Miracle-dz/UniFAR-FTUs huggingface dataset:
Incremental feature selection for efficient classification of dynamic graph bags

Learning and analyzing graph data is one of the most fundamental research areas in machine learning and data mining. Among numerous graph‐based data structures, this paper focuses on a graph bag (simply, bag), which corresponds to a training object containing one or more graphs, and a label is available only for a bag. This type of a bag can represent various real‐world objects such as drugs, web pages, XML documents, and images, among many others, and there have been many researches on models for learning this type of bag data. Within this research context, we define a novel problem of dynamic graph bag classification, and propose an algorithm to solve this problem. Dynamic bag classification aims to build a classification model for bags, which are presented in a streaming fashion, ie, frequent emerging of new bags or graphs over time. Given such changes made to the bag dataset, our proposed algorithm aims to update incrementally the top‐m most discriminative features instead of searching for them from scratch. Incremental gSpan and incremental gScore are proposed as core parts of our algorithm to deal with a stream of bags efficiently. We evaluate our algorithm on two real‐world datasets in terms of both feature selection time and classification accuracy. The experimental results demonstrate that our algorithm derives an informative feature set much faster than the existing one originally designed for targeting static bag data, with little accuracy loss.
132 Myoclonic Status Epilepticus in Nonprogressive Encephalopathy

Brief History-Evolution of the Concept Myoclonic status epilepticus in nonprogressive encephalopathies (MSNE) or Myoclonic encephalopathy in nonprogressive disorders was first described by Dalla Bernardina et al. (1980). The term was used to indicate the existence of a clinical condition characterized by repeated myoclonic status in infants and young children with nonprogressive encephalopathy (Dalla Bernardina et al. 2002).
The Social Construction of a Hate Crime Epidemic

Although definitions vary from state to state, "hate crime" generally means a crime against persons or property motivated in whole or in part by racial, ethnic, religious, gender, sexual orientation and other prejudices. ' Politicians, journalists, interest groups, and some criminologists insist that the United States is experiencing an acrossthe-board hate crime "epidemic. " The use of the epidemic metaphor is meant to dramatize a sharply accelerating hate crime rate. Assertions that a hate crime epidemic exists are almost always accompanied by recommendations for new "hate crime laws" that increase minimum and/or maximum punishment for offenders. This Article attempts to deconstruct the claim that the United States is experiencing a hate crime epidemic. Drawing on the "social construction of reality" perspective,2 we attempt to show how the "reality" of a hate crime epidemic has come to prevail. First, we examine the hate crime epidemic hypothesis and identify its proponents, including advocacy groups, the media, academics, and politicians. Second, we examine the hate crime data collection efforts of the AntiDefamation League (ADL), the Southern Poverty Law Center's
Perancangan Sistem Pengontrol Keamanan Rumah dengan Smart CCTV Menggunakan Arduino Berbasis Telegram

The development of increasingly modern times like now, has make us to always be inspired and provide new ideas in developing appropriate and advanced technology, then it needs a tool that can help humans to facilitate access to obtain information, one of them is home security information, because not a few criminal acts that occur in our homes when we are outside, then more supervision is needed, so with that problem created the idea to make a tool (smart cctv) as our home monitor by utilizing the telegram application as a remote controller, serial camera VC0706 as a media image capture, and using the NodeMCU ESP8266 as the controller. After the prototype test results which is conducted each function of each component used already functions in the order specified, when the device is activated NodeMCU ESP8266 will be directly connected to the specified Wi-Fi network, a camera connected to a surveillance monitor can also automatically take pictures at the same time and send images to the Telegram application when the sensor detects movement, the buzzer will also automatically ring so that it can provide information to those around that at our house there is a crime attempt.
“Laptops are better”:Medical students' perceptions of laptops versus tablets and smartphones to support their learning

In recent years there has been a shift from the expectation that students will be supporting their learning with desktop and laptop computers to the increasing use of tablet computers (Payne, Wharrad, & Watts, 2012). This move has been reflected by initiatives from universities in the US and UK that have provided medical students with tablets to support their studies (Mathis, 2011; The University of Manchester, 2013). Noting this trend and considering how tablets might better support medical students, lecturers within the medical school at Lancaster University sought to find out whether their students – who had been provided with a laptop when they began their studies – perceived that they would be better served in their medical degrees by issuing them with either a laptop or a tablet. In March-April 2013, 137 students completed an online questionnaire which included open questions in which they were also encouraged to qualify their reasons. The quantitative results showed clearly that the students wanted to retain the provision of laptops rather than receiving tablets and this view was reinforced by responses to the open questions. For example, the responses showed that the medical students had a clear preference for writing up reports on a laptop rather than on a tablet. Even so, responses to the questions suggested some limitations in how far the students understood and used the capabilities of tablet computers even amongst those who already owned a tablet and/or a smart phone. Results were surprising in light of the noted trend towards tablet provision and uptake amongst medical students and therefore warrant further consideration. Emerging findings suggest that many of the medical students do not perceive tablets as suitable devices for writing, which brings forward issues relating to the concept of affordances (Parchoma, in press) and possibly medical students’ levels of digital literacy. These and other ideas will be much further developed by the point of the conference. The paper is currently work in progress. A literature review is underway; quantitative results have been analysed and coding has just begun for the analysis of the qualitative results. The results of the study will be presented at the conference for feedback.
Noninferiority Testing in Clinical Trials : Issues and Challenges

