Miracle-dz/UniFAR-FTUs huggingface dataset:
Economic growth or social expenditure: what is more effective in decreasing poverty and income inequality in the EU - a panel VAR approach

Are economic growth and social expenditure effective in decreasing poverty and income inequality in the European Union? We try to provide an answer to this ques - tion by using a Panel VAR model for the period from 2010 to 2019, using a sample of 28 European member states plus Norway and Iceland. We find that although both economic growth and social expenditure decrease poverty, economic growth is more effective at decreasing poverty than social expenditure. However, when it comes to income inequality, economic growth seems to increase it, while social expenditure seems to lower it.
The X-ray spectra of the extragalactic sources in the Einstein extended medium sensitivity survey

The X-ray energy distribution of a large sample of faint extragalactic X-ray sources is studied. Two independent methods are used to determine that the average spectral index for the sources is about 0.95. The intrinsic dispersion of the spectral index distribution is about 0.36. The sources are characterized by a range of power law slopes in the soft X-ray band with a mean of 1.03 + 0.05 or - 0.06 and an intrinsic dispersion of about 0.36. The present analysis extends knowledge of the AGN spectral properties to sources which are about three times more distant and more than 10 times fainter than those previously studied. There is no evidence in the data for any change in the mean spectral index of either extragalactic sources as a whole or AGN in particular, as a function of the X-ray flux in the flux range 10 to the -11th to 10 to the -13th ergs/sq cm/s. 22 references.
Post-COVID Syndrome in Adults—An Overview

This article provides an overview of various aspects related to post-COVID syndrome. Apart from its prevalence, symptoms and sequelae, risk determinants, and psychosocial implications, the pathogenesis of post-COVID condition is discussed in more detail. A focus on thrombo-inflammation in SARS-CoV-2 infection, the role of neutrophil extracellular traps, and the prevalence of venous thromboembolism is made. Moreover, COVID-19 and post-COVID syndrome in immunocompromising conditions, and the impact of vaccination on the prevention and treatment of post-COVID symptoms are reviewed. Autoimmunity is a hallmark of post-COVID syndrome, and, therefore, is another focus of this article. Thus, misdirected cellular and humoral immune responses can enhance the risk of latent autoimmunity in post-COVID syndrome. Facing the high prevalence of COVID-19 cases worldwide, it can be assumed that autoimmune disorders will increase globally over the next few years. Recent advances in identifying genetically determined variants may open the avenue for a better understanding of the susceptibility to and severity of SARS-CoV-2 infection and post-COVID syndrome.
Attention-Based Cross-Modal CNN Using Non-Disassembled Files for Malware Classification

The role of malware classification is crucial in addressing the explosive increase in malware variants. By classifying malware instances into malware families, malware analysts can apply appropriate techniques and tools to handle malware variants in each family. Using high-level representations of malware, such as disassembled codes, yields meaningful classification performance. However, malware classification based on disassembled codes depends on the practically implausible assumption that every malware is correctly reversed by disassemblers. Unfortunately, sophisticated malware, which has anti-disassembly capabilities, seeks to confuse disassemblers, yielding incorrectly disassembled codes. In this study, we focus on malware family classification, which requires no disassembly, and propose a new CNN-based malware classification model using non-disassembled malware files (i.e., binary files). Our model associates two modalities: “malware images” and “structural entropies,” which are converted and extracted from binary files. Both modalities have different granularities of bytes and chunks that complement each other. The model adopts a cross-modal attention mechanism to combine the features of the two modalities by moderating their expressive limitations. We validate our model using three popular datasets from the Kaggle Microsoft Malware Classification, Malimg, and BODMAS datasets. The experimental results show that our model identifies malware families with a higher degree of accuracy than previous methods and does not require the burden of disassembling.
SCMA: A Scattering Center Model Attack on CNN-SAR Target Recognition

