Miracle-dz/UniFAR-FTUs huggingface dataset:
Anxiety, Depression, Insomnia and Stress during the COVID-19 Pandemic: Prevalence and risk according to associated experiences in the general population

Introduction: COVID-19 mortality in Peru is high and its impact on the mental health of the adult population is a significant problem. This study aims to identify the prevalence of and risk for anxiety, depression, insomnia, and stress in the general population in terms of associated experiences during the COVID-19-pandemic. Methods: An observational and cross-sectional study was conducted through an online survey completed by 880 people from two Peruvian cities (Lima and Huaraz). The Depression, Anxiety and Stress Scale 21 (DASS-21) and the Athens Insomnia Scale were used. Results: Prevalence rates of 34.4% for anxiety, 20.7% for depression, 36.8% for insomnia and 12.8% for stress were found. In terms of associated experiences: fear of COVID-19 infection was a risk factor for insomnia, depression, anxiety, and stress; contact with COVID-19 cases was a risk factor for insomnia, anxiety, and stress; death of households from COVID-19 was the highest risk factor for insomnia (OR=12.26) and stress (OR=7). Households testing positive for COVID-19 was a risk factor for anxiety and stress and testing positive for COVID-19 was a risk factor for anxiety. There is a significant relationship among the mental health variables under study. Conclusions: The prevalence and identification of pandemic-associated experiences as risk factors for anxiety, depression, insomnia, and stress in the COVID-19 pandemic allows for the designing of mental health intervention and prevention programs aimed at the general population. There is a direct relationship among anxiety, depression, insomnia, and stress during the COVID-19 pandemic.
Spectral gap lower bound for the one-dimensional fractional Schr\

We prove the uniform lower bound for the difference $\lambda_2 - \lambda_1$ between first two eigenvalues of the fractional Schr\"odinger operator, which is related to the Feynman-Kac semigroup of the symmetric $\alpha$-stable process killed upon leaving open interval $(a,b) \in \R $ with symmetric differentiable single-well potential $V$ in the interval $(a,b)$, $\alpha \in (1,2)$. "Uniform" means that the positive constant appearing in our estimate $\lambda_2 - \lambda_1 \geq C_{\alpha} (b-a)^{-\alpha}$ is independent of the potential $V$. In general case of $\alpha \in (0,2)$, we also find uniform lower bound for the difference $\lambda_{*} - \lambda_1$, where $\lambda_{*}$ denotes the smallest eigenvalue related to the antisymmetric eigenfunction $\phi_{*}$. We discuss some properties of the corresponding ground state eigenfunction $\phi_1$. In particular, we show that it is symmetric and unimodal in the interval $(a,b)$. One of our key argument used in proving the spectral gap lower bound is some integral inequality which is known to be a consequence of the Garsia-Rodemich-Rumsey-Lemma.
Spatial equity and healthcare access in the COVID-19 pandemic

Healthcare facilities around the world become overwhelmed by the number of infected coronavirus patients that needed to be treated during the COVID-19 outbreak, resulting in medical staff and healthcare services shortages. Regarding to understand and minimize the inequalities in healthcare services, it is crucial to evaluate the available healthcare resource, particularly the intensive care unit (ICU) beds that are critical for the COVID-19 pandemic. Therefore, this study aims to explore and determine the spatial distribution of the confirmed COVID-19 patients and the healthcare capacities in the province of Ubon Ratchathani, Thailand. Applying the GIS platform with the data analysis of 2SFCA (Two-Step Floating Catchment Area) based approach, we emphasize the spatial distribution of both patients and healthcare resources in the study area. The spatial accessibility index regarding the physicians and ICU beds was determined and highlighted in each district. Additionally, the vulnerable regions were identified by the level of healthcare accessibility. We believe this study offers valuable insight in gaining a better understanding and supporting effective response activities toward pandemic resilience.
Dual-Energy Spectral Computed Tomography: Comparing True and Virtual Non Contrast Enhanced Images

