Wheeled robot measures leaf angles to help breed better corn plants

Peer-Reviewed Publication

NORTH CAROLINA STATE UNIVERSITY

 

IMAGE: RESEARCHERS FROM NORTH CAROLINA STATE UNIVERSITY AND IOWA STATE UNIVERSITY HAVE DEMONSTRATED AN AUTOMATED TECHNOLOGY CAPABLE OF ACCURATELY MEASURING THE ANGLE OF LEAVES ON CORN PLANTS IN THE FIELD. THIS TECHNOLOGY MAKES DATA COLLECTION ON LEAF ANGLES SIGNIFICANTLY MORE EFFICIENT THAN CONVENTIONAL TECHNIQUES, PROVIDING PLANT BREEDERS WITH USEFUL DATA MORE QUICKLY. THIS IMAGE SHOWS THE AUTONOMOUS ROBOT, WITH MULTIPLE TIERS OF PHENOSTEREO CAMERAS. view more 

CREDIT: LIRONG XIANG, NC STATE UNIVERSITY

Researchers from North Carolina State University and Iowa State University have demonstrated an automated technology capable of accurately measuring the angle of leaves on corn plants in the field. This technology makes data collection on leaf angles significantly more efficient than conventional techniques, providing plant breeders with useful data more quickly.

“The angle of a plant’s leaves, relative to its stem, is important because the leaf angle affects how efficient the plant is at performing photosynthesis,” says Lirong Xiang, first author of a paper on the work and an assistant professor of biological and agricultural engineering at NC State. “For example, in corn, you want leaves at the top that are relatively vertical, but leaves further down the stalk that are more horizontal. This allows the plant to harvest more sunlight. Researchers who focus on plant breeding monitor this sort of plant architecture, because it informs their work.

“However, conventional methods for measuring leaf angles involve measuring leaves by hand with a protractor – which is both time-consuming and labor-intensive,” Xiang says. “We wanted to find a way to automate this process – and we did.”

The new technology – called AngleNet – has two key components: the hardware and the software.

The hardware, in this case, is a robotic device that is mounted on wheels. The device is steered manually, and is narrow enough to navigate between crop rows that are spaced 30 inches apart –the standard width used by farmers. The device itself consists of four tiers of cameras, each of which is set to a different height to capture a different level of leaves on the surrounding plants. Each tier includes two cameras, allowing it to capture a stereoscopic view of the leaves and enable 3D modeling of plants.

As the device is steered down a row of plants, it is programmed to capture multiple stereoscopic images, at multiple heights, of every plant that it passes.

All of this visual data is fed into a software program that then computes the leaf angle for the leaves of each plant at different heights.

“For plant breeders, it’s important to know not only what the leaf angle is, but how far those leaves are above the ground,” Xiang says. “This gives them the information they need to assess the leaf angle distribution for each row of plants. This, in turn, can help them identify genetic lines that have desirable traits – or undesirable traits.”

To test the accuracy of AngleNet, the researchers compared leaf angle measurements done by the robot in a corn field to leaf angle measurements made by hand using conventional techniques.

“We found that the angles measured by AngleNet were within 5 degrees of the angles measured by hand, which is well within the accepted margin of error for purposes of plant breeding,” Xiang says.

“We’re already working with some crop scientists to make use of this technology, and we’re optimistic that more researchers will be interested in adopting the technology to inform their work. Ultimately, our goal is to help expedite plant breeding research that will improve crop yield.”

The paper, “Field-based robotic leaf angle detection and characterization of maize plants using stereo vision and deep convolutional neural networks,” is published open access in the Journal of Field Robotics. Corresponding author of the paper is Lie Tang, a professor of agricultural and biosystems engineering at Iowa State. The paper was co-authored by Jingyao Gai, of Iowa State and Guanxi University; Yin Bao, of Iowa State and Auburn University; and Jianming Yu and Patrick Schnable, of Iowa State. The work was done with support from the National Science Foundation, under grant number 1625364; and from the Plant Sciences Institute at Iowa State.

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JOURNAL

Journal of Field Robotics

DOI

10.1002/rob.22166 

METHOD OF RESEARCH

Experimental study

SUBJECT OF RESEARCH

Not applicable

ARTICLE TITLE

Field-based robotic leaf angle detection and characterization of maize plants using stereo vision and deep convolutional neural networks

POSTMODERN ALCHEMY

Study finds silicon, gold and copper among new weapons against COVID-19

n/a

Peer-Reviewed Publication

CURTIN UNIVERSITY

New Curtin research has found the spike proteins of SARS-CoV-2, a strain of coronaviruses that caused the COVID-19 pandemic, become trapped when they come into contact with silicon, gold and copper, and that electric fields can be used to destroy the spike proteins, likely killing the virus.