Convolutional neural networks (CNNs) have been widely used in synthetic aperture radar (SAR) target recognition, which can extract feature automatically. However, due to its own structural flaws, CNNs are easy to be fooled by adversarial examples, even if they have excellent performance. In this letter, a novel attack named scattering center model attack (SCMA) is designed, and its generation process does not rely on the prior knowledge of any neural network. Therefore, we can get a stable way which can be applied to any neural network. In addition, an improved scattering center model extraction method, which is the pre-part of SCMA, can filter out the useless noise to optimize the stability of attack. In the experiment, SCMA is compared with advanced attack algorithms. From the experimental results, it is clear to find that SCMA has excellent performance in terms of transfer attack success rate. Furthermore, visualization and interpretability analysis underpin the theoretical feasibility of SCMA.
Tissue-specific assessment of oxidative status: Wild boar as a case study

In recent decades, there has been a fast-growing interest in using biomarkers of oxidative stress (BOS) in conservation programs of many vertebrate species. Biomarkers of oxidative stress can be measured in different biological samples (e.g., body fluids and tissues). However, since comparisons of the same battery of BOS among tissues of the same individual are scarce in the literature, the chosen target tissues regularly rely on arbitrary decisions. Our research aimed to determine if the oxidative status of free-ranging wild boar (Sus scrofa) naturally infected with Mycobacterium spp (etiological agent of tuberculosis, TB), varies depending on the sample where it was quantified. We compared antioxidant p-nitrophenyl esterase activity (EA), glutathione peroxidase (GPX) concentrations, and total oxidative status (TOS) in serum, lung, spleen, kidney, and muscle of 63 wild boar hunter-harvested in central Spain. Biomarkers of oxidative stress in serum had higher concentrations than in other tissues. The poor agreement between serum and other tissues highlights the importance of running complete BOS assessments in the same fluid or tissue. Further, low concentrations of BOS in tissues of TB-affected individuals were observed, and significant differences between healthy and sick boar were only detected in the serum of individuals developing mild TB and in the muscle of individuals with mild or severe disease status. However, all organs from wild boars affected with mild TB were not in oxidative imbalance compared to healthy control animals, suggesting that wild boars may cope well with TB. Our data indicate that serum and other tissues can be used as BOS in field conservation programs to monitor wildlife population health. Still, context-specific validations are needed to determine the most appropriate samples to use. Graphical Abstract This drawing represents the concept of oxidative stress resulting from an imbalance arising as a consequence of the rate of production of reactive oxygen species exceeding the capacity of the antioxidant defence and repair mechanisms. Oxidative stress then leads to subsequent oxidative damage to biomolecules, tissue dysfunction and disease. Our work is intended to explore how the choice of a biological sample (e.g., muscle, serum, organs) influences oxidative status assessment in wild boar naturally infected with tuberculosis.
Perceptual Substitution Based Haptic Texture Rendering for Narrow-Band Reproduction

Recorded high-resolution texture vibration contains perceptually redundant spectral information due to tactile limitations of human skin. Also, accurate reproduction of recorded texture vibration is often infeasible for widely available haptic reproduction systems at mobile devices. Usually, haptic actuators can only reproduce narrow-bandwidth vibration. With the exception of research setups, rendering strategies need to be developed, that utilize the limited capabilities of various actuator systems and tactile receptors while minimizing a negative impact on perceived quality of reproduction. Therefore, the aim of this study is to substitute recorded texture vibrations with perceptually sufficient simple vibrations. Accordingly, similarity of band-limited noise, single sinusoid and amplitude-modulated signals on display are rated compared to real textures. Considering that low and high frequency bands of noise signals might be implausible and redundant, different combinations of cut-off frequencies are applied to noise vibrations. Moreover, suitability of amplitude-modulation signals are tested for coarse textures in addition to single sinusoids because of their capability of creating pulse-like roughness sensation without too low frequencies. With the set of experiments, narrowest band noise vibration with frequencies between 90 Hz to 400 Hz is determined according to the fine textures. Furthermore, AM vibrations are found to be more congruent than single sinusoids to reproduce too coarse textures.
Gut Microbial Profile Changes in Patients with Gallbladder Stones after UDCA/CDCA Treatment

