Miracle-dz/UniFAR-FTUs huggingface dataset:
COVID-19: Looking for the Exit

The paper examines optimal policy responses to COVID 19 by building on an epidemiological model based on analysis of the biology of the SARS-CoV-2 virus. The epidemiological model maps the distributions of serial and generation intervals of the coronavirus into a SEIR model with Erlang distributions. This model is then used in an optimizing social planner problem. Among a number of policy strategies considered, special attention is given to cyclical strategies of k days of work and 14 − k days of lockdown in fortnight batches, coming after a period of full lockdown. The planner optimally chooses the strategy in terms of k days and in terms of three starting-time points (lockdown, implementation of the k strategy, and release). The results, applied using calibrated values for the U.S. economy, indicate that cyclical strategies provide for significant improvement in the trade-offs of health outcomes (deaths, breaches of ICU capacity) and economic outcomes (loss of output, employment, and consumption). The paper explores the underlying mechanism. A key aspect is that there is a fundamental choice between aiming for “effective R” herd immunity and waiting for a vaccine. Inter alia, we show that some prevalent SIR modeling in the recent COVID 19 Economics literature derives disease dynamics, which are erroneous, and which leads to a mis-specification of the planner problem. ∗Department of Molecular Biology, Weizmann Institute of Science, Rehovot, Israel. †Department of Economics, Ben Gurion University, Beer Sheva, Israel. ‡Department of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot, Israel. §Corresponding author. The Eitan Berglas School of Economics, Tel Aviv University, Tel Aviv, Israel. yashiv@tauex.tau. ac.il
Spatio-temporal dynamics of intra-host variability in SARS-CoV-2 genomes AUTHORS AND AFFILIATIONS

During the course of the COVID-19 pandemic, large-scale genome sequencing of SARS-CoV-2 has been useful in tracking its spread and in identifying Variants Of Concern (VOC). Besides, viral and host factors could contribute to variability within a host that can be captured in next-generation sequencing reads as intra-host Single Nucleotide Variations (iSNVs). Analysing 1,347 samples collected till June 2020, we recorded 18,146 iSNV sites throughout the SARS-CoV-2 genome. Both, mutations in RdRp as well as APOBEC and ADAR mediated RNA editing seem to contribute to the differential prevalence of iSNVs in hosts. Noteworthy, 41% of all unique iSNVs were reported as SNVs by 30th September 2020 in samples submitted to GISAID, which increased to ~80% by 30th June 2021. Following this, analysis of another set of 1,798 samples sequenced in India between November 2020 and May 2021 revealed that majority of the Delta (B.1.617.2) and Kappa (B.1.617.1) variations appeared as iSNVs before getting fixed in the population. We also observe hyper-editing events at functionally critical residues in Spike protein that could alter the antigenicity and may contribute to immune escape. Thus, tracking and functional annotation of iSNVs in ongoing genome surveillance programs could be important for early identification of potential variants of concern and actionable interventions.
Temporal Stability of Moral Dilemma Judgments: A Longitudinal Analysis Using the CNI Model

Although moral dilemma judgments are influenced by a variety of situational factors, there is evidence for considerable disagreement between individuals. Using the CNI model to disentangle (a) sensitivity to consequences, (b) sensitivity to moral norms, and (c) general preference for inaction versus action in responses to moral dilemmas, the current research examined the temporal stability of individual differences along the three dimensions. Across two time points 1 month apart, sensitivity to consequences (r = .81) and sensitivity to norms (r = .84) showed high levels of stability that were comparable to the Big Five personality traits; general preference for inaction versus action showed lower stability (r = .41). Exploratory analyses revealed reliable associations between the three dimensions of moral dilemma judgments and three of the Big Five (extraversion, agreeableness, openness). Together, these findings provide evidence for stable individual differences in moral dilemma judgments that are related to basic personality traits.
Trans Cohorts Metabolomic Modulation Following Long-Term Successful Therapy in HIV-Infection

