Miracle-dz/UniFAR-FTUs huggingface dataset:
Urgency of Criminal Functionality on the Perpetrators of Santet

The belief in the existence of supernatural crimes is inherent in the lives of Indonesian people, the view of people who think that santet is something that can cause harm to others makes santet seen as a crime. Santet is an act of harming others using magic. Departing from this, this study aims to explore criminal law for users of santet crimes. The method used in this research is normative legal research, data obtained through literature study. The study results show that in criminal understanding, santet can be legally accounted for by reviewing articles that substantially imply regulation not only on general issues but also on uncommon issues such as santet. Sorting and clustering the substance of santet becomes the central point so that the arguments issued can be legally accounted for, caution in understanding the sides of the importance of santet will lead to ideas that can be justified. In the understanding of the criminal law of santet which is still difficult to accept by many people, in fact theoretically capable of being legally responsible, an open view of legal issues is the key to how the law can be fully enforced on everything that violates the rights of others, as well as on problems santet by the discussion that has been explained that in understanding the law must be open but not out of the rules of the substance of the existing article.
The Fitting Procedure for Longitudinal Shower Profiles Observed with the Fluorescence Detector of the Pierre Auger Observatory

The Pierre Auger Observatory uses fluorescence telescopes in conjunction with ground level particle detectors to measure high-energy cosmic rays and reconstruct, with greater precision, their arrival direction, their energy and the depth of shower maximum. The depth of shower maximum is important to infer cosmic ray mass composition. The fluorescence detector is capable of directly measuring the longitudinal shower development, which is used to reconstruct the cosmic ray energy and the atmospheric depth of shower maximum. However, given the limited field of view of the fluorescence detector, the shower profile is not always fully contained within the detector observation volume. Therefore, considerations need to be taken in order to reconstruct some events. In this contribution we will describe the method that the Pierre Auger Collaboration uses to reconstruct the longitudinal profiles of showers and present the details of its performance, namely its resolution and systematic uncertainties.
An improved adaptive backstepping approach on static var compensator controller of nonlinear power systems

The transient stability problem of a single‐machine infinite‐bus system with static var compensator is solved in this paper, where the static var compensator controller is designed by an improved backstepping method combining error compensation, adaptive backstepping control, and sliding mode variable structure control. Crucially, the error compensation term, which chooses in the step of virtual control by the adaptive backstepping method, is introduced to ensure that the system states are bounded, maintaining the nonlinearity of the power systems while also improving the speed of parameter identification. Meanwhile, the Lyapunov function is constituted step by step to achieve stability of the subsystem. In addition, a parameter updating law and a nonlinear control law are explicitly given to asymptotically stabilize the closed‐loop system. Finally, a simulation is used to illustrate the effectiveness and the practicality of the proposed control approach.
A parametric analytical model of the atmospheric muon flux at sea-level and its application in the field of the muon transmission radiography

Atmospheric muons represent the primary component of cosmic radiation detected at sea-level. Their speciﬁc characteristics - natural abundance, energy-based ability to penetrate objects, harm-lessness - make them an essential tool for performing non-destructive imaging of the internal structure of objects by means of muon transmission radiography (MTR), a 2D technique optimised for studying large objects such as mountains and volcanoes, and multiple scattering muon tomography (MSMT), a 3D technique exploited for relatively small objects. On the other hand, the considerable presence of atmospheric muons and secondary particles produced by them in-ﬂuences the measurements of low background experiments, designed to reveal dark matter and neutrinos signals. In all cases, the need to have a reliable model that accurately describes the energy spectrum and the angular distribution of the ﬂux of atmospheric muons at sea-level is evident. This contribution describes the development of a parametric analytical model built by ﬁtting a selected set of empirical models developed in the last decades to the data measured by ADAMO (Florence
Predictors of cancer screening behavior of the working population in China based on the information-motivation-behavioral skills model

Background The cancer screening rate in the working population is very low in China. Information-motivation-behavioral skills (IMB) model has been applied to elucidate screening behavior for various chronic diseases but has not been investigated in analyzing cancer screening behavior. This study aimed to examine factors influencing cancer screening behavior and their linkages based on the IMB model. Methods A cross-sectional study was conducted in Shanghai, China from August to October 2021. Data were obtained through an anonymous questionnaire. Predictive relationships between variables in the IMB model and cancer screening behavior were evaluated. Structural equation modeling (SEM) was constructed to demonstrate the utility of the IMB model. Results Among the 556 participants included in the analysis, 34.4% of participants had ever done a cancer screening. The construct validation analysis supported that the measure items included were acceptable. SEM found that knowledge of cancer warning signs and symptoms (β = 0.563, p < 0.001) and cancer screening behavioral skills (β = 0.264, p = 0.003) were related to participation in cancer screening, whereas cancer screening motivation was not directly influenced the participation in cancer screening (β = − 0.075, p = 0.372). Conclusion The cancer screening rate was found to be lower than expected in the working population. The IMB model could be used to make decisions in implementing behavioral interventions to participate in cancer screening among the Chinese working population. Enhancing the knowledge of cancer warning signs and symptoms and strengthening behavioral skills should be focused on to improve participation in cancer screening.
Ecuaciones en Diferencias Finitas Parciales en Mallas Eléctricas

