Miracle-dz/UniFAR-FTUs huggingface dataset:
Real time feature extraction of ECG signal on android platform

Ambulatory cardiac monitoring has become an important scenario nowadays as a standard preventive cardiological procedure for detection of cardiac abnormalities. In the proposed system it is achieved with the Android smart phone. Heart rate variability (HRV) analysis is well known to give information about the autonomic heart rate modulation mechanism. In order to avoid erroneous conclusions, it is of utmost importance that only sinus rhythms are present in the cardiogram. Therefore, preprocessing of the RR interval time series is necessary. This paper presents an advanced automated algorithm to preprocess RR intervals obtained from a normal ECG. Validation of this algorithm was performed on recorded ECG signals by holter recorder and MIT-BIH database. The proposed algorithm therefore restricts the manual data check to the absolute minimum and allows a reliable HRV analysis.
Advances in the Treatment of Fragile X Syndrome

The FMR1 mutations can cause a variety of disabilities, including cognitive deficits, attention-deficit/hyperactivity disorder, autism, and other socioemotional problems, in individuals with the full mutation form (fragile X syndrome) and distinct difficulties, including primary ovarian insufficiency, neuropathy and the fragile X-associated tremor/ataxia syndrome, in some older premutation carriers. Therefore, multigenerational family involvement is commonly encountered when a proband is identified with a FMR1 mutation. Studies of metabotropic glutamate receptor 5 pathway antagonists in animal models of fragile X syndrome have demonstrated benefits in reducing seizures, improving behavior, and enhancing cognition. Trials of metabotropic glutamate receptor 5 antagonists are beginning with individuals with fragile X syndrome. Targeted treatments, medical and behavioral interventions, genetic counseling, and family supports are reviewed here.
Diverse Contribution of Bone Marrow Cells to Neointimal Hyperplasia After Mechanical Vascular Injuries

Abstract— We and others have suggested that bone marrow-derived progenitor cells may contribute to the pathogenesis of vascular diseases. On the other hand, it was reported that bone marrow cells do not participate substantially in vascular remodeling in other experimental systems. In this study, three distinct types of mechanical vascular injuries were induced in the same mouse whose bone marrow had been reconstituted with that of GFP or LacZ mice. All injuries are known to cause smooth muscle cell (SMC) hyperplasia. At 4 weeks after wire-mediated endovascular injury, a significant number of the neointimal and medial cells derived from bone marrow. In contrast, marker-positive cells were seldom detected in the lesion induced by perivascular cuff replacement. There were only a few bone marrow-derived cells in the neointima after ligation of the common carotid artery. These results indicate that the origin of intimal cells is diverse and that contribution of bone marrow-derived cells to neointimal hyperplasia depends on the type of model.
Stability in possibilistic linear equality systems under continuous triangular norms

We consider linear equality systems where all the parameters may be fuzzy variables specified by their possibility distribution, the operations addition and multiplication by a real number of fuzzy parameters are defined via a suptriangular norm composition, and the equations are understood in possibilistic sense. We show that when the triangular norm defining the operations and equations is continuous, then the possibility distribution of the solution of these systems depend continuously on the fuzzy parameters.
Mechanisms of Electrical Activation and Conduction in the Gastrointestinal System: Lessons from Cardiac Electrophysiology

The gastrointestinal (GI) tract is an electrically excitable organ system containing multiple cell types, which coordinate electrical activity propagating through this tract. Disruption in its normal electrophysiology is observed in a number of GI motility disorders. However, this is not well characterized and the field of GI electrophysiology is much less developed compared to the cardiac field. The aim of this article is to use the established knowledge of cardiac electrophysiology to shed light on the mechanisms of electrical activation and propagation along the GI tract, and how abnormalities in these processes lead to motility disorders and suggest better treatment options based on this improved understanding. In the first part of the article, the ionic contributions to the generation of GI slow wave and the cardiac action potential (AP) are reviewed. Propagation of these electrical signals can be described by the core conductor theory in both systems. However, specifically for the GI tract, the following unique properties are observed: changes in slow wave frequency along its length, periods of quiescence, synchronization in short distances and desynchronization over long distances. These are best described by a coupled oscillator theory. Other differences include the diminished role of gap junctions in mediating this conduction in the GI tract compared to the heart. The electrophysiology of conditions such as gastroesophageal reflux disease and gastroparesis, and functional problems such as irritable bowel syndrome are discussed in detail, with reference to ion channel abnormalities and potential therapeutic targets. A deeper understanding of the molecular basis and physiological mechanisms underlying GI motility disorders will enable the development of better diagnostic and therapeutic tools and the advancement of this field.
A Bayesian Model of the Uncanny Valley Effect for Explaining the Effects of Therapeutic Robots in Autism Spectrum Disorder

