Miracle-dz/UniFAR-FTUs huggingface dataset:
Atrial High Rate Episodes Detected by Pacemaker Diagnostics Predict Death and Stroke: Report of the Atrial Diagnostics Ancillary Study of the MOde Selection Trial (MOST)

Background—Some current pacing systems can automatically detect and record atrial tachyarrhythmias that may be asymptomatic. We prospectively studied a 312-patient (pt) subgroup of MOST (MOde Selection Trial), a 2010-patient, 6-year randomized trial of DDDR versus VVIR pacing in sinus node dysfunction (SND). The purpose of the study was to correlate atrial high rate events (AHREs) detected by pacemaker diagnostics with clinical outcomes. Methods and Results—Pacemakers were programmed to log an AHRE when the atrial rate was >220 bpm for 10 consecutive beats. Analysis was confined to patients with at least 1 AHRE duration exceeding 5 minutes. The 312 patients were median age 74 years, 55% female, and 60% had a history of SVT. 160 of 312 (51.3%) patients enrolled had at least 1 AHRE >5 minutes duration over median follow-up of 27 months. Cox proportional hazards analysis assessed the relationship of AHREs with clinical events, adjusting for prognostic variables and baseline covariates. The presence of any AHRE was an independent predictor of the following: total mortality (hazard ratio AHRE versus no AHRE and 95% confidence intervals=2.48 [1.25, 4.91], P =0.0092); death or nonfatal stroke (2.79 [1.51, 5.15], P =0.0011); and atrial fibrillation (5.93 [2.88, 12.2], P =0.0001). There was no significant effect of pacing mode on the presence or absence of AHREs. Conclusions—AHRE detected by pacemakers in patients with SND identify patients that are more than twice as likely to die or have a stroke, and 6 times as likely to develop atrial fibrillation as similar patients without AHRE.
Segmentation of biomedical images using active contour model with robust image feature and shape prior

In this article, a new level set model is proposed for the segmentation of biomedical images. The image energy of the proposed model is derived from a robust image gradient feature which gives the active contour a global representation of the geometric configuration, making it more robust in dealing with image noise, weak edges, and initial configurations. Statistical shape information is incorporated using nonparametric shape density distribution, which allows the shape model to handle relatively large shape variations. The segmentation of various shapes from both synthetic and real images depict the robustness and efficiency of the proposed method. © 2013 The Authors. International Journal for Numerical Methods in Biomedical Engineering published by John Wiley & Sons, Ltd.
The lactate and ventilatory thresholds in resistance training

This study was designed to identify the lactate threshold (LT) and first ventilatory threshold (VT1) in a graded resistance half‐squat test and determine whether both thresholds are produced at the same workload. A further goal was to compare the visual inspection and algorithm adjustment methods of detecting both thresholds during graded resistance exercise.
Properties of amorphous carbon nitride prepared by RF reactive sputtering

The local microstructure and optical and electrical properties were investigated of amorphous carbon nitride (a-CN) films deposited by reactive radio-frequency (RF) sputtering. Two series prepared in nitrogen or in a nitrogen and argon mixture were studied. The optical properties were investigated by transmittance/reflectance and photothermal deflection spectroscopies. Combined infrared measurements and Raman scattering spectroscopies were used to investigate the microstructure of a-CN films in terms of nitrogen incorporation within the films and C sp 2 content. These experiments were completed by dark electrical conductivity measurements performed in coplanar configuration in the temperature range 50–450 K. The films exhibit semiconductor behaviour and the temperature dependence suggests two types of conduction. An increase in nitrogen incorporation induces an increase with clustering of sp 2 phase replacing C=C olefinic groups with aromatic groups.
Algebraically special axisymmetric solutions of the higher-dimensional vacuum Einstein equation

