Ramirez-Marquez, associate professor and division director of Enterprise Science and Engineering at Stevens, who grew up in the earthquake-prone Mexico City knows this first-hand. “Whenever there’s an earthquake, a city-wide alarm goes off and everybody leaves wherever they are and stays in the middle of the street — that’s a prevention phase,” he says. “Then there’s a restoration phase when people engage with others in the community, whether it’s sharing food and water or helping rescue people from under the debris.” The community’s solidarity and togetherness — one for all and all for one, per a Latin proverb — are key to bouncing back.

In scientific terms, this togetherness is defined as community cohesion, which encapsulates the sense of belonging, mutual support among members and shared values or sentiments, all of which boost community’s ability to withstand disasters. But whether this cohesion directly influences how well a community recovers from extreme events is not known, explains Alexander Gilgur who had studied this subject with Ramirez-Marquez as a Ph.D. student. “Resilience is a measure of how quickly and/or effortlessly the system recovers from a disturbance,” says Gilgur. “The causal relationship between cohesion and resilience appears logical, but it has not been proven mathematically.”

To address that issue, Gilgur and Ramirez-Marquez developed mathematical techniques to measure community cohesion and its resilience, which they outlined in a recent paper, published in the journal of Socio-Economic Planning Sciences. They investigated two case studies of the same San Francisco Bay Area community during 2020 wildfires and during 2022-23 rainstorms.

In their work, they found that during the less intense adverse events such the rainstorms, the community performance improved despite the increasing stress levels. However, in high-stress disturbances such as the wildfires, the community’s performance suffered. “We found that there’s a negative correlation between the resilience of a community and the strength of disturbance,” says Ramirez-Marquez.

In fact, in some cases, the disturbance could be so strong that people may forsake their community. Ramirez-Marquez cites the recent Los Angeles fires example (which wasn’t part of the study, but is telling), where more affluent residents hired private firefighters to keep their houses safe. “So when the stress is very strong, some might say, ‘oh, well, I don’t care about the community, I care about myself.’ The stress can be so high that the concept of community cohesion no longer stands.”

The scientists also found that the emotion intensity has a strong effect on community cohesion. “For helping communities be more resilient, emotional engagement is a very important factor,” says Gulgur, adding that it doesn’t matter whether emotions are positive or negative. “Anger and fear are equally powerful as joy and love.” On the contrary, people’s economic level does not have a direct effect on the community cohesion, “because the disaster might affect everyone,” says Ramirez-Marquez.

He notes that developing metrics to assess community cohesiveness and resilience offers practical benefits. If we can establish the causal link between cohesiveness and resilience, we can then set thresholds, limits or targets — and use these metrics to implement policies that aim to reach the desired numbers to improve resilience.

“Community cohesiveness is essentially a social glue that holds people together,” Ramirez-Marquez says. Quantifying that glue is challenging, yet being able to do so can help indicate whether a given community is resilient or can be stronger. “These metrics can then be used by policymakers to implement policies that make communities more resilient.”

The consequences of heavy drinking — which is defined as four or more drinks per occasion for women and five or more for men — are felt throughout the college community. These include blackouts, academic underperformance and interpersonal problems. Then there are the secondhand consequences for students who don’t drink, such as interrupted study, aggression, assault and having to care for intoxicated peers.

In a new study, researchers from the Brown University School of Public Health developed and tested an intervention called Counter-Attitudinal Advocacy (CAA). CAA involves advocating for a position that contradicts a personally held attitude or behavior. In this context, CAA targets positive perceptions of heavy drinking and the belief that alcohol is an essential part of college life.

In randomized controlled trials at two sites with 585 college students, researchers compared CAA to the well-established Personalized Normative Feedback (PNF) to evaluate their effectiveness in decreasing drinks per week, peak blood alcohol concentration and alcohol-related consequences relative to a control group. Researchers focused on drinks per week, a standard measure given the irregular drinking patterns of college students, who often veer between heavy drinking and alcohol-free days.

Ultimately, they worked on answering two main questions:

• Does CAA effectively reduce alcohol-related risk compared to our control?
• How does CAA compare to PNF, which has proven to be an effective low-cost way of reducing alcohol consumption among high-risk students?