One of the core features of autism spectrum disorder (ASD) is impaired reciprocal social interaction, especially in processing emotional information. Social robots are used to encourage children with ASD to take the initiative and to interact with the robotic tools to stimulate emotional responses. However, the existing evidence is limited by poor trial designs. The purpose of this study was to provide computational evidence in support of robot-assisted therapy for children with ASD. We thus propose an emotional model of ASD that adapts a Bayesian model of the uncanny valley effect, which holds that a human-looking robot can provoke repulsion and sensations of eeriness. Based on the unique emotional responses of children with ASD to the robots, we postulate that ASD induces a unique emotional response curve, more like a cliff than a valley. Thus, we performed numerical simulations of robot-assisted therapy to evaluate its effects. The results showed that, although a stimulus fell into the uncanny valley in the typical condition, it was effective at avoiding the uncanny cliff in the ASD condition. Consequently, individuals with ASD may find it more comfortable, and may modify their emotional response, if the robots look like deformed humans, even if they appear “creepy” to typical individuals. Therefore, we suggest that our model explains the effects of robot-assisted therapy in children with ASD and that human-looking robots may have potential advantages for improving social interactions in ASD.
Access control in wireless sensor networks

Wireless sensor networks consist of a large amount of sensor nodes, small low-cost wireless computing devices equipped with different sensors. Sensor networks collect and process environmental data and can be used for habitat monitoring, precision agriculture, wildfire detection, structural health monitoring and many other applications. Securing sensor networks calls for novel solutions, especially because of their unattended deployment and strong resource limitations. Moreover, developing security solutions without knowing precisely against what threats the system should be protected is impossible. Thus, the first task in securing sensor networks is to define a realistic adversary model. We systematically investigate vulnerabilities in sensor networks, specifically focusing on physical attacks on sensor node hardware. These are all attacks that require direct physical access to the sensor nodes. Most severe attacks of this kind are also known as node capture, or node compromise. Based on the vulnerability analysis, we present a novel general adversary model for sensor networks. If the data collected within a sensor network is valuable or should be kept confidential then the data should be protected from unauthorized access. We determine security issues in the context of access control in sensor networks in presence of node capture attacks and develop protocols for broadcast authentication that constitute the core of our solutions for access control. We develop broadcast authentication protocols for the case where the adversary can capture up to some threshold t sensor nodes. The developed protocols offer absolute protection while not more than t nodes are captured, but their security breaks completely otherwise. Moreover, security in this case comes at a high cost, as the resource requirements for the protocols grow rapidly with t. One of the most popular ways to overcome impossibility or inefficiency of solutions in distributed systems is to make the protocol goals probabilistic. We therefore develop efficient probabilistic protocols for broadcast authentication. Security of these protocols degrades gracefully with the increasing number of captured nodes. We conclude that the perfect threshold security is less appropriate for sensor networks than the probabilistic approach. Gracefully degrading security offers better scalability and saves resources, and should be considered as a promising security paradigm for sensor networks.
Real-time Collision Detection for Dynamic Hardware Tessellated Objects

We present a novel method for real-time collision detection of patch based, displacement mapped objects using hardware tessellation. Our method supports fully animated, dynamically tessellated objects and runs entirely on the GPU. In order to determine a collision between two objects, we first find the intersecting volume of the corresponding object oriented bounding boxes. Next, patches of both objects are tested for inclusion within this volume. All possibly colliding patches are then voxelized into a uniform grid of single bit voxels. Finally, the resulting voxelization is used to detect collisions. Testing two moderately complex models containing thousands of patches can be done in less than a millisecond making our approach ideally suited for real-time games.
Numerical Facet Range Partition: Evaluation Metric and Methods

Faceted navigation is a very useful component in today's search engines. It is especially useful when user has an exploratory information need or prefer certain attribute values than others. Existing work has tried to optimize faceted systems in many aspects, but little work has been done on optimizing numerical facet ranges (e.g., price ranges of product). In this paper, we introduce for the first time the research problem on numerical facet range partition and formally frame it as an optimization problem. To enable quantitative evaluation of a partition algorithm, we propose an evaluation metric to be applied to search engine logs. We further propose two range partition algorithms that computationally optimize the defined metric. Experimental results on a two-month search log from a major e-Commerce engine show that our proposed method can significantly outperform baseline.
Predicting Cumulative Number of Failures in Software Using an ANN-PSO Based Approach

Software project managers need information such as cumulative number of failures present in a software after testing a certain period of time to determine release time of software. In this paper, an artificial neural network (ANN) based model which uses a new network architecture is proposed to predict cumulative number of failures in software. An extra layer is added between input layer and hidden layer of ANN which uses logarithmic activation function to scale the inputs of ANN. An ANN-PSO based approach is developed in which Particle Swarm Optimization (PSO) method is used to train the ANN. The experiment is carried out using three data sets available in literature and results are compared with existing models found in literature. The results shown that the proposed method is able to produce better prediction than some existing models.
Accretion disc outbursts: a new version of an old model

