Miracle-dz/UniFAR-FTUs huggingface dataset:
Families of $m$-variate distributions with given margins and $m(m-1)/2$ bivariate dependence parameters

A class of ra-variate distributions with given margins and m(m ? l)/2 dependence parameters, which is based on iteratively mixing conditional distributions, is derived. The family of multivariate normal distributions is a special case. The motivation for the class is to get parametric families that have m(m ? l)/2 dependence parameters and properties that the family of multivariate normal distributions does not have. Properties of the class are studied, with details for (i) conditions for bivariate tail dependence and non-trivial limiting multivariate extreme value distributions and (ii) range of dependence for a bivariate measure of association such as Kendall's tau.
Effect of network topology on the ordering dynamics of voter models

We introduce and study the reverse voter model, a dynamics for spin variables similar to the well‐known voter dynamics. The difference is in the way neighbors influence each other: once a node is selected and one among its neighbors chosen, the neighbor is made equal to the selected node, while in the usual voter dynamics the update goes in the opposite direction. The reverse voter dynamics is studied analytically, showing that on networks with degree distribution decaying as k−v, the time to reach consensus is linear in the system size N for all v > 2. The consensus time for link‐update voter dynamics is computed as well. We verify the results numerically on a class of uncorrelated scale‐free graphs.
A Survey on Design, Actuation, Modeling, and Control of Continuum Robot

In this paper, we describe the advances in the design, actuation, modeling, and control field of continuum robots. After decades of pioneering research, many innovative structural design and actuation methods have arisen. Untethered magnetic robots are a good example; its external actuation characteristic allows for miniaturization, and they have gotten a lot of interest from academics. Furthermore, continuum robots with proprioceptive abilities are also studied. In modeling, modeling approaches based on continuum mechanics and geometric shaping hypothesis have made significant progress after years of research. Geometric exact continuum mechanics yields apparent computing efficiency via discrete modeling when combined with numerical analytic methods such that many effective model-based control methods have been realized. In the control, closed-loop and hybrid control methods offer great accuracy and resilience of motion control when combined with sensor feedback information. On the other hand, the advancement of machine learning has made modeling and control of continuum robots easier. The data-driven modeling technique simplifies modeling and improves anti-interference and generalization abilities. This paper discusses the current development and challenges of continuum robots in the above fields and provides prospects for the future.
Efficient and Accurate Synthesis for Array Pattern Shaping

Array pattern synthesis (APS) aims to create the desired array pattern as closely as possible to the prescribed mask template by varying the element excitations of the array. Herein, an efficient approach for the APS to control the sidelobe level is proposed. After designing the mask template to meet the prescribed sidelobe requirements and the waveform pattern, a set of element excitations is calculated through the Fourier transform performed on the projection the waveform pattern onto the mask template. Then, a desired array pattern can be synthesized from this updated set of excitation coefficients. The proposed APS approach directly presents a mathematical formulation of the exact set of excitations without any iterative optimization process. The proposed method is particularly suited for many array elements in linear antenna array. Thus, the proposed APS achieves substantial improvements in terms of computation complexity, performance, and ease of implementation in the algorithm when compared with conventional methods. Several simulation results are provided to verify the efficacy and effectiveness of the proposed method.
Clinical Outcomes after Immunotherapies in Cancer Setting during COVID-19 Era: A Systematic Review and Meta-Regression

