Miracle-dz/UniFAR-FTUs huggingface dataset:
The Situation of Food Security and Related Factors in Female Teachers of Yasuj Education School Board

Background & aim: Food insecurity is recognized as a serious public health problem in the world and has attracted the attention of the public, professionals, and policymakers. Food insecurity and hunger can affect social and mental health as well as physical health. Given that women make up half of human society and have a significant and far-reaching impact on public health; the present study aimed to assess the food security status among female teachers of Yasuj education school board. Methods: In this descriptive-analytical study conducted in 2018, 400 female teachers were randomly selected as a sample from the female teachers of Yasuj Education School Board using a list of random numbers assigned to teachers by the simple randomization method. The Radimer-Cornell questionnaire was used to assess the food security, and a Seca scale and a tape measure were used to measure weight and height respectively. Data were analyzed using descriptive statistics, chi-square, and one-way ANOVA. Results: In the present study, the mean and standard deviation of participant’s age was 37/87±6/89 years and the mean and standard deviation of body mass index was 25/90±3/70 kg/m 2 . The results of the present study indicated that in terms of body mass index, 123 people had a BMI below 25 (30/8 % = normal weight), 197 people had a BMI of 25 to 30 (49.2% = overweight) and 80 people had a BMI of more than 30 (20 % = obese). 70/5 % of teachers suffered from varying degrees of food insecurity, and only 29/5 % of the women studied had complete food security. They reported food insecurity on household (50%), individual (12%), and child (8.5%) scales. In examining the factors related to food security, the results of statistical tests showed that economic status, housing status, spouse's job, and participants' education have a significant statistical relationship with three scales of food insecurity (household, individual and child)(p<0/05). Conclusion: The results of the present study indicated that there are degrees of food insecurity in a large part of the female teachers' community and that social and economic factors also play an important role in this food insecurity. It seems that it is possible to take steps to improve this problem with appropriate policies and executive strategies.
On the Dirichlet problem for degenerate Beltrami equations

We show that every homeomorphic $W^{1,1}_{\rm loc}$ solution $f$ to a Beltrami equation $\bar{\partial}f=\mu \partial f$ in a domain $D\subset\Bbb C$ is the so--called lower $Q-$homeomorphism with $Q(z)=K^T_{\mu}(z, z_0)$ where $K^T_{\mu}(z, z_0)$ is the tangent dilatation of $f$ with respect to an arbitrary point $z_0\in {\bar{D}}$ and develop the theory of the boundary behavior of such solutions. Then, on this basis, we show that, for wide classes of degenerate Beltrami equations $\bar{\partial}f=\mu \partial f$, there exist regular solutions of the Dirichlet problem in arbitrary Jordan domains in $\Bbb C$ and pseudoregular and multi-valued solutions in arbitrary finitely connected domains in $\Bbb C$ bounded by mutually disjoint Jordan curves.
Internet of Things: Security and Solutions Survey

The overwhelming acceptance and growing need for Internet of Things (IoT) products in each aspect of everyday living is creating a promising prospect for the involvement of humans, data, and procedures. The vast areas create opportunities from home to industry to make an automated lifecycle. Human life is involved in enormous applications such as intelligent transportation, intelligent healthcare, smart grid, smart city, etc. A thriving surface is created that can affect society, the economy, the environment, politics, and health through diverse security threats. Generally, IoT devices are susceptible to security breaches, and the development of industrial systems could pose devastating security vulnerabilities. To build a reliable security shield, the challenges encountered must be embraced. Therefore, this survey paper is primarily aimed to assist researchers by classifying attacks/vulnerabilities based on objects. The method of attacks and relevant countermeasures are provided for each kind of attack in this work. Case studies of the most important applications of the IoT are highlighted concerning security solutions. The survey of security solutions is not limited to traditional secret key-based cryptographic solutions, moreover physical unclonable functions (PUF)-based solutions and blockchain are illustrated. The pros and cons of each security solution are also discussed here. Furthermore, challenges and recommendations are presented in this work.
The isomorphism conjecture for groups with generalized free product structure

