Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic Modeling and Interactive Performance of PARM: A Parallel Upper-Limb Rehabilitation Robot Using Impedance Control for Patients after Stroke

The robot-assisted therapy has been demonstrated to be effective in the improvements of limb function and even activities of daily living for patients after stroke. This paper presents an interactive upper-limb rehabilitation robot with a parallel mechanism and an isometric screen embedded in the platform to display trajectories. In the dynamic modeling for impedance control, the effects of friction and inertia are reduced by introducing the principle of virtual work and derivative of Jacobian matrix. To achieve the assist-as-needed impedance control for arbitrary trajectories, the strategy based on orthogonal deviations is proposed. Simulations and experiments were performed to validate the dynamic modeling and impedance control. Besides, to investigate the influence of the impedance in practice, a subject participated in experiments and performed two types of movements with the robot, that is, rectilinear and circular movements, under four conditions, that is, with/without resistance or impedance, respectively. The results showed that the impedance and resistance affected both mean absolute error and standard deviation of movements and also demonstrated the significant differences between movements with/without impedance and resistance (p < 0.001). Furthermore, the error patterns were discussed, which suggested that the impedance environment was capable of alleviating movement deviations by compensating the synergetic inadequacy between the shoulder and elbow joints.
Texterra at SemEval-2018 Task 7: Exploiting Syntactic Information for Relation Extraction and Classification in Scientific Papers

In this work we evaluate applicability of entity pair models and neural network architectures for relation extraction and classification in scientific papers at SemEval-2018. We carry out experiments with representing entity pairs through sentence tokens and through shortest path in dependency tree, comparing approaches based on convolutional and recurrent neural networks. With convolutional network applied to shortest path in dependency tree we managed to be ranked eighth in subtask 1.1 (“clean data”), ninth in 1.2 (“noisy data”). Similar model applied to separate parts of the shortest path was mounted to ninth (extraction track) and seventh (classification track) positions in subtask 2 ranking.
Transcranial magnetic stimulation for the treatment of cocaine addiction: evidence to date

There is a common consensus in considering substance-use disorders (SUDs) a devastating chronic illness with social and psychological impact. Despite significant progress in understanding the neurobiology of SUDs, therapeutic advances have proceeded at a slower pace, in particular for cocaine-use disorder (CUD). Transcranial magnetic stimulation (TMS) is gaining support as a safe and cost-effective tool in the treatment of SUDs. In this review, we consider human studies that have investigated the efficacy of TMS in achieving therapeutic benefits in treating CUD. All studies conducted to date that have evaluated the therapeutic effect of TMS in CUD are included. We focus on the protocol of stimulation applied, emphasizing the neurophysiological effects of coils employed related to outcomes. Moreover, we examine the subjective and objective measurements used to assess the therapeutic effects along the timeline considered. The revision of scientific literatures underscores the therapeutic potential of TMS in treating CUD. However, the variability in stimulation protocols applied and the lack of methodological control do not allow us to draw firm conclusions, and further studies are warranted to examine the interaction between TMS patterns of stimulation relative to clinical outcomes in depth.
Automotive Attacks and Countermeasures on LIN-Bus

This paper presents a security analysis of the Local Interconnect Network (LIN) that is used in assembly units such as seats, steering wheels, and doors in vehicles. Recently, the number of security threats to in-vehicle networks such as the Controller Area Network has increased. In contrast, there have been no reports that evaluate the security of LIN in detail. The security analysis of LIN is important because it is used in units related to seats, steering wheels, etc. and it is at risk for an attack. In this paper, we present the first evaluation on the security of LIN. We present case studies of attacks that use the characteristics of a commonly-used error handling mechanism. In the attacks, the attacker intentionally stops communication using the error handling mechanism and sends a false response in place of a valid one. We experimentally show the feasibility of the attacks using a vehicle microcontroller. Furthermore, we present countermeasures against the attacks. The results of this study show that there is vulnerability to attack when the error handling mechanism is simply designed. We believe that this study will contribute to improvements in security of in-vehicle communications.
Quantum Chaotic aspects of Biophysical