Abstract Spectral computed tomography (CT) imaging is one of several image reconstruction techniques based on the use of dual-layer CT. The intensity and attenuation of the radiation are measured in relation to different wavelengths, and such a procedure results in complex three-dimensional (3D) imaging and (pseudo) color adjustment of the soft tissue. This paper compares true non-contrast (TNC) enhanced images with virtual non-contrast (VNC) enhanced ones. Virtual native images are acquired by means of spectral computed tomography, and it has been suggested that VNCs could potentially substitute real native images to reduce significantly the total radiation dose from multiphase spectral CT. A comparison was performed by defining certain parameters that represent the difference between the measured and the calculated values in the images. The parameters included the mean value and standard deviation of the computed tomography number, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). All of these items were analyzed via statistical tests using p-value. The results are interpreted and correlated with those presented by other authors, who, however, did not make an examination on a comprehensive basis - five tissues simultaneously by using a single device. Prospectively, if analogies were found between the two types of images, it would be possible to skip the TNC image, thus markedly reducing the radiation dose for the patient.
Frequency magnitude distribution and spatial correlation dimension of earthquakes in north-east Himalaya and adjacent regions

Abstract The north-east sector of the Himalaya is one of the most active tectonic belts, with complex geological and tectonic features. The b-value and spatial correlation dimension (Dc) of earthquake distribution in the north-east Himalaya and its adjacent regions (20–32°N and 88–98°E) are estimated in the present study. Based on seismicity and faulting pattern, the region is divided into five active regions, namely the (i) South-Tibet, (ii) Eastern-Syntaxis, (iii) Himalayan-Frontal Arc, (iv) Arakan-Yoma belt and (v) Shillong-Plateau. A homogeneous catalogue of 1,416 earthquakes (mb ≥ 4.5) has been prepared from a revised catalogue of the ISC (International Seismological Centre). The b-value has been appraised by the maximum likelihood estimation method, while Dc values have been calculated by the correlation integral method; b-values of 1.08 ± 0.09, 1.13 ± 0.05, 0.92 ± 0.05, 1.00 ± 0.03 and 0.98 ± 0.08 have been computed for the South-Tibet, Eastern-Syntaxis, Himalayan-Frontal Arc, Arakan-Yoma belt and Shillong-Plateau region, respectively. The Dc values computed for the respective regions are 1.36 ± 0.02, 1.74 ± 0.04, 1.57 ± 0.01, 1.8 ± 0.01, and 1.83 ± 0.02. These values are > 1.5, except for the South-Tibet (1.36 ± 0.02). The b-values around the global average value (1.0) reflect the stress level and seismic activity of the regions, while high Dc values refer to the heterogeneity of the seismogenic sources.
Precision electroweak analysis after the Higgs boson discovery

Until recently precision electroweak computations were fundamentally uncertain due to lack of knowledge about the existence of the Standard Model Higgs boson and its mass. For this reason substantial calculational machinery had to be carried along for each calculation that changed the Higgs boson mass and other parameters of the Standard Model. Now that the Higgs boson is discovered and its mass is known to within a percent, we are able to compute reliable semi-analytic expansions of electroweak observables. We present results of those computations in the form of expansion formulae. In addition to the convenience of having these expressions, we show how the approach makes investigating new physics contributions to precision electroweak observables much easier.
Indian and Chinese Metal Futures Markets: A Linkage Analysis

Abstract This paper aims to test the long-run and short-run relationships between the Indian and Chinese metal futures markets using the weekly closing prices of three nonferrous metals, that is, copper, aluminium, and zinc, for the period of 2009–2020. The empirical results show no cointegration for any of the three metals. The Granger causality test suggests a unidirectional relationship from India to China for copper futures and bidirectional causality for aluminium and zinc futures markets. This paper contributes to the literature by studying the relationship between the mentioned two emerging markets, which are top producers and consumers in commodities and have growing futures markets. The results have important implications for investors, portfolio makers, and policymakers of emerging economies.
Growth patterns and condition factor of the mudskipper (Periophthalmus gracilis) in mangrove ecosystem rehabilitation areas in Banda Aceh and Aceh Besar, Indonesia