In this article we study the K- and L-theory of groups acting on trees. We consider the problem in the context of the fibered isomorphism conjecture of Farrell and Jones. We show that in the class of residually finite groups it is enough to prove the conjecture for finitely presented groups with one end. Also, we deduce that the conjecture is true for the fundamental groups of graphs of finite groups and of trees of virtually cyclic groups. To motivate the reader we include a survey on some classical works on this subject.
Ultracold dipolar gases in optical lattices

This tutorial is a theoretical work, in which we study the physics of ultra-cold dipolar bosonic gases in optical lattices. Such gases consist of bosonic atoms or molecules that interact via dipolar forces, and that are cooled below the quantum degeneracy temperature, typically in the nK range. When such a degenerate quantum gas is loaded into an optical lattice produced by standing waves of laser light, new kinds of physical phenomena occur. Then, these systems realize extended Hubbard-type models, and can be brought to a strongly correlated regime. The physical properties of such gases, dominated by the long-range, anisotropic dipole–dipole interactions, are discussed using the mean-field approximations and exact quantum Monte Carlo techniques (the worm algorithm).
The multiplicity of massive stars

Abstract Binaries are excellent astrophysical laboratories that provide us with direct measurements of fundamental stellar parameters. Compared to single isolated stars, multiplicity induces new processes, offering the opportunity to confront our understanding of a broad range of physics under the extreme conditions found in, and close to, astrophysical objects. In this contribution, we will discuss the parameter space occupied by massive binaries, and the observational means to investigate it. We will review the multiplicity fraction of OB stars within each regime, and in different astrophysical environments. In particular we will compare the O star spectroscopic binary fraction in nearby open clusters and we will show that the current data are adequately described by an homogeneous fraction of f ≈ 0.44. We will also summarize our current understanding of the observed parameter distributions of O + OB spectroscopic binaries. We will show that the period distribution is overabundant in short period binaries and that it can be described by a bi-modal Öpik law with a break point around P ≈ 10 d. The distribution of the mass-ratios shows no indication for a twin population of equal mass binaries and seems rather uniform in the range 0.2 ≤ q = M2/M1 ≤ 1.0.
Pedestrian Flow Prediction and Route Recommendation with Business Events

Due to the potential economic benefits, pedestrian flow is considered an essential indication of public spaces. Pedestrian flow prediction is designed to assist operators in making decisions (such as shopping center owners). Operators hold certain events, such as sales promotions, to attract surrounding pedestrians; we refer to this type of event as a business event. Business events attract pedestrian flows, which means business opportunities for the merchants. Moreover, their placement will affect the distributions of the pedestrian flows. However, deciding which route is chosen for a specified event is difficult. To the best of our knowledge, we are the first to consider business events when predicting pedestrian flow. In this paper, we investigate two problems: one is pedestrian flow prediction with business events, and the other is route recommendation for business events. First, we propose an Attraction-Based Matrix Factorization model (ABMF) to efficiently predict the pedestrian flow with business events, which introduces the attraction index of different categories to pedestrians in matrix factorization. Second, we leverage the Skip-gram mode to learn the latent representations and improve the pair-wise ranking loss to a flow-aware-based method (SG-FWARP), which aims to learn events’ latent representations for route recommendation. Compared with other state-of-the-art methods, the experimental results show ABMF can predict pedestrian flow matrix with a similarity of over 0.9 compared with the ground truth, and SG-FWARP can recommend routes for business events with high accuracy.
An Introductory Survey of Entropy Applications to Information Theory, Queuing Theory, Engineering, Computer Science, and Statistical Mechanics

