. Pivoting, they launched mpathic to make the engine more readily and widely available.

Developing both Grammarly for empathy and an API, mpathic wants to do more than simply promote good relations between employees. Given the expanding globalization of many corporations and the growing pool of employees from other parts of the country and the world, mpathic wants to provide human resources departments with a tool that can help smooth the onboarding of employees. Since different regions have different ideas and attitudes about what constitutes civil and sensitive behavior, mpathic can be used to help integrate new hires into their new team more rapidly.

Lord is quick to point out that mpathic doesnt just suggest text corrections but makes other kinds of behavioral suggestions, too. In this way, the user builds an understanding of empathic communication and behavior through context, use and repetition.

We actually make corrections that are very behavioral, said Lord. So, it may not even be a replacement of a word or transformation of the text. Instead, the AI may suggest calling a meeting or getting on the phone, because certain things dont need to be in an email.

Though mpathic grew out of Empathy Rocks, the gamified training platform continues to provide empathic listening training as it acquires new data thats used to train mpathics EaaS. The platform was designed by the teams empathy designer, Dr. Jolley Paige, who notes the many factors that need to be considered at a time when AI bias is such a concern.

We were thinking about gender, age, culture, where youre located in the country, but also about different abilities, too, Jolley said. So, if somebody has a language processing disorder, how would that impact how they interact with this game?

While some people may have concerns about using AI to modify human behavior, lots of companies see value in such an approach. Some of our early enterprise partners are looking at plugging mpathic into their Slack, Gmail or whatever, primarily because theyre interested in this idea of quickly onboarding cross-cultural and global teams, Lord said. I think it can be useful for unifying mission values language for a company.

Last month, mpathic was one of 14 startups that pitched at PIE Demo Day. PIE (Portland Incubator Experiment) is led by general manager Rick Turoczy and seeks to provide founders often first-time entrepreneurs with access to mentorship and networks.

Empathy Rocks and mpathic intentionally source and curate their data to include underrepresented voices and are part of All Tech is Human as well as other communities committed to ethical AI development.

Empathic AI is part of a much broader field of computer science, originally known as affective computing and more recently referred to as emotion AI or artificial emotional intelligence. Originating out of MIT Media Lab and other research institutes about 25 years ago, emotion AI involves systems that can read, interpret and interact with human emotions. Since emotion and especially empathy are central to the human condition, such work has the potential to make our technologies interact more easily, humanely and responsibly with people, both at home and in the workplace.

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This startup aims to improve workplace conversations with empathy-as-a-service software - GeekWire

Human Behavior

Dogs understand humans in ways that wolves never will Earth.com – Earth.com

It seems that 14,000 years of domestication has taught dogs to understand aspects of human behavior that their wolf ancestors never latched onto.

Researchers at Duke University ran a recent study that compared the behavior of dog puppies and wolf puppies. The wolves were raised with round-the-clock human interaction that included being hand-fed and sleeping in the caretakers beds. By contrast, the dog puppies remained with their mothers and littermates and were exposed to less interaction with humans.

The puppies were then given tasks that showcased their skills at interpreting what humans are thinking. In one test, a food treat was hidden in one of two bowls and a researcher pointed or stared at the correct bowl in order to give the puppy a clue.

The results were remarkable! The dog puppies were twice as likely to find the treat and this applied to puppies as young as eight weeks old. The dog puppies simply understood that the humans were trying to help them solve the problem and took their cues from the researchers behavior. None of the wolf puppies did better than a random guess.

In another test, the puppies were given food in a closed container that was challenging to open. While the wolf puppies took the container away to try and solve the problem on their own, the dog puppies looked to the people for help, as if to say: Im stuck, can you fix this?

Study first author Hannah Salomons explained that the dog and wolf puppies do not differ in other tests of cognitive skill, such as memory or muscle impulse control. But in terms of people-reading skills, the dog puppies clearly had social cognitive skills that the wolf puppies lacked.