Lead researcher Dr Nadim Darwish, from the School of Molecular and Life Sciences at Curtin University said the study found the spike proteins of coronaviruses attached and became stuck to certain types of surfaces.

“Coronaviruses have spike proteins on their periphery that allow them to penetrate host cells and cause infection and we have found these proteins becomes stuck to the surface of silicon, gold and copper through a reaction that forms a strong chemical bond,” Dr Darwish said.

“We believe these materials can be used to capture coronaviruses by being used in air filters, as a coating for benches, tables and walls or in the fabric of wipe cloths and face masks.

“By capturing coronaviruses in these ways we would be preventing them from reaching and infecting more people.”

Co-author PhD candidate Essam Dief, also from the School of Molecular and Life Sciences at Curtin University said the study also found the coronavirus could be detected and destroyed using electrical pulses.

“We discovered that electric current can pass through the spike protein and because of this, the protein can be electrically detected. In the future, this finding can be translated to involve applying solution to a mouth or nose swab and testing it in a tiny electronic device able to electrically detect the proteins of the virus. This would provide instant, more sensitive and accurate COVID testing,” Mr Dief said.

“Even more exciting, by applying electrical pulses, we found the spike protein’s structure is changed and at certain magnitude of the pulses, the protein is destroyed. Therefore, electric fields can potentially deactivate coronaviruses.

“So, by incorporating materials such as copper or silicon in air filters, we can potentially capture and consequently stop the spread of the virus. Also importantly, by incorporating electric fields through air filters for example, we also expect this to deactivate the virus.

“The study is exciting both fundamentally as it enables a better understanding of coronaviruses and from an applied perspective in helping to develop tools to fight the transmission of current and future coronaviruses.”

Published in Chemical Science, the research is available online here: SARS-CoV-2 spike proteins react with Au and Si, are electrically conductive and denature at 3 × 10 8 V m −1 : a surface bonding and a single-protein c … – Chemical Science (RSC Publishing) DOI:10.1039/D2SC06492H.

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JOURNAL

Chemical Science

DOI

10.1039/D2SC06492H 

METHOD OF RESEARCH

Experimental study

SUBJECT OF RESEARCH

Cells

ARTICLE TITLE

SARS-CoV-2 spike proteins react with Au and Si, are electrically conductive and denature at 3 × 108 V m−1: a surface bonding and a single-protein circuit study

As naloxone treatment becomes more widespread heroin use is not on the rise among adolescents

Peer-Reviewed Publication

COLUMBIA UNIVERSITY'S MAILMAN SCHOOL OF PUBLIC HEALTH

March 6, 2023-- The adoption of laws around naloxone use is not associated with changes in adolescent lifetime heroin or injection drug use (IDU), finds a new study at Columbia University Mailman School of Public Health. According to latest results, naloxone access and pharmacy naloxone distribution were more consistently associated with decreases rather than increases in lifetime heroin and IDU among adolescents. While some critics contend that naloxone expansion may inadvertently promote high-risk substance use behaviors among adolescents, until now this question had not been directly investigated. The findings are published online in the International Journal of Drug Policy. 

“Findings from our research do not support the hypothesis that broader availability of naloxone between the years studied of 2007 to 2019 increased heroin use or injection drug use among adolescents and suggest that increased adolescent drug use as an unintended consequence of naloxone availability is an unfounded concern,” said Emilie Bruzelius, MPH, a doctoral student in the Department of Epidemiology at Columbia Mailman School and first author.

As of 2019, all U.S. states had adopted legislation to improve naloxone access and facilitate use. “Because most opioid overdose deaths are preventable its timely administration has lifesaving potential to restore normal breathing and prevent death, and broadening access to naloxone is a key component of the US opioid overdose epidemic response,” says Bruzelius.

The researchers obtained data on adolescent substance use from the Youth Risk Behavior Surveillance System (YRBSS), a national survey that monitors health risk behaviors among high school students. The analysis was restricted to students 15-18 years old to focus on the ages in which substance use is more prevalent, and among whom overdose deaths are rising. From 2007 to 2019, all but three states (MN, OR, WA) participated in the survey. In addition to state-level naloxone (NAL) adoption the researchers looked at transaction data on retail NAL dispensing from the prescription database IQVIA which captures approximately 92 percent of U.S. retail pharmacies, including prescriptions from all payers but excluding prescriptions obtained by mail or dispensed within hospitals.