Clausius was the first to coin the term “entropy” roughly 160 years ago. Since then, many scholars from several scientific fields have continued to enhance, develop, and interpret the data. This study describes the concept of entropy and its applications to information theory, queuing theory, engineering systems, computing, and statistical mechanics. The choice of these applications was subjected to the size limitation of the paper. Having said that, entropy has a great applicability to other scientific disciplines. Even more interesting is the nature of entropy as a measurement of uncertainty, dis-order, or turbulence was the main core of attraction to a considerable number of scholars in all academic areas of research expertise to both employ it and make a significant research advancement. Its goal is to present a coherent picture of how classical entropies might be used in engineering and computer science. It is attempted to create a concise exposition that strikes a balance between conceptual importance and instrumental relevance. A representative list of references closes this review.
Foxes caught in the same snare: a methodological review of social radon studies

Abstract Mitigating risk from exposures to indoor radon is a critical public health problem confronting many countries worldwide. In order to ensure effective radon risk management based on social scientific evidence, it is essential to reduce scientific uncertainty about the state of social methodology. This paper presents a review of methodological (best) practices, and sensitivity to bias, in research on public attitudes and behaviours with regards to radon risks. Using content analysis, we examined characteristics of research design, construct measurement, and data analysis. Having identified certain challenges based on established and new typologies used to assess methodological quality, our research suggests that there is a need for attention to (limitations of) cross-sectional design, representative and appropriate sampling, and a pluralist approach to methods and analysis. Furthermore, we advocate for more comparative research, rigorous measurement and construct validation. Lastly, we argue that research should focus on behavioural outcomes to ensure effective radon risk management. We conclude that for any field to thrive it is crucial that there is methodological reflexivity among researchers. Our recommendations serve as a useful guide for researchers and practitioners seeking to understand and enhance the rigor of social methodology in their field.
A descriptive approach to the class NP

Descriptive complexity is the study of the expressive power of logical languages. There exists a close relationship between the expressive power of a logical language and the computational complexity of the properties captured by such a language. R. Fagin proved that every sentence in second-order existential logic expresses a problem that can be decided by a non-deterministic polynomial time Turing machine: SO$\exists$ = NP (9). With this fact as our starting point, we study the sentences that express properties that are complete for the class NP via first-order projections (fops). This type of reductions arises naturally in descriptive complexity, and it is known that all problems complete for NP via fops are FO-isomorphic (1). Our study of SO$\exists$ sentences includes a normal form for sentences that describe NP-complete properties, the development of syntactic tools for proving problems NP-complete via fops, the definition of syntactic families of problems that have a similar syntactic structure, the study of the approximability of the problems in the syntactic families that we define, and a descriptive version of the PCP theorem. This dissertation is organized in seven chapters. In Chapter 1, we present an overview of our research area and results. In Chapter 2, we review the concepts and definitions of descriptive complexity. In Chapter 3 we describe a normal form for SO$\exists$ sentences that define a NP-complete problems via fops. In Chapter 4 we present syntactic tools to prove problems NP-complete via fops and use them to prove that a large number of the known NP-complete problems remain complete via fops. Among these tools, we define families of problems with similar syntactic structure. In Chapter 5, we study the approximation properties of some of the families defined in chapter 4. In Chapter 6, we prove a descriptive version of the PCP theorem. This descriptive version implies both the PCP theorem in its computational version and Fagin's theorem. We close this work with Chapter 7 presenting our conclusions and suggestions for future research motivated by this dissertation.
Predictive Analysis for Social Diffusion: The Role of Network Communities