This paper presents a method to analyze a triangular network of equal electrical impedances, and composed by triangular meshes constituted themselves by these impedances; and shows how to obtain a partial, finite differences equation, relating the Maxwell current in each mesh (n,m) with those currents in the currents in the neighboring meshes. The differences equation is solved by the method of Lagrange, and boundary conditions are applied in order to obtain explicitly the total, equivalent impedance of the network and the distribution of the Maxwell currents across thew hole network. This treatment surpasses the usual one of isolating meshes and nodes, applying the two laws of Kirchhoff tocurrents and voltages and finally solving a large system of linear algebraic equations by numerical or algebraic methods. During many years as an electrical engineer, the author has not seen used this methodology, so that he considers this is an original and useful addition to the theory of electric circuits.
The HAWC ultra-high-energy gamma-ray map with more than 5 years of data

In 2020, the HAWC Collaboration presented the first catalog of gamma-ray sources emitting above 56 TeV and 100 TeV. With nine sources detected, this was the highest-energy source catalog to date. Here, we present the results of re-analysis of the old data, along with additional data acquired since then. We use a new version of the reconstruction software with better pointing accuracy and improved gamma/hadron separation. We now see more than 25 sources above 56 TeV, with most sources being located in the Galactic plane. The vast majority of these seem to be leptonic pulsar wind nebulae, but some have been shown to have hadronic emission. We will show spectra and discuss possible emission mechanisms of some of the most interesting sources, including the ones the HAWC Collaboration considers PeVatron candidates.
A Combinatorial Registration Method for Forward-Looking Sonar Image

In this article, we present a novel and robust registration method for autonomous underwater vehicles (AUV) using the forward-looking sonar (FLS). Due to the sparsity and repeatability of the underwater environment, and the loss of elevation angle, the FLS is difficult to consistently provide reliable information. The feature extraction and matching are the main difficulties encountered in registrations. This motivates us to propose a method to deal with various underwater environments and provide reliable information to improve the robustness and accuracy of the registration. First, the sonar images are preprocessed to highlight the region of interest and transformed. Next, a sonar image sequence is used for preliminary registration. Last, a combinatorial method including a feature-based region selection and a region-based registration is proposed. The validation is based on datasets and real-world experiments. Comparison studies verify the effectiveness of the proposed method.
Search for TeV Gamma Ray Emission from Fast Radio Burst Locations with the HAWC Obsevatory

The number of observed Fast Radio Burst (FRB) events has grown rapidly over the last few years, but their origin remains unknown. Multiwavelength follow-ups have been encouraged by radio astronomers but the transient nature of the events makes targeted follow-ups difficult unless a source is known to repeat. A wide field-of-view instrument, such as HAWC can overcome this limitation using archival data. In this study we search for very high energy (VHE) gamma rays from FRB source locations over the largest population studied at this energy. Using data from the HAWC Observatory we look at over 200 FRB events from 141 unique locations and search for persistent emission and transient activity in 600 s surrounding the burst time. The results are then placed in context of available models and maximum gamma-ray emission levels from FRBs.
Autonomous Human and Animal Classification Using Synthetic 2D Tensor Data Based on Dual-Receiver mmWave Radar System

Human and animal classification under the rubble is necessary to successfully rescue survivors post-disaster, and interference from other animals is becoming an issue in noncontact monitoring with radar. Many animals in indoor and outdoor environments have characteristics similar to humans, where they are easily mistaken for human targets, which would trigger a false alarm. A novel human and animal classification through single-receiver and dual-receiver mmWave radar at 77 GHz is presented. The system uses feedback signal responses from targets with dual-receiver mmWave radar and classifies human and animal features using a convolution neural network (CNN) based on synthetic 2D Tensor data. The performance is compared to the classification result using a deep learning and backpropagation neural network (BPNN) from a single mmWave radar dataset under the measurement distance and number of objects. Our experimental results showed that using dual receivers was very useful and performed well in classifying humans and animals, with an average accuracy rate of 99% in the classification of 2 and 3 classes, 83% in 6 classes, and 68% in 10 classes. The performance showed an excellent result considering that this system’s application avoids false alarms in human rescue applications during post-disaster periods and exceeds the accuracy of several previous studies.
Integrating ethnomathematics approach in teaching school mathematics