Adolescence and early adulthood is typically the period when nonmedical opioid and heroin initiation occur. From 2007 to 2019, 920,333 students aged 15-18 participated in the YRBSS.  Lifetime heroin use was self-reported by 2.75 percent and lifetime injection drug us by 2.48 percent. There was a small decrease in heroin use over the period; in 2007, rates decreased to 2.27 percent. while lifetime IDU remained stable.

“Given the limited magnitude of both associations, we interpreted these results as failing to provide meaningful support for the risk compensation hypothesis,” said Bruzelius. However, we do realize that heroin use and IDU are generally rare outcomes that are often underreported given their stigmatizing nature.”

Naloxone is recognized as one of the most valuable tools for reducing opioid overdose deaths, yet access in many places still remains low given the number of people at risk.  Naloxone treatment laws are designed to reduce this gap by facilitating access to this lifesaving medication and therefore increasing opportunities to directly intervene in an overdose. However, concerns that naloxone access might inadvertently increase opioid misuse and overdose—the risk compensation hypothesis—appear to remain a barrier to distribution efforts, both in the U.S. and internationally.

“Efforts to improve naloxone access should continue to be an urgent public health priority, including among adolescents who represent an increasingly vulnerable population at risk for fatal and nonfatal overdose,” observed Silvia Martins, MD, PhD, Columbia Mailman School professor of epidemiology, and senior author. “As a critical public health measure we urge further removal of naloxone access barriers. Given that the overdose epidemic continues to affect our nation as a whole, this is is an important priority not only for adolescents but people of all ages.”

Co-authors include Katherine Keyes, Deborah Hasin, and Christine Mauro, Columbia Mailman School of Public Health; Hillary Samples and Stephen Crystal, Rutgers Institute for Health; Magdalena Cerdá, Victoria Jent, and Katherine Wheeler-Martin, NYU Grossman School of Medicine; and Corey Davis, Harm Reduction Legal Project.

The study was supported by the National Institutes of Health, National Institute on Drug Abuse, NIH-NIDA, grant R01 DA045872.

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JOURNAL

International Journal of Drug Policy

DOI

10.1016/j.drugpo.2023.103980 

IMDEA Software participates in the European project CONFIDENTIAL6G to ensure the trustworthiness of emerging AI tools and IoT devices

CONFIDENTIAL6G will base its research on 3 pillars: confidential computing, post-quantum cryptography and confidential communication

Meeting Announcement

IMDEA SOFTWARE INSTITUTE

 

IMAGE: IGNACIO CASCUDO AT THE IMDEA SOFTWARE INSTITUTE view more 

CREDIT: IMDEA SOFTWARE INSTITUTE

The IMDEA Software Institute participates in the European CONFIDENTIAL6G project in which, together with other actors, the objective is to extend the levels of security and reliability of the network to optimize its use in Artificial Intelligence (AI) tools.

6G technology will be the successor of 5G as the sixth generation of mobile connectivity.Although it is still in an early development phase, it is expected to be able to further reduce latency in connections between devices and significantly increase transmission speed. For that reason, the 6G network will be particularly useful for IoT and will enable deep integration of emerging AI tools, new hardware components and accelerators, computing and networking functions, and peripheral nodes. In this regard, 6G technology infrastructures must, among other things, ensure the reliability, trustworthiness and resilience of a globally connected continuum of heterogeneous environments supported by the convergence of networks and computing systems to enable new future digital services (IoT) that can potentially revolutionize many industries. 

The substantial increase in network coverage and heterogeneity raises concerns that 6G security and privacy may be worse than previous generations. Current security is not designed to serve a massive number of heterogeneous, highly mobile, connected devices. So: "if these networks are going to improve our transportation, provide personalized updates to our appliances, optimize the energy we consume in homes, offices and even cities and make healthcare more efficient, we need to ensure that everything is going to work as it should," says Ignacio Cascudo, researcher at IMDEA Software Institute.

The project

"Confidential Computing and Privacy-preserving Technologies for 6G (CONFIDENTIAL6G) starts with a total budget of more than 5.2 million euros, nearly 5 million euros of which come from European funds*.

A total of 13 entities from 9 countries make up the project consortium coordinated by the Greek company Wings ICT Solutions. The Spanish participation is made up of IMDEA Software Institute and Telefónica.