We have developed 1D time-dependent numerical models of accretion discs, using an adaptive grid technique and an implicit numerical scheme, in which the disc size is allowed to vary with time. The code fully resolves the cooling and heating fronts propagating in the disc. We show that models in which the radius of the outer edge of the disc is fixed produce incorrect results, from which probably incorrect conclusions about the viscosity law have been inferred. In particular we show that outside-in outbursts are possible when a standard bimodal behaviour of the Shakura–Sunyaev viscosity parameter α is used. We also discuss to what extent insufficient grid resolution has limited the predictive power of previous models. We find that the global properties (magnitudes, etc.) of transient discs can be addressed by codes using a high, but reasonable, number of fixed grid points. However, the study of the detailed physical properties of the transition fronts generally requires resolutions which are out of reach of fixed grid codes. It appears that most time-dependent models of accretion discs published in the literature have been limited by resolution effects, improper outer boundary conditions, or both.
Neutral Higgs boson contributions to the decays B̄ d , s → μ + μ − in the MSSM at large tan β

It is well known that the Minimal Supersymmetric Standard Mo del (MSSM) can enhanceB (B̄d,s → μ+μ−) by orders of magnitude [1], even if we assume the Cabibbo-Kobayashi-Maskawa (CKM) matrix to be the only source of flavour violation. Of particular interest is the quantity R ≡ B (B̄d → μ+μ−)/B (B̄s → μ+μ−), since (i) the theoretical errors cancel to a large extent, and (ii) it offers a theoretica lly clean way of extracting the ratio |Vtd/Vts| in the Standard Model, which predicts RSM ∼ |Vtd/Vts| ∼ O(10−2). Exploring three different scenarios of modified minimal flavour violat ion (MFV), we find that part of the MSSM parameter space can accommodate large B̄d,s → μ+μ− branching fractions, while being consistent with various experimental constrai n s. More importantly, we show that the ratioR can be as large as O(1), while the individual branching fractions may be amenable to detection by ongoing experiments. We conclude t hat within the MSSM with largetan β the decay rates of̄ Bd,s → μ+μ− be of comparable size even in the case where flavour violation is due solely to the CKM matrix.
Combined Control Scheme For Monitoring Quality Characteristics

In the literature, the Exponentially Weighted Moving Average (EWMA) and Exponentially Weighted Moving Variance (EMWV) control schemes have been used separately to monitor the process average and process variability respectively. Here the two are combined and applied on simulated process with different level of variation. The control limit interval (CLI) and the average run length (ARL) were evaluated for the combined chart. The combined chart performed better than the two independently. Furthermore, an algorithm was developed for the two control charts and implemented on visual basic VB6.0. The obtained results show that the combined EWMA and EWMV control chart is very sensitive in detecting shift in production process and every shift in the process mean is always preceded by shift in the process variability.
Technology Change or Resistance to Changing Institutional Logics: The Rise and Fall of Digital Equipment Corporation

This article uses an institutional lens to analyze organizational failure. It does this through a historical case study of Digital Equipment Corporation, an innovator and market leader of minicomputers who faltered and eventually failed during the period of technological change brought on by the emergence of the personal computer. The failure of Digital Equipment Corporation is interesting because it occurred despite its ability to adapt to changing technological forces. An institutional analysis shows that while Digital Equipment Corporation was able to develop personal computers widely considered technologically superior to its competitors, it resisted broader changes occurring in its institutional context. This study suggests that responding to external forces of change, such as technology, may not be enough. An organization must determine if and how such change might lead to a shift in its institutional context and then develop strategies to address such change.
What’s stopping you? The contribution of gender essentialism to sex differences in subject choice

The present study considered the impact of gender essentialism on sex differences in subject choice. Secondary school children, aged 11-12 years (N = 30) and 15-16 years (N = 26), were randomly assigned to one of three experimental conditions, and completed a thought experiment requiring them to make inferences about two gendered attributes; academic subject ability and gender-stereotyped properties, of a hypothetical male and female; (a) raised in an opposite sex environment; (b) following a brain transplant from a member of the opposite sex and (c) a 'normal' male or female, acting as a baseline response. Results from the experiment indicated that children do hold essentialist beliefs about gender. However, such beliefs vary as a function of both the age of participants, and the gendered attribute considered. We conclude that gender essentialism may account for the persistence of sex differences in subject choice.
High resolution optical mapping reveals conduction slowing in connexin 43 deficient mice