The research provides evidence that the ability of dogs to understand human gestures is a product of domestication, said Professor Brian Hare.

The experts also found that dog puppies are 30 times more likely to approach a stranger compared to wolf puppies.

Theres lots of different ways to be smart, said Salomons. Animals evolve cognition in a way that will help them succeed in whatever environment theyre living in.

With the dog puppies we worked with, if you walk into their enclosure they gather around and want to climb on you and lick your face, whereas most of the wolf puppies run to the corner and hide.

For thousands of years, dogs have lived in association with humans and those that could interpret human behavior would have had a better chance of survival. The genes for their social cognitive skills have been passed down through the generations, such that todays dogs are masters at understanding the behavioral cues given by their masters.

The study is published in the journal Current Biology.

By Alison Bosman, Earth.com Staff Writer

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Dogs understand humans in ways that wolves never will Earth.com - Earth.com

Human Behavior

More warming a threat to the Hajj and human habitation in the Middle East – Yale Climate Connections

Its not the heat, its the humidity. That simple phrase sums up a major danger pilgrims face (in addition to COVID-19) during the coming week during the Hajj, the annual Islamic pilgrimage to Mecca (Makkah), the holiest city for Muslims. This year, the Hajj falls during the period July 17-22, which is typically among the hottest weeks of the year; levels of heat stress are predicted to approach the danger level on several of the days.

Mecca is located approximately 45 miles inland from the Saudi city of Jeddah, which lies on the coast of the Red Sea. Humid air from the Red Sea often penetrates inland to Mecca when winds blow out of the west, raising the heat stress to dangerous levels for the two million-plus pilgrims who typically attend the five-day Hajj. (This years Hajj is limited to just 60,000 participants because of the COVID-19 pandemic.)

While the heat index which measures heat stress due to high temperatures combined with high humidity is often used to quantify dangerous heat, a more precise measure of heat stress is the wet-bulb temperature (TW), which can be measured by putting a wet cloth placed around the bulb of a thermometer and then blowing air across the cloth. The wet-bulb temperature increases with increasing temperature and humidity and is a measure of mugginess. The U.S. National Weather Service defines the Danger threshold for TW at 24.6 degrees Celsius (76.3F), and Extreme Danger at 29.1 degrees Celsius (84.4F), assuming a 45% relative humidity. The latest forecasts from the GFS model predict that TW will mostly remain below the Danger threshold during this years Hajj, but TW could exceed the Danger threshold on Sunday and Wednesday afternoon if moist winds blow off of the ocean. The high temperatures each day during the Hajj are predicted to be 36-39 degrees Celsius (97-102F).

Observations from the Mecca weather station indicate a significant rise in average TW during the past 30 years nearly 2 degrees Celsius (3.6F). This increase is well above the global average, and can be largely attributed to human-caused global warming. High heat stress events are common when the Hajj occurs during summer; over the 30year period 1984-2013, the danger threshold (TW of 24.6 degrees Celsius) was exceeded in 58% of years. However, the Extreme Danger threshold of 29.1 degrees Celsius was not reached.

While the floor of the Great Mosque, its covered areas, and the surrounding tents that pilgrims stay in are all air conditioned, the ritual of Hajj involves spending about 20-30 hours outdoors over a period of five days. The main outdoor activities, which occur in and surrounding Mecca, are:

1) Tawaf, or praying outside the Great Mosque of Mecca (Alharam) for a few hours on two different occasions;2) Wakuf, or standing on the side of Mount Arafat for one day between sunrise and sunset, recognized as the most important activity of the Hajj; and3) Ramy AlJamrat, or walking in Mina (outskirts of Mecca) for several hours per day (called Stoning of the Devil), repeated in a sequence of three days.

Muslims who are in good health and can afford it are obligated to participate in the Hajj at least once in their lifetimes, and their desire to participate becomes more urgent as their age advances. As a result, a disproportionate fraction of Hajj participants are elderly and at higher risk of heat-related illness.