The CONFIDENTIAL6G project aims to preserve the privacy and security of sensitive data by focusing on the protection of data in use, in transit and at the edge. Data in use is an unsolved problem whose solutions are beginning to emerge with Confidential Computing. Second, CONFIDENTIAL6G will enhance data in transit by protecting communications with post-quantum cryptography, blockchain technologies, and secure access control and data traceability platforms. And finally, the project will also act on edge data by working on specifying the most suitable post-quantum cryptographic approach to serve constrained Edge and IoT devices.

The IMDEA Software Institute will contribute to this project with the development of privacy-preserving computation technologies such as secure multi-party computation, zero knowledge proofs and homomorphic encryption.

*“This project has received funding from the European Union’s Horizon Digital, Industry and Space programme (Grant agreement No. 101096435).”

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DOI

10.3030/101096435 

CITIZEN SCIENCE

Phone-based measurements provide fast, accurate information about the health of forests

Peer-Reviewed Publication

UNIVERSITY OF CAMBRIDGE

 

IMAGE: RESEARCHERS HAVE DEVELOPED AN ALGORITHM THAT USES COMPUTER VISION TECHNIQUES TO ACCURATELY MEASURE TREES ALMOST FIVE TIMES FASTER THAN TRADITIONAL, MANUAL METHODS. THE RESEARCHERS, FROM THE UNIVERSITY OF CAMBRIDGE, DEVELOPED THE ALGORITHM, WHICH GIVES AN ACCURATE MEASUREMENT OF TREE DIAMETER, AN IMPORTANT MEASUREMENT USED BY SCIENTISTS TO MONITOR FOREST HEALTH AND LEVELS OF CARBON SEQUESTRATION. view more 

CREDIT: UNIVERSITY OF CAMBRIDGE

Researchers have developed an algorithm that uses computer vision techniques to accurately measure trees almost five times faster than traditional, manual methods.

The researchers, from the University of Cambridge, developed the algorithm, which gives an accurate measurement of tree diameter, an important measurement used by scientists to monitor forest health and levels of carbon sequestration.

The algorithm uses low-cost, low-resolution LiDAR sensors that are incorporated into many mobile phones, and provides results that are just as accurate, but much faster, than manual measurement techniques. The results are reported in the journal Remote Sensing.

The primary manual measurement used in forest ecology is tree diameter at chest height. These measurements are used to make determinations about the health of trees and the wider forest ecosystem, as well as how much carbon is being sequestered.

While this method is reliable, since the measurements are taken from the ground, tree by tree, the method is time-consuming. In addition, human error can lead to variations in measurements.

“When you’re trying to figure out how much carbon a forest is sequestering, these ground-based measurements are hugely valuable, but also time-consuming,” said first author Amelia Holcomb from Cambridge’s Department of Computer Science and Technology. “We wanted to know whether we could automate this process.”

Some aspects of forest measurement can be carried out using expensive special-purpose LiDAR sensors, but Holcomb and her colleagues wanted to determine whether these measurements could be taken using cheaper, lower-resolution sensors, of the type that are used in some mobile phones for augmented reality applications.

Other researchers have carried out some forest measurement studies using this type of sensor, however this has been focused on highly-managed forests where trees are straight, evenly spaced and undergrowth is regularly cleared. Holcomb and her colleagues wanted to test whether these sensors could return accurate results for non-managed forests quickly, automatically, and in a single image.

“We wanted to develop an algorithm that could be used in more natural forests, and that could deal with things like low-hanging branches, or trees with natural irregularities,” said Holcomb.

The researchers designed an algorithm that uses a smartphone LiDAR sensor to estimate trunk diameter automatically from a single image in realistic field conditions. The algorithm was incorporated into a custom-built app for an Android smartphone, and is able to return results in near real-time.

To develop the algorithm, the researchers first collected their own dataset by measuring trees manually and taking pictures. Using image processing and computer vision techniques, they were able to train the algorithm to differentiate trunks from large branches, determine which direction trees were leaning in, and other information that could help it refine the information about forests.

The researchers tested the app in three different forests – one each in the UK, US and Canada – in spring, summer and autumn. The app was able to detect 100% of tree trunks, and had a mean error rate of 8%, which is comparable to the error rate when measuring by hand. However, the app sped up the process significantly, and was about four and a half times faster than measuring trees manually.

“I was surprised the app works as well as it does,” said Holcomb. “Sometimes I like to challenge it with a particularly crowded bit of forest, or a particularly oddly-shaped tree, and I think there’s no way it will get it right, but it does.”