Background: This study aims to describe COVID-19–related clinical outcomes after immunotherapies (ICIs) for cancer patients. Methods: In this meta-analysis, we searched databases to collect data that addressed outcomes after immunotherapies (ICIs) during the COVID-19 pandemic. The primary endpoint was COVID-19–related mortality. Secondary endpoints included COVID-related hospital readmission, emergency room (ER) visits, opportunistic infections, respiratory complications, need for ventilation, and thrombo-embolic events. Pooled event rates (PERs) were calculated and a meta-regression analysis was performed. Results: A total of 262 studies were identified. Twenty-two studies with a total of forty-four patients were eligible. The PER of COVID-19–related mortality was 39.73%, while PERs of COVID-19–related ER visits, COVID-19–related pulmonary complications, and COVID-19–related ventilator needs were 40.75%, 40.41%, and 34.92%, respectively. The PER of opportunistic infections was 34.92%. The PERs of the use of antivirals, antibiotics, steroids, prophylactic anticoagulants, and convalescent plasma were 62.12%, 57.12%, 51.36%, 41.90%, and 26.48%, respectively. There was a trend toward an association between previous respiratory diseases and COVID-19–related mortality. Conclusion: The rates of COVID-19–related mortality, ER visits, pulmonary complications, need for a ventilator, and opportunistic infections are still high after ICIs during the COVID-19 pandemic. There was a trend toward an association between previous respiratory diseases and COVID-19–related mortality.
The High Energy Solar Spectroscopic Imager (HESSI) mission

The primary scientific objective of the High Energy Solar Spectroscopic Imager (HESSI) Small Explorer mission selected by NASA is to investigate the physics of particle acceleration and energy release in solar flares. The HESSI instrument utilizes Fourier-transform imaging with 9 bi-grid rotating modulation collimators and cooled germanium detectors to make observations of X-rays and γ-rays from ∼3 keV to ∼17 MeV. It will provide the first imaging spectroscopy in hard X-rays, with ∼2 arcsec angular resolution, time resolution of 2s for full image (tens of ms for crude image), and ∼1 keV energy resolution; the first solar γ-ray line spectroscopy with ∼1–5 keV energy resolution; and the first solar γ-ray line and continuum imaging, with ∼36-arcsec angular resolution. The instrument is mounted on a Sun-pointed spin-stabilized spacecraft, and is planned to be launched in July 2000 into a 600 km-altitude, 38° inclination orbit. HESSI will provide detailed information on the energetic particle populations at th.
Rural Classes and Credit Participation: The Itasy Livelihood Classes (Madagascar) Between Risk-aversion and Debt Capacity

ABSTRACT While technical and economic factors are traditionally advanced to explain the failures of microfinance, a growing literature explores how moral factors and socioeconomic norms help to shape financial behaviors. In order to examine this issue in more depth, we conducted an empirical analysis of the links between socioeconomic stratification and financial behaviors. This original perspective enriches the literature on financial inclusion in the under-explored Malagasy context. Using data from the 2008 Itasy Observatory survey, we conducted a cluster analysis to identify five classes of rural households, ranging from a very poor and insecure group to an upper group of educated farming and non-farming households. Using a multinomial treatment-effects model, we established distinct ‘class-based’ credit behaviors showing that financial needs vary according to the users’ socioeconomic profile. What is more, such financial behaviours can be explained by taking social factors into account in addition to economic ones.
Fast shape retrieval using term frequency vectors

Similarity based retrieval of visual shapes is performed using a vector space technique originally developed for document retrieval. In that technique, a document is represented by a vector in which each component is the frequency of occurrence of a specific term (word or phrase) in that document. Similarity between query and database documents is measured by the normalized inner product of the vectors. In the shape retrieval system, contours are partitioned into perceptually significant segments that have a role analogous to words in a document. Short sequences of segments are analogous to phrases. Each shape is represented by a vector of the frequency of occurrences of each term (segments or segment sequences). Fast retrieval is achieved by using a B+ tree and inverted lists. Additionally, a new similarity measure is introduced and shown to result in improved performance over the normalized inner product.
Risk factors profile of coronary artery disease among medical students at Al-Azhar University, Cairo

