Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast Collision Culling in Large-Scale Environments Using GPU Mapping Function

This paper presents a novel and efficient GPU-based parallel algorithm to cull non-colliding object pairs in very large-scale dynamic simulations. It allows to cull objects in less than 25ms with more than 100K objects. It is designed for many-core GPU and fully exploits multi-threaded capabilities and data-parallelism. In order to take advantage of the high number of cores, a new mapping function is defined that enables GPU threads to determine the objects pair to compute without any global memory access. These new optimized GPU kernel functions use the thread indexes and turn them into a unique pair of objects to test. A square root approximation technique is used based on Newton's estimation, enabling the threads to only perform a few atomic operations. A first characterization of the approximation errors is presented, enabling the fixing of incorrect computations. The I/O GPU streams are optimized using binary masks. The implementation and evaluation is made on largescale dynamic rigid body simulations. The increase in speed is highlighted over other recently proposed CPU and GPU-based techniques. The comparison shows that our system is, in most cases, faster than previous approaches.
Flexible Multi-Objective Particle Swarm Optimization Clustering with Game Theory to Address Human Activity Recognition Fully Unsupervised

Most research in human activity recognition is supervised, while non-supervised approaches are not completely unsupervised. In this paper, we provide a novel ﬂexible multi-objective particle swarm optimization (PSO) clustering method based on game theory (FMOPG) to discover human activities fully unsupervised. Unlike conventional clustering methods that estimate the number of clusters and are very time-consuming and inaccurate, an incremental technique is introduced which makes the proposed method ﬂexible in dealing with the number of clusters. Using this technique, clusters that have a better connectedness and good separation from other clusters are gradually selected. To improve the convergence speed of PSO in achieving the best solution and dealing with spherical shape clusters, updating of particles’ velocity is modiﬁed using the concept of mean-shift vector. To solve multi-objective optimization problems, Nash equilibrium in game theory is used to select the optimal solution on the pareto front. Gaussian mutation is also employed on the pareto front to generate diverse solutions and create a balance between exploitation and exploration. The proposed method is compared with state-of-the-art methods on ﬁve challenging datasets. FMOPG has improved clustering accuracy by 3.65% compared to automated methods. Moreover, the incremental technique has improved the clustering time by 71.18%.
Data Mining Patterns of Thought

Modern educational and psychological measurements are governed by models that do not allow for identification of patterns of student thought. However, in many situations, including diagnostic assessment, it is more important to understand student thought than to score it. We propose using entropy-based clustering to group responses to both a standard achievement test and a test specifically designed to reveal different facets of student thinking. We show that this approach is able to identify patterns of thought in these domains, although there are limitations to what information can be obtained from multiple choice responses alone.
Effect of Thymus vulgaris on Initial Cell Attachment and Preformed Biofilm of Salmonella Enteritidis

Bacteria within a biofilm have a distinct phenotype from planktonic cells and generally show higher tolerance to antimicrobial agents, such as disinfectant treatments and antibiotics. Due to the increased tolerance against antimicrobial treatments, biofilms are hard to eradicate and they cause all kinds of problems in medical and industrial settings. Therefore, the purpose of this study was to examine the influence of Thymus vulgaris essential oil on the initial adhesion and preformed biofilm of Salmonella Enteritidis. Results for antimicrobial activity of Th. vulgaris essential oil obtained using broth microdilution method against S. Enteritidis were identical for all tested isolates (MIC/MFC=0.156/0.3125 µL/mL). In order to understand the anti-biofilm action of essential oil (EO), its effect was tested on both the initial cell attachment by planktonic cells as well as on preformed biofilms. Obtained results indicated that the effect of Th. vulgaris essential oil on initial cell attachment of tested isolates SE4, SE5, SE7 and SE9 was dosage dependent manner, although even at 0.5×MIC biomass attachment was reduced by 74.2%, 77.7%, 73.6% and 70.1%, respectively. Fairly high, but not complete, inhibition of cell attachment was achieved using 1×MIC of this EO. Using 1×MIC, biomass attachment of tested isolates SE4, SE5, SE7 and SE9 was reduced for 91.4%, 90.2%, 90.6% and 88.4%, respectively. When the same EO was tested against a preformed biofilm, its inhibitory effect was reduced greatly.
Cloning, Expression and Purification of L7/L12 Ribosomal Gene of Brucella melitensis 16M

