פרסומים

Abstract

Intragroup empathy is vital for resilience. However, it is often impaired in advantaged-dominated environments when one adopts advantaged-group characteristics to climb the social ladder. The current work examines contextual factors that may affect intragroup empathy: the motivation behind adopting the advantaged-group characteristics, and negative encounters with members of the advantaged group. We hypothesized that coercively, versus willingly, adopting advantaged-group characteristics will increase intragroup empathy both when the outcomes are negative and positive. We further hypothesized that a negative encounter with an advantaged-group member would increase intragroup empathy, compared to no encounter. In three studies, Palestinian students in Israeli academia were assigned to read scripts depicting the academic experience of a Palestinian student adopting advantaged-group characteristics. We tested (a) the effects of motivation following a negative outcome (N = 182); (b) the effects following a positive outcome (N = 205); and (c) the interaction between a negative encounter with an advantaged-group member and motivation, and its effect on intragroup empathy (N = 282). Intragroup empathy was higher in the coerced condition compared to the free-willing condition both for negative and positive outcomes. A negative encounter with an advantaged-group member increased intragroup empathy in the willing condition. By illuminating contextual variables that shape intragroup empathy, this research shows that impairment in intragroup empathy is not inevitable. This work may serve as a foundation for future interventions.

More than a third of the world's population lives in drylands and is disproportionally at risk of hydrometeorological hazards such as drought and flooding. While existing studies have widely explored weather systems governing precipitation formation in humid regions, our understanding of the atmospheric processes generating precipitation in arid regions remains fragmented at best. Here we show, using a variety of precipitation datasets, that Rossby wave breaking is a key atmospheric driver of precipitation in arid regions worldwide. Rossby wave breaking contributes up to 90% of daily precipitation extremes and up to 80% of total precipitation amounts in arid regions equatorward and downstream of the midlatitude storm tracks. The relevance of Rossby wave breaking for precipitation increases with increasing land aridity. Contributions of wave breaking to precipitation dominate in the poleward and westward portions of arid subtropical regions during the cool season. Given the projected precipitation decline and the large uncertainty in projections of precipitation extremes in these regions, our findings imply that Rossby wave breaking plays a crucial role in projections and uncertainties of future precipitation changes in societally vulnerable regions that are exposed to both freshwater shortages and flood hazards.

The broad and equidistant spectrum of frequency combs has had a profound impact on spectroscopic studies. Particularly, experiments involving the coupling of frequency combs to cavities have already enabled unprecedented broadband and sensitive spectroscopy on a single-molecule level. The emergence of integrated, compact, and broadband Kerr-microcombs holds promise to bring many metrological and spectroscopic studies outside of the lab. However, performing cavity-enhanced direct frequency comb spectroscopy on-chip has remained a challenge. Here, we couple a microcomb source with a microcavity to extend the advantages of cavity-enhanced spectroscopy to photonically integrated circuits. By harnessing the coherent nature of the Kerr-comb and high-Q microcavity enhancement, we obtain a detailed dispersion landscape of the guided-wave mode and comprehensive frequency-dependent cavity lineshapes. Our microcomb-cavity coupling can facilitate photonically integrated cavity-enhanced biochemical spectroscopy by evanescently coupling analytes to the cavity’s guided mode, a mode of operation we analyze numerically and provide guidelines for its potential implementation. Demonstrated detailed dispersion measurements, overperforming state-of-the-art table-top tunable lasers in available bandwidth, show potential for integrated non-linear optics applications, as precise dispersion management is crucial for such processes. Our chip-scale comb-cavity coupled platform suggests an integrated, broadband, cost-effective, and accurate tool for the non-linear optics studies as well as for ultra-compact bio- and chemical-sensing platform.