Introduction Equivalence and Noninferiority Testing One-Sided and Two-Sided Hypotheses Equivalence Margin delta Choice of delta Ethical Issues and Declaration of Helsinki Conventional Approach versus Role-Reversal Approach Notations and Noninferiority Hypotheses Choice of Noninferiority Margin for the Mean Difference Introduction Proposed delta Motivations Choice of epsilon and Interpretation How Do You Know the Effect Size? Assay Sensitivity Constancy Assumption versus Assay Sensitivity Discussion Choice of Noninferiority Margin for the Mean Ratio and Hazard Ratio Introduction Why Mean Ratio? Mean Ratio for Continuous Endpoints Hazard Ratio for Survival Endpoints Discussion Noninferiority Hypotheses with Binary Endpoints Introduction Noninferiority Hypothesis Based on the Difference or Ratio of Two Proportions NI Hypothesis Based on the Odds Ratio Discussion Two Statistical Approaches for Testing the Noninferiority Hypothesis Introduction One-Sided versus Two-Sided Fixed-Margin Method Synthesis Method Fixed-Margin Method versus Synthesis Method Efficacy Preservation versus Discounting Control of Type I Error Rates Switching between Superiority and Noninferiority Introduction Background Statistical Issues with Simultaneous Testing Decision-Theoretic Views Conditional Type I Error Rate in Superiority Testing Discussion and Concluding Remarks Multiple Historical Studies and Meta-Analysis Introduction Meta-Analysis and Systematic Review Fixed-Effect Model Random-Effects Model Constancy Assumption in the Context of Meta-Analysis Discounting-and-then-Pooling Approach Discussion Three Treatment Groups Introduction Gold-Standard Design Two Test Treatments versus an Active Control Equivalence of Three Test Groups Regulatory Guidances Introduction Guidelines in the Anti-Infective Area with a Binary Endpoint EMEA/CPMP Document FDA Draft Guidance Intention-to-Treat versus Per-Protocol Introduction Background Analyses of Randomized Control Trials Intention-to-Treat Analysis versus Per-Protocol Analysis in Superiority Trials Intention-to-Treat Analysis versus Per-Protocol Analysis in Noninferiority Trials Implementation of an Intention-to-Treat Analysis in Randomized Control Trials Thrombolytic Example Introduction Background CBER Criteria in the Assessment of New Thrombotics in June 1999 Discussion Issues and Challenges Introduction Fundamental Issues Advances in Noninferiority Trials Current Controversial Issues Issues and Challenges Index References appear at the end of each chapter.
Self-Attention for Speech Emotion Recognition

Speech Emotion Recognition (SER) has been shown to beneﬁt from many of the recent advances in deep learning, including recurrent based and attention based neural network architectures as well. Nevertheless, performance still falls short of that of hu-mans. In this work, we investigate whether SER could beneﬁt from the self-attention and global windowing of the transformer model. We show on the IEMOCAP database that this is indeed the case. Finally, we investigate whether using the distribution of, possibly conﬂicting, annotations in the training data, as soft targets could outperform a majority voting. We prove that this performance increases with the agreement level of the annotators.
PMnet: Learning of Disentangled Pose and Movement for Unsupervised Motion Retargeting

In this paper, we propose a deep learning framework for unsupervised motion retar-geting. In contrast to the existing method, we decouple the motion retargeting process into two parts that explicitly learn poses and movements of a character. Here, the ﬁrst part retargets the pose of the character at each frame, while the second part retargets the character’s overall movement. To realize these two processes, we develop a novel architecture referred to as the pose-movement network (PMnet), which separately learns frame-by-frame poses and overall movement. At each frame, to follow the pose of the input character, PMnet learns how to make the input pose ﬁrst and then adjusts it to ﬁt the target character’s kinematic conﬁguration. To handle the overall movement, a normalizing process is introduced to make the overall movement invariant to the size of the character. Along with the normalizing process, PMnet regresses the overall movement to ﬁt the target character. We then introduce a novel loss function that allows PMnet to properly retarget the poses and overall movement. The proposed method is veriﬁed via several self-comparisons and outperforms the state-of-the-art (sota) method by reducing the motion retargeting error (average joint position error) from 7.68 (sota) to 1.95 (ours).
Time-Driven Activity-Based Cost Accounting: A Critical Review