Despite successful combination antiretroviral therapy (cART), persistent low-grade immune activation together with inflammation and toxic antiretroviral drugs can lead to long-lasting metabolic adaptation in people living with HIV (PLWH). The successful short-term cART reported abnormalities in the metabolic reprogramming in PLWH, but the long-term consequences are unknown. This study investigated alterations in the plasma metabolic profiles by comparing PLWH and matched HIV-negative controls (HC) from Cameroon and India. We used untargeted and targeted LC-MS/MS-based metabolic profiling in PLWH with long-term (>5years) successful therapy in a trans cohorts approach. Advanced statistical and bioinformatics analyses showed altered amino acid metabolism, more specifically to glutaminolysis in PLWH with therapy than HIV-negative controls that can lead to excitotoxicity in both the cohorts. A significantly lower level of neurosteroids was observed in both cohorts and could potentiate neurological impairments in PLWH. The modulation of cellular glutaminolysis promoted increased cell death and latency reversal in pre-monocytic HIV-1 latent cell model U1, which may be essential for the clearance of the inducible reservoir in HIV-integrated cells. Our patient-based metabolomics and in vitro study, therefore, highlight the importance of altered glutaminolysis in PLWH that can be linked accelerated neurocognitive aging and metabolic reprogramming in latently infected cells.
Improving the Nutritional Values of Wheat and Rice Crackers by Using Cauliflowers

The present study described the enhancement of the nutritional values of wheat and rice crackers by adding cauliflowers. The results showed that 25% 75% cauliflower replaced in crackers increased the consumer acceptability, nutritional value, antioxidant activity, minerals, and anti-carcinogenic effect. Moreover, it also improved the functional properties and sensory quality. The results revealed that the raw samples of cauliflower recorded the highest value of moisture, ash, protein and fiber 89.29%, 7.68%, 19.04% and 10.18% on dry weight, respectively. The crackers formula of cauliflower: wheat 75%:25% and cauliflower: rice 75%:25% recorded the highest values in ash, protein, fat, and fiber. The data showed that increasing cauliflower percentage in crackers formula causing a parallel increase in all determined chemical composition. Cauliflower samples exhibited the highest antioxidant activity (92.94%). Also, crackers samples of cauliflower: wheat 75%:25% crackers, recorded 57.6% for antioxidant activity. The highest values of phenols and flavonoids for cauliflower cracker samples (cauliflower: wheat 75%:25% and cauliflower: rice 50%:50%) have increased up to (5.75 and 5.49) respectively. The results showed that the higher mineral content is the sulfur (635.96 mg/100g) in raw cauliflower, while (1.00 mg/100g, and 0.99 mg/100g sulfur content) in wheat and rice respectively. Moreover, the result found that as the cauliflower percentage increases, the minerals contents especially sulfur increase. Furthermore, the cauliflower displayed moderate activity for human hepatocellular carcinoma, colon cancer and intestinal epithelial barrier treatment, (IC50 = 183.4 ± 6.8, 175.8 ± 7.1 and 207.2 ± 8.5 μg/mL, respectively). There were significant differences in the taste property; the highest degree of acceptance of the taste was obtained to crackers samples which were replaced with cauliflower more than the control.
Understanding wind-driven melt of patchy snow cover

Abstract. The simplified representation of snow processes in most large-scale hydrological and climate models is known to introduce considerable uncertainty in the predictions and projections of water availability. During the critical snowmelt period, the main challenge in snow modeling is that net radiation is spatially highly variable for a patchy snow cover, resulting in large horizontal differences in temperatures and heat fluxes. These differences can drive advection of turbulent heat from the snow free areas to the snow patches, potentially enhancing the melt rates at the leading edge and increasing the variability of subgrid melt rates. To get more insight in these processes, we examine the melt along the upwind and downwind edges of a 50 meter long snow patch in the Finseelvi catchment, Norway, and try to explain the observed behaviour with highly idealized simulations of heat fluxes and air movement over patchy snow. The melt of the snow patch was monitored from 11 June until 15 June 2019 by making use of height maps obtained through the photogrammetric Structure-from-Motion principle. A vertical melt of 23 ± 2.0 cm was observed at the upwind edge over the course of the field campaign, whereas the downwind edge melted only 3 ± 0.4 cm. When comparing this with meteorological measurements, we estimate the turbulent heat fluxes to be responsible for 60 to 80 % of the upwind melt of which a significant part is caused by the latent heat flux. The melt at the downwind edge approximately matches the melt occurring due to net radiation. To better understand the dominant processes, we represented this behaviour in idealized direct numerical simulations, which are based on the measurements on a single snow patch by Harder et al. (2017) and resemble a flat patchy snow cover with typical snow patch sizes of 15, 30 and 60 m. Using these simulations, we found that the reduction of the vertical temperature gradient over the snow patch was the main cause for the reductions in sensible heat over distance from the leading edge, independent of typical snow patch size. Moreover, we observed that the sensible heat fluxes at the leading edge and the decay over distance were independent of snow patch size as well, which resulted in a 15 % and 25 % reduction in average snowmelt for respectively a doubling and quadrupling of typical snow patch size. These findings lay out pathways to include the effect of local-scale heat advection based on the typical snow patch size in large-scale hydrological and climate models to improve snowmelt modelling.
Ungoliant: An Optimized Pipeline for the Generation of a Very Large-Scale Multilingual Web Corpus