Background: Ursodeoxycholic acid (UDCA) and chenodeoxycholic acid (CDCA) are used to treat patients with asymptomatic or mildly symptomatic gallstone disease. This study was conducted to evaluate the efficacy of gallbladder (GB) stone dissolution by UDCA/CDCA and the impact of treatment on gut microbial profiles. Methods: Fifteen treatment-naive patients with GB stones were initially included, but two dropped out during the treatment period. UDCA/CDCA was administered for 6 months. Abdominal ultrasonography was performed to evaluate response to treatment. In addition, fecal samples were collected before and after treatment for gut microbiome profiling. Then, 16S ribosomal RNA gene sequencing was carried out on fecal samples obtained before and after treatment, and results were compared with those of forty healthy controls. Results: Eight (62%) of the thirteen evaluable patients treated with UDCA/CDCA responded to treatment (four achieved complete GB stone resolution and four partial dissolution). Taxonomic compositions of fecal samples at the phylum level showed a significantly lower relative abundance of the Proteobacteria phylum in the pre-UDCA/CDCA group than in the healthy control group (p = 0.024). At the genus level, the relative abundances of five bacteria (Faecalibacterium, Roseburia, Lachnospira, Streptococcus, and Alistipes) differed in the control and pre-UDCA/CDCA group. Interestingly, the abundance of Roseburia was restored after 6 months of UDCA/CDCA treatment. Conclusion: Gut microbial dysbiosis was observed in GB stone patients and partially reversed by UDCA/CDCA treatment, which also effectively dissolved GB stones.
Progressive Transitions from Algorithmic to Conceptual Understanding in Student Ability To Solve Chemistry Problems: A Lakatosian Interpretation.

The main objective of this study is to construct models based on strategies students use to solve chemistry problems and to show that these models form sequences of progressive transitions similar to what the history of science refers to as progressive “problemshifts” that increase the explanatory/heuristic power of the models. Results obtained show the considerable difference in student performance on chemistry problems (mol, gases, solutions, and photoelectric effect) that require algorithmic or conceptual understanding. The difference between student performance on algorithmic and conceptual problems can be interpreted as a process of progressive transitions (models) that facilitate different degrees of explanatory power to student conceptual understanding. A parallel is drawn between the methodology of idealization (simplifying assumptions) used by scientists and the construction of strategies (models) used by students to facilitate conceptual understanding. A major educational implication of this study is that the relationship between algorithmic and conceptual problems is not dichotomous, but rather characterized by a continuum that consists of sequences of models that facilitate greater conceptual understanding. This reconstruction of student strategies to solve problems (progressive transitions) can provide the teacher a framework to anticipate as to how student understanding could develop from being entirely algorithmic to conceptual. © 1995 John Wiley & Sons, Inc.
Compared effectiveness of sodium zirconium cyclosilicate and calcium polystyrene sulfonate on hyperkalemia in patients with chronic kidney disease

Hyperkalemia is a well-recognized electrolyte abnormality in patients with chronic kidney disease (CKD). Potassium binders are often used to prevent and treat hyperkalemia. However, few studies have evaluated the difference in serum potassium (K+) level-lowering effect during the post-acute phase between the novel potassium binder, sodium zirconium cyclosilicate (ZSC), and conventional agents. This retrospective study included patients who received potassium binders (either ZSC or calcium polystyrene sulfonate [CPS]) in our hospital between May 2020 and July 2022. The patients were divided into the ZSC and CPS groups. After propensity score matching, we compared changes from baseline to the first follow-up point, at least 4 weeks after initiating potassium binders, in electrolytes including K+ level between the two groups. Of the 132 patients, ZSC and CPS were administered in 48 and 84 patients, respectively. After matching, 38 patients were allocated to each group. The ZSC group showed greater reduction in K+ levels than did the CPS group (P < 0.05). Moreover, a significant increase in serum sodium minus chloride levels, a surrogate marker for metabolic acidosis, was observed in the ZSC group (P < 0.05). Our results demonstrated that ZSC could potentially improve hyperkalemia and metabolic acidosis in patients with CKD.
Grain‐Boundary Diffusion

The diffusion of nickel into grain boundaries of various tilt angles in copper bicrystals was studied. The concentration contours from the grain boundary and the lateral lattice diffusion were measured by means of electron‐probe microanalysis. The product of grain‐boundary width and diffusion coefficient were calculated, and comparisons were made with theoretical solutions. The grain‐boundary coefficient is concentration dependent above 3% nickel in a 45° tilt boundary. With lower tilt angles, the coefficient is concentration dependent above 0.5% nickel.
Formation Mechanisms and Source Apportionments of Nitrate Aerosols in a Megacity of Eastern China Based On Multiple Isotope Observations