A d-dimensional spacetime is ‘axisymmetric’ if it possesses an SO(d − 2) isometry group whose orbits are (d − 3)-spheres. In this paper, algebraically special, axisymmetric solutions of the higher-dimensional vacuum Einstein equation (with cosmological constant) are investigated. Necessary and sufficient conditions for static axisymmetric solutions to belong to different algebraic classes are presented. Then general (possibly time-dependent) axisymmetric solutions are discussed. All axisymmetric solutions of algebraic types II, D, III and N are obtained
Inducible nitric oxide synthase (iNOS) in muscle wasting syndrome, sarcopenia, and cachexia

Muscle atrophy—also known as muscle wasting—is a debilitating syndrome that slowly develops with age (sarcopenia) or rapidly appears at the late stages of deadly diseases such as cancer, AIDS, and sepsis (cachexia). Despite the prevalence and the drastic detrimental effects of these two syndromes, there are currently no widely used, effective treatment options for those suffering from muscle wasting. In an attempt to identify potential therapeutic targets, the molecular mechanisms of sarcopenia and cachexia have begun to be elucidated. Growing evidence suggests that inflammatory cytokines may play an important role in the pathology of both syndromes. As one of the key cytokines involved in both sarcopenic and cachectic muscle wasting, tumor necrosis factor α (TNFα) and its downstream effectors provide an enticing target for pharmacological intervention. However, to date, no drugs targeting the TNFα signaling pathway have been successful as a remedial option for the treatment of muscle wasting. Thus, there is a need to identify new effectors in this important pathway that might prove to be more efficacious targets. Inducible nitric oxide synthase (iNOS) has recently been shown to be an important mediator of TNFα-induced cachectic muscle loss, and studies suggest that it may also play a role in sarcopenia. In addition, investigations into the mechanism of iNOS-mediated muscle loss have begun to reveal potential therapeutic strategies. In this review, we will highlight the potential for targeting the iNOS/NO pathway in the treatment of muscle loss and discuss its functional relevance in sarcopenia and cachexia.
Analyzing coevolutionary games with dynamic fitness landscapes

Coevolutionary games cast players that may change their strategies as well as their networks of interaction. In this paper a framework is introduced for describing coevolutionary game dynamics by landscape models. It is shown that coevolutionary games invoke dynamic landscapes. Numerical experiments are shown for prisoner's dilemma (PD) and snow drift (SD) games that both use either birth-death (BD) or death-birth (DB) strategy updating. The resulting landscapes are analyzed with respect to modality and ruggedness.
Sonification Report: Status of the Field and Research Agenda

The purpose of this paper is to provide an overview of sonification research, including the current status of the field and a proposed research agenda. This paper was prepared by an interdisciplinary group of researchers gathered at the request of the National Science Foundation in the fall of 1997 in association with the International Conference on Auditory Display (ICAD)
Parameterized access control: from design to prototype

Peer-to-peer overlays provide a substrate well suited to building distributed storage systems. Applications that use the infrastructure need the ability to control access to their data. However, traditional authorization services were not designed to operate in the face of network partitions, malicious nodes, and on an Internet-wide scale. We describe the implementation of the Decentralized Authentication and Authorization Layer (DAAL), a mechanism to leverage the storage functionality of the overlay and obviate the need for an online, centralized access control service. The system can efficiently identify malicious nodes and continue to operate correctly when an arbitrary, predefined fraction of the network is unreachable (as occurs during an attack against the routing infrastructure or during a distributed denial-of-service attack). DAAL melds the access request efficiency of capability-based systems with the revocation power of reference monitor-based access control lists. It avoids the use of distributed leases as they create a vulnerability window during which there is a gap between the security policy and configuration. Actualizing the design can be challenging. Hence, we describe the protocol details and how they can be abstracted behind a minimal, intuitive application programming interface. As a proof of concept, we implemented DAAL as a Java prototype on a 200-node peer-to-peer overlay distributed across the world.
Eliciting a sense of virtual community among knowledge contributors

