Miracle-dz/UniFAR-FTUs huggingface dataset:
Autonomic nervous system profile in fibromyalgia patients and its modulation by exercise: a mini review

This review imparts an impressionistic tone to our current understanding of autonomic nervous system abnormalities in fibromyalgia. In the wake of symptoms present in patients with fibromyalgia (FM), autonomic dysfunction seems plausible in fibromyalgia. A popular notion is that of a relentless sympathetic hyperactivity and hyporeactivity based on heart rate variability (HRV) analyses and responses to various physiological stimuli. However, some exactly opposite findings suggesting normal/hypersympathetic reactivity in patients with fibromyalgia do exist. This heterogeneous picture along with multiple comorbidities accounts for the quantitative and qualitative differences in the degree of dysautonomia present in patients with FM. We contend that HRV changes in fibromyalgia may not actually represent increased cardiac sympathetic tone. Normal muscle sympathetic nerve activity (MSNA) and normal autonomic reactivity tests in patients with fibromyalgia suggest defective vascular end organ in fibromyalgia. Previously, we proposed a model linking deconditioning with physical inactivity resulting from widespread pain in patients with fibromyalgia. Deconditioning also modulates the autonomic nervous system (high sympathetic tone and a low parasympathetic tone). A high peripheral sympathetic tone causes regional ischaemia, which in turn results in widespread pain. Thus, vascular dysregulation and hypoperfusion in patients with FM give rise to ischaemic pain leading to physical inactivity. Microvascular abnormalities are also found in patients with FM. Therapeutic interventions (e.g. exercise) that result in vasodilatation and favourable autonomic alterations have proven to be effective. In this review, we focus on the vascular end organ in patients with fibromyalgia in particular and its modulation by exercise in general.
Vision-based face tracking system for window interface: prototype application and empirical studies

In this paper, we study the effective use of gaze information for human-computer interaction based on a stereo-based vision system which can track the 3D position and orientation of a user in real-time. We have integrated our face-tracking system into the X Window interface system, and conducted experiments to evaluate the effectiveness of our proposed framework for using gaze information for window interfaces.
COOPERATIVE CONTROL OF A MULTI-TIER MULTI-AGENT ROBOTIC SYSTEM FOR PLANETARY EXPLORATION

The aim of this paper is to address some key design issues of a multi-tier multi-agent system (M2S), such as to define the control architecture of the multiple agents within the two tiers (e.g. centralized and distributed), and the control or reasoning algorithm that allows individual agent to organize its behaviors, learn and/or adapt to unknown and dynamic conditions.
A Stable Southern Margin of Asia During the Cretaceous: Paleomagnetic Constraints on the Lhasa‐Qiangtang Collision and the Maximum Width of the Neo‐Tethys

The timing of the north‐south collision between two terranes can be determined by the overlap of their paleolatitudes or the change of their convergence rate. For example, the overlapping paleolatitudes of the Lhasa terrane and Tethyan Himalaya and the dramatic decrease in the velocity of the Indian plate are usually ascribed to the India‐Asia collision at ~55 Ma. However, little is known about the paleolatitudinal evolution and velocity change of the Lhasa terrane resulting from the Lhasa‐Qiangtang collision during the Jurassic‐Cretaceous period. To better constrain the velocity change of the Lhasa terrane during this period, to constrain when and where the Lhasa‐Qiangtang collision occurred, and to assess the distribution of land and sea in the Tethyan realm, we provide a high‐quality Cretaceous paleomagnetic pole obtained from the limestone from the western part of the Lhasa terrane, which yields a paleolatitude of ~16.8° ± 1.9°N for the sampling area (32.2°N, 80.8°E) during the time interval of ~113–72 Ma. We compile existing paleomagnetic results from the Lhasa terrane, Qiangtang terrane, Tethyan Himalaya, and India and reveal that the Lhasa‐Qiangtang collision most likely occurred at or near the J/K boundary at ~19°N for the reference point at (32°N, 88°E) and that the Neo‐Tethys reached its maximum width (≥~7450 km) during this period.
Guidelines for designing BJT amplifiers with low 1/f AM and PM noise