Brucellosis is an important zoonotic disease transmitted to human and is also responsible for causing huge economic loss to livestock industry worldwide. Numerous candidate antigens of Brucella have been reported to induce protective effect against the organism, among which L7/L12 is an important one. In this study, the L7/L12 ribosomal gene of Brucella melitensis 16M was PCR amplified and cloned into prokaryotic expression vector pPROExHTb and the positive clones were confirmed by restriction enzyme digestion and sequencing. Recombinant clone was induced with 1mM of IPTG and the expressed protein was purified by Nickel affinity chromatography and quantified. The purified the recombinant L7/L12 protein was subjected to western blot analysis with hyperimmune serum, raised against it in rabbits and also with pooled clinical serum which revealed specific band of 16kDa confirming its antigenicity. This recombinant L7/L12 antigen can be used as protective antigen for control of brucellosis.
Manual Clustering Reﬁnement using Interaction with Blobs

The huge amount of different automatic clustering methods emphasizes one thing: there is no optimal clustering method for all possible cases. In certain application domains, like genomics and natural language processing, it is not even clear if any of the already known clustering methods sufﬁce. In such cases, an automatic clustering method is often followed by manual reﬁnement. The reﬁned version may then be used as either an illustration, a reference, or even an input for a rule based or other machine learning algorithm as a new clustering method. In this paper, we describe a novel interaction technique to manual cluster reﬁnement using the metaphor of soap bubbles, represented by special implicit surfaces (blobs). For instance, entities can simply be moved inside and outside of these blobs. A modiﬁed force-directed layout process automatically arranges entities equidistant on the screen. The modiﬁcations include a reduction to the expected amount of computation per iteration down to O ( | V | log | V | + | E | ) in order to achieve a high response time for use in an interactive system. We also spend a considerable amount of effort making the display of blobs fast enough for an interactive system.
Longitudinal Flight Dynamics Modeling and Stability Analysis of the Flapping Wing Aircraft with Folding Wing

Foldable Flapping Wing Aircraft is a kind of aircraft that generates lift and thrust with foldable wings flapping up and down. In this paper, the kinematics model of foldable Flapping Wing Aircraft is constructed with reference to bats. The aerodynamic modeling method is a combination of the quasi-constant model and the elemental theory with wash effect. The longitudinal dynamics model is constructed through multi-rigid body finite element method. Robust variable gain control method is used to analyze the closed-loop longitudinal stability of foldable Flapping Wing Aircraft
Site‐specific modulators control how geophysical and socio‐technical drivers shape land use and land cover

Human utilisation of natural resources is the most important direct driver of land cover patterns in the Anthropocene. Here, we present a conceptual framework for how the effects of geophysical drivers (e.g., topography, soil, climate, and hydrol-ogy) and socio ‐ technical drivers (e.g., technology, legal regulation, economy, and culture) on land use and land cover are shaped by site ‐ specific modulators such as local topography and social and cultural backgrounds of individuals. The framework is demonstrated by examples from the literature, with emphasis on the north ‐ western European lowland agricultural region. For example, a geophysical driver such as slope of the terrain constrains land use and is thereby an important driver of land covers, for example, forests. This effect of slope can vary depending on site ‐ specific modulators such as local soil fertility, local topographic heterogeneity, and shifting human population densities. Acknowledging the importance of site ‐ specific modulators on how geophysical and socio ‐ technical drivers shape land use and land covers will strengthen research on human – environmental interactions – especially important with the future increase in human populations in a constant changing world.
A sequential mechanism for clathrin cage disassembly by 70-kDa heat-shock cognate protein (Hsc70) and auxilin

An essential stage in endocytic coated vesicle recycling is the dissociation of clathrin from the vesicle coat by the molecular chaperone, 70-kDa heat-shock cognate protein (Hsc70), and the J-domain-containing protein, auxilin, in an ATP-dependent process. We present a detailed mechanistic analysis of clathrin disassembly catalyzed by Hsc70 and auxilin, using loss of perpendicular light scattering to monitor the process. We report that a single auxilin per clathrin triskelion is required for maximal rate of disassembly, that ATP is hydrolyzed at the same rate that disassembly occurs, and that three ATP molecules are hydrolyzed per clathrin triskelion released. Stopped-flow measurements revealed a lag phase in which the scattering intensity increased owing to association of Hsc70 with clathrin cages followed by serial rounds of ATP hydrolysis prior to triskelion removal. Global fit of stopped-flow data to several physically plausible mechanisms showed the best fit to a model in which sequential hydrolysis of three separate ATP molecules is required for the eventual release of a triskelion from the clathrin–auxilin cage.
Escherichia coli O157:H7 and Other E. coli Strains Share Physiological Properties Associated with Intestinal Colonization

ABSTRACT Escherichia coli isolates (72 commensal and 10 O157:H7 isolates) were compared with regard to physiological and growth parameters related to their ability to survive and persist in the gastrointestinal tract and found to be similar. We propose that nonhuman hosts in E. coli O157:H7 strains function similarly to other E. coli strains in regard to attributes relevant to gastrointestinal colonization.
The Sea as a Rich Source of Structurally Unique Glycosaminoglycans and Mimetics