Background: Coronary artery disease (CAD) represents an increasing public health problem worldwide. Measuring CAD risk factors among young adults will be helpful in reduction and control of their future risk to CAD also and other cardiovascular disease (CVD). Objective: To identify the pattern of CAD risk factors among Al-Azhar University medical students (males and females) of all educational grades. Methodology: A comparative cross sectional study was conducted on 1142 (755 and 387) medical students at the Faculty of Medicine- Boys and Girls respectively-Al-Azhar University in Cairo. Data were collected through a self-administered questionnaire, anthropometric and blood pressure measurements were taken. Also, biochemical investigations for blood glucose and lipid profile were conducted on a subsample of 24% from total sample. SPSS version 20 was used for data analysis. Results: The mean age of participants was 21.17±1.78 with males constituting two thirds of the sample. The majority of participants had at least one risk factor to CAD. The most prevalent risk factor of CAD was insomnia (73.5%) followed by consumption of carbonated beverages (62.3%) and fatty meat (46.4%). Also, stress (46.6%), overweight/or obesity (34.2%), physical inactivity (34%) and hypertension (19.5%) were predominant risk factors. Whereas, smoking prevalence was low (7.1%). Dyslipidemia was detected among 23% of the studied subsample. Conclusion : CAD risk factors were highly prevalent among medical students. However, smoking was present only among males and with a low prevalence. Initiation of health educational programs to raise awareness about CAD risk factors and periodic screening programs to detect CAD risk factors are recommended. 2022; 3(2):119-130
Finding Communities of Related Genes

We present an automated method of identifying communities of functionally related genes from the biomedical literature. These communities encapsulate human gene and protein interactions and identify groups of genes that are complementary in their function. We use graphs to represent the network of gene cooccurrences in articles mentioning particular keywords, and find that these graphs consist of one giant connected component and many small ones. In addition, the vertex degree distribution of the graphs follows a power law, whose exponent we determine. We then use an algorithm based on betweenness centrality to identify community structures within the giant component. The different structures are then aggregated into a final list of communities, whose members are weighted according to how strongly they belong to them. Our method is efficient enough to be applicable to the entire Medline database, and yet the information it extracts is significantly detailed, applicable to a particular problem, and interesting in and of itself. We illustrate the method in the case of colon cancer and demonstrate important features of the resulting communities.
The Effects of Innovation Adoption and Social Factors between Sustainable Supply Chain Management Practices and Sustainable Firm Performance: A Moderated Mediation Model

The aim of this study was to develop higher-order scales for assessing sustainable supply chain management practices, innovation adoption, and sustainable firm performance in the restaurant sector. Three different higher-order scales were developed for assessing the SSCM, SFP and innovation adoption. The first scale for SSCM higher-order construct consisted of service–product supply chain management practices (SPSSCM), service–setting supply chain management practices (SSSSCM), and service–delivery supply chain management practices (SDSSCM). The second higher-order scale for sustainable firm performance (SFP) consisted of economic, operational, environmental, and socio-cultural performance. The third higher-order scale for innovation adoption (INNO) consisted of “product- and process-based innovation”, “marketing-based innovation”, “technology-based innovation” and “organizational innovation”. The face, content, construct, convergent, and discriminant validity was tested using pilot study, expert opinion, EFA, and CFA. With 178 responses collected from restaurateurs, managers, and supervisors of casual restaurants in Prachuap Khiri Khan province in Thailand, this study evaluates the direct effects of SSCM on SFP. It further evaluates the mediating role of innovation adoption between sustainable supply chain management practices and firm performance and the moderated mediation effects of socio-demographic factors such as age, gender, education, and experience. The results reveal that sustainable supply chain management practices can positively lead to sustainable firm performance. However, irrespective of the indirect effects of socio-demographic factors, adopting innovation completely mediates the relationship between sustainable supply chain management practices and firm performance.
The nature of the glass and gel transitions in sticky spheres

Institute of Industrial Science, University of Tokyo,4-6-1 Komaba, Meguro-ku, Tokyo, 153-8505, Japan. (Dated: 22nd September 2014)Glasses [1] and gels [2] are the two dynamically arrested, disordered states of matter. Despitetheir importance, their similarities and di erences remain elusive, especially at high density. Weidentify dynamical and structural signatures which distinguish the gel and glass transitions in acolloidal model system of hard and \sticky" spheres. Gelation is induced by crossing the gas-liquidphase-separation line [3{5] and the resulting rapid densi cation of the colloid-rich phase leads to asharp change in dynamics and local structure. Thus, we nd that gelation is rst-order-like and canoccur at much higher densities than previously thought: far from being low-density networks, gelshave a clear \thermodynamic" de nition which nevertheless leads to a non-equilibrium state witha distinct local structure characteristic of a rapidly quenched glass. In contrast, approaching theglass transition, the dynamics slow continuously accompanied by the emergence of local ve-foldsymmetric structure. Our ndings provide a general thermodynamic, kinetic, and structural basisupon which to distinguish gelation from vitri cation.I. INTRODUCTION
Computing More Consistent Multigroup Nuclear Data Covariances