Purpose – This paper examines the claims made about an alternative approach for the determination of overhead costs referred to as the time-driven activity-based model. Design/methodology/approach – The approach employed is based on examining the application of the model as developed in the literature and explores the components involved in the implementation process of time-driven activity-based accounting. Originality/value – As a consequence of the analysis and comparison of the differences between activity-based costing and time-driven activity-based accounting are minimal and questions remain unanswered as to the validity of the claims made about the timedriven activity-based model.
Comparison of Wired and Wireless Bio-Electrical Impedance Fluid Status Monitoring Devices and Validation to Body Mass and Urine Specific Gravity Changes Following Mild Dehydration

Abstract : Dehydration is a major health and performance risk in military operations and there is a need for rapid, non-invasive and early detection. A fluid status assessment method, ZOE2, is FDA approved for fluid status monitoring. The ZOE2 measures thoracic bio-electrical impedance. A new wireless version of the ZOE2, the ZOE wireless (ZOEW), has been developed and proposed for assessment of fluid status in the field. Some investigations have reported impedance as a valid measure of hydration status in clinical or controlled settings. However, there is speculation as to the utility of bio-electrical impedance post-exercise or in a field setting. The objectives of this study were fourfold: 1) to compare biological measurements of the new ZOEW monitor with the FDA approved and patented ZOE2 monitor currently being used in the healthcare market; 2) to assess the test-retest reliability of the ZOEW monitor; 3) to compare the sensitivity and validity of the ZOEW monitor and the ZOE2 monitor to assess mild hydration status changes post-exercise in a field setting; 4) to assess the usability of the ZOEW monitor. Thirty-two participants from the USAFA Wrestling Team were recruited. Nude body weight, urine specific gravity, ZOE2 and ZOEW measurements were taken before and after a typical 90- minute wrestling practice session. Usability was tested when participants were asked to complete a survey to assess perceptions of ease of use. Similar values were obtained from the ZOE2 and ZOEW monitors. Although both body weight and urine specific gravity changes were significantly different from pre- to post-practice indicating mild dehydration, no significant differences were detected between pre- to post-practice for the ZOE2 or ZOEW device. Bio-electrical impedance, as measured by the ZOEW monitor and the ZOE2 monitor in this study, does not appear to be a valid measure of mild, post-exercise hydration status change as compared to body weight and urine specific gravity.
A novel diG motif in ORF3a protein of SARS-Cov-2 for intracellular transport

The ongoing SARS-CoV-2/COVID-19 pandemic caused a global public health crisis. Yet, everyone’s response to SARS-CoV-2 infection varies, and different viral variants confer diverse pathogenicity. Thus, it is imperative to understand how viral determinants contribute to COVID-19. Viral ORF3a protein is one of those viral determinants, as its functions are linked to induction of cell and tissues damages, disease severity and cytokine storm that is a major cause of COVID-19-related death. ORF3a is a membrane-associated protein. Upon synthesis, it is transported from endoplasmic reticulum, Golgi apparatus to plasma membrane and subcellular endomembranes including endosomes and lysosomes. However, how ORF3a is transported intracellularly remains elusive. The goal of this study was to carry out a systematic mutagenesis study to determine the structural relationship of ORF3a protein with its subcellular locations. Single amino acid (aa) and deletion mutations were generated in the putative function-relevant motifs and other regions of interest. Immunofluorescence and ImageJ analyses were used to determine and quantitate subcellular locations of ORF3a mutants in comparison with wildtype ORF3a. The wildtype ORF3a localizes predominantly (Pearson’s coefficients about 0.8) on the membranes of endosomes and lysosomes. Consistent with earlier findings, deletion of the YXXΦ motif, which is required for protein export, retained ORF3a in the Golgi apparatus. Interestingly, mutations in a double glycine (diG) region (aa 187–188) displayed a similar phenotype to the YXXΦ deletion, implicating a similar role of the diG motif in intracellular transport. Indeed, interrupting any one of the two glycine residues such as deletion of a single (dG188), both (dG187/dG188) or substitution (G188Y) of these residues led to ORF3a retention in the Golgi apparatus (Pearson’s coefficients ≥0.8). Structural analyses further suggest that the diG motif supports a type-II β-turn between the anti-parallel β4 and β5 sheets and connects to the YXXΦ motif via hydrogen bonds between two monomers. The diG- YXXΦ interaction forms a hand-in-hand configuration that could facilitate dimerization. Together, these observations suggest a functional role of the diG motif in intracellular transport of ORF3a.
Automatic Labeling of Topic Models Using Graph-Based Ranking