Glycosaminoglycans (GAGs) are sulfated glycans capable of regulating various biological and medical functions. Heparin, heparan sulfate, chondroitin sulfate, dermatan sulfate, keratan sulfate and hyaluronan are the principal classes of GAGs found in animals. Although GAGs are all composed of disaccharide repeating building blocks, the sulfation patterns and the composing alternating monosaccharides vary among classes. Interestingly, GAGs from marine organisms can present structures clearly distinct from terrestrial animals even considering the same class of GAG. The holothurian fucosylated chondroitin sulfate, the dermatan sulfates with distinct sulfation patterns extracted from ascidian species, the sulfated glucuronic acid-containing heparan sulfate isolated from the gastropode Nodipecten nodosum, and the hybrid heparin/heparan sulfate molecule obtained from the shrimp Litopenaeus vannamei are some typical examples. Besides being a rich source of structurally unique GAGs, the sea is also a wealthy environment of GAG-resembling sulfated glycans. Examples of these mimetics are the sulfated fucans and sulfated galactans found in brown, red and green algae, sea urchins and sea cucumbers. For adequate visualization, representations of all discussed molecules are given in both Haworth projections and 3D models.
Doubly Robust and Multiple-Imputation-Based Generalized Estimating Equations

Generalized estimating equations (GEE), proposed by Liang and Zeger (1986), provide a popular method to analyze correlated non-Gaussian data. When data are incomplete, the GEE method suffers from its frequentist nature and inferences under this method are valid only under the strong assumption that the missing data are missing completely at random. When response data are missing at random, two modifications of GEE can be considered, based on inverse-probability weighting or on multiple imputation. The weighted GEE (WGEE) method involves weighting observations by the inverse of their probability of being observed. Imputation methods involve filling in missing observations with values predicted by an assumed imputation model, multiple times. The so-called doubly robust (DR) methods involve both a model for the weights and a predictive model for the missing observations given the observed ones. To yield consistent estimates, WGEE needs correct specification of the dropout model while imputation-based methodology needs a correctly specified imputation model. DR methods need correct specification of either the weight or the predictive model, but not necessarily both. Focusing on incomplete binary repeated measures, we study the relative performance of the singly robust and doubly robust versions of GEE in a variety of correctly and incorrectly specified models using simulation studies. Data from a clinical trial in onychomycosis further illustrate the method.
Modulation of the T-type cardiac Ca channel by changes in proton concentration

Single-channel measurements and whole-cell experiments with the two suction electrode, voltage clamp technique were used to investigate the effects of external and internal proton concentrations on T-type Ca channels in heart muscle cells of the guinea pig. As in the L-type Ca channel, an increase in the external proton concentration decreases T- type currents, while external alkalinization enlarges the currents. In contrast to the L-type Ca channel, however, a change in the internal proton concentration does not modulate T-type Ca currents. The T-type Ca channel is much more sensitive to variations in pHo than the L-type Ca channel. By the combination of single-channel and whole-cell experiments we can conclude that the observed changes in macroscopic currents are due to (a) changes in the single-channel conductance and in the probability of the T-type Ca channel being open, and (b) the titration of the negative surface charges in the neighborhood of the T- type Ca channel with shifts of both the activation and inactivation processes of the channel. The pHo-induced changes in the maximal conductance (gmax) of the T-type Ca channel show an apparent pKa in the range of 7.1-7.5, while the titration of the negative surface charges near the channel shows an apparent pKa of 7.1 with a concomitant surface potential of -24.6 mV at 5.4 mM [Ca]o. These pKa values, less acid than the pKa values found for the pHo-induced, L-type Ca channel modulation, might imply a physiological importance of this novel type of channel modulation.
Journal Pre-proof A Recent Survey on Instance-Dependent Positive and Unlabeled Learning

Training with conﬁdent positive-labeled instances has received a lot of attention in Positive and Unlabeled (PU) learning tasks, and this is formally termed “Instance-Dependent PU learning”. In instance-dependent PU learning, whether a positive instance is labeled depends on its labeling conﬁdence. In other words, it is assumed that not all positive instances have the same probability to be included by the positive set. Instead, the instances that are far from the potential decision boundary are with larger probability to be labeled than those that are close to the decision boundary. This setting has practical importance in many real-world applications such as medical diagnosis, outlier detection, object detection, etc. In this survey, we ﬁrst present the preliminary knowledge of PU learning, and then review the representative instance-dependent PU learning settings and methods. After that, we thoroughly compare them with typical PU learning methods on various benchmark datasets and analyze their performances. Finally, we discuss the potential directions for future research.
RAVCC: Robust Authentication Protocol for RFID based Vehicular Cloud Computing

