Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of Galaxy Clusters on the Propagation of Ultrahigh-energy Cosmic Rays

Galaxy clusters are the largest objects in the Universe kept together by gravity. Most of their baryonic content is made of a magnetized diffuse plasma. We investigate the impact of such a magnetized environment on the propagation of ultrahigh-energy cosmic rays (UHECRs). The intracluster medium (ICM) is described according to the self-similar assumption, in which gas density and pressure profiles are fully determined by the cluster mass and redshift. The magnetic field is scaled to the thermal components of the ICM under different assumptions. We model the propagation of UHECRs in the ICM using a modified version of the Monte Carlo code SimProp, where hadronic processes and diffusion in the turbulent magnetic field are implemented. We provide a universal parameterization that approximates the UHECR fluxes escaping from the environment as a function of the most relevant quantities, such as the mass of the cluster, the position of the source with respect to the center of the cluster, and the nature of the accelerated particles. We show that galaxy clusters are an opaque environment, especially for UHECR nuclei. The role of the most massive nearby clusters in the context of the emerging UHECR astronomy is finally discussed.
Analysis of the Values and Meaning of the Kulisusu Ethnic Traditional Weaving Fabric Craft Motifs

The purposes of this research were (1) to analyze the process of making Kulisusu ethnic woven fabrics (2) to analyze the meaning of the motifs contained in the traditional Kulisusu ethnic woven crafts (3) to analyze the educational values contained in the traditional Kulisusu ethnic woven crafts. This research is a qualitative research and uses a descriptive approach. Data collection is carried out using observation, interviews, and documentation. The results showed that the process of making Kulisusu ethnic woven fabric crafts consisted of 9 stages, namely 1) materials; 2) tools 3) traditional rituals 4) drawing motifs: 5) spinning threads; 6) sorting yarn (pouluri); 7) Arranging yarn (Lopo); 8) tying the motifs on the warp; and 9) weaving (Mohoru). The meaning of the motif contained in the woven fabric of the Kulisusu ethnicity is the vertical motif which means the relationship between humans and the God; horizontal motifs that are meaningful about human relationships with other humans; and natural motifs that are meaningful about the relationship between humans and nature. The educational values contained in the traditional weaving crafts of the Kulisusu ethnicity are religious values, honest values, love for the motherland, social care values and responsibility values.
Lift force on spherical nanoparticles in shear flows of rarefied binary gas mixtures

In this work, we study the lift force on spherical nanoparticles suspended in a shear flow of rarefied binary gas mixtures. Analytical formulae are developed using the gas kinetic theory by considering non-rigid-body intermolecular interactions between the particle and gas molecules. It has been shown that the lift force formulae can be reduced to those in pure gases. It is also found that the direction of the lift force on nanoparticles in binary gas mixtures can be changed by varying the temperature, gas–particle interaction and/or gas concentrations.
Model-based x-ray energy spectrum estimation algorithm from CT scanning data with spectrum filter

With the development of technology, the traditional X-ray CT can’t meet the modern medical and industry needs for component distinguish and identification. This is due to the inconsistency of X-ray imaging system and reconstruction algorithm. In the current CT systems, X-ray spectrum produced by X-ray source is continuous in energy range determined by tube voltage and energy filter, and the attenuation coefficient of object is varied with the X-ray energy. So the distribution of X-ray energy spectrum plays an important role for beam-hardening correction, dual energy CT image reconstruction or dose calculation. However, due to high ill-condition and ill-posed feature of system equations of transmission measurement data, statistical fluctuations of X ray quantum and noise pollution, it is very hard to get stable and accurate spectrum estimation using existing methods. In this paper, a model-based X-ray energy spectrum estimation method from CT scanning data with energy spectrum filter is proposed. First, transmission measurement data were accurately acquired by CT scan and measurement using phantoms with different energy spectrum filter. Second, a physical meaningful X-ray tube spectrum model was established with weighted gaussian functions and priori information such as continuity of bremsstrahlung and specificity of characteristic emission and estimation information of average attenuation coefficient. The parameter in model was optimized to get the best estimation result for filtered spectrum. Finally, the original energy spectrum was reconstructed from filtered spectrum estimation with filter priori information. Experimental results demonstrate that the stability and accuracy of X ray energy spectrum estimation using the proposed method are improved significantly.
Spatial domain indirect holographic technique for antenna near‐field phaseless measurements