Analysis of mice with genetically altered expression of cardiac connexins can provide insights into the role of individual gap junction channel proteins in cell-to-cell communication, impulse propagation, and arrhythmias. However, conflicting results have been reported regarding conduction velocity slowing in mice heterozygous for a null mutation in the gene encoding connexin43 (Cx43). Methods: High-resolution optical mapping was used to record action potentials from 256 sites, simultaneously, on the ventricular surface of Langendorff perfused hearts from 15 heterozygous (Cx431 /2) and 8 wildtype (Cx431 /1) mice (controls). A sensitive method for measuring epicardial conduction velocity was developed to minimize confounding influences of subepicardial breakthrough and virtual electrode effects. Results: Epicardial conduction velocity was significantly slower (23 to 35%, P,0.01) in Cx431 /2 mice compared to wildtype. There was no change in conduction patterns or anisotropic ratio (Cx431 /2 1.5460.33; Cx431 /1 1.5760.17) suggesting that Cx43 expression was reduced uniformly throughout myocardium. The magnitude of reductions in conduction velocity and Cx43 protein expression (45%) were similar in mice in which the null allele occurred in a pure C57BL/6J genetic background versus a mixed (C57BL/6J X 129) background. Action potential duration did not differ between mice of different genotypes. Conclusions: A |50% reduction of Cx43 expression causes significant conduction velocity slowing in the Cx431 /2 mouse heart. The apparent lack of conduction velocity changes reported in previous studies may be related to technical factors rather than variations in genetic background. High-resolution optical mapping is a powerful tool for investigating molecular determinants of propagation and arrhythmias in genetically engineered mice.  2001 Elsevier Science B.V. All rights reserved.
Overall Energy Efficient Clustering Algorithm in UWB-Based Wireless Sensor Network

UWB technology advances the lifetime of UWB-based wireless sensor networks (WSNs) and clustering enhances utilization of limited energy resources of the network.Since cluster heads (CHs) usually forward data via multi-hop, energy consumed by each CH vary with relay traffic and its member size. To achieve energy balance, an overall energy efficient clustering (OEEC) algorithm is proposed. It elects CH by a voting mechanism and divides nodes into clusters in adaptive size by measuring distances among nodes accurately based on UWB and taking energy of the nodes into consideration.The voting approach lets sensors vote for their neighbors to elect suitable CHs. CHs closer to base station (BS) have smaller size than those farther to reduce energy consumption in intra-cluster data transmission and preserve more energy for inter-cluster data forwarding. Simulation results show that the proposed clustering algorithm balances the overall energy consumption efficiently and prolongs the network lifetime which is much better than LEACH obviously.
Styrene maleic acid-encapsulated paclitaxel micelles: antitumor activity and toxicity studies following oral administration in a murine orthotopic colon cancer model

Oral administration of paclitaxel (PTX), a broad spectrum anticancer agent, is challenged by its low uptake due to its poor bioavailability, efflux through P-glycoprotein, and gastrointestinal toxicity. We synthesized PTX nanomicelles using poly(styrene-co-maleic acid) (SMA). Oral administration of SMA-PTX micelles doubled the maximum tolerated dose (60 mg/kg vs 30 mg/kg) compared to the commercially available PTX formulation (PTX [Ebewe]). In a murine orthotopic colon cancer model, oral administration of SMA-PTX micelles at doses 30 mg/kg and 60 mg/kg reduced tumor weight by 54% and 69%, respectively, as compared to the control group, while no significant reduction in tumor weight was observed with 30 mg/kg of PTX (Ebewe). In addition, toxicity of PTX was largely reduced by its encapsulation into SMA. Furthermore, examination of the tumors demonstrated a decrease in the number of blood vessels. Thus, oral delivery of SMA-PTX micelles may provide a safe and effective strategy for the treatment of colon cancer.
Real-Time and Secure Wireless Health Monitoring

We present a framework for a wireless health monitoring system using wireless networks such as ZigBee. Vital signals are collected and processed using a 3-tiered architecture. The first stage is the mobile device carried on the body that runs a number of wired and wireless probes. This device is also designed to perform some basic processing such as the heart rate and fatal failure detection. At the second stage, further processing is performed by a local server using the raw data transmitted by the mobile device continuously. The raw data is also stored at this server. The processed data as well as the analysis results are then transmitted to the service provider center for diagnostic reviews as well as storage. The main advantages of the proposed framework are (1) the ability to detect signals wirelessly within a body sensor network (BSN), (2) low-power and reliable data transmission through ZigBee network nodes, (3) secure transmission of medical data over BSN, (4) efficient channel allocation for medical data transmission over wireless networks, and (5) optimized analysis of data using an adaptive architecture that maximizes the utility of processing and computational capacity at each platform.