Since their measurement tool requires no specialised training and uses sensors that are already incorporated into an increasing number of phones, the researchers say that it could be an accurate, low-cost tool for forest measurement, even in complex forest conditions.

The researchers plan to make their app publicly available for Android phones later this spring.

The research was supported in part by the David Cheriton Graduate Scholarship, the Canadian National Research Council, and the Harding Distinguished Postgraduate Scholarship.

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JOURNAL

Remote Sensing

DOI

10.3390/rs15030772 

ARTICLE TITLE

Robust Single-Image Tree Diameter Estimation with Mobile Phones

Juggling morality while we learn

Peer-Reviewed Publication

NETHERLANDS INSTITUTE FOR NEUROSCIENCE - KNAW

New research from the Netherlands Institute for Neuroscience sheds light on how the brain juggles morally conflicting outcomes during learning. ‘People choosing their own gain at the expense of others were able to understand and empathize with the potential negative impacts, but still ultimately choose to pursue their own benefit.’

We sometimes have to learn that certain actions are good for us, but harm others, while alternative actions are less profitable for us, but prevent harm to others. How we juggle these morally conflicting outcomes during learning remains unknown. In particular: if you ultimately want to go for the most profitable option for yourself, would you avoid realizing that this hurts others?

Here, researchers from the Netherlands Institute for Neuroscience show that participants differ substantially in their preference, with some choosing actions that benefit themselves, and others, actions that prevent harm, and were therefore in a unique position to explore how people deal with the ‘collateral damage’ this choice entails. Do they turn a blind eye or act in full awareness? Laura Fornari, Kalliopi Ioumpa and their team supervised by Valeria Gazzola and Christian Keysers looked into the question of how participants learn the uncomfortable truth that sometimes self-money means other-harm and vice versa; and how they adapt to changes during the tasks.

Test with symbols

During the experiments, participants had to learn that one of two symbols led to high monetary gains for the self 80% of the time, and to a painful but tolerable shock to the hand of a fellow human being with the same probability. The other symbol led to low monetary gains for the self 80% of the time, and to lower intensity, non-painful shocks to the confederate with the same probability. At the beginning of each block, participants did not know the associations between symbols and outcomes.

“Overall, people had stable preferences: some tended to choose the option that gave them more money, others the option that prevented shocks to others. This was already known from previous studies. The question we were really interested in was how they would learn which symbol satisfies their preference” Valeria Gazzola, the senior investigator of this project explained. “And this is where things became interesting: would someone that ultimately wants to make money, and hence wants to choose the option that delivers more money, conveniently ignore that this hurts others”?

Avoiding empathy to minimize moral conflict?

Laura Fornari: ‘Using computational modeling we showed that this is not the case: participants tracked expected values of self-benefits and other-harms separately throughout the task. This means that participants that over time chose to maximize their benefits learned and remained aware of the pain they were causing to the other. Brain patterns coding the pain of others were indeed found to correlate with how much pain we expect our choice to cause.  This suggests that even when attention is directed to the specific aim to maximize our gain at the expense of others, empathic responses do still occur allowing us to remain aware of the pain we cause”

But why do people do that? Why don’t they make their lives easier, and concentrate on their own gains at the exclusion of the pain of others? The team could show that this is probably to allow participants to adapt to changes in circumstances. The authors suddenly removed one of the two forces in the moral dilemma. “We told the participants that in the next ten trials, all was going to be the same, except that we wouldn’t pay out any of the money anymore”, explained Laura Fornari. If participants hadn’t learned which symbol was hurting the other participant, despite  the money taken out of the occasion, they may have just continued to use their preferred symbol. Yet, they quickly shifted away from it because they knew it would hurt the other.

“With this task modification, we were also able to show that despite participants updating their choices according to the removed outcome, this shift was not total, and a bias toward the preferred outcome remained. This suggests that people maximizing self-benefits will now choose that option less often than when money was being paid out, but will not completely change their decision to go for the other-benefiting option all the time. How much weight we give to money does influence our choices and how much we learn about the pain of others. ”  continues Christian Keysers.

But what exactly happened in the brain of the participants?

“We know where in the brain people normally process the pain of others. In those brain regions, we found activity that tracked how much pain the other person was receiving independently of the preferences of the participant. This accounts for why even the more selfish participants knew about the pain they were causing. However, brain regions associated with value signals were representing the pain of others less in participants that chose less often to prevent harm to others. Our brain thus juggles moral learning in interesting ways: somewhere we realize what we do quite objectively, while somewhere else, we value this impact more or less depending on our ultimate goals,’ concludes Kalliopi Ioumpa. Laura Fornari: “Looking at future directions, our novel approach that combines learning and decision making in a morally conflicting context could be applied to atypical populations that manifest less socially-adaptive behaviors. For example, it would be interesting to investigate whether individuals with antisocial tendencies present a similar ability to track separate associations over time, or whether they are more able to suppress their responses to the pain of others and mainly focus on the outcome of interest.”