A spatial domain formulation of an indirect holographic technique, useful for antenna near‐field phase retrieval, is presented in this paper. The proposed approach is based on the adoption of three synthetic reference signals, giving three sets of amplitude‐only near‐field data. These are directly processed in the spatial domain to accurately retrieve the near‐field phase, from which the antenna radiation features can be subsequently computed. Despite the standard indirect holographic approach, no data processing is required in the spectral (Fourier transform) domain, thus completely avoiding the problem of spectrum overlapping which limits the accuracy of standard method. The effectiveness of the proposed technique is demonstrated by a numerical test on a linear dipole array, as well as by experimental results on a ridged‐horn antenna.
License to Layoff? Unemployment Insurance and the Moral Cost of Layoffs

This study presents moral cost as a novel behavioral constraint on firm resource adjustment, specifically layoff decisions that can cause severe harm to employees. Revising the prevailing negative view of managers as purely self-interested, we propose that managers care about their employees and incur moral cost from layoffs. We leverage expansions in unemployment insurance as a quasi-natural experiment that reduces economic hardship for laid-off workers and, in turn, the moral cost of layoffs to managers. We find that these expansions license larger layoffs. The effects are stronger for chief executive officers (CEOs) with stronger prosocial preferences who dismiss fewer workers despite low performance, such as non-Republican, internally promoted, small town, or family firm CEOs, and weaker for CEOs who lack the discretion to avoid moral cost due to shareholder or financial pressures. Our findings suggest that the role of moral cost is substantial but also highly heterogeneous and readily suppressed by external pressures. Supplemental Material: The online appendices are available at https://doi.org/10.1287/orsc.2022. 16734 .
Bayesian Flaw Characterization from Eddy Current Measurements with Grain Noise

The Bayesian approach to inference from measurement data has the potential to provide highly reliable characterizations of flaw geometry by quantifying the confidence in the estimate results. The accuracy of these confidence estimates depends on the accuracy of the model for the measurement error. Eddy current measurements of electrically anisotropic metals, such as titanium, exhibit a phenomenon called grain noise in which the measurement error is spatially correlated even with no flaw present. We show that the most commonly used statistical model for the measurement error, which fails to account for this correlation, results in overconfidence in the flaw geometry estimates from eddy current data, thereby reducing the effectiveness of the Bayesian approach. We then describe a method of modeling the grain noise as a Gaussian process (GP) using spectral mixture kernels, a type of non-parametric model for the covariance kernel of a GP This provides a broadly applicable, data-driven way of modeling correlati.
Jet Energy Scale Corrections and their Impact on Measurements of the Top-Quark Mass at CMS

The final state of many physics processes at the Large Hadron Collider (LHC) is dominated by jets, the experimental signature of quarks and gluons. The precise measurement of jets is a prerequisite to understand these processes. In this thesis, the determination of jet-energy corrections at CMS using dijet events is described, and the investigation of a correction specifically tailored to improve the reconstruction of b-jets in top-quark mass measurements is presented. Dijet events are used to determine the response relative to the central detector region in data and simulation as a function of the pseudorapidity η. Two complementary response estimators are introduced and detailed supplementary studies, e.g. of the time stability of the response, are performed. For the 2011 data-taking period, the MC/Data differences are found to be below 5% in the tracker-covered detector region with systematic uncertainties of less than 1%. Furthermore, a study of b-jet properties in 2012 data is presented. The correlation of various such observables with the response is exploited to improve the jet-energy measurement of b-jets. A resolution improvement of about 10% can be achieved, and the evaluation of b-jet specific jet-energy scale uncertainties (b-JES) indicates improvements of about 30%. This additional correction is applied to an existing measurement of the top-quark mass in the muon+jets channel. It leads to a statistical sensitivity improvement of about 10% and a reduction of systematic uncertainties related to the b-JES from 0.6 GeV to 0.3 GeV.
Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching

A popular distribution for the modelling of discrete count data is the Poisson distribution. However, count data usually exhibit over dispersion or under dispersion when modelled by a Poisson distribution in empirical modelling. The presence of excess zeros is also closely related to over dispersion. Two new mixed Poisson distributions, namely a three-parameter Poisson-exponentiated Weibull distribution and a fourparameter generalized Sichel distribution is introduced to model over dispersed, zeroinflated and long-tailed count data. Some of the theoretical properties of the distributions are derived and the distributions' characteristics are studied. A Monte Carlo simulation technique is examined and employed to overcome the computational issues arising from the intractability of the probability mass function of some mixed Poisson distributions. For parameter estimation, the simulated annealing global optimization routine and an EM-algorithm type approach for maximum likelihood estimation are studied. Examples are provided to compare the proposed distributions with several other existing mixed Poisson models. Another approach to modelling count data is by examining the relationship between the counts of number of events which has occurred up to a fixed time t and the inter-arrival times between the events in a renewal process. A family of count distributions, which is able to model under- and over dispersion, is presented by considering the inverse Gaussian distribution, the convolution of two gamma distributions and a finite mixture of exponential distributions as the distribution of the inter-arrival times. The probability function of the counts is often complicated thus a method using numerical Laplace transform inversion for computing the probabilities and the renewal function is proposed. Parameter estimation with maximum likelihood estimation is considered with applications of the count distributions to under dispersed and over dispersed count data from the literature.
Effects of resveratrol in an animal model of osteoporosis: a meta-analysis of preclinical evidence

Background Resveratrol is a natural polyphenol compound that is widely present in herbal medicines such as Reynoutria japonica Houtt. , Veratrum nigrum L. , and Catsiatora Linn and is used in traditional Chinese medicine to treat metabolic bone deseases. Animal experiments have shown that resveratrol may have a strong treatment effect against osteoporosis (OP). The purpose of this study was to explore the efficacy of resveratrol in treating OP animal models based on preclinical research data. Methods This study was completed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We searched the PubMed, Embase, Cochrane Library, and China National Knowledge Infrastructure (CNKI) databases from inception to May 8, 2023, to identify animal experiments on the treatment of OP with resveratrol. The effect sizes of bone mineral density (BMD), parameters of micro-CT, serum calcium, phosphorus, alkaline phosphatase (ALP) and osteocalcin were expressed as the mean differences (MDs) and 95% confidence intervals (CIs). RevMan 5.4 software was used for data analysis. Results This meta-analysis included a total of 15 animal experiments, including 438 OP rats. The meta-analysis results showed that compared with the control group, resveratrol (<10, 10–25, 40–50, ≥ 60 mg/kg/day) significantly increased femoral and lumbar bone mineral density (BMD) in OP rats (p < 0.05). Resveratrol (<10 mg/kg/day) significantly increased the BMD of the total body (MD = 0.01, 95% CI: 0.01 to 0.01, p < 0.001). In terms of improving the parameters related to micro-CT, resveratrol (40–50 mg/kg/day) can increase trabecular thickness and trabecular number and reduce trabecular spacing (p < 0.05). Compared with the control group, resveratrol can reduce the concentration of calcium and phosphorus in serum but has no significant effect on serum ALP and osteocalcin (p > 0.05). The results of subgroup analysis showed that resveratrol increased the whole-body BMD of SD rats (p = 0.002) but did not improve the whole-body BMD of 3-month-old rats (p = 0.17). Conclusion Resveratrol can increase BMD in OP rat models, and its mechanism of action may be related to improving bone microstructure and regulating calcium and phosphorus metabolism. The clinical efficacy of resveratrol in the treatment of OP deserves further research.
Mental simulation of future possibilities: Preparing for action or protecting the self?