Here’s what they found: Participants who received PNF reported significantly fewer drinks per week than the control group, while those who received CAA reported significantly fewer consequences. CAA had a harm reduction effect on consequences — its intended focus — but not on consumption of alcohol, which it did not target.

“Both interventions take just 5-10 minutes, making them ideal for broad prevention efforts,” said Kate Carey, co-lead investigator of the study and professor of behavioral and social sciences at Brown. “Our results showed that PNF did reduce alcohol consumption, as expected. But CAA specifically reduced the number of problems participants reported due to drinking. So, while they had different effects, they were complementary — giving us another useful tool for harm reduction.”

Carey explained that PNFs show participants how their drinking habits stack up against those of their peers, often exposing a common misconception that others drink more than they actually do: an insight that can help them adjust their own behavior. In contrast, CAA encourages participants to reflect on why it is a good idea to avoid alcohol-related problems, such as passing out or taking excessive risks, and to identify specific actions they can take to minimize these risks.

“Instead of directly telling students what to do, we prompt them to generate their own strategies,” Carey said. “This makes the intervention personalized and non-confrontational. Unlike some interventions that make people feel defensive about their drinking, CAA frames the discussion more broadly: ‘Why is it good for young people to avoid problems?’ rather than ‘You personally need to change.'”

As participants responded to these prompts, a research assistant or peer asked them to explain their written responses. Carey noted that this act of verbal reinforcement likely strengthened the intervention’s effect, since we tend to feel more committed to our viewpoints when we share them publicly.

It’s important to have a variety of brief interventions, since no single approach works for everyone, Carey stressed. Offering multiple evidence-based options increases the chances of reaching more people who are undergoing a period of heightened risk.

The research team, which includes co-primary investigators Angelo DiBello associate professor of applied and professional psychology at Rutgers University and Clayton Neighbors, professor of social psychology at the University of Houston, are encouraged that CAA provides another effective tool — especially for those who may not respond to PNF.

“Despite extensive research, the connection between a jet’s initial conditions and its final particle distribution has remained elusive,” said Charles Joseph Naim, a research associate at the Center for Frontiers in Nuclear Science (CFNS) in SBU’s Department of Physics and Astronomy. “This study, for the first time, establishes a direct connection between the ‘entanglement entropy’ at the earliest stage of jet formation and the particles that emerge as a jet evolves.”

The evidence comes from an analysis of jet particles emerging from proton-proton collisions captured by the ATLAS experiment at the Large Hadron Collider, a 17-mile-circumference circular collider located at CERN, the European Organization for Nuclear Research. In these powerful collisions, the individual building blocks of the colliding protons, known as quarks and gluons, scatter off one another and sometimes get knocked free with enormous amounts of energy. But quarks can’t stay free for long. They and the gluons that normally hold them together immediately begin to split and reconnect through a branching process called fragmentation. The result is the formation of many new composite particles made of pairs or triplicates of quarks — collectively known as hadrons — that spray out of the collision in a coordinated way, that is, as a jet.

“We wanted to see if the distribution of the hadrons in the jet was influenced by the level of entanglement among the quarks and gluons at the time the jet first formed,” said Abhay Deshpande, a distinguished professor at SBU. Deshpande holds a joint appointment as director of science for the Electron-Ion Collider (EIC), a new nuclear physics research facility under construction at Brookhaven Lab, and he is also currently serving as Brookhaven Lab’s interim associate laboratory director for nuclear and particle physics.

The analysis was motivated in part by earlier research by study co-authors Zhoudunming Tu and Dmitri Kharzeev, both with faculty roles at SBU and appointments at Brookhaven Lab. Their study, published last year, revealed a connection between entanglement among quarks and gluons within protons and the overall distribution of particles emerging from proton-proton and electron-proton smashups. In that work, the higher the entanglement entropy among the quarks and gluons, the greater the entropy, or “messiness,” in the distribution of particles produced.

“This earlier study revealed that there is maximal entanglement among the quarks and gluons within the high-energy proton,” said Tu. “In this work, we extend this approach to the production of jets, which form from the fragmentation of those quarks and gluons. Will there also be maximal entanglement ‘inside’ these fragmenting high-energy quarks and gluons?”