Source: Nature Communications

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JOURNAL

Nature Communications

DOI

10.1038/s41467-023-36807-3 

ARTICLE TITLE

Neuro-computational mechanisms and individual biases in action-outcome learning under moral conflict

ARTICLE PUBLICATION DATE

6-Mar-2023

Diversity training for police officers: one-and-done efforts aren't enough

Recommendations include "booster" training, embedding lessons and strategies with other organizational initiatives

Peer-Reviewed Publication

ASSOCIATION FOR PSYCHOLOGICAL SCIENCE

What explains persistent racial disparities in policing, despite police departments’ repeated investments in bias-training programs? A wide range of data indicate that police in the United States tend to stop, arrest, injure, or kill more Black people than White people. Calvin K. Lai (Washington University in St. Louis) and Jaclyn A. Lisnek (University of Virginia) analyzed the effectiveness of a day-long implicit-bias-oriented diversity training session designed to increase U.S. police officers’ knowledge of bias, concerns about bias, and use of evidence-based strategies to mitigate bias. Their findings, recently published in Psychological Science, suggest that “diversity trainings as they are currently practiced are unlikely to change police behavior.” 

Immediately after these trainings, police officers have strong intentions to use the strategies they’ve learned, explained Lai in a forthcoming interview on Under the Cortex, the APS podcast. But “one month later there wasn’t that kind of follow through.” 

In 2020 and 2021, Lai and Lisnek evaluated 251 training sessions (in-person or remote) in which 24 different educators taught the Managing Bias program—developed by the Anti-Defamation League to reduce the influence of biases in the behaviors of police officers, improve the relationship between the community and the police, and increase safety—to different police departments with a history of Black–White racial disparities in policing. This day-long training consists of an interactive workshop, led by two educators, that uses activities to educate officers about the origins and differences between explicit and implicit bias, how biases may affect their behavior, and gaps in understanding between police and the community. After learning about biases, officers were trained on strategies and skills to reduce biased behavior.  

Lai, a recipient of the APS 2023 Janet Taylor Spence Award for Early Career Contributions, and Lisnek surveyed police officers immediately before the training to establish a baseline, assessing knowledge and concern about bias, usage of strategies to manage bias, and characteristics relevant to police training (e.g., centrality of police identity, expectations of respect from community members). A second survey, administered immediately after the training, evaluated knowledge and concern about bias plus the intention to use the strategies to manage bias.  

Results indicated that before the training, officers showed low understanding of and concern about bias, but the training immediately increased their knowledge and concern about bias. Right after the training, officers reported feeling empowered and motivated to use the strategies they learned to manage bias. However, another survey one month later found that officers’ concerns about bias had returned to pre-intervention levels and their use of these strategies had declined compared with their reported intentions immediately after training. Nevertheless, their general understanding of biases remained as high as immediately after the training. 

Future research, Lai said, will attempt “to close that gap between officers really being motivated but not finding ways to follow through using some of these bias mitigation strategies.”  

The researchers also identified characteristics of diversity training that might affect its efficacy. For instance, previous literature has suggested embedding such efforts with other organizational initiatives, having managers reinforce them, and evaluating expected behavior as a part of job performance. The training examined in this study was implemented and administered by an external organization. Adding booster sessions instead of a one-and-done training model could also increase effectiveness, Lai and Lisnek said.  

Finally, the strategies taught could have had low applicability outside of a lab in real-world policing, another factor that can also undermine training effectiveness. “One of the things we’re finding is that there might not be these great one-size-fits-all solutions for combating bias at work,” said Lai. It may be necessary “to think very concretely and specifically” about the daily work activities where police officers may be inclined to discriminate—and then provide “super-tailored strategies” to mitigate those behaviors. 

Journalists: email news@psychologicalscience.org for a copy of this research article.