Abstract It is not uncommon that the covariances of multigroup nuclear data do not obey the sum rules of nuclear data. We present a matrix nearness problem of finding a nearest symmetric matrix with given null vectors and solve it when the distance is measured in the Frobenius norm. The problem appears to be new. We propose that the method should be used to find nearest consistent multigroup covariance matrices with respect to the sum rules of redundant nuclear data. If the multigroup covariances cannot be easily interpreted in a consistent manner, there is some ambiguity in choosing values for the covariances that are not explicitly mentioned. We present and compare a simple and a heuristic characterization method. Three practical examples are processed and analyzed: relative covariances of cross sections of 9440Zr and absolute covariances of cross sections of 5024Cr and 23290Th. We demonstrate that satisfactory results can be achieved. We discuss the properties of the proposed method and the characterization methods and suggest possible improvements. The methods can be used as a part of a quality assurance program and might be valuable additions to nuclear data processing codes.
Ultrafast line detector

Abstract. This article introduces the fastest line detector so far published in the literature. This algorithm is 14.88 times faster than the next fastest line detector, the EDLines, and 94.7 times faster than the line segment detector. It is hundreds of times faster and more reliable than the Standard Hough Transform. The article also introduces an ingeniously simple method for detecting and combining patterns. The algorithm takes advantage of several look-up tables to recognize and fit straight-line patterns. As the first step, it recognizes any possible 4 × 4 pixel line patterns among the binary edge pixels and then uses several small look-up tables to decide whether the connected patterns form a line or not. It is specially designed for real-time processing of the high-resolution images such as the ones used in computer vision applications.
Estimating Average Daily Traffic on Low-Volume Roadways in Louisiana

Traffic volume is an important parameter that agencies use as a decisive factor, especially at the time of design, maintenance, and operation of roadways. Thus, its correct estimation is very essential. There are already a few established proprietary products available on the market that can predict traffic volumes. In addition, past studies have used several mathematical models to predict traffic volume. Relatively fewer studies have been conducted on predicting traffic volume on low-volume roadways. To bridge the gap on the prediction of traffic volume for low- and high-volume roadways, this study seeks to find practical, cost-effective, and progressive methods of estimating and classifying traffic on low-volume rural roadways. Across the state of Louisiana, 395 locations with low traffic volumes of less than 500 vehicles per day were selected. Census tract data was used to extract demographic and socioeconomic information for each location. Two prediction models—linear regression and random forest regression models—were developed to predict traffic volumes on these low-volume roadways. The results showed that the linear regression model had the highest predictive accuracy, with R-square of 0.979 and root mean square error of 70.26 compared with the RMSE of 110.23 for the random forest regression model. Both models found functional class, land use, number of lanes, population density, median age, median household income, and household density significantly affecting the traffic volume.
Spectrum of Cardiovascular Autonomic Dysfunction and 24-hour Blood Pressure Variability in Idiopathic Parkinson's Disease