Since the introduction of large language models in Natural Language Processing, large raw corpora have played a crucial role in Computational Linguistics. However, most of these large raw corpora are either available only for English or not available to the general public due to copyright issues. Nevertheless, there are some examples of freely available multilingual corpora for training Deep Learning NLP models, such as the OSCAR and Paracrawl corpora. However, they have quality issues, especially for low-resource languages. Moreover, recreating or updating these corpora is very complex. In this work, we try to reproduce and improve the goclassy pipeline used to create the OSCAR corpus. We propose a new pipeline that is faster, modular, parameterizable, and well documented. We use it to create a corpus similar to OSCAR but larger and based on recent data. Also, unlike OSCAR, the metadata information is at the document level. We release our pipeline under an open source license and publish the corpus under a research-only license.
A Re-Evaluation of the Swiss Hail Suppression Experiment using Permutation Techniques shows Enhancement of Hail Energies when Seeding

Grossversuch IV is a large and well documented experiment on hail suppression by silver iodide seeding. The original 1986 evaluation remained vague, although indicating a tendency to increase hail when seeding. The strategy to deal with distributions of hail energy far from normal was not optimal. The present re-evaluation sticks to the question asked and avoids both misleading transformations and unsatisfactory meteorological predictors. The raw data show an increase by about a factor of 3 for the hail energy when seeding. This is the opposite of what seeding is supposed to do. The probability to obtain such a result by chance is below 1%, calculated by permutation and bootstrap techniques applied on the raw data. Confidence intervals were approximated by bootstrapping as well as by a new method called "correlation imposed permutation" (CIP).
Architecture of the Genotype-Phenotype Map and the Coevolution of Complexity

The addition of parasites to a host population can drive an escalation in the host population’s phenotypic complexity – even in the absence of a direct ﬁtness advantage for this increase. Parasites restrict certain regions of the genotype space, decreasing the ﬁtness and the probability of survival of particular host phenotypes. While many artiﬁcial life frameworks model a direct correlation between genotype and ﬁt- ness, the structure of genotype-phenotype maps can have important effects on evolutionary dynamics. Using a simple coarse-grained model for phenotypic transitions during evolution, we show that the escalation in phenotypic complexity under neutral co-evolution is dependent on the structure of the genotype-phenotype map. We discuss these results using the metaphor of evolutionary spandrels and highlight how these structural considerations might allow us to capture biological phenomena more accurately.
The ExtremeX global climate model experiment: Investigating thermodynamic and dynamic processes contributing to weather and climate extremes

Abstract. The mechanisms leading to the occurrence of extreme weather and climate events are varied and complex. They generally encompass a combination of dynamical and thermodynamical processes, as well as drivers external to the climate system, such as anthropogenic greenhouse gas emissions and land-use change. Here we present the ExtremeX multi-model intercomparison experiment, which was designed to investigate the contribution of dynamic and thermodynamic processes to recent weather and climate extremes. The numerical experiments are performed with three Earth System Models: CESM, MIROC, and EC-Earth. They include control experiments with interactive atmosphere and land surface conditions, and experiments where either the atmospheric circulation, soil moisture or both are constrained using observation-based values. The temporal evolution and magnitude of temperature anomalies during heatwaves is well represented in the experiments with constrained atmosphere. However, mean climatological biases in temperature and precipitation are not substantially reduced in any of the constrained experiments, highlighting the importance of error compensations and tuning in the standard model versions. The results further reveal that both atmospheric circulation patterns and soil moisture conditions substantially contribute to the occurrence of heat extremes. Soil moisture effects are particularly important in the tropics, the monsoon areas and the Great Plains of the United States.
The Somali region in ethiopia: a neglected human rights tragedy

This article reviews Ethiopia's human rights record with a particular focus on the human rights situation in the Somali region. Attention is paid to the atrocities committed against civilians, specifically community and political leaders as well as members of the Somali State legislature. Furthermore, the 2000 famine is discussed as a human rights issue in the light of indications that this famine was deliberately choreographed. The article also explores human rights violations inflicted upon the Somali region's population following the discovery of natural gas and the denial of benefits thereof to the local community. In conclusion some future scenarios are examined to ascertain to what extent they might possibly change the prospects for the people in the Somali region.
Surface representation impacts on turbulent heat fluxes in the Weather Research and Forecasting (WRF) model (v.4.1.3)