The teacher is one of the key factors in the transmission of curricular objectives to their students. Their knowledge and positive attitude toward students' ethnomathematics and its pedagogical approach play an important role to make classroom teaching culture friendly. This paper is intended to explore the in-service teachers’ knowledge of ethnomathematics and perception on the integration of the ethnomathematics approach in their teaching with respect to the demographic factors of in-service teachers such as gender, academic status, teaching experience, teacher training, and nature of institution they associated. This study was conducted among 120 in-service mathematics teachers from 32 secondary schools in Kathmandu District. The explanatory sequential mix method was employed to carry out this study. The perception of in-service teachers on ethnomathematics pedagogy in their classroom teaching was measured with survey instruments in the first stage. For further justification of the results obtained from the quantitative data, six teachers with different demographic factors were interviewed in the second stage of the data collection process. The relationship between in-service teachers’ understanding on ethnomathematics and different demographic factors was investigated using the Pearson Chi-square test. From the statistical data analysis, it was found that there is no relationship between gender, academic qualifications, and teachers' training in their understanding of ethnomathematics. However, a significant relationship was found between the teachers' experience and nature of the institutions they were involved, and their understanding on ethnomathematics. In-service teachers have a similar understanding on ethnomathematics and their perception in the integration of the ethnomathematics approach in the teaching of school mathematics.
Compactness properties of perturbed sub-stochastic C_0-semigroups on L^1() with applications to discreteness and spectral gaps

We deal with positive C0-semigroups (U(t))t>0 of contractions in L( ;A; ) with generator T where ( ;A; ) is an abstract measure space and provide a systematic approach of compactness properties of perturbed C0-semigroups et(T V ) t 0 (or their generators) induced by singular potentials V : ( ; ) ! R+. More precise results are given in metric measure spaces ( ; d; ). This new construction is based on several ingredients: new a priori estimates peculiar to Lspaces, local weak compactness assumptions on unperturbed operators, Dunford-Pettisarguments and the assumption that the sublevel sets M := fx;V (x) Mg are thin at in nity with respect to (U(t))t>0. We show also how spectral gaps occur when the sublevel sets are not thin at in nity. This formalism combines intimately the kernel of (U(t))t>0 and the sublevel sets M . Inde nite potentials are also dealt with. Various applications to convolution semigroups, weighted Laplacians and Witten Laplacians on 1-forms are given.
Downscaling ERA5 wind speed data: a machine learning approach considering topographic influences

Energy system modeling and analysis can provide comprehensive guidelines to integrate renewable energy sources into the energy system. Modeling renewable energy potential, such as wind energy, typically involves the use of wind speed time series in the modeling process. One of the most widely utilized datasets in this regard is ERA5, which provides global meteorological information. Despite its broad coverage, the coarse spatial resolution of ERA5 data presents challenges in examining local-scale effects on energy systems, such as battery storage for small-scale wind farms or community energy systems. In this study, we introduce a robust statistical downscaling approach that utilizes a machine learning approach to improve the resolution of ERA5 wind speed data from around 31 km × 31 km to 1 km × 1 km. To ensure optimal results, a comprehensive preprocessing step is performed to classify regions into three classes based on the quality of ERA5 wind speed estimates. Subsequently, a regression method is applied to each class to downscale the ERA5 wind speed time series by considering the relationship between ERA5 data, observations from weather stations, and topographic metrics. Our results indicate that this approach significantly improves the performance of ERA5 wind speed data in complex terrain. To ensure the effectiveness and robustness of our approach, we also perform thorough evaluations by comparing our results with the reference dataset COSMO-REA6 and validating with independent datasets.
Parameterization of Cumulus Convection in a Tropical Cyclone Model

As a continuation of a previous study (Yamasaki, 1986), two numerical experiments of tropical cyclones with and without environmental vertical shear flow are performed. Effects of cumulus convection are parameterized so that mesoscale features of tropical cyclones may be simulated by taking account of rainwater effects. The behavior and the structure of computed rainbands appear to be similar to those of observed rainbands. However, more definite observational studies are necessary to estimate the degree of validity of the cumulus parameterization and to improve it.
A New Paradigm for Polling

Scientific fields operate within paradigms that define problems and solutions for a community of researchers. The dominant paradigm in polling centers on random sampling, which is unfortunate because random sampling is, for all practical purposes, dead. The pollsters who try to produce random samples fail because hardly anyone responds. And more and more pollsters do not even try. The field therefore has folded weighting-type adjustments into the paradigm, but this too is unfortunate because weighting works only if we assume away important threats to sampling validity, threats that loom particularly large in the growing non-probability polling sector. This paper argues that the polling field needs to move to a more general paradigm built around the Meng (2018) equation that characterizes survey error for any sampling approach, including non-random samples. Moving to this new paradigm has two important benefits. First, this new paradigm elevates new insights, including the fact that survey error increases with population size when individuals’ decisions to respond are correlated with how they respond. This insight helps us understand how small sampling defects can metastasize into large survey errors. Second, the new paradigm points the field toward new methods that more directly identify and account for sampling defects in a non-random sampling environment. This paper describes the intuition and potential power of these new tools, tools that are further elaborated in Bailey (2023b).
Consumers’ Corporate Social Responsibility Perception and Anti-Consumer Awareness: Roles of Compassion and Corporate Social Responsibility Authenticity in South Korea