In this paper we discuss guidelines for designing linear bipolar junction transistor amplifiers with low 1/f amplitude modulation (AM) and phase modulation (PM) noise. These guidelines are derived from a new theory that relates AM and PM noise to transconductance fluctuations, junction capacitance fluctuations, and circuit architecture. We analyze the noise equations of each process for a common emitter (CE) amplifier and use the results to suggest amplifier designs that minimize the 1/f noise while providing other required attributes such as high gain. Although we use a CE amplifier as an example, the procedure applies to other configurations as well. Experimental noise results for several amplifier configurations are presented.
CHAOSOM: Collaboration between Chaos and Self-Organizing Map

In this study, we try to implant chaotic features into the learning algorithm of self-organizing map. We call this concept as Chaotic SOM (CHAOSOM) . As a first step to realize CHAOSOM, we consider the case that learning rate and neighboring coefficient of SOM are refreshed by chaotic pulses generated by the Hodgkin-Huxley equation. We apply the CHAOSOM to solve a traveling salesman problem and confirm that the chaotic feature improves the performance.
The Curse of Expertise: The Effects of Expertise and Debiasing Methods on Predictions of Novice Performance

Experts are often called on to predict the performance of novices, but cognitive heuristics may interfere with experts' ability to capitalize on their superior knowledge hi predicting novice task performance. In Study 1, experts, intermediate users, and novices predicted the time it would take novices to complete a complex task. In Study 2, expertise was experimentally manipulated. In both studies, those with more expertise were worse predictors of novice performance times and were resistant to debiasing techniques intended to reduce underestimation. Findings from these studies suggest that experts may have a cognitive handicap that leads to underestimating the difficulty novices face and that those with an intermediate level of expertise may be more accurate in predicting novices' performance. Organizations often rely on experts to predict the performance of novices. Project managers predict team
On providing prior knowledge for learning relational search heuristics

In this paper, we propose the use of two relational learning systems, hamlet and evock, for acquiring useful search control heuristics in the context of automated task planning. In particular, we discuss the influence of different ways of providing prior background knowledge to such systems. We compare the results of providing initial information by means of a human-centered approach against two automated approaches. The first automated one consists of using the output of hamlet as input to the learning process of evock, and viceversa. The second automated approach consists of using another planner for providing guidance towards solutions of problems.
A memetic co-clustering algorithm for gene expression profiles and biological annotation

With the invention of microarrays, researchers are capable of measuring thousands of gene expression levels in parallel at various time points of the biological process. To investigate general regulatory mechanisms, biologists cluster genes based on their expression patterns. In this paper, we propose a new memetic co-clustering algorithm for expression profiles, which incorporates a priori knowledge in the form of gene ontology information. Ontologies offer a mechanism to capture knowledge in a shareable form that is also processable by computers. The use of this additional annotation information promises to improve biological data analysis and simplifies the identification of processes that are relevant under the measured conditions.
StreamMR: An Optimized MapReduce Framework for AMD GPUs

MapReduce is a programming model from Google that facilitates parallel processing on a cluster of thousands of commodity computers. The success of MapReduce in cluster environments has motivated several studies of implementing MapReduce on a graphics processing unit (GPU), but generally focusing on the NVIDIA GPU. Our investigation reveals that the design and mapping of the MapReduce framework needs to be revisited for AMD GPUs due to their notable architectural differences from NVIDIA GPUs. For instance, current state-of-the-art MapReduce implementations employ atomic operations to coordinate the execution of different threads. However, atomic operations can implicitly cause inefficient memory access, and in turn, severely impact performance. In this paper, we propose Streamer, an OpenCL MapReduce framework optimized for AMD GPUs. With efficient atomic-free algorithms for output handling and intermediate result shuffling, Stream MR is superior to atomic-based MapReduce designs and can outperform existing atomic-free MapReduce implementations by nearly five-fold on an AMD Radeon HD 5870.
SRAM delay fault modeling and test algorithm development