Member-initiated virtual communities for product knowledge sharing and commerce purposes are proliferating as useful alternatives to company information and commerce Web sites. Although such communities are easy to create with the availability of numerous tools, the challenge lies in keeping the community alive and thriving. Key to sustainability is members' Sense Of Virtual Community (SOVC) so that they feel responsible for contributing their knowledge and creating value for others. However, it is unclear what leads to the SOVC among knowledge contributors. Building on appraisal theory, we hypothesize that the fulfillment of contributors' informational, instrumental, entertainment, self-discovery, and social enhancement needs will increase their SOVC. To test the hypotheses, we surveyed knowledge contributors in a beauty-product-related community to examine the relationship between their needs' fulfillment and SOVC levels. Other than the social enhancement need, all other needs' fulfillment were found to be positively related to SOVC levels. To further understand how the SOVC of knowledge contributors changes over time, we conducted a longitudinal analysis of a panel of these members. We discovered that over time, changes in the perceived fulfillment of their instrumental, entertainment, and self-discovery needs determined the change of their SOVC. The results have implications for future research as well as for the sustainability and value generation from such virtual communities.
Analytical model for a tunnel field-effect transistor

The tunnel field-effect transistor (TFET) is a promising candidate for the succession of the MOSFET at nanometer dimensions. Due to the absence of a simple analytical model for the TFET, the working principle is generally not well understood. In this paper a new TFET structure is introduced and using Kanepsilas model, an analytical expression for the current through the TFET is derived. Furthermore, a compact expression for the TFET current is derived and conclusions concerning TFET design are drawn. The obtained analytical expressions are compared with results from a 2D device simulator and good agreement at low gate voltages is demonstrated.
A Joint Intensity and Depth Co-sparse Analysis Model for Depth Map Super-resolution

High-resolution depth maps can be inferred from low-resolution depth measurements and an additional high-resolution intensity image of the same scene. To that end, we introduce a bimodal co-sparse analysis model, which is able to capture the interdependency of registered intensity and depth information. This model is based on the assumption that the co-supports of corresponding bimodal image structures are aligned when computed by a suitable pair of analysis operators. No analytic form of such operators exist and we propose a method for learning them from a set of registered training signals. This learning process is done offline and returns a bimodal analysis operator that is universally applicable to natural scenes. We use this to exploit the bimodal co-sparse analysis model as a prior for solving inverse problems, which leads to an efficient algorithm for depth map super-resolution.
Determination of the DNA-binding kinetics of three related but heteroimmune bacteriophage repressors using EMSA and SPR analysis

Bacteriophages P2, P2 Hy dis and WΦ are very similar but heteroimmune Escherichia coli phages. The structural genes show over 96% identity, but the repressors show between 43 and 63% identities. Furthermore, the operators, which contain two directly repeated sequences, vary in sequence, length, location relative to the promoter and spacing between the direct repeats. We have compared the in vivo effects of the wild type and mutated operators on gene expression with the complexes formed between the repressors and their wild type or mutated operators using electrophoretic mobility shift assay (EMSA), and real-time kinetics of the protein–DNA interactions using surface plasmon resonance (SPR) analysis. Using EMSA, the repressors formed different protein–DNA complexes, and only WΦ was significantly affected by point mutations. However, SPR analysis showed a reduced association rate constant and an increased dissociation rate constant for P2 and WΦ operator mutants. The association rate constants of P2 Hy dis was too fast to be determined. The P2 Hy dis dissociation response curves were shown to be triphasic, while both P2 and WΦ C were biphasic. Thus, the kinetics of complex formation and the nature of the complexes formed differ extensively between these very closely related phages.
Chemotherapy or Targeted Therapy as Second-Line Treatment of Advanced Gastric Cancer. A Systematic Review and Meta-Analysis of Published Studies