In this paper, we propose a dual-motive theory of how future possibilities are typically simulated and evaluated. According to this framework, people attempt to strike a balance between preparing for action (approach-based expansion) and protecting the self against threat (avoidance-based narrowing), in which the main function of future thinking is to prepare the person for action. As suggestive empirical basis, we review selected findings from psychology and social science—including cognitive sampling of alternative possibilities, prediction, planning, moral judgment, experienced and anticipated emotion, and mental health research. Across these diverse domains, approach-based expansion can lead to agentic optimism, constructing a wide space of positive possibilities to pursue and choose from, whereas avoidance-based narrowing can lead to defensive pessimism, reducing the attentional perspective to a risk-minimizing exit strategy. The overarching goal with proposing this simplified framework is to help organize research on possibility-generation through a motivational lens, focusing on context-dependent changes in the two modes of prospective motivation: approach-based expansion versus avoidance-based narrowing. Hopefully, the proposed dual-motive framework can serve as a guide for new directions in future research, exploring how alternative possibilities are created, realized, and sometimes neglected in human life.
A fast pyramid matching algorithm for infrared object detection based on region covariance descriptor

In order to achieve the purpose of infrared object detection, two phases are essential, including feature selection and matching strategy. Good Features should be discriminative, robust and easy to compute. The matching strategy affects the accuracy and efficiency of matching. In the first stage, instead of the joint distribution of the image statistics, we use region covariance descriptor and calculate region covariance using integral images. The idea presented here is more general than the image sums or histograms, which were already published before. In the second feature matching stage, we describe a new and fast pyramid matching algorithm under the distance metric, which performed extremely rapidly than a brute force search. We represent an object with five covariance matrices of the image features computed inside the object region. Instead of brute force matching, we constructed the image pyramid and decomposed the source image and object image into several levels, which included different image resolutions. After the completion of coarse match, fine-match is essential. The performance of region covariance descriptor is superior to other methods, and the pyramid matching algorithm performs extremely rapidly and accurately, as it is shown, and the large rotations and illumination changes are also absorbed by the covariance matrix.
Mathematical Programming Representation for Approximate Representation of Flow Lines

Mathematical programming representation has been recently used to describe the behavior of discrete event systems as well as their formal properties. This paper proposes an approximate mathematical programming model for the simulation of flow lines with finite buffer capacities. The approximation exploits the concept of time buffer, modeled as a constraint that put into a temporal relationship the completion times of two jobs in a sample path. The system performance estimated by the approximate formulation are between two extreme values calculated from the solution of a linear programming model. When the linear model is coupled with a buffer optimization model, the extreme values represent the upper and lower bounds containing the optimal solution. The main advantage of the proposed formulation is that it preserves its linearity even when used for buffer optimization.
Measurement and evaluation for head injury of pedestrian impact using high-speed digital image correlation

Abstract. This paper presents the use of the high-speed digital image correlation (DIC) method for measurement of the head injury of a pedestrian in a vehicle–pedestrian collision experiment. Two simultaneous high-speed cameras captured the images of the impact process between the head-simulator and the car hood. The DIC method can achieve comprehensive analysis of the impact and help to reconstruct the impact process, from which not only the velocity, acceleration of the headform impactor, and the head injury criterion (HIC) but also the angular velocity and acceleration can be calculated. The possibility of using DIC to calculate of the neck injury criterion (NIC) is also discussed in this paper. Furthermore, the quantitative calculation of the full-field deformation of the car hood during the collision can also be achieved with the DIC method, which is of great practical value in optimizing automobile design and collision protection. A vehicle–pedestrian collision experiment is carried out, and the comprehensive results show that the DIC method can obtain accurate and comprehensive data in the calculation of human and vehicle collision.
A Benchmark Study of Graph Models for Molecular Acute Toxicity Prediction