Static Zn–Br2 batteries are considered an attractive option for cost-effective and high-capacity systems for large energy storage. Yet, the corrosive nature of the Zn–Br2 electrolytes entails a careful selection of all cells' ingredients to avoid rapid degradation of the batteries upon cycling. Thanks to their high chemical resistance and excellent conductivity, carbonaceous electrodes are typically utilized as current collectors for the cathode side, while thin Zn or Ti foils are most widely used as the anodes' current collectors. However, these metals tend to corrode fast, thus undermining the desirable performance of the cells as durable and stable rechargeable batteries. We demonstrate the effective utilization of carbon nanotubes (CNT) films as highly stable anode current collector for Zn–Br2 batteries. Dispersion of the CNT beforehand in slurries containing anionic, cationic, or neutral surfactants yielded distinct chemical and physical characteristics of these carbonaceous electrodes. This, in turn, led to significant differences in the morphology of the deposited Zn, consequently affecting the electrochemical performance of the Zn anodes. These findings provide insight into the interactions between Zn cations and the surface of CNTs, offering opportunities for further surface modifications of CNTs as effective anodes’ substrates for Zn–Br2 batteries.

Security concerns about immigration are on the rise. Many countries respond by fortifying their borders. Yet little is known about the influence of border security measures on perceived threat from immigration. Borders might facilitate group identities and spread fear of outsiders. In contrast, they might enhance citizens’ sense of security and control over immigration. We test these claims using survey experiments run on a quota sample of over 1000 Americans. The findings show that allocating more government resources to border security increases desired levels of immigration. This effect is likely driven by a sense of control over immigration, induced by border security measures even when the number or characteristics of immigrants remain unchanged. Our findings suggest that border controls, which are widely considered as symbols of closure and isolation, can increase public support for immigration.
 

Chickpea (Cicer arietinum L.) is a major grain legume grown worldwide as a staple protein source. Traditionally, it is a rain-fed crop, but supplemental irrigation can increase yields and counteract the challenges posed by the changing climate worldwide. A fast and non-destructive plant water status assessment method may streamline irrigation management. The main objective of this study was to remotely assess the leaf water potential (LWP) and leaf area index (LAI) of field-grown chickpea. Five irrigation treatments were applied in two farm experiments and two commercial fields. Ground hyperspectral canopy reflectance and Vegetation and Environment monitoring on a New Micro-Satellite (VENµS) images acquired throughout the study. In parallel, LWP and LAI measurements were captured in the field. Vegetation indices (VIs) and machine learning (ML) based on all spectral bands were used to calibrate and validate spectral estimation models. The normalized difference spectral index (NDSI) that used bands on 1600 and 1730 nm (NDSI(1600,1730)) selected in the current study yielded the LWP lowest estimation error on independent validation (RMSE = 0.19 [MPa]) using linear regression. VENµS based VIs resulted in relatively lower LWP estimation accuracy (RMSE = 0.23–0.29 [MPa]) compared to VIs calculated from ground hyperspectral data (RMSE = 0.19–0.21 [MPa]). Artificial neural network (ANN) models for LWP from ground and space spectral data showed similar performances (RMSE = 0.15–0.17 [MPa]), and were both more accurate than VIs. LWP response to the irrigation treatments was faster than the LAI response and was captured by the NDSI(1600,1730). The low correlation found between LWP and LAI (r = 0.08–0.44) supports the conclusion that spectral reflectance of chickpea canopy can be used to estimate LWP per se and is only partially affected by morphological changes induced by irrigation treatments and canopy development. The ability to rapidly estimate chickpea LWP may improve irrigation scheduling in the future.

The growing demand for energy has increased the need for battery storage, with lithium-ion batteries being widely used. Among those, nickel-rich layered lithium transition metal oxides [LiNi1-x-yCoxMnyO2 NCM (1 - x - y > 0.5)] are some of the promising cathode materials due to their high specific capacities and working voltages. In this study, we demonstrate that a thin, simple coating of polyalanine chiral molecules improves the performance of Ni-rich cathodes. The chiral organic coating of the active material enhances the discharge capacity and rate capability. Specifically, NCM811 and NCM622 electrodes coated with chiral molecules exhibit lower voltage hysteresis and better rate performance, with a capacity improvement of >10% at a 4 C discharge rate and an average improvement of 6%. We relate these results to the chirally induced spin selectivity effect that enables us to reduce the resistance of the electrode interface and to reduce dramatically the overpotential needed for the chemical process by aligning the electron spins.