The water and energy transfers at the interface between the Earth’s surface and the atmosphere should be correctly simulated in numerical weather and climate models. This implies the need for a realistic and accurate representation of land cover (LC), including appropriate parameters for each vegetation type. In some cases, the lack of information and crude representation of the surface lead to errors in the simulation of soil and atmospheric variables. This work investigates the ability of the Weather Research and Forecasting (WRF) model to simulate surface heat fluxes in a heterogeneous area of southern France using several possibilities for the surface representation. In the control experiments, we used the default LC database in WRF, which differed significantly from the actual LC. In addition, sub-grid variability was not taken into account since the model uses, by default, only the surface information from the dominant LC category in each pixel (dominant approach). To improve this surface simplification, we designed three new interconnected numerical experiments with three widely used land surface models (LSMs) in WRF. The first one consisted of using a more realistic and higher-resolution LC dataset over the area of analysis. The second experiment aimed at investigating the effect of using a mosaic approach; 30 m subgrid surface information was used to calculate the final grid fluxes based on weighted averages from values obtained for each LC category. Finally, in the third experiment, we increased the model stomatal conductance for conifer forests due to the large flux errors associated with this vegetation type in some LSMs. The simulations were evaluated with gridded area-averaged fluxes calculated from five tower measurements obtained during the Boundary-Layer Late Afternoon and Sunset Turbulence (BLLAST) field campaign. The results from the experiments differed depending on the LSM and displayed a high dependency of the simulated fluxes on the specific LC definition within the grid cell, an effect that was enhanced with the dominant approach. The simulation of the fluxes improved using the more realistic LC dataset except for the LSMs that included extreme surface parameters for coniferous forest. The mosaic approach produced fluxes more similar to reality and served to particularly improve the latent heat flux simulation of each grid cell. Therefore, our findings stress the need to include an accurate surface representation in the model, including soil and vegetation sub-grid information with updated surface parameters for some vegetation types, as well as seasonal and man-made changes. This will improve the modelled heat fluxes and ultimately yield more realistic atmospheric processes in the model. Published by Copernicus Publications on behalf of the European Geosciences Union. 3940 C. Román-Cascón et al.: Surface impacts on fluxes in WRF
Extreme floods in Europe: going beyond observations using reforecast ensemble pooling

Abstract. Assessing the rarity and magnitude of very extreme flood events occurring less than twice a century is challenging due to the lack of observations of such rare events. Here we develop a new approach, pooling reforecast ensemble members from the European Flood Awareness System (EFAS) to increase the sample size available to estimate the frequency of extreme local and regional flood events. We assess the added value of such pooling, determine where in Central Europe one might expect the most extreme events, and evaluate how event extremeness is related to physiographic and meteorological catchment characteristics. We work with a set of 234 catchments from the Global Runoff Data Center for which performance of simulated floods is satisfactory when compared to observed streamflow. We pool EFAS-simulated flood events for 10 perturbed ensemble members and lead times from 22 to 46 days, where flood events are only weakly dependent (< 0.25 average correlation across lead times). The resulting large ensemble (130 time series instead of one) enables analyses of very extreme events, which occur less than twice a century. We demonstrate that such ensemble pooling produces more robust estimates with considerably reduced uncertainty bounds (by ~80 % on average) than observation-based estimates but may equally introduce biases arising from the simulated meteorology and hydrological model. Our results show that specific flood return levels are highest in steep and wet regions and are comparably low in regions with strong flow regulation through dams. Furthermore, our pooled flood estimates indicate that the probability of regional flooding is higher in Central Europe and Great Britain than in Scandinavia. We conclude that reforecast ensemble pooling is an efficient approach to increase sample size and to derive robust local and regional flood estimates in regions with sufficient hydrological model performance.
Game Jam Natives?: The Rise of the Game Jam Era in Game Development Cultures

Game jams bring all kinds of creators together to make games from scratch in a relatively short time, often based on shared design constraints. The most influential game jam, Global Game Jam (GGJ) was established in 2009 as an annual event connecting game makers around the globe with shared theme and time-space. The growth of the GGJ indicates the establishment of game jam era: in ten years GGJ expanded from 1 600 to 47 000 participants and diverse set of other game jams are organized modelling GGJ or its online counterpart, Ludum Dare (LD). Even though many game jams are directed towards hobbyist creators or game development students, also professionals take part on these events. Game companies run their internal game jams for various reasons from experimentation and recreation to recruitment and education. Game jams are so widely spread, that they are destined to impact the game making cultures at large. In this paper, I am proposing that we live in the era of game jams and the generation of game makers that have started their development careers within this era are native to game jams.