Abstract The mudskipper is one of the fishes that inhabit mangrove ecosystems. Its growth and distribution is influenced by food sources, tidal action, and environmental factors. The aims of the research were to analyze the growth patterns and condition factors of the mudskipper, Periophthalmus gracilis Eggert, inhabiting mangrove ecosystem rehabilitation areas in Banda Aceh and Aceh Besar, Aceh Province, Indonesia. The research period in these mangrove ecosystems was from August to October 2020. The research was conducted at three sampling stations using the purposive sampling method to determine their location. The mudskippers caught at each station were identified and body length and weight were measured. Physicochemical water parameters were measured directly at the sampling stations to determine the suitability of them for mudskipper growth and occurrence. The mean total lengths (TL) and weights (W) of the mudskipper specimens caught at stations 1, 2, and 3 were 52.0 mm and 6.2 g; 53.5 mm and 6.4 g, and 56.0 mm 6.7 g, respectively. The growth patterns of the mudskippers from the three sampling stations were negative (b < 3), and Fulton’s condition factor (K) exceeded 1. The K value at stations 1, 2, and 3 ranged from 1.28 to 3.62, 1.15 to 3.56, and 1.05 to 3.89, respectively. The relative weights (Wr) at the three stations were 103.8 ± 26.5, 104.3 ± 29.3, and 104.1 ± 28.2, respectively. Wr >100 indicated that there was sufficient food availability, low predator density, and the environment was in equilibrium. Furthermore, physicochemical water parameters at the study stations were suitable and within optimal ranges for the mudskipper. Significant differences in total length were noted among specimens from the three stations (P < 0.05); however, no significant differences in body weight were noted at them (P > 0.05).
The contribution of young core-collapse supernova remnants to the X-ray emission near quiescent supermassive black holes

Appreciable star formation, and, therefore, numerous massive stars, are frequently found near supermassive black holes (SMBHs). As a result, core-collapse supernovae in these regions should also be expected. In this paper, we consider the observational consequences of predicting the fate of supernova remnants (SNRs) in the sphere of influence of quiescent SMBHs. We present these results in the context of `autarkic' nuclei, a model that describes quiescent nuclei as steady-state and self-sufficient environments where the SMBH accretes stellar winds with no appreciable inflow of material from beyond the sphere of influence. These regions have properties such as gas density that scale with the mass of the SMBH. Using predictions of the X-ray lifetimes of SNRs originating in the sphere of influence, we make estimates of the number of core collapse SNRs present at a given time. With the knowledge of lifetimes of SNRs and their association with young stars, we predict a number of core-collapse SNRs that grows from ~1 around Milky Way-like (4.3 x 10^6 Msun) SMBHs to ~100 around the highest mass (10^10 Msun) SMBHs. The presence of young SNRs will amplify the X-ray emission near quiescent SMBHs, and we show that the total core-collapse SNR emission has the potential to influence soft X-ray searches for very low-luminosity SMBHs. Our SNR lifetime estimates also allow us to predict star formation rates in these regions. Assuming a steady-state replenishment of massive stars, we estimate a star formation rate density of 2 x 10^-4 Msun/yr/pc^2 around the Milky Way SMBH, and a similar value around other SMBHs due to a weak dependence on SMBH mass. This value is consistent with currently available observations.
Indirect detection of self-interacting asymmetric dark matter

Self-interacting dark matter resolves the issue of cuspy profiles that appear in non-interacting cold dark matter simluations; it may additionally resolve the so-called "too big to fail" problem in structure formation. Asymmetric dark matter provides a natural explanation of the comparable densities of baryonic matter and dark matter. In this paper, we discuss unique indirect detection signals produced by a minimal model of self-interacting asymmetric scalar dark matter. Through the formation of dark matter bound states, a dark force mediator particle may be emitted; the decay of this particle may produce an observable signal. We estimate the produced signal and explicitly demonstrate parameters for which the signal exceeds current observations.
Flow barriers: What prevents software developers from experiencing flow in their work