Such a state of maximal entanglement among the jet-forming quarks and gluons predicts a connection between the jet fragmentation function and the entropy, or disorder, of hadrons emerging from the jet. This entropy would be observed as a large number of different types of hadrons — mainly pions, kaons, and protons — striking the detector. Conversely, such an observation of a high degree of disorder among jet particles and its correlation with the initial fragmentation predictions would be evidence of this maximal entanglement in the fragmenting quarks and gluons.

When the scientists looked at the data from the LHC’s proton-proton collisions, the distribution of jet hadrons matched this prediction based on maximal entanglement in the earliest stage of jet formation.

“This new study offers a novel quantum-level perspective on the fragmentation process,” said Kharzeev.

Study co-author Jaydeep Datta, a research scientist at SBU, added, “This study paves the way for further exploration of how quantum entanglement influences hadron formation, including at the upcoming Electron-Ion Collider.”

The EIC will have active participation from many Stony Brook University faculty and students, and it promises unprecedented precision in studying quantum entanglement effects in high-energy collisions. Among other things, the EIC will compare jets emerging from electron-proton collisions with jets emerging from electron-nucleus collisions. These experiments will explore how far the quantum effects extend within nuclei — and potentially modify the microcosm within protons.

This research was funded by the Center for Frontiers in Nuclear Science at Stony Brook University; the DOE Office of Science; the Co-design Center for Quantum Advantage, a Brookhaven-led National Quantum Information Science Research Center also supported by the DOE Office of Science; and by a Laboratory Directed Research and Development project at Brookhaven Lab.

The UB team is formed by José Pablo Rivas-Fernández, first author of the article, and Carme Rovira, ICREA research professor, both from the UB’s Faculty of Chemistry and the UB Institute of Theoretical and Computational Chemistry (IQTCUB), in coordination with Casper Wilkens, biotechnologist at the Technical University of Denmark (DTU). Experts from the Norwegian University of Science and Technology (NTNU) and North Carolina State University (United States) have also participated.

Despite the abundance of alginates in the marine environment, their range of opportunities, especially in the biomedical sector, is severely limited by the inhomogeneity of their composition in the natural state — they may contain a mixture of mannuronic acid and guluronic acid sugars in varying proportions. Knowledge of the mechanism of action of AL enzymes when they specifically break the bonds connecting the mannuronic acid-type sugars in this polymer will help to overcome these limitations. “The results lay the groundwork for manipulating these enzymes and designing variants with better catalytic properties and higher efficiency on a large scale.

By using industrial techniques and bioprocesses, it will be possible to optimize the production of ‘tailored alginates’ in sufficient quantities to meet society’s needs,” the researchers explain. “These findings will also allow for a “better use of natural resources and boost the green economy by using enzymes as key tools in the production of these alginates,” say the authors.

Computational analysis with the MareNostrum 5 supercomputer

Part of the study was based on the computational analysis of the action mechanism of these enzymes, using as a starting point the three-dimensional structures of the AL enzyme in interaction with different alginate variants, obtained by the DTU collaborators. Based on this structure and using the resources of the MareNostrum 5 supercomputer at the Barcelona Supercomputing Center — Centro Nacional de Supercomputación (BSC-CNS), the UB team has carried out molecular dynamics simulations, using multiscale quantum mechanics and molecular mechanics techniques to model and obtain a detailed description at the atomic level of the chemical reaction that takes place during the degradation of alginates.

These simulations have reconciled previous scientific discrepancies about the number of stages in which the reaction occurs, confirming that it happens in a single stage and that the polymer breaks at the centre, not at one end. They have also cleared the nature of the transition state — the highest energy configuration during the reaction — as a highly negatively charged species. “This finding suggests that we may be able to control at what point the polymer breaks down by mutations of certain amino acids in the enzyme’s active centre,” the researchers explain.

Another important element of the study is that the enzymes analysed belong to family 7 of lyases, the most abundant known to date, which allows extrapolating the mechanism described to other enzymes with high biotechnological potential.

These findings also facilitate the identification of key residues or amino acids that can be targeted to improve the efficiency of these enzymes, a very promising line of research on which the UB team is already working.