With the advent of deep-submicron VLSI technologies, the working speed of SRAM circuits has grown to a level that at-speed testing of SRAM has become an important issue. We present delay fault models for SRAM, i.e., the faults that affect the access time of the SRAM circuit. We also develop the test algorithm that detects these faults. The proposed SRAM delay-fault test algorithm has a complexity of 3N + 2k read/write operations, where N is the number of words and k is the word count in a row.
Measuring lung resistivity using electrical impedance tomography

The use of electrical impedance tomography (EIT) imaging techniques in the measurement of lung resistivity for detection and monitoring of apnea and edema is proposed. In EIT, currents are injected into a subject using multiple electrodes, and boundary voltages are measured to reconstruct a cross-sectional image of internal resistivity distribution. It is found that a simplified, therefore fast, version of the impedance imaging method can be used for detection and monitoring of apnea and edema. The feasibility of this method has been shown through computer simulations and human experiments. The authors speculate that the EIT imaging technique will be more reliable than the current impedance apnea monitoring method, since they are monitoring the change of internal lung resistivity. However, more study is required to verify that this method performs better in the presence of motion artifact than the conventional two-electrode impedance apnea monitoring method. <<ETX>>
Comprehensive Evaluation of the Pixel – Based Skin Detection Approach for Pornography Filtering in the Internet Resources

A robust skin detector is the primary need of many fields of computer vision, including face detection, gesture recognition, and pornography filtering. Less than 10 years ago, the first paper on automatic pornography filtering was published. Since then, different researchers claim different color spaces to be the best choice for skin detection in pornography filtering. Unfortunately, no comprehensive work is performed on evaluating different color spaces and their performance for detecting naked people. In this way, researchers refer to the results ion skin detection for face detection, which underlies different imaging conditions. In this paper, we examine 21 color spaces in all their possible representations for pixel–based skin detection in pornographic images. In this way, this paper holds the largest investigation in the field of skin detection, and only one run on the pornographic images.
Modifying Hargreaves-Samani Equation for Estimating Reference Evapotranspiration in Dryland Regions of Amudarya River Basin

Reference evapotranspiration (ETo) is a key factor in determining the amount of water needed for crops, which is crucial to correct irrigation planning. FAO Penman-Monteith (EToPM) is among the most popular method to estimate ETo. Apparently sometimes it is difficult to compute ETo using Penman-Monteith due to challenges on data availability. FAO Penman-Monteith method requires many parameters (solar radiation, air temperature, wind speed and humidity), while Hargreaves-Samani method calculates ETo based on air temperature. Because Central Asia is a data limited region with weather stations unable to provide all required parameters for the PM method, this study aimed to estimate ETo using the Hargreaves and Samani (HS) method in Karshi Steppe, in Kashkadarya province, in southern Uzbekistan, based on data from 2011 to 2017. Reference evapotranspiration calculated by non-modified HS method is underestimated during the summer months. The reason for this underestimation might be higher air temperature and wind speed during these months. Therefore, the HS method in its original form cannot be used in our study area to estimate ETo. Modification of the EToHS, through application of a bias correction factor, had better performance and allowed improving the accuracy of the ETo calculation for this region. The calculated ETo values can inform decision making and management practices regarding water allocation, irrigation scheduling and crop selection in dry land regions of Amudarya river basin and the greater Central Asia area.
Developing Fault Tolerant Distributed Systems by Refinement