The Hajj occurs every year on the same days of the Muslim calendar, which follows the lunar cycle. Since the lunar year is shorter than the solar year by about 11 days, the Hajj shifts about 11 days earlier every year, and cycles back to the same date in the solar calendar after about 33 years. The danger of extreme heat during Hajj will wane this decade as the dates transition from July to June and then May. But during the years 2045-2053, and again in 2079-2086, Hajj will fall during August-October. These are the months when wet bulb temperatures peak in Mecca, as a result of the combination of extreme heat and prevailing westerly winds that bring humid air from the Red Sea.

A 2019 paper by MIT scientist Suchul Kang and colleagues, Future Heat Stress During Muslim Pilgrimage (Hajj) Projected to Exceed Extreme Danger Levels, painted a very concerning picture for future Hajj events in a warming climate. The researchers showed that under a moderate global warming scenario, the maximum wet bulb temperature could be expected to exceed the Extreme Danger threshold of 29.1 degrees Celsius 15% of the time during Hajj in the years 2045-2053, and exceed the Danger threshold 91% of the time (Figure 3).

Along similar lines, a 2021 paper led by Fahad Saeed (Climate Analytics) and colleagues, From Paris to Makkah: heat stress risks for Muslim pilgrims at 1.5 C and 2 C, warns that the odds of exceeding the danger threshold at Mecca increase substantially for global warming of 1.5C and 2C levels that are likely to be exceeded this century in the moderate scenario discussed above and that the Extreme Danger threshold may be surpassed during summer months.

The two deadliest stampedes during Hajj both occurred during days with extreme heat and humidity, when the maximum wet bulb temperature exceeded the 24.6 degrees Celsius Danger threshold. On July 2, 1990, 1,426 pilgrims died in a stampede when the maximum temperature (Tmax) reached 41.7 degrees Celsius (107F) and wetbulb temperature (TWmax) hit 25.1 degrees Celsius (77.8 F). Similarly, on September 24, 2015, more than 2,000 pilgrims died in a stampede when Tmax and TWmax reached 48.3 degrees Celsius (118.9F) and 27.3 degrees Celsius (81.1F), respectively. The exact cause of these stampedes is unknown, but extreme heat is known to increase aggressive human behavior.

Since human skin temperature averages close to 35 degrees Celsius (95F), wet-bulb temperatures above that value prevent all people from dispelling internal heat, leading to fatal consequences within six hours, even for healthy people in well-ventilated conditions. A wet-bulb temperature a few degrees lower is fatal for most people, but not all.

A 2020 paper in the open-access journal Science Advances by Raymond et al., Potentially Fatal Combinations of Humidity and Heat Are Emerging across the Globe, identified 14 examples of 35C wet-bulb readings that have already occurred since 1987 at five stations in Pakistan, Saudi Arabia, and the United Arab Emirates (UAE). These conditions generally lasted less than six hours (see Bob Hensons May 2020 post for details).

Those researchers found that the frequency of TW values reaching 27C, 29C, 31C, and 33C across the world all showed doubling trends between 1979 and 2017. They predicted that dangerous wet-bulb readings will continue to spread across vulnerable parts of the world, affecting millions more people, as human-caused climate change continues.

Higher wet-bulb temperatures will be particularly dangerous in the Indus River valley along the India/Pakistan border, where thousands of laborers work outdoors in pre-monsoon heat that can reach dangerous levels during May, June, and July. Jacobabad, Pakistan (population 191,000), has already recorded six days when the wet-bulb temperature exceeded the limits of human survivability: 35 degrees Celsius. A 2015 heat wave killed 3,477 people in India/Pakistan, ranking as the fourth deadliest heat wave in world history, according to the international disaster database, EM-DAT. Four of the 10 deadliest heat waves on record in the EM-DAT database have affected India and/or Pakistan.