Inorganic nitrate (NO3−) is a crucial component of fine particulate matter (PM2.5) in haze events in China. Understanding the formation mechanisms of nitrate and the sources of NOx was critical to control the air pollution. In this study, measurements of multiple isotope compositions of nitrate (δ18O‐NO3−, δ17O‐NO3−, and δ15N‐NO3−) in PM2.5 were conducted in Hangzhou from 9 October 2015 to 24 August 2016. Our results showed that oxygen anomaly of nitrate (Δ17O‐NO3−: 20.0‰–37.9‰) and nitrogen isotope of nitrate (δ15N‐NO3−: −2.9‰ to 18.1‰) values were higher in winter and lower in summer. Based on Δ17O‐NO3− observation and a Bayesian model, NO3 radical chemistry was found to dominate the nitrate formation in winter, while photochemical reaction (NO2 + OH) was the main pathway in summer. After considering the nitrogen isotopic fractionation in the NOx(g)‐NO3−(p) conversion, the average contributions of coal combustion, vehicle exhausts, biomass burning, and soil emission were 50% ± 9%, 19% ± 12%, 26% ± 15%, and 5% ± 4%, respectively, to nitrate aerosols during the whole sampling period. Coal combustion was the most important nitrate source in Hangzhou, especially in winter (∼56%). The contribution of soil emission increased significantly in summer due to active soil microbial processes under high temperature environment.
Energy-efficient and noise-tolerant neuromorphic computing based on memristors and domino logic

The growing scale and complexity of artificial intelligence (AI) models has prompted several new research efforts in the area of neuromorphic computing. A key aim of neuromorphic computing is to enable advanced AI algorithms to run on energy-constrained hardware. In this work, we propose a novel energy-efficient neuromorphic architecture based on memristors and domino logic. The design uses the delay of memristor RC circuits to represent synaptic computations and a simple binary neuron activation function. Synchronization schemes are proposed for communicating information between neural network layers, and a simple linear power model is developed to estimate the design’s energy efficiency for a particular network size. Results indicate that the proposed architecture can achieve 1.26 fJ per classification per synapse and achieves high accuracy on image classification even in the presence of large noise.
Well-to-wheel performance of internal combustion engine vehicles and electric vehicles – study for future Indian market

ABSTRACT Thanks to top-notch vehicle testing and internationally standardized inspections, the modes of transportation are cleaner and more efficient today. Though the development for conventional internal combustion engine vehicles (ICEVs) has almost saturated today, yet it retains the commercial/heavy-duty (trucks and buses) automobile market. Thus, it becomes of utmost importance to analyze the well-to-wheel efficiency for determining the overall energy consumption and greenhouse gas (GHG) emissions while transitioning toward sustainable transportation. Electric vehicles (EVs) do have environmental impacts that are directly related to the country’s electricity generation, as they may involve fossil burning where other alternative sources of energy are not adequately present. This paper presents the overall energy efficiencies and GHG emissions from commercial/heavy-duty ICEVs and EVs. The study also briefly compares the other vehicle segments like 2 Wheeler, 3 Wheeler, and cars. Finally, the results show that commercial/heavy-duty ICEVs are advantageous over heavy-duty EVs when the GHG emissions are considered as of today. The commercial/heavy-duty ICEVs emit over 405 g CO2e/km, and counter EVs produce 706 g CO2e/km. The GHG emissions from 2 Wheeler ICEV were 46 g CO2e/km and by the same segment, EV is 13 g CO2e/km. Moving toward the car segment, an ICEV car produces around 158 g CO2e/km and an EV of a similar model emits 67 g CO2e/km. Furthermore, the 3 Wheeler ICEV emits around 99 g CO2e/km and a 3 Wheeler EV produces lesser at 24 g CO2e/km. Moving further on well-to-wheel energy efficiency, ICEVs have a maximum overall energy efficiency of 28%. Since EVs use various sources of energy for charging the battery, the overall efficiency was found to be at least 21% and maximum up to 39%. Thus, on an average EVs presently have a well-to-wheel efficiency of 32% when electricity generation mix is used for charging.
Retinal blood vessel diameters in children and adults exposed to a simulated altitude of 3,000 m