Distributed systems are usually large and complex systems composed of various components. System components are subject to various errors. These failures often require error recovery to be conducted at architectural-level. However, due to complexity of distributed systems, specifying fault tolerance mechanisms at architectural level is complex and error prone. In this paper, we propose a formal approach to specifying components and architectures of fault tolerant distributed and reactive systems. Our approach is based on refinement in the action system formalism – a framework for formal model-driven development of distributed systems. We demonstrate how to specify and refine fault tolerant components and complex distributed systems composed of them. The proposed approach provides designers with a systematic method for developing distributed fault tolerant systems.
Hunt For The Unique, Stable, Sparse And Fast Feature Learning On Graphs

For the purpose of learning on graphs, we hunt for a graph feature representation that exhibit certain uniqueness, stability and sparsity properties while also being amenable to fast computation. This leads to the discovery of family of graph spectral distances (denoted as FGSD) and their based graph feature representations, which we prove to possess most of these desired properties. To both evaluate the quality of graph features produced by FGSD and demonstrate their utility, we apply them to the graph classification problem. Through extensive experiments, we show that a simple SVM based classification algorithm, driven with our powerful FGSD based graph features, significantly outperforms all the more sophisticated state-of-art algorithms on the unlabeled node datasets in terms of both accuracy and speed; it also yields very competitive results on the labeled datasets - despite the fact it does not utilize any node label information.
Large-signal model and nonlinear control of PWM converters in discontinuous conduction mode

State-space average value modeling of dc-dc converters in continuous and discontinuous modes have been conferred remarkable recognition in the literature. This paper presents different aspects of averaged value modeling of flyback converter operating in discontinuous conduction mode (DCM). Moreover, a second order sliding mode controller is designed and analyzed for flyback converter. The advantages of second order sliding mode controller is that it reduces the chattering effect of conventional first-order sliding mode controller. The performance of the designed controller is evaluated using MATLAB/Simulink simulation under different loading conditions.
The Addition of a Tramadol Infusion to Morphine Patient-Controlled Analgesia After Abdominal Surgery: A Double-Blinded, Placebo-Controlled Randomized Trial

In this double-blinded, randomized controlled trial, we tested whether the addition of tramadol to morphine for patient-controlled analgesia (PCA) resulted in improved analgesia efficacy and smaller morphine requirements compared with morphine PCA alone after abdominal surgery in adults. Sixty-nine patients were randomly allocated into two groups, each receiving morphine 1 mg/mL via PCA after surgery. The tramadol group received an intraoperative initial loading dose of tramadol (1 mg/kg) and a postoperative infusion of tramadol at 0.2 mg · kg−1 · h−1. The control group received an intraoperative equivalent volume of normal saline and a postoperative saline infusion. Postoperatively, tramadol was associated with improved subjective analgesic efficacy (P = 0.031) and there was significantly less PCA morphine use in the tramadol group (P = 0.023). No differences between the groups were found with regard to nausea, antiemetic use, sedation, or quality of recovery (all P > 0.05). We conclude that a tramadol infusion combined with PCA morphine improves analgesia and reduces morphine requirements after abdominal surgery compared with morphine PCA alone.
Age and Gender Identification using Stacking for Classification

This paper presents our approach of identifying the profile of an unknown user based on the activities of known users. The aim of author profiling task of PAN@CLEF 2016 is cross-genre identification of the gender and age of an unknown user. This means training the system using the behavior of different users from one social media platform and identifying the profile of other user on some different platform. Instead of using single classifier to build the system we used a combination of different classifiers, also known as stacking. This approach allowed us explore the strength of all the classifiers and minimize the bias or error enforced by a single classifier.
On the robustness of joint optimization on transducer-based decoding graphs

It is our believe that joint optimization of acoustic and language models meets the inherent correlation between them, and thus expected to achieve better recognition performance. This nice approach should be effective in achieving robust speech recognition where the testing conditions are different from those of training. The acoustic and language models are integrated together into a unified decoding graph using weighted finite state transducers. In this paper, we report experimental results of the joint optimization of acoustic and language models on the Resource Management (RM1) continuous speech recognition. The results show that the proposed joint optimization approach is effective under noisy conditions for unseen testing utterances and achieved relative word error rate reduction from 7% to 17% for different noise levels. These results emphasize our expectation about the robustness of the proposed joint optimization approach.
Polyvinyl alcohol‐coated perfluorocarbon supports for metal chelating affinity separation of a monoclonal antibody