Software development requires high problem-solving skills and creativity, making it a profession with good opportunities to become immersed in a flow experience. The characteristics of flow experience are absorption, enjoyment, and intrinsic motivation toward the activity. This study aims to better understand the barriers that prevent software developers from experiencing flow at work. Previous research has mostly examined software developers’ productivity, flow being one component of productive workdays. This study addresses the research gap by exploring the barriers to experiencing flow in software development. A qualitative questionnaire was used to gather data about flow experiences from 405 respondents. The most prominent flow barriers that emerged from these responses were interruptions , too easy, boring, or repetitive tasks , lack of opportunities , insufficient requirements , timetables and deadlines , and problems with technology or software . The results suggest that there are many more flow barriers in software development than what have been discussed in the context of productivity. These findings open up an interesting avenue for researching flow experiences in the software development context. The implication for practice is uncovering common flow barriers in software development, which can help both developers and managers identify these barriers, try to mitigate them, and facilitate more flow experiences at work.
Study of LINER sources with broad Hα emission - Spectral energy distribution and multiwavelength correlations

(Abridged) We attempt to infer the accretion mechanism and radiative processes giving rise to the SEDs of a well-defined optically-selected sample of LINERs showing a definite detection of broad Halpha emission (LINER 1s). We construct SEDs for six LINER~1s with simultaneous UV and X-ray fluxes, and we looked for multiwavelength, radio to X-ray and UV to X-ray, correlations. At a given X-ray luminosity, the average SED of the six LINER 1s in our sample: (1) resembles the SED of radio-loud quasars in the radio band, ~-2.7, (2) exhibits a weak UV bump, ~-1.17+-0.02 with a dispersion sigma=0.01, and (3) displays a X-ray spectrum similar to radio-quiet quasars. The bolometric luminosities inferred from the SEDs are extremely faint, at least two orders of magnitude lower than AGN. The X-ray bolometric correction, kappa_(2-10 keV), of our sample is lower than in the case of AGN, with a mean value of 16. We find a strong anticorrelation between the radio loudness parameter, R_X, and the Eddington ratio for our sample, confirming previous results. Moreover, we find a positive correlation between the radio luminosity and the X-ray luminosity which places AGN-powered LINERs, on a radio-power scale, right between low luminosity Seyferts and low luminosity radio galaxies. We complement our alpha_ox list with values derived on a well defined sample of UV-variable LINERs, and establish a strong positive correlation between alpha_ox (considering negative values) and the Eddington ratio, in contrast to the correlation found for luminous AGN. Lastly, we tested two different fundamental planes existing in the literature on our sample, in an attempt to put constraints on the debated origin of the X-ray emission, "RIAF versus jet". The results came contradictory with one pointing toward a RIAF-dominated X-ray emission process and the other pointing toward a jet domination.
Polynomial Asymptotic Estimates of Gegenbauer, Laguerre, and Jacobi Polynomials

We discuss asymptotic forms of CJ( x ), L~( x), P~0t,/3) ( x ), the Gegenbauer, Laguerre and Jacobi polynomials. The asymptotic behavior of these classical orthogonal polynomials has been the subject of several investigations. The research usually concentrates on the case that the degree n of the polynomial is the large parameter, and for all classical orthogonal polynomials the asymptotic behavior is well established now. Inside the domain of the zeros of the polynomial the behavior can be described in terms of elementary functions, such as trigonometric functions. In the domain where the transition from oscillatory to monotonic behavior occurs, familiar higher transcendental functions can be used as estimates. For example, the "first" zeros of the Jacobi polynomial can be approximated in terms of the zeros of the J Bessel function. In SzEGO ( 1958) several classical results can be found. For Jacobi polynomials he gives an estimate of
Employment Agglomerations and Spatial Mismatch in the Metropolitan Area of Bogota