With the wide usage of organic compounds, the assessment of their acute toxicity has drawn great attention to reduce animal testing and human labor. The development of graph models provides new opportunities for acute toxicity prediction. In this study, five graph models (message-passing neural network, graph convolution network, graph attention network, path-augmented graph transformer network, and Attentive FP) were applied on four toxicity tasks (fish, Daphnia magna, Tetrahymena pyriformis, and Vibrio fischeri). With the lowest prediction error, Attentive FP was reported to have the best performance in all four tasks. Moreover, the attention weights of the Attentive FP model helped to construct atomic heatmaps and provide good explainability.
Antioxidants Amelioration Is Insufficient to Prevent Acrylamide and Alpha-Solanine Synergistic Toxicity in BEAS-2B Cells

Cells produce free radicals and antioxidants when exposed to toxic compounds during cellular metabolism. However, free radicals are deleterious to lipids, proteins, and nucleic acids. Antioxidants neutralize and eliminate free radicals from cells, preventing cell damage. Therefore, the study aims to determine whether the antioxidants butylated hydroxyanisole (BHA) and butylated hydroxytoluene (BHT) will ameliorate the maximum dose of acrylamide and alpha (α)-solanine synergistic toxic effects in exposed BEAS-2B cells. These toxic compounds are consumed worldwide by eating potato products. BEAS-2B cells were simultaneously treated with BHA 10 μM and BHT 20 μM and incubated in a 5% CO2 humidified incubator for 24 h, followed by individual or combined treatment with acrylamide (3.5 mM) and α-solanine (44 mM) for 48 h, including the controls. Cell morphology, DNA, RNA, and protein were analyzed. The antioxidants did not prevent acrylamide and α-solanine synergistic effects in exposed BEAS-2B cells. However, cell morphology was altered; polymerase chain reaction (PCR) showed reduced RNA constituents but not DNA. In addition, the toxic compounds synergistically inhibited AKT/PKB expression and its downstream genes. The study showed BHA and BHT are not protective against the synergetic toxic effects of acrylamide and α-solanine in exposed BEAS-2B cells.
AKARI NIR spectroscopy of interstellar ices

Abstract The Infrared Camera (IRC) onboard AKARI has a near-infrared (2--5μm) spectroscopic capability with high sensitivity that allows us to study the major ice components in various objects. In particular, H2O and CO2 ice absorption features have been detected towards nearby galaxies, including several young stellar objects (YSOs) in the Large Magellanic Cloud (LMC), as well as a number of HII region-PDR complexes for the first time by IRC spectroscopy. While observations in the LMC show a high ratio (~0.34) of the CO2 to H2O ice column densities, the ratios in Galactic HII-region-PDR complexes are in the range of 0.1--0.2, being compatible with those found in Galactic massive YSOs in previous studies. The good correlation supports concurrent formation of the two ice species on the grain surface and the higher ratio in the low-metallicity LMC suggests possible environmental effects in the formation process.
Voice of the Customer: Factors Impacting Beneficiary Choice of Programs in TRICARE

Little is known about how a consumer would choose a health plan if cost was not an option such as in the Military Health System. We sought to identify how to recruit TRICARE beneficiaries into new pilot programs challenged by low recruitment. We developed a semistructured interview guide by adapting a framework established by Klinkman to assess factors in choosing a health plan. Using social media platforms, we recruited TRICARE Prime and Select beneficiaries to participate in key informant interviews from October to December 2022. We conducted inductive thematic analysis to determine key areas of concern. We interviewed a total of 20 TRICARE Prime and Select beneficiaries. The majority were women, above age 40, had a master's degree, a sponsor in the US Army and of senior officer rank. Four overarching themes emerged: (I) patient choice; (II) access to care; (III) quality of care; and (IV) cost. This evaluation of TRICARE beneficiaries explores how to motivate high-quality value-based care in a traditionally fee for service system.