A 2015 paper by Pal and Eltahir, Future temperature in southwest Asia projected to exceed a threshold for human adaptability, warned that human habitability will be severely impacted in the nations of Pakistan, India, Saudi Arabia, the United Arab Emirates, Iran, Iraq, Yemen, Oman, Qatar, Bahrain, and Kuwait in coming decades. They suggested those nations would benefit by supporting strong efforts to rein in climate change and forsake a business as usual approach. A business as usual approach would likely lead to summertime high temperatures by 2100 reaching 60 degrees Celsius (140F) in Kuwait and the United Arab Emirates, and 55 degrees Celsius (131F) in Mecca, Saudi Arabia. Wet-bulb temperatures would likely exceed 36 degrees Celsius (97F) beyond the limit of human survival at some locations in Iran, the UAE, and Qatar. The authors wrote: A plausible analogy of future climate for many locations in Southwest Asia is the current climate of the desert of Northern Afar on the African side of the Red Sea, a region with no permanent human settlements owing to its extreme climate.

The data point to a logical conclusion: It would be strongly in the interest of the nations of Southwest Asia, and of other regions, to support aggressive efforts to reign in climate change to protect the Hajj and the future of human habitability in their countries.

The rest is here:
More warming a threat to the Hajj and human habitation in the Middle East - Yale Climate Connections

Human Behavior

More than two hours of daily screen time linked to cognitive, behavioral problems in children born extremely preterm – National Institutes of Health

Media Advisory

Thursday, July 15, 2021

NIH-funded study finds deficits in overall IQ, problem solving skills and impulse control.

Among 6- and 7-year-olds who were born extremely preterm before the 28th week of pregnancy those who had more than two hours of screen time a day were more likely to have deficits in overall IQ, executive functioning (problem solving skills), impulse control and attention, according to a study funded by the National Institutes of Health. Similarly, those who had a television or computer in their bedrooms were more likely to have problems with impulse control and paying attention. The findings suggest that high amounts of screen time may exacerbate the cognitive deficits and behavioral problems common to children born extremely preterm.

The study was conducted by Betty R. Vohr, M.D., and colleagues. It appears in JAMA Pediatrics. Funding was provided by NIHs Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Heart, Lung, and Blood Institute; and National Center for Advancing Translational Sciences.

Previous studies have linked high amounts of screen time among children born full-term to language and developmental, behavioral and other problems. In the current study, researchers analyzed data from a study of children born at 28 weeks or earlier. Of 414 children, 238 had more than two hours of screen time per day and 266 had a television or computer in their bedrooms. Compared to children with less screen time per day, those with high amounts of screen time scored an average deficit of nearly 8 points on global executive function percentile scores, roughly 0.8 points lower on impulse control (inhibition) and more than 3 points higher on inattention. Children with a television or computer in their bedrooms also scored lower on measures of inhibition, hyperactivity and impulsivity.

The authors concluded that the findings support the need for physicians to discuss the potential effects of screen time with families of children born extremely preterm.

Andrew Bremer, M.D., Ph.D., Acting Chief, NICHD Pregnancy and Perinatology Branch, is available for comment.

Vohr, BE, et al. Association of high screen-time use with school-age cognitive, executive function, and behavior outcomes in extremely preterm children. JAMA Pediatrics.2021. doi:10.1001/jamapediatrics.2021.2041

About the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD): NICHD leads research and training to understand human development, improve reproductive health, enhance the lives of children and adolescents, and optimize abilities for all. For more information, visit https://www.nichd.nih.gov.

About the National Institutes of Health (NIH):NIH, the nation's medical research agency, includes 27 Institutes and Centers and is a component of the U.S. Department of Health and Human Services. NIH is the primary federal agency conducting and supporting basic, clinical, and translational medical research, and is investigating the causes, treatments, and cures for both common and rare diseases. For more information about NIH and its programs, visit http://www.nih.gov.