The diffusion of information and behaviors over social networks is of considerable interest in research fields ranging from sociology to computer science and application domains such as marketing, finance, human health, and national security. Of particular interest is the possibility to develop predictive capabilities for social diffusion, for instance enabling early identification of diffusion processes which are likely to become "viral" and propagate to a significant fraction of the population. Recently we have shown, using theoretical analysis, that the dynamics of social diffusion may depend crucially upon the interactions of social network communities, that is, densely connected groupings of individuals which have only relatively few links between groups. This paper presents an empirical investigation of two related hypotheses which follow from this finding: 1. ) inter-community interaction is predictive of the reach of social diffusion and 2. ) dispersion of the diffusion phenomenon across network communities is a useful early indicator that the propagation will be "successful". We explore these hypotheses with case studies involving the emergence of the Swedish Social Democratic Party at the turn of the 20th century, the spread of the SARS virus in 2002-2003, and blogging dynamics associated with real world protest activity. These empirical studies demonstrate that network community-based diffusion metrics do indeed possess predictive power, and in fact can be more useful than standard measures.
FPGA Implementation of Addition-based CORDIC-SNN With Izhikevich Neurons

When implementing a Spiking Neural Network, several neuron models can be applied, including, the integrate and fire model, the Hodgkin Huxley model, and the Izhikevich model. These models have varying properties. The integrate-and-fire model is a simplified model and does not produce many of the firing behaviors of a biological neuron to a great extent. The Hodgkin Huxley model captures several properties of a biological neuron but isn’t very energy efficient due to its complexity. The Izhikevich neuron, on the other hand, is not very complex and can produce several firing behaviors seen in biological neurons. This reduced complexity of the Izhikevich neuron makes it more energy-efficient than the Hodgkin Huxley neuron, and a suitable candidate for the implementation of biologically plausible neural networks. To implement an Izhikevich neuron, two ordinary differential equations are required, one of which involves a mathematical square operation. This paper proposes an energy-efficient method of implementing a simple spiking neural network for image classification on an FPGA using the MNIST dataset. CORDIC (Coordinate Rotation Digital Computer) algorithm is used to implement the neuron while time-dependent backpropagation is used in training. Finally, our model is implemented on a NEXYS 4 FPGA (Field Programmable Gate Array) board to speed-up the operation of the neural network and to observe the hardware resource requirements. Results show a slight improvement in energy efficiency when a single CORDIC and an Izhikevich neuron implemented without CORDIC are compared. This resulted in a larger difference in power consumed when a larger network was implemented on an FPGA.
Transformer-Less Soft-Switching High-Gain PWM Boost Converter With Reduced Components and Increased Effective Duty Cycle

A transformer-less soft-switching high-gain pulsewidth-modulation (PWM) converter is proposed in this article. The proposed converter is derived from a single-switch dual-inductor transformer-less boost converter by replacing the complementary diode connected to the switch with a synchronous rectifier switch. Moreover, the peak value of the reverse current of the rear-end inductor in continuous bidirectional conduction mode (CBCM) is regulated to exceed the input inductor valley current. Based on these two measures, the zero-voltage switching (ZVS) for all switches and the natural turn-off for the output diode are realized, and the effective duty cycle is enhanced. Besides, the proposed ZVS converter has the merits of fewer power components count, reduced voltage stress, and lower cost. Furthermore, the ringing issue in the original topology under light load or high input voltage conditions is eliminated. The operation principle, steady-state characteristics, dynamic model, soft-switching operation, and realization conditions are analyzed in detail, and subsequently, the parameter design method is elaborated. The proposed topology demonstrates an enhanced efficiency performance over wide operating operations with a maximum efficiency of 97.1%.
Room temperature near-field microwave imaging with an YBa2Cu3O7 Josephson cantilever

Josephson junctions from the high-temperature superconductor YBa2Cu3O7 operated in a temperature range of 40–80K cooled by a cryocooler can be deployed on a cantilever to detect microwave radiation. The spatial scanning step width used here is 15μm with operating distance of the cooled Josephson cantilever to the surface of the device under test (DUT) of about 150μm. The DUT is operated at room temperature. Due to the realization as an active cantilever a topographic image of the DUT as well as the microwave power distribution can be obtained.
Former CEO Director and Audit Fees