This study examines the effect of consumers’ perceptions of corporate social responsibility (CSR) on their anti-consumer awareness. Specifically, this study aims to uncover the mechanisms through which the consumer’s CSR perception relates to their formation of anti-consumer awareness. A survey design was adopted to test this study’s hypotheses. We collected data from 310 consumers in South Korea and used path analysis and bootstrapping to test the hypotheses. Our results showed that consumers’ CSR perception is negatively related to their anti-consumer awareness. Notably, consumers’ perception of CSR activities is positively related to their perceptions of compassion toward organizations, which, in turn, is also positively associated with their perception of CSR authenticity. Furthermore, compassion and CSR authenticity serially mediate the negative relationship between CSR perception and anti-consumer awareness. Our findings shed light on the importance of engaging in CSR activities from consumers’ perspectives. Specifically, our findings suggest that organizations need to proactively engage in CSR activities with authenticity to maintain and even further their reputation among consumers. Furthermore, by demonstrating the psychological processes of how CSR activities translate into consumers’ attitudes toward the organizations, our study provides fruitful avenues for future research.
Modeling Separation and Cavitation Behind a Blunt Body

Cavitation flow behind a blunt body is modeled using a physics-based numerical model of cavitation initiation and transition to larger cavities. The calculations initiate from the dynamics of nuclei, then tracks the dispersed bubble phase with a two-phase viscous model. This solver includes a level set method to model coalescence of the nuclei into large cavities and to track the dynamics of the resulting free surfaces. A transition scheme enables collection of the bubbles into a large cavity and also enables breakup of a large cavity into a bubble cloud. Using this model, simulations are conducted for different flow velocities and corresponding cavitation regimes. When the velocity is relatively small (i.e., large cavitation number), flow separation behind the body results in the shedding of vortices, which capture nuclei in their cores to form elongated vortical cavities. As the flow velocity increases (or as the ambient pressure decreases) the flow evolves into a separated flow with a large cavity behind the body. A reentrant jet may form and move upstream into the cavity towards the body. This jet periodically shears off portions of the cavity volume, resulting in large amounts of bubble clouds. These results are in good qualitative agreements with experimental observations.
Relationship between elimination disorders and internalizing‐externalizing problems in children: A systematic review and meta‐analysis

Abstract Background Elimination disorders are highly prevalent in childhood and often associated with clinically relevant comorbid psychological disorders. The aim of this study is to determine if, and to what extent, children with elimination disorders show higher internalizing and externalizing problems than their healthy peers. Methods A multistep literature search was performed from database inception until May 1st, 2022. PRISMA/MOOSE‐compliant systematic review (PROSPERO: CRD42022303555) were used to identify studies reporting on internalizing and/or externalizing symptoms in children with an elimination disorder and a healthy control (HC) group. First, a systematic review was provided. Second, where data allowed for it, a quantitative meta‐analysis with random effects model was conducted to analyze the differences between the elimination disorder and the HC groups for internalizing and externalizing symptoms. Effect size was standardized mean difference. Meta‐regression analyses were conducted to examine the effect of sex, age, and study quality. Funnel plots were used to detect a publication bias. Where found, the trim and fill method was used to correct it. Results 36 articles were included, 32 of them reporting on enuresis (n = 3244; mean age = 9.4; SD = 3.4; 43.84% female) and 7 of them on encopresis (n = 214; mean age = 8.6; SD = 2.3; 36.24% female). Children with an elimination disorder presented significantly lower self‐concept (ES:0.42; 95%CI [0.08; 9.76]; p = 0.017) and higher symptom scores for thought problems (ES:−0.26; 95%CI: −0.43;−0.09]; p = 0.003), externalizing symptoms (ES: −0.20; 95%CI [−0.37;−0.03]; p = 0.020), attention problems (ES:−0.37; 95%CI [−0.51;−0.22]; p = 0.0001), aggressive behavior (ES:−0.33; 95%CI [−0.62;−0.04]; p = 0.025) and social problems (ES:−0.39; 95%CI [−0.58;−0.21]; p = 0.0001). Significant publication biases were found across several of the studied domains. No significant effect of sex, age or quality of the study score was found. Conclusions Children with an elimination disorder may have significant internalizing and externalizing problems, as well as impaired self‐concept. It is recommendable to screen for them in children with enuresis or encopresis and provide appropriate interventions.