Introduction: Technological advances have made high-altitude ski slopes easily accessible to skiers of all ages. However, research on the effects of hypoxia experienced during excursions to such altitudes on physiological systems, including the ocular system, in children is scarce. Retinal vessels are embryologically of the same origin as vessels in the brain, and have similar anatomical and physiological characteristics. Thus, any hypoxia-related changes in the morphology of the former may reflect the status of the latter. Objective: To compare the effect of one-day hypoxic exposure, equivalent to the elevation of high-altitude ski resorts in North America and Europe (∼3,000 m), on retinal vessel diameter between adults and children. Methods: 11 adults (age: 40.1 ± 4.1 years) and 8 children (age: 9.3 ± 1.3 years) took part in the study. They spent 3 days at the Olympic Sports Centre Planica (Slovenia; altitude: 940 m). During days 1 and 2 they were exposed to normoxia (FiO2 = 0.209), and day 3 to normobaric hypoxia (FiO2 = 0.162 ± 0.03). Digital high-resolution retinal fundus photographs were obtained in normoxia (Day 2) and hypoxia (Day 3). Central retinal arteriolar equivalent (CRAE) and venular equivalents (CRVE) were determined using an Automated Retinal Image Analyser. Results: Central retinal arteriolar and venular equivalents increased with hypoxia in children (central retinal arteriolar equivalent: 105.32 ± 7.72 µm, hypoxia: 110.13 ± 7.16 µm, central retinal venular equivalent: normoxia: 123.39 ± 8.34 µm, hypoxia: 130.11 ± 8.54 µm) and adults (central retinal arteriolar equivalent: normoxia: 105.35 ± 10.67 µm, hypoxia: 110.77 ± 8.36 µm; central retinal venular equivalent: normoxia: 126.89 ± 7.24 µm, hypoxia: 132.03 ± 9.72 µm), with no main effect of group or group*condition interaction. A main effect of condition on central retinal arteriolar and venular equivalents was observed (central retinal arteriolar equivalent:normoxia: 105.34 ± 9.30 µm, hypoxia: 110.50 ± 7.67 µm, p < 0.001; central retinal venular equivalent: normoxia: 125.41 ± 7.70 µm, hypoxia: 131.22 ± 9.05 µm, p < 0.001). Conclusion: A 20-hour hypoxic exposure significantly increased central retinal arteriolar and venular equivalents in adults and children. These hypoxia-induced increases were not significantly different between the age groups, confirming that vasomotor sensitivity of the retinal vessels to acute hypoxia is comparable between adults and prepubertal children.
Multivariate batch means and control variates

We consider applying the nonoverlapping batch means output analysis method in conjunction with the control-variate variance-reduction technique to estimate a steady-state multivariate mean vector. The effects of the number of batches and the number of control variates on the multivariate point and region estimators and the univariate point and interval estimators are considered. The results are experiment analysis guidelines in terms of an appropriate range of the number of batches to choose as a function of the number of responses and control variates. The results have implications for terminating simulations as well.
Extreme ultraviolet transitions of Fe XXI in solar, stellar and laboratory spectra

Recent R-matrix calculations of electron impact excitation rates for transitions among the 2s22p2, 2s2p3 and 2p4 levels of Fe xxi are used to derive theoretical electron density (Ne) sensitive emission-line ratios involving 2s22p2–2s2p3 transitions in the ∼98–146A wavelength range. A comparison of these with observations from the PLT tokamak plasma, for which the electron density has been independently determined, reveals generally very good agreement between theory and experiment, and in some instances removes discrepancies found previously. The observed Fe xxi ratios for a solar flare, obtained with the OSO–5 satellite, imply electron densities which are consistent, with discrepancies that do not exceed 0.2 dex. In addition, the derived values of Ne are similar to those estimated for the high-temperature regions of other solar flares. The good agreement between theory and observation, in particular for the tokamak spectra, provides experimental support for the accuracy of the present line-ratio calculations, and hence for the atomic data on which they are based.