ABSTRACT This study investigates the relationship between former chief executive officer (CEO) directors and audit pricing. We find that the former CEO directors negatively impact the company’s audit fees. The results do not change after conducting a series of robustness tests. Former CEO directors reduce the company’s operating risk, improve the company’s earnings quality, and reduce the company’s audit fees. Meanwhile, they are more effective at monitoring in companies with less analyst following, lower proportion of female directors, and non-family firms, thus reducing audit fees. Further evidence shows that larger auditors are more likely to reduce audit fees for their clients that have former CEOs retained on the board of directors.
Pair cascades in the magnetospheres of strongly magnetized neutron stars

We present numerical simulations of electron-positron pair cascades in the magnetospheres of magnetic neutron stars for a wide range of surface fields (Bp = 10 12 – 10 15 G), rotation periods (0.1–10 s), and field geometries. This has been motivated by the discovery in recent years of a number of radio pulsars with inferred magnetic fields comparable to those of magnetars. Evolving the cascade generated by a primary electron or positron after it has been accelerated in the inner gap of the magnetosphere, we follow the spatial development of the cascade until the secondary photons and pairs leave the magnetosphere, and we obtain the pair multiplicity and the energy spectra of the cascade pairs and photons under various conditions. Going beyond previous works, which were restricted to weaker fields (B 3×10 12 G; this tends to suppress synchrotron radiation so that the cascade can develop only at a larger distance from the stellar surface. Nevertheless, we find that the total number of pairs and their energy spectrum produced in the cascade depend mainly on the polar cap voltage BpP 2 , and are weakly dependent on Bp (and P) alone. We discuss the implications of our results for the radio pulsar death line and for the hard X-ray emission from magnetized neutron stars.
Development of health monitoring system using smart intelligent device

Electronic technology plays a vital role in healthcare, not only for sensory equipment but also for communication and recording. As a result, the Internet of Things (IoT) is the most recent communication breakthrough in healthcare. In this work, we present a system that tracks patient health using a Blynk application, a micro-controller as a communication gateway, and sensors. When the output of the detector changes, a buzzer is embedded into the controller to alert the nursing staff. The sensor connects to a micro-controller, which is then interfaced with the liquid-crystal display (LCD) panel and wireless local area network (LAN) to provide notifications. An alert will be sent to the doctor through IoT if the system detects a change in the patient’s pulse rate or blood pressure, and the patient’s heartbeat, blood pressure, and body temperature will be displayed in real-time via Cloud. As a result, an IoT-based patient health monitoring system could save lives by efficiently monitoring patients’ health in real- time.
Peran Edukasi Akuntansi Dalam Penerapan Akuntansi Rumah Tangga Selama Masa Pandemi Covid-19

Studi ini bertujuan untuk menguji peran edukasi akuntansi dalam penerapan akuntansi rumah tangga selama masa pandemi Covid-19. Studi ini menggunakan metode eksperimen yang membagi 20 partisipan menjadi kelompok A dan Kelompok B. Temuan studi ini menunjukkan bahwa bahwa edukasi akuntansi memiliki peran dan pengaruh yang cukup signifikan dalam mendorong penerapan akuntansi rumah tangga. Hal ini dapat dilihat dari respons kelompok eskperimen, yaitu Kelompok A yang telah diberikan edukasi akuntansi melalui sosialisasi video dan juga diberi periode untuk menerapkan akuntansi rumah tangga secara mandiri. Sementara itu, seluruh responden kelompok kontrol, yaitu Kelompok B yang tidak diberikan edukasi akuntansi, tidak melakukan perubahan apapun pada metode pengelolaan keuangan rumah tangga dan tidak berusaha mencari informasi mengenai akuntansi rumah tangga. Hasil studi juga menunjukkan bahwa dari kedua persepsi Kelompok A dan Kelompok B, dapat disimpulkan bahwa dengan suara terbanyak, kemudahan merupakan faktor utama yang dicari oleh rumah tangga dalam menentukan metode pengelolaan keuangan.