This paper examines the wage premium of being located inside the Central Business Centre (CBD) or employment sub-centres in the metropolitan area of Bogota. Then, following literature on spatial mismatching, analyses potential impacts of agglomerations on social and productive exclusion. The core argument is that socially or productively excluded groups in Bogota do not benefit from positive externalities arising from agglomerations because they face multiple spatial barriers that prevent their effective access. Based on spatial statistics and estimations, I find an elasticity or ‘wage premium’ close to 6% and huge disparities between UPZs and municipalities in the metropolitan area of Bogota. This means, CBD and employment sub-centres in Bogota work as exclusive locations. Consequently, policies should be focused on increasing strategic accessibility through housing, transport, economic development through land-use regulations and institutional arrangements.
The Impact of Job Stress, Role Ambiguity and Work–Life Imbalance on Turnover Intention during COVID-19: A Case Study of Frontline Health Workers in Saudi Arabia

The main objective of the present study is to examine the impact of job stress, role ambiguity, work–life imbalance and burnout on employee turnover intention. Moreover, the mediating role of burnout between job stress, role ambiguity, work–life imbalance and turnover intention is also examined. The data collection for this quantitative research was conducted through the “Questionnaire” technique. The questionnaire was developed based on previously established questions available in the literature. The data were collected using simple random sampling from the healthcare workers of KSA. From the distributed questionnaire, 73.5% of the usable questionnaires were returned. This study used SPSS and PLS for the analysis of the data to highlight the most significant variables that impact the employees’ turnover intentions among KSA health workers. The findings show that job burnout is clearly related to turnover intentions and is positively affected by both role stress and role ambiguity. Moreover, a statistically positive association is found between work–life imbalance and burnout among the healthcare workers in KSA. Furthermore, the mediating role of burnout is also confirmed in this study. The study also indicates that role ambiguity and role stress due to COVID-19 may create burnout among employees, which may lead to turnover intention among healthcare workers. There is a lack of research on the assessment of the impact of the novel COVID-19-related job stress, role ambiguity and work–life imbalance on the medical staff’s turnover intentions in hospitals. This study fills the gap of the limited studies conducted regarding the identification of the factors that can create turnover intention among healthcare workers of KSA by providing empirical evidence from a Gulf country, Saudi Arabia. This study provides managerial implications for hospital management and health policymakers to develop a strategy to retain the employees. Furthermore, healthcare administrators need to pay close attention to front line workers’ turnover intentions as these medical heroes are the vital part of our society who assist patients to receive their initial treatment during the COVID-19 pandemic.
Pruning the Communication Bandwidth between Reinforcement Learning Agents through Causal Inference: An Innovative Approach to Designing a Smart Grid Power System

Electricity demands are increasing significantly and the traditional power grid system is facing huge challenges. As the desired next-generation power grid system, smart grid can provide secure and reliable power generation, and consumption, and can also realize the system’s coordinated and intelligent power distribution. Coordinating grid power distribution usually requires mutual communication between power distributors to accomplish coordination. However, the power network is complex, the network nodes are far apart, and the communication bandwidth is often expensive. Therefore, how to reduce the communication bandwidth in the cooperative power distribution process task is crucially important. One way to tackle this problem is to build mechanisms to selectively send out communications, which allow distributors to send information at certain moments and key states. The distributors in the power grid are modeled as reinforcement learning agents, and the communication bandwidth in the power grid can be reduced by optimizing the communication frequency between agents. Therefore, in this paper, we propose a model for deciding whether to communicate based on the causal inference method, Causal Inference Communication Model (CICM). CICM regards whether to communicate as a binary intervention variable, and determines which intervention is more effective by estimating the individual treatment effect (ITE). It offers the optimal communication strategy about whether to send information while ensuring task completion. This method effectively reduces the communication frequency between grid distributors, and at the same time maximizes the power distribution effect. In addition, we test the method in StarCraft II and 3D environment habitation experiments, which fully proves the effectiveness of the method.