Chemotherapy is a cornerstone in treatments of gastric cancer, but despite its benefit, less than 60% of patients receive salvage therapy in clinical practice. We performed a systematic review and meta-analysis based on trial data on the role of second-line treatment of advanced gastric cancer. MEDLINE/PubMed and Cochrane Library were searched for randomized phase III trials that compared active therapy to best supportive care in advanced gastric cancer. Data extraction was conducted according to the PRISMA statement. Summary HR for OS was calculated using a hierarchical Bayesian model and subgroup analysis was performed based on baseline Eastern Cooperative Oncology Group Performance Status (ECOG) performance status (0 vs. 1 or more). A total of 1,407 patients were evaluable for efficacy, 908 were treated in the experimental arms, with chemotherapy (231 pts) or with targeted therapies (677 pts). The risk of death was decreased by 18% (HR = 0.82; 95% CI, 0.79–0.85; posterior probability HR≥1: <0.00001) with active therapies. Chemotherapy and ramucirumab were able to decrease this risk by 27% and 22%, respectively. No differences were found between chemotherapy and ramucirumab. In patients with ECOG = 0 a greater benefit was found for chemotherapy with a reduction of the risk of death by 43% and no benefits were found for ramucirumab or everolimus. In patients with ECOG = 1 or more a significant reduction of the risk of death by 32% was reported in patients treated with ramucirumab, even if no significant difference was reported between chemotherapy and ramucirumab. This analysis reports that active and available therapies are able to prolong survival in patients with advanced gastric cancer with a different outcome based on initial patient’s performance status. New trials based on a better patient stratification are awaited.
Rapid Detection Viable Escherichia Coli O157 in Raw Milk Using Loop-Mediated Isothermal Amplification with Aid of Ethidium Monoazide

The distinction between viable and dead cells was a major issue in detection of pathogenic microbe in foods especially when foods had been subjected to thermal processing. The performance of a loop-mediated isothermal amplification (LAMP) assay with aid of ethidium monoazide (EMA) for detecting viable Escherichia coli O157 in raw milk was presented in this paper. Three pairs of primers were specially designed for recognizing eight distinct sequences of rfbE gene. LAMP can only amplified DNA of viable Escherichia coli O157 because EMA selectively penetrated dead cells and covalently bound to DNA, detection limit level for artificially contaminated raw milk samples by the EMA-LAMP assay was 440 cfu/mL corresponding to 3–5 cells per reaction tube, while the detection level by EMA-PCR was 4.4×104 cfu/mL. In conclusion, EMA-LAMP had offered a novel assay for distinction between viable and dead cells with promising application in food safety detection.
Cluster, Allocate, Cover: An Efficient Approach for Multi-robot Coverage

This article presents an algorithm for online multirobot coverage that proceeds with minimal knowledge of the already explored region and the frontier cells. It creates clusters of frontier cells which are designated to robots using an optimal assignment scheme. Coverage is then performed using a novel path planning technique. Many approaches that use clustering for multi-robot coverage do not specify strict time criteria for re-clustering. Moreover, the motion plans they use result in redundant coverage. To overcome these limitations, an appropriate motion plan for the robots is chosen based on the context of already covered frontiers. Dispersion of robots is vital for efficient coverage and is an emergent behavior in our approach. The efficacy of the proposed approach is tested in simulation and on a multi-robot test-bed. The algorithm performs better than some state of the art approaches.
A novel malware analysis for malware detection and classification using machine learning algorithms

Nowadays, Malware has become a serious threat to the digitization of the world due to the emergence of various new and complex malware every day. Due to this, the traditional signature-based methods for detection of malware effectively becomes an obsolete method. The efficiency of the machine learning model in context to the detection of malware files has been proved by different researches and studies. In this paper, a framework has been developed to detect and classify different files (e.g exe, pdf, php, etc.) as benign and malicious using two level classifier namely, Macro (for detection of malware) and Micro (for classification of malware files as a Trojan, Spyware, Adware, etc.). Cuckoo Sandbox is used for generating static and dynamic analysis report by executing files in the virtual environment. In addition, a novel model is developed for extracting features based on static, behavioral and network analysis using analysis report generated by the Cuckoo Sandbox. Weka Framework is used to develop machine learning models by using training datasets. The experimental results using proposed framework shows high detection rate with an accuracy of 100% using J48 Decision tree model, 99% using SMO (Sequential Minimal Optimization) and 97% using Random Forest tree. It also shows effective classification rate with accuracy 100% using J48 Decision tree, 91% using SMO and 66% using Random Forest tree. These results are used for detecting and classifying unknown files as benign or malicious.
Bead-Based Multiplex Genotyping of Human Papillomaviruses