Background: Uncertainty prevails regarding the patterns of autonomic dysfunction in patients with idiopathic Parkinson's disease (IPD). This study was undertaken with the aim of assessing the complete spectrum of cardiovascular autonomic function tests (CAFTs) and blood pressure variability patterns in IPD patients while comparing the same with age-matched controls. Methods: Patients with IPD presenting to the Christian Medical College and Hospital from December 2016 to November 2018 along with age-matched controls were prospectively evaluated using CAFTs. The IPD patients also underwent ambulatory blood pressure (BP) monitoring (ABPM), and the diurnal systolic BP differences were used to classify into dippers (10-20%), non-dippers (0–10%), reverse dippers (<0%), and extreme dippers (>20%). Results: Autonomic dysfunction (AD) was prevalent in 41 (68.3%) IPD patients even in early disease (median (inter-quartile range) symptom duration 2 (1–4) years, mean Hoehn and Yahr (H&Y) stage 2 (1.5–2.8). Both sympathetic and parasympathetic parameters were impaired among IPD patients when compared to healthy controls. (E: I ratio 1.17 ± 0.12 vs 1.26 ± 0.14 (P < 0.001), Valsalva ratio (VR) 1.33 ± 0.27 vs 1.55 ± 0.25 (P < 0.001), PRT100 9.6 ± 8.0 vs 3.1 ± 1.8 (P < 0.001), tilt-up SBPAvg change 8.8 (4.2–13.8) vs 1.8 (−2.9–6.1) (P < 0.001), tilt-up HRAvg change 4.8 (2.2–8.2) vs 1.9 (−0.7–5.1) (P < 0.001). BP variability was demonstrated in 47 (79.7%) of IPD patients, with reverse dipping pattern in 28 (47.5%) seen more frequently in this cohort. Conclusions: Timely detection of AD may be helpful not only in recognizing IPD in its pre-motor stages but also in optimizing management for this population of patients. BP variability and abnormal dipping patterns on ABPM can be a potential marker of dysautonomia.
Constant Weight Polar Coded Orthogonal Space-Time Block Codes for Dimmable Indoor MIMO-VLC Systems

The concatenation of constant weight polar code (CWPC) with orthogonal space-time block code (OSTBC), known as CWPC-OSTBC scheme is proposed for the indoor multiple-input multiple output visible light communication (MIMO-VLC) systems in this letter. The CWPC helps to mitigate against flickering, provides desired dimming targets, and coding gain while the OSTBC achieves MIMO diversity gain. Flicker mitigation and dimming control are obtained based on the modified Knuth balancing method with enhanced prefix coding. This method does not utilise lookup table and thus, it is practicable in the real-time. Numerical results are presented to discuss the channel capacity and bit-error-rate (BER) performance of the proposed CWPC-OSTBC scheme considering different parameters. The results show that increasing the transmission antennas of the OSTBC system provides diversity gains. More so, the CWPC-OSTBC scheme yields an improved coding gain compared to polar code without balancing and other state-of-the-art methods.
Moving toward Praxis: Disrupting the Banking Model in English Teacher Education

ABSTRACT In this article, we reflect on pedagogy we implemented to help teachers enact praxis in their classrooms. We explore how our own classroom spaces inadvertently reified banking education and ways we can disrupt the “schoolishness of school” in teacher preparation. We share a series of reflective vignettes from each author followed by a collaboratively written discussion with hope that readers will also explore their culturally relevant instruction and guide teachers to go beyond awareness of students’ ethnic and cultural diversity to achieve authentic commitment to educational equity and justice.
Homotopy commutativity of -spaces with finitely generated cohomology

We show that a simply connected homotopy associative and homotopy commutative mod 3 H -space with (cid:12)nitely generated mod 3 cohomol- ogy is homotopy equivalent to a (cid:12)nite product of K ( Z ; 2), Sp (2), the three-connected cover Sp (2) h 3 i and the homotopy (cid:12)ber Sp (2) h 3;3 i i of the map [3 i ] : Sp (2) ! K ( Z ; 3) for i (cid:21) 1. Our result also shows that a connected C p -space in the sense of Sugawara with (cid:12)nitely generated mod p cohomology has the homotopy type of a (cid:12)nite product of K ( Z ; 1), K ( Z ; 2) and K ( Z =p i ; 1) for i (cid:21) 1.
A comment on anti-brane singularities in warped throats

We compute the imaginary self-dual (ISD) and imaginary anti-self-dual (IASD) fluxes for the Klebanov-Strassler background perturbed by a stack of p anti-D3 branes. We show that, at linear order in p, they both have a singularity in the near-brane region. While one can argue that the IASD flux may disappear at full non-linear level, no such argument exists for the ISD mode. An analogy with anti-D6 backreaction suggests that such singularity may survive once full backreaction is taken into account and may be a universal feature of anti-brane solutions.