Moreover, the results improve the understanding of the chemical evolution of alginate during its degradation, a fundamental element for the design of probes capable of identifying and isolating alginate lyases, which have not yet been described. In this sense, UB researchers are currently working on the design of probes that allow the efficient identification of new enzymes active in carbohydrates.

This study is part of Carbocentre, a project funded by a Synergy Grant from the European Research Council (ERC).

Virginia Tech researchers have gained a better understanding of this insidious virus by studying its rodent hosts in North America. Using National Science Foundation data, they found three hotspots of hantavirus circulation in wildlife — Virginia, Colorado, and Texas — and identified 15 rodent species as carriers, including six species that had not previously been identified as hosts of the virus.

The details of their study was published in Ecosphere.

“This project is timely because hantavirus is considered an emerging disease of pandemic potential with symptoms that resemble severe COVID-19 infections,” said Paanwaris Paansri, a Ph.D. student in the Department of Fish and Wildlife Conservation and co-author of the study.

Hantaviruses are a family of viruses that have been identified in regions all over the globe and can reach mortality rates similar to other diseases of high concern, such as nipah and Ebola. In Asia, hemorrhagic fever with renal syndrome is caused by the Hantaan virus, in Europe that syndrome is caused by the Dobrava-Belgrade virus, and in North and South America, hantavirus pulmonary syndrome is caused by Sin Nombre virus and Andes virus — all hantaviruses. Sin Nombre virus was first discovered in New Mexico in 1993.

Little is known about the ecology of hantaviruses in wildlife except that the pathogen is spread to humans by inhalation of aerosolized excreta, urine, or saliva from asymptomatic rodent hosts, and it can be fatal in humans.

The Virginia Tech team used data from the National Science Foundation’s National Ecological Observatory Network program to gain a better understanding of hantavirus circulation in its sylvatic cycle — the pathogen’s life cycle in wildlife — by examining the environmental influences and geographical distribution of the rodent hosts. The program collected and tested 14,004 blood samples from 49 species at 45 field sites across the United States from 2014-19.

“In North America, Peromyscus maniculatus, the deer mouse, is the most common carrier but our study also revealed that other rodent species have a higher prevalence of hantavirus, which changes the current paradigm in hantavirus circulation in wildlife,” said Paansri, whose mentor Associate Professor Luis E. Escobar, led the study and is an affiliate with the Fralin Life Sciences Institute. “This new information is expected to help us understand where and when hantavirus is most likely to occur, which is crucial for predicting outbreaks and informing public health officials.”

The discovery of six new rodent species of hantavirus hosts is significant. Some of these newly discovered hosts inhabit regions where traditional hosts, such as the deer mouse or the white-footed mouse (Peromyscus leucopus), are absent, meaning they could be potential reservoirs of the virus in new or overlooked areas.

“This expands our understanding of the basic biology of the virus and shows that the virus is more adaptable than previously believed,” Paansri said. “This has direct implications for surveillance strategies and risk assessments and can help explain some cases of hantavirus in humans where the main reservoir is absent or rare.”

In addition to expanding the known host species, the researchers were able to gain a better understanding of seasonal trends and effects of seasonal weather shifts. For example, warmer winters and increased precipitation can increase rodent populations and drier conditions can facilitate the generation of contaminated dust containing particulates from rodent excrement and saliva, increasing the risk of transmission to humans.

“Climate change can cause population increases or distributional shifts of rodents, altering the epidemiology of hantavirus,” Paansri said. “These fluctuations can lead to more frequent rodent-human interactions and increase the chance of spillover. We found some evidence that rodent demography and hantavirus prevalence can be predicted months in advance.”

The actual number of human cases of hantavirus infections is largely unknown, according to Paansri, because many infections remain silent, meaning the infected individual may not develop any symptoms or the symptoms could mirror other diseases, such as the common cold or influenza.

The researchers plan to further explore the extent to which climatic variations influence hantavirus transmission in wildlife and in humans..

“We believe that many lessons learned from this study can be generalized to other wildlife diseases, considering that their distribution is global,” Paansri said.

Abdelghafar Alkishe, a Virginia Tech 2022-23 presidential postdoctoral fellow, also worked on this study.