Inhibiting fear-related thoughts and defensive behaviors when they are no longer appropriate to the situation is a prerequisite for flexible and adaptive responding to changing environments. Such inhibition of defensive systems is mediated by ventromedial prefrontal cortex (vmPFC), limbic basolateral amygdala (BLA), and brain stem locus-coeruleus noradrenergic system (LC-NAs). Non-invasive, transcutaneous vagus nerve stimulation (tVNS) has shown to activate this circuit. Using a multiple-day single-cue fear conditioning and extinction paradigm, we investigated long-term effects of tVNS on inhibition of low-level amygdala modulated fear potentiated startle and cognitive risk assessments. We found that administration of tVNS during extinction training facilitated inhibition of fear potentiated startle responses and cognitive risk assessments, resulting in facilitated formation, consolidation and long-term recall of extinction memory, and prevention of the return of fear. These findings might indicate new ways to increase the efficacy of exposure-based treatments of anxiety disorders.

Objective: This article analyzed gender differences in professional advancement following the outbreak of the Covid-19 pandemic based on data from open-source software developers in 37 countries. Background: Men and women may have been affected differently from the social distancing measures implemented to contain the Covid-19 pandemic. Given that men and women tend to work in different jobs and that they have been unequally involved in childcare duties, school and workplace closings may have impacted men's and women's professional lives unequally. Method: We analyzed original data from the world's largest social coding community, GitHub. We first estimated a Holt-Winters forecast model to compare the predicted and the observed average weekly productivity of a random sample of male and female developers (N=177,480) during the first lockdown period in 2020. To explain the crosscountry variation in the gendered effects of the Covid-19 pandemic on software developers' productivity, we estimated two-way fixed effects models with different lockdown measures as predictors - school and workplace closures, in particular. Results: In most countries, both male and female developers were, on average, more productive than predicted, and productivity increased for both genders with increasing lockdown stringency. When examining the effects of the most relevant types of lockdown measures separately, we found that stay-at-home restrictions increased both men's and women's productivity and that workplace closures also increased the number of weekly contributions on average - but for women, only when schools were open. Conclusion: Having found gender differences in the effect of workplace closures contingent on school and daycare closures within a population that is relatively young and unlikely to have children (software developers), we conclude that the Covid-19 pandemic may indeed have contributed to increased gender inequalities in professional advancement.

In recent years, increasing concerns have been raised about the environmental risk of microplastics in freshwater ecosystems. Small microplastics enter the water either directly or accumulate through disintegration of larger plastic particles. These particles might then be ingested by filter-feeding zooplankton, such as rotifers. Particles released into the water may also interact with the biota through the formation of aggregates, which might alter the uptake by zooplankton. In this study, we tested for size-specific aggregation of polystyrene microspheres and their ingestion by a common freshwater rotifer Brachionus calyciflorus. The ingestion of three sizes of polystyrene microspheres (MS) 1-, 3-, and 6-mu m was investigated. Each MS size was tested in combination with three different treatments: MS as the sole food intake, MS in association with food algae and MS aggregated with biogenic matter. After 72 h incubation in pre-filtered natural river water, the majority of the 1-mu m spheres occurred as aggregates. The larger the particles, the higher the relative number of single particles and the larger the aggregates. All particles were ingested by the rotifer following a Type-II functional response. The presence of algae did not influence the ingestion of the MS for all three sizes. The biogenic aggregation of microspheres led to a significant size-dependent alteration in their ingestion. Rotifers ingested more microspheres (MS) when exposed to aggregated 1- and 3-mu m MS as compared to single spheres, whereas fewer aggregated 6-mu m spheres were ingested. This indicates that the small particles when aggregated were in an effective size range for Brachionus, while the aggregated larger spheres became too large to be efficiently ingested. These observations provide the first evidence of a size- and aggregation-dependent feeding interaction between microplastics and rotifers. Microplastics when aggregated with biogenic particles in a natural environment can rapidly change their size-dependent availability. The aggregation properties of microplastics should be taken into account when performing experiments mimicking the natural environment.

Elaeidobius kamerunicusis the most important insect pollinator in oil palm plantations. In this study, the mitochondrial genome (mitogenome) ofE. kamerunicus(17.729 bp), a member of the Curculionidae family, will be reported. The mitogenome consisted of 13 protein-coding genes (PCGs), 22 transfer RNA genes (tRNAs), 2 ribosomal RNA genes (rRNAs), and a putative control region (CR). Phylogenetic analysis based on 13 protein-coding genes (PCGs) using maximum Likelihood (ML) methods indicated thatE. kamerunicusbelongs to the Curculionidae family. This mitochondrial genome provides essential information for understanding genetic populations, phylogenetics, molecular evolution, and other biological applications in this species.

The radiation belts of the Earth, filled with energetic electrons, comprise complex and dynamic systems that pose a significant threat to satellite operation. While various models of electron flux both for low and relativistic energies have been developed, the behavior of medium energy (120-600 keV) electrons, especially in the MEO region, remains poorly quantified. At these energies, electrons are driven by both convective and diffusive transport, and their prediction usually requires sophisticated 4D modeling codes. In this paper, we present an alternative approach using the Light Gradient Boosting (LightGBM) machine learning algorithm. The Medium Energy electRon fLux In Earth's outer radiatioN belt (MERLIN) model takes as input the satellite position, a combination of geomagnetic indices and solar wind parameters including the time history of velocity, and does not use persistence. MERLIN is trained on >15 years of the GPS electron flux data and tested on more than 1.5 years of measurements. Tenfold cross validation yields that the model predicts the MEO radiation environment well, both in terms of dynamics and amplitudes o f flux. Evaluation on the test set shows high correlation between the predicted and observed electron flux (0.8) and low values of absolute error. The MERLIN model can have wide space weather applications, providing information for the scientific community in the form of radiation belts reconstructions, as well as industry for satellite mission design, nowcast of the MEO environment, and surface charging analysis.