ABSTRACT Typing of human papillomaviruses (HPV) by DNA hybridization procedures, such as reverse line blot (RLB) assay, is sensitive and well validated. However, the application of these assays to high-throughput analyses is limited. Here, we describe the development of multiplex human papillomavirus genotyping (MPG), a quantitative and sensitive high-throughput procedure for the identification of multiple high- and low-risk genital HPV genotypes in a single reaction. MPG is based on the amplification of HPV DNA by a general primer PCR (GP5+/6+) and the subsequent detection of the products with type-specific oligonucleotide probes coupled to fluorescence-labeled polystyrene beads (Luminex suspension array technology). Up to 100 different HPV types can be detected simultaneously with MPG, and the method is fast and labor saving. We detected all 22 HPV types examined with high specificity and reproducibility (the median interplate coefficient of variation was below 10%). Detection limits for the different HPV types varied between 100 and 800 pg of PCR products. We compared the performance of MPG to an established RLB assay on GP5+/6+-PCR products derived from 94 clinical samples. The evaluation showed an excellent agreement (kappa = 0.922) but also indicated a higher sensitivity of MPG. In conclusion, MPG appears to be highly suitable for large-scale epidemiological studies and vaccination trials as well as for routine diagnostic purposes.
StoreGPU: exploiting graphics processing units to accelerate distributed storage systems

Today Graphics Processing Units (GPUs) are a largely underexploited resource on existing desktops and a possible cost-effective enhancement to high-performance systems. To date, most applications that exploit GPUs are specialized scientific applications. Little attention has been paid to harnessing these highly-parallel devices to support more generic functionality at the operating system or middleware level. This study starts from the hypothesis that generic middleware level techniques that improve distributed system reliability or performance (such as content addressing, erasure coding, or data similarity detection) can be significantly accelerated using GPU support. We take a first step towards validating this hypothesis, focusing on distributed storage systems. As a proof of concept, we design StoreGPU, a library that accelerates a number of hashing based primitives popular in distributed storage system implementations. Our evaluation shows that StoreGPU enables up to eight-fold performance gains on synthetic benchmarks as well as on a high-level application: the online similarity detection between large data files.
Proteomic analysis of skeletal organic matrix from the stony coral Stylophora pistillata

It has long been recognized that a suite of proteins exists in coral skeletons that is critical for the oriented precipitation of calcium carbonate crystals, yet these proteins remain poorly characterized. Using liquid chromatography-tandem mass spectrometry analysis of proteins extracted from the cell-free skeleton of the hermatypic coral, Stylophora pistillata, combined with a draft genome assembly from the cnidarian host cells of the same species, we identified 36 coral skeletal organic matrix proteins. The proteome of the coral skeleton contains an assemblage of adhesion and structural proteins as well as two highly acidic proteins that may constitute a unique coral skeletal organic matrix protein subfamily. We compared the 36 skeletal organic matrix protein sequences to genome and transcriptome data from three other corals, three additional invertebrates, one vertebrate, and three single-celled organisms. This work represents a unique extensive proteomic analysis of biomineralization-related proteins in corals from which we identify a biomineralization “toolkit,” an organic scaffold upon which aragonite crystals can be deposited in specific orientations to form a phenotypically identifiable structure.
A Visualization Approach for Cross-level Exploration of Spatiotemporal Data

Spatiotemporal data often relates to different levels of granularity in space, time, and data. Yet, bringing these levels together for an integrated visual exploration across levels poses a challenge up to this day. With this paper, we aim to provide a first solution approach to this challenge, which decomposes the data in its various levels to be able to show them side-by-side. Based on this decomposition, we derive a visual exploration approach that consists of a novel multilevel visualization, adjoined traditional spatial and temporal views, as well as of tailored exploration techniques for their concerted use. We exemplify the utility of this approach by case studies on election and poll data from Germany's various administrative levels and different time spans.