Generated topic label, an alternative representation of topics learned by topic model, is widely used to help the user interpret the topics more efficiently. A major challenge now is to label a discovered topic accurately in an objective way. This article introduces a novel graph-based ranking model (TLRank), to find a meaningful topic label with high Relevance, Coverage, and Discrimination. The model applies a specific strategy that suppresses or enhances the matrix transition probability according to the textual similarity between vertices (sentences) and the characteristics of vertices respectively. Moreover, to boost diversity and enhance performance, TLRank scores the candidate sentences and refrains redundancy of topic labels simultaneously in a single labeling process. In our experiments, the evaluation results showed that the TLRank model significantly and consistently outperformed the prevailing state-of-the-art and classic models in topic labeling task.
The Impact of Competitive Quasi-Market on Service Delivery in Benue State University, Makurdi Nigeria

This research the impact of competitive quasi market on service delivery in Benue State University, Makurdi Nigeria. Both primary and secondary source of data and information were used for the study and questionnaire was used to extract information from the purposively selected respondents. The population for this study is one hundred and seventy three (173) administrative staff of Benue State University selected at random. The statistical tools employed was the classical ordinary least square (OLS) and the probability value of the estimates was used to tests hypotheses of the study. The result of the study indicates that a positive relationship exist between Competitive quasi marketing in Benue State University, Makurdi Nigeria (CQM) and Transparency in the service delivery (TRSP) and the relationship is statistically significant (p<0.05). Competitive quasi marketing (CQM) has a negative effect on Observe Competence in Benue State University, Makurdi Nigeria (OBCP) and the relationship is not statistically significant (p>0.05). Competitive quasi marketing (CQM) has a positive effect on Innovation in Benue State University, Makurdi Nigeria (INVO) and the relationship is statistically significant (p<0.05) and in line with a priori expectation. This means that a unit increases in Competitive quasi marketing (CQM) will result to a corresponding increase in innovation in Benue State University, Makurdi Nigeria (INVO) by a margin of 22.5%. It was concluded that government monopoly in the provision of certain types of services has greatly affected the quality of service experience in the institution. It was recommended among others that the stakeholders in the market has to be transparent so that the system will be productive to serve the society effectively
Differences between English and Chinese in the Implementation of the RSA algorithm

In this paper, we explore the implementation of RSA Public Key Cryptography in both English and Chinese. We begin by examining the history of ancient and modern cryptography, public key cryptography, the key distribution problem and how the RSA algorithm solves the key distribution problem. We then show how the RSA algorithm works in practice, on both English and Chinese characters, words and sentences. We end with a comparison of differences in implementation between the two languages.
Evaluating Health Care Financing Reforms in Africa

__Abstract__ Africa is on a steady economic growth path. Over the last decade, most Sub-Saharan African (SSA) countries outperformed European and North-American countries’ growth rates, as shown in Figure 1. A number of SSA countries are among the fastest growing economies in the world, coming from very low income levels, and moderate growth is predicted for most of these countries (International Monetary Fund, 2014; Rodrik, 2014). However, trends in the health status of the African population are lagging behind. Since 1990, most regions in the world have achieved a reduction in child mortality of at least 60 percent and Eastern Asia even reduced the number of children not reaching their fifth birthday by 74 percent. Over that same period, SSA achieved a reduction of only 45 percent (calculations based on Millennium Development Goals Report (2014)). Not only do trends in health status lag behind in SSA, the levels are also considerably lower. Almost half of all child deaths worldwide occur in SSA and disparities in child mortality between the poor and the better off are increasing. SSA has the highest maternal mortality ratio with 510 deaths per 100,000 live births, 70 percent of new HIV infections occur in this region (United Nations, 2014) and frequent outbreaks of other infectious diseases like Ebola create an important threat to population health. In addition to these infectious diseases, increased levels of non-communicable diseases associated with economic development create a “double burden of disease” (Maher et al., 2010). This combination of a high disease burden and steady economic growth creates both the need and the opportunity for health care financing reforms to improve equitable access to good quality health care, the topic of this thesis.
A rate‐maximizing spectrum sharing algorithm for cognitive radio networks with generic resource constraints

Algorithms for spectrum sharing over resource‐limited cognitive radio networks are often designed to solve specific problems. This means that a certain algorithm deals specifically with a certain limited resource, and is not suitable for other resources. This limitation violates the software‐defined networking philosophy, where a scheme has to be reprogrammable to cope with different limited resources that can dynamically arise depending on network conditions. In this work, we investigate the problem of spectrum sharing in resource‐limited cognitive radio networks. Specifically, we introduce a novel spectrum sharing algorithm that is compatible with software‐defined networks, in the sense that it can be reprogrammed to support multiple constraints on resources of different types. A main feature of the proposed scheme is that computations could be distributed across multiple processing units to reduce computational complexity on each unit. In addition, the proposed algorithm is equipped with a fairness scheme. Simulation results demonstrate the efficacy of the proposed scheme.