Vehicular cloud computing (VCC) stands for vehicle cloud computing, which combines cloud, vehicular networking, and Internet of Things (IoT) and related technologies. VCC is defined as vehicle-to-vehicle, vehicle-to-infrastructure, and vehicle-to-device communication in which vehicles have communication sensing capabilities. Vehicle resources, cloud infrastructure, and the Internet of Things are all used by VCC. VCC, on the other hand, places a premium on communication security and the privacy of communicators. We present an ECC based authentication framework for Radio Frequency Identification (RFID) based on VCC, which is equipped with a radio frequency identification, to meet the goal of safe communication while maintaining anonymity. To prove the claim of safe communication, we employ formal security analysis in the random oracle model, BAN logic and informal analysis. On the basis of desirable performance parameters, we explain and evaluate the performance of the suggested framework, as well as compare it to similar systems. The proposed architecture, according to our findings, provides all needed security criteria while also permitting effective communication.
Integrated approach to Web ontology learning and engineering

Developing the Semantic Web, seeking to improve the semantic awareness of computers connected via the Internet, requires a systematic, computer-oriented world representation. Researchers often refer to such a model as an ontology. Despite the work done on them in recent years, ontologies have yet to be widely applied and used. Research has devoted only limited attention to such practical issues as techniques and tools aimed at an ontology's actual construction and content. The authors have built a software environment, centered around the OntoLearn tool, which can build and assess a domain ontology for intelligent information integration within a virtual user community. OntoLearn has already been tested in two European projects, where it functioned as the basis for a semantic interoperability platform used by small- and medium-sized tourism enterprises. Further, developers can easily adapt OntoLearn to work with other general-purpose ontologies.
Seizure outcome after switching antiepileptic drugs: A matched, prospective study

Outcomes after changing antiepileptic drugs (AEDs) have largely been studied in single cohort series. We recently reported the first study to examine this question in a controlled manner. Here we expand on these results by using a matched, prospective methodology applied to both uncontrolled and well‐controlled patients taking any AED.
The Effects of Official English Laws on Limited-English-Proficient Workers

This paper examines whether workers with limited English skills suffer adverse effects in the labor market when states declare English the official language. Official English laws may harm individuals who do not speak English very well if employers view the laws as allowing or requiring them to adopt workplace Englishonly rules that lower the demand for limited-English-proficient workers. Using data from the 1980 and 1990 Censuses, I estimate whether the earnings and other labor market outcomes of workers with limited English proficiency in states that adopted official English laws declined relative to other workers’. I find substantial negative effects on the annual earnings of men with limited English proficiency. JEL classification: J71, J78
Economic Evaluation Alongside Multinational Clinical Trials: Study Considerations for GUSTO iib

Abstract Data relevant to economic evaluation are being collected alongside clinical trials with increasing frequency. When these trials involve health outcomes and resource utilization in many different countries, numerous methodologic problems arise. This paper describes and discusses the methodology for economic evaluation that will be used in the Economic Substudy of GUSTO llb, as an example of how to address the problems that arise in economic evaluations linked to international trials.
The Influence of Attitudinal Variables on the Frequency of Water-Pipe Smoking and on Driving Ability

Waterpipe Tobacco Smoking (WTS) has become increasingly more popular, especially among youth. The present study examined which factors influence the decision to engage in WTS and to what degrees. In addition, we examined the influence of WTS on driving abilities. The population of the study consisted of 100 Israeli Arabs (70 WTS users and 30 non-users). The study applied a case-control design, whereby WTS users completed driving tasks using a simulator before and after a single session of WTS and were compared to non-users who completed similar driving tasks. Physiological measures, heart rate and blood oxygenation, were taken before each task. Distinguishing between frequent and infrequent WTS users, participants were asked to complete a questionnaire based on Ajzen’s Theory of Planned Behav- ior. WTS status was found to be in a statistically significant negative correlation with driving abilities. Frequent users had a relatively higher risk for violations and crashes compared to infrequent users. The physiological symptoms dis-played were consistent with those expected due to hypoxia. Planned Behavior Theory (PBT) proved efficient in predicting the decision to engage in WTS. The findings support the hypothesis that WTS causes a reduction in driving abilities via hypoxia while underscoring the role of PBC in determining WTS behavior. It is imperative that policymakers be made aware of the growing popularity of WTS, especially amongst youth, given the secondary life-threatening effects it may have. The influence of PBC has been demonstrated in regards to various health behaviors, including smoking, but has not WTS. In particular, future interventions should target the component of personal behavioral control in order to reduce WTS usage.
Deciding on progression of joint damage in paired films of individual patients: smallest detectable difference or change

Progression of radiological joint damage is usually based on the simultaneous assessment of a series of films from an individual patient (“paired”, with or without known sequence). In this setting the degree of progression that can be reliably detected above the measurement error is best determined by the smallest detectable change, and overestimated by the traditionally calculated smallest detectable difference. This knowledge is important for calculation of the proportion of patients showing radiographic progression in clinical trials.