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More than two hours of daily screen time linked to cognitive, behavioral problems in children born extremely preterm - National Institutes of Health

Human Behavior

‘As I See It’ with Columnist Jon Huer: Want to save nature? Save society first – The Recorder

Let me start with a question: Can you support a healthy, sustainable environment in a capitalist system devoted to all-out consumption? With some qualifications, most would say, Yes, we can. Most of our answers would be in the affirmative because we could not find an alternative way of life, like giving up consumer capitalism, once we said, No.

During our walk at Greenfield Community Collegetoday, we saw a rabbit that was in no hurry to scamper away, obviously unafraid of the two-legged creatures nearby. This small encounter with the rabbit reminded me of the articles I read recently in the Recorder on the large subject of nature or nature-related habits of mind in connection with environmentalism. Further thinking about the subject brought me to the idea that whether we love and support nature or remain indifferent to it, the consequences are the same. The fate of the rabbit, and that of other creatures in nature, is wholly unrelated to whether we personally love nature or are indifferent to it.

Here is the subsequent gist of my sociology of nature: All things about nature are governed by the rules of society and its policies of how the society wishes to govern nature. Its the city, the county, and the state, and ultimately the nation and the whole humanity that determine whether the rabbit, and other such creatures, survive well, not whether or not we love the rabbit. Indeed, it is the nitty-gritty aspects of governing politics the budget, the manpower, the rulesand our human habits that determine the fate of nature and all the creatures living in it. Environmentalism is about our survival, not natures. If we do well with society, nature does well too, but not necessarily the other way around. One of the writers on environmentalism quoted a U.N. report that emphasizes human behavior in environmental protection: We must redefine our way of life and consumption.

We tend to think that nature, in reality a sub-category of society, is something separate from our social existence. We claim to love nature even when we have a very negligent society that systematically destroys all that is in nature by overdevelopment, pollution, exploitation and neglect. In order to save nature, or its environmental impact, we must first save our society, for society is everything that nature is. Not a single animal, like the rabbit we saw today, not a single petal in the wild flowers, not a single blade of grass, can simply belong to nature without what our society does to control it and manage it. It is wonderful to observe that many people profess to love nature and the environment, as my wife genuinely does. But if one loves nature, one must love the society first and pay attention to whats going on with the society and what people are doing in society to destroy ones beloved nature or to preserve it.

While indifferent to nature, I am keenly aware how humanity is slowly destroying nature by rapidly destroying society. In general, a society that is decent, just and wholesome as a human society also tends to be decent, just and wholesome toward nature, for nature depends so critically on the society that functions as its steward. Just observe Scandinavia or Japan, whose decent social systems also maintain a very friendly and thriving natural environment.

The articles in the Recorder seemed to argue that if we loved and understood nature well, we would have a peaceful and harmonious human world as well. I would say the opposite: If we loved and understood the society in which we live and the human beings we are part of, I would say, we can also have a peaceful and harmonious natural world. Wherever we witness nature threatened and destroyed, we witness a human society thats doing the damage. All things, good and evil, begin from the society and end in nature, not the other way around.

All forms of loving nature are expressed through doing something about it in society. If you loved humanity in society, it would solve all environmental problems. Everything on this earth, including the welfare of the wild rabbits and flowers, begins and ends with humanity in society. You cannot enjoy a vegetarian sandwich and a glass of organic wine by the beautifully-manicured river while, across the river, poor people live in squalor and are shot by police. On the other hand, how could a city, where all citizens live peacefully and in harmony with one another, not have a beautiful, clean river?

If you love nature, then make sure that all humanity on this earth live in a decent way. How could we love nature without first loving our most immediate nature, namely, our neighborhood and its inhabitants, the neighbors?

Jon Huer, columnist for the Recorder and a retired professor, is the author of The Wages of Sin: Americas Dilemma of Profit Against Humanity, a book about Americas political economy. He lives in Greenfield.

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'As I See It' with Columnist Jon Huer: Want to save nature? Save society first - The Recorder