Reference  

Lai, C. K., & Lisnek, J. A. (2023). The impact of implicit-bias-oriented diversity training on police officers’ beliefs, motivations, and actions. Psychological Science. https://journals.sagepub.com/doi/10.1177/09567976221150617 

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JOURNAL

Psychological Science

DOI

10.1177/09567976221150617 

METHOD OF RESEARCH

Experimental study

SUBJECT OF RESEARCH

People

ARTICLE TITLE

The Impact of Implicit-Bias-Oriented Diversity Training on Police Officers’ Beliefs, Motivations, and Actions

The Mozart effect myth: Listening to music does not help against epilepsy

A new study by psychologists at the University of Vienna shows that there is no scientific evidence supporting the alleged positive effect of Mozart's Sonata KV448 on epilepsy

Peer-Reviewed Publication

UNIVERSITY OF VIENNA

Over the past fifty years, there have been remarkable claims about the effects of Wolfgang Amadeus Mozart's music. Reports about alleged symptom-alleviating effects of listening to Mozart’s Sonata KV448 in epilepsy attracted a lot of public attention. However, the empirical validity of the underlying scientific evidence has remained unclear. Now, University of Vienna psychologists Sandra Oberleiter and Jakob Pietschnig show in a new study published in the prestigious journal Nature Scientific Reports that there is no evidence for a positive effect of Mozart's melody on epilepsy. 

In the past, Mozart’s music has been associated with numerous ostensibly positive effects on humans, animals, and even microorganisms. For instance, listening to his sonata has been said to increase the intelligence of adults, children, or fetuses in the womb. Even cows were said to produce more milk, and bacteria in sewage treatment plants were said to work better when they heard Mozart's composition. 

However, most of these alleged effects have no scientific basis. The origin of these ideas can be traced back to the long-disproven observation of a temporary increase in spatial reasoning test performance among students after listening to the first movement allegro con spirito of Mozart’s sonata KV448 in D major. 

More recently, the Mozart effect experienced a further variation: Some studies reported symptom relief in epilepsy patients after they had listened to KV448. However, a new comprehensive research synthesis by Sandra Oberleiter and Jakob Pietschnig from the University of Vienna, based on all available scientific literature on this topic, showed that there is no reliable evidence for such a beneficial effect of Mozart’s music on epilepsy. They found that this alleged Mozart effect can be mainly attributed to selective reporting, small sample sizes, and inadequate research practices in this corpus of literature. "Mozart’s music is beautiful, but unfortunately, we cannot expect relief from epilepsy symptoms from it" conclude the researchers. 

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JOURNAL

Nature

DOI

10.1038/s41598-023-30206-w 

ARTICLE TITLE

Unfounded authority, underpowered studies, and non-transparent reporting perpetuate the Mozart effect myth: A multiverse meta-analysis.

ARTICLE PUBLICATION DATE

6-Mar-2023

Cheap charcoal air filters offer improvements to in-vehicle air quality

Peer-Reviewed Publication

UNIVERSITY OF BIRMINGHAM

A cheap charcoal air filter can reduce nitrogen dioxide (NO2) inside vehicles by as much as 90%, compared to levels outside the vehicle.

Research presented in a report by WM Air, the West Midlands Air Quality Improvement Programme at the University of Birmingham, shows that charcoal filters, which costs around £10-£20, can effectively remove NO2 from the air within vehicle cabins.

NO2 is a common air pollutant that can aggravate diseases such as asthma and increase the risks of respiratory infections. Traffic emissions are a dominant source of NO2, and so road users inside vehicles are exposed as air circulates into vehicle cabins from outside through open windows and ventilation systems.

While ventilation systems do currently filter air, this is typically via a pollen filter. These prevent tiny particles and pollen getting inside the vehicle, but they have little effect on gases such as NO2. The activated carbon filters, in contrast, remove NO2 through a process called adsorption, in which the NO2 reacts with the carbon to stick to the surface area of the filter.

As with the pollen filter, the effectiveness of the carbon filter decreases over time, meaning it should be replaced regularly when the vehicle is serviced.

Lead researcher Dr Vasileios Matthaios said: “Our findings show clearly that there are benefits to switching to activated carbon air filters, reducing exposure to NO2 and the risk of related adverse health effects. These filters are simple, effective and inexpensive and should be considered, particularly for people who spend long periods of time in vehicles such as professional drivers.”

A research paper outlining the findings is published in Science of the Total Environment. In this study, the researchers tested NO2 in 10 different vehicles, ranging in size and type (petrol, diesel, hybrid and electric were all included). Air quality measurements inside the vehicles were taken with a range of ventilation conditions (AC turned on or off and windows either closed or partially open).

Each vehicle was tested three times, firstly with its original air filter in place, then with a pollen filter, and lastly with the activated charcoal filter.