The preparation, characterisation and testing of stable non‐porous coated perfluorocarbon supports functionalised with the metal chelate, iminodiacetic acid (IDA) is described. Polyvinyl alcohol (PVA), a neutral hydrophilic polymer was esterified with perfluorooctanoyl chloride and anchored to the surface of solid perfluorocarbon particles through multiple fluorophilic interactions. The PVA‐coated particles were then activated by epoxidation and coupled with IDA. The presence of surface‐attached chelates was clearly demonstrated by the binding and selective desorption of Zn2+ ions. Three particulate perfluorocarbons were selected as potential starting materials and the conditions for preparation of metal chelating adsorbents optimised with respect to ease of manufacture, ligand density and binding capacity towards a monoclonal antibody known to bind to commercial Zn2+‐IDA supports. The choice of base particle strongly influenced the ligand densities and specific binding capacities towards the monoclonal antibody that could be achieved under optimal preparative conditions. Possible ways in which these metal chelating adsorbents may be employed to recover the monoclonal antibody directly from culture vessels are discussed.
Show me your eyes! The combined use of eye tracking and virtual reality applications for cognitive assessment

Attention and working memory are essential aspects of human cognitive abilities. When these capacities are impaired, virtual reality applications (VRAs) can be a tool to assess and rehabilitate. However, most VRAs use indirect manual reaction time measures to make inferences about visual attention processes. Since behavioral measures are quite indirect, eye tracking (ET) can offer a better alternative to probe more directly where and how attention is deployed. We propose two tasks with different levels of perceptual complexity for assessing visual attention and performance. Two comparative visual search tasks, as part of a set of cognitive tasks in the Systemic Lisbon Battery (SLB), a VRA designed to assess of cognitive impairments, were randomly presented to 39 healthy participants while the eye movements were continuously recorded. The total fixation duration, the number of visits in the areas of interest, along with the total execution time changed as a function of the overall score of cognitive ability. The present study demonstrates that the "spot the differences" tasks in SLB, combined with ET, are a reliable, sensitive and unobtrusive method to assess cognitive abilities in healthy individuals with a relevant potential use in clinical samples.
A Comparative Evaluation of Techniques for Single-Frame Discrimination of Nonstationary Sinusoids

Many spectral analysis and modification techniques require the separation of sinusoidal from nonsinusoidal signal components of a Fourier spectrum. Techniques exist for the estimation of the parameters of nonstationary sinusoids, and for discriminating these from other components, within a single Fourier frame. We present a comparative study of five methods for sinusoidal discrimination, considering their effectiveness and their computational cost.
Autoimmune Hepatitis: Clinical Review with Insights into the Purinergic Mechanism of Disease

Autoimmune hepatitis (AIH) is an important disorder that predominantly results in inflammatory liver disease in genetically predisposed women. The clinicopathological picture is characterized by symptoms associated with both systemic inflammation and hepatic dysfunction, and with increased serum aminotransferases, elevated IgG, autoantibodies, and interface hepatitis on liver biopsy. AIH usually results in liver injury as a consequence of chronic hepatitis and cirrhosis. However, rarely, patients may present with fulminant liver failure. Early diagnosis is important in all instances because the disease can be highly responsive to immunosuppressive therapeutic options. Left untreated, the disease is associated with high morbidity and mortality. Here we provide an overview of the current state of knowledge on AIH and summarize the treatment options for this serious condition in adults. We also discuss the pathogenesis of the disease as a possible consequence of autoimmunity and the breakdown of hepatic tolerance. We focus on regulatory T cell impairments as a consequence of changes in CD39 ectonucleotidase expression and altered purinergic signaling. Further understanding of hepatic tolerance may aid in the development of specific and well-tolerated therapies for AIH.