The researchers found that overall, in-vehicle NO2 concentrations were on average 1.6 times lower when the windows were closed and the ventilation system recirculated air, compared to levels when the windows were open. When new standard pollen filters were fitted, NO2 concentrations were almost unchanged between closed windows and fresh air coming through the ventilation system and with windows open.

However, with activated carbon filters fitted, in-vehicle NO2 levels were on average 14.3 times lower with closed windows and recirculated air. Even with fresh air coming through the ventilation system, NO2 levels were 6.6 times lower than levels with windows open.  Maintaining appropriate ventilation is also important to prevent drowsiness.

Professor William Bloss, co-author on the paper, said: “These results show a fairly simple way to improve air quality inside vehicles, although as the main source of NO2 is our cities is diesel vehicles, reducing traffic emissions overall will bring the greatest air quality benefit across the general population.”

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JOURNAL

Science of The Total Environment

DOI

10.1016/j.scitotenv.2022.160395 

METHOD OF RESEARCH

Experimental study

SUBJECT OF RESEARCH

Not applicable

ARTICLE TITLE

NO2 levels inside vehicle cabins with pollen and activated carbon filters: A real world targeted intervention to estimate NO2 exposure reduction potential

The next pandemic: Researchers develop tool to identify existing drugs to use in a future outbreak

Algorithm calculates how to effectively “repurpose” present-day therapies for future use

Peer-Reviewed Publication

NEW YORK UNIVERSITY

A global team of researchers has created an algorithmic tool that can identify existing drugs in order to combat future pandemics. The work, reported in the Cell Press journal Heliyon, offers the possibility of responding more quickly to public-health crises.

“There is no silver bullet to defeat the Covid pandemic as it takes us over a public-health roller-coaster of deaths and devastation,” explains Naomi Maria, an immunologist, a visiting scientist at New York University’s Courant Institute of Mathematical Sciences, and the paper’s lead author. “However, using this AI tool, coupled with in vitro data and other resources, we’ve been able to model the SARS-CoV-2 infection and identify several COVID-19 drugs currently available as potentially effective in battling the next outbreak.”

“Drug repurposing strategies provide an attractive and effective approach for quickly targeting potential new interventions,” adds Bud Mishra, a professor at NYU’s Courant and one of the paper’s senior authors. “Identifying and selecting ahead of time the best candidates, prior to costly and laborious in vitro and in vivo experiments and ensuing clinical trials, could significantly improve disease-specific drug development.”

COVID-19 has shown to be a daunting challenge over the past three years, even though vaccines and hygienic practices have, over time, lessened its severity. However, despite these tools to combat it, SARS-CoV-2—the virus that causes COVID-19—continues to spread and take lives. This is due, in part, to its ability to rapidly diversify in its target cell-types, immune-response pathways, and modes of transmission. These traits make traditional approaches to vaccine and drug design less effective than in the past—and especially when the virus co-infects with other pathogens, such as RSV and influenza.  

Recognizing that current methods leave us chasing the virus, the team—which also included researchers from the Feinstein Institutes for Medical Research at Northwell Health in New York, the Red Cross Blood Bank Foundation Curaçao, the Curaçao Biomedical Health and Research Institute, the Netherlands’ University Medical Center Groningen, and Catania University’s Department of Clinical and Experimental Medicine in Sicily—conceived an approach aimed at closing the gap in future pandemics: repurposing existing drugs to fight back.

To do so, they developed a systems biology tool, the PHENotype SIMulator (PHENSIM). PHENSIM simulates tissue-specific infection of host cells of SARS-CoV-2 and then performs, through a series of computer—or in silico—experiments to identify drugs that would be candidates for repurposing. The algorithm computes, taking into account selected cells, cell lines, and tissues and under an array of contexts, by propagating the effects and alterations of biomolecules—such as differentially expressed genes, proteins, and microRNAs—and then calculates antiviral effects. The team confirmed the validity of the tool by comparing its results with recently published in vitro studies, demonstrating PHENSIM’s potential power in aiding effective drug repurposing.    

The researchers are part of RxCovea—a multi-disciplinary group of immunologists, biologists, chemists, data scientists, game theorists, geneticists, mathematicians, and physicians, among others, that seeks to develop innovative strategies to address COVID-19.

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JOURNAL

Heliyon

METHOD OF RESEARCH

Computational simulation/modeling

SUBJECT OF RESEARCH

Not applicable

ARTICLE TITLE

Application of the PHENotype SIMulator for Rapid Identification of Potential Candidates in Effective COVID-19 Drug Repurposing

ARTICLE PUBLICATION DATE

6-Mar-2023