‘Quantum Biophysical Semeiotics’ – QBS is an extension of classical semeiotics, an original medical science, which allows to interpret the body signals for diagnostic purposes. The key of this new discipline is the awareness that human bodies is a continuum of biological systems whose dynamics follow the laws of deterministic chaos, able to be measured by mean of nonlinear statistical invariants. Furthermore, in a recent discovery energy, information and communication between DNA and bio-systems are strictly connected with quantum behavior. An integrated quantum-chaotic approach is evidenced as epistemological base for a new approach to modern sciences.
Regularized Kernel and Neural Sobolev Descent: Dynamic MMD Transport

We introduce Regularized Kernel and Neural Sobolev Descent for transporting a source distribution to a target distribution along smooth paths of minimum kinetic energy (defined by the Sobolev discrepancy), related to dynamic optimal transport. In the kernel version, we give a simple algorithm to perform the descent along gradients of the Sobolev critic, and show that it converges asymptotically to the target distribution in the MMD sense. In the neural version, we parametrize the Sobolev critic with a neural network with input gradient norm constrained in expectation. We show in theory and experiments that regularization has an important role in favoring smooth transitions between distributions, avoiding large discrete jumps. Our analysis could provide a new perspective on the impact of critic updates (early stopping) on the paths to equilibrium in the GAN setting.
Prevalence of Helicobacter pylori cagA and iceA Genes and Their Association with Gastrointestinal Diseases

H. pylori infection causes peptic ulcer, chronic gastritis, mucosa-associated lymphoid tissue lymphoma, and gastric carcinoma. It has several virulence factors such as cytotoxin-associated gene A(cagA) and the induced by contact with epithelium antigen (iceA). We aimed to explore the relationship between cagA and iceA of H. pylori and gastrointestinal diseases. One hundred and eighteen patients who attended Gastrointestinal Endoscopy Unit at Zagazig University Hospitals, Egypt, were included in this study. Two gastric biopsies were collected and evaluated by rapid urease test (RUT) and PCR. cagA and iceA genes were amplified by PCR. We found that 54 patients (45.76%) were positive by both RUT and PCR. cagA and iceA genes were present in 57.4% and 46.29% of the studied patients, respectively. cagA was the most prevalent gene in gastritis (33.3%) and peptic ulcer (68.7%). iceA1/iceA2 positive genes were the most prevalent in gastric cancer (75%). iceA1 gene was present in 38.7% of cagA positive cases, but iceA2 gene was present in 45.2% of cagA positive cases. iceA1/iceA2 positive genes were present in 29% of cagA positive cases. In conclusion, cagA and iceA genes could be used as markers for severe gastrointestinal diseases. iceA gene was strongly related to cagA gene.
A Comparison of Reinforcement Learning Methodologies in Two-Party and Three-Party Negotiation Dialogue

We use reinforcement learning to learn dialogue policies in a collaborative furniture layout negotiation task. We employ a variety of methodologies (i.e., learning against a simulated user versus co-learning) and algorithms. Our policies achieve the best solution or a good solution to this problem for a variety of settings and initial conditions, including in the presence of noise (e.g., due to speech recognition or natural language understanding errors). Also, our policies perform well even in situations not observed during training. Policies trained against a simulated user perform well while interacting with policies trained through co-learning, and vice versa. Furthermore, policies trained in a two-party setting are successfully applied to a three-party setting, and vice versa.
Surgical Management of Lumbar and Thoracolumbar Spinal Fractures: Indications, Surgical Technique and Evaluation on a Series of 64 Patients Treated with Percutaneous Posterior Osteosynthesis Combined with Kyphoplasty or Anterior Arthrodesis

Introduction: Fractures of the lumbar spine and thoracolumbar junction are common in spinal trauma. The aim of this work is to analyze the nature of the indications, the morbidity as well as the results of these treatment regimens. Patients and Methods: A retrospective, single-center study, based on a review of 64 patients with lumbar spine and thoracolumbar junction fractures (T10-L2) without neurological disorders, was collected in the neurosurgery department of the North Hospital and University Hospital (CHU), Marseille over a period of 2 years from January 2015 to December 2016. Posterior percutaneous osteosynthesis were more or less associated with kyphoplasty preceded anterior arthrodesis. Clinical and radiological endpoints were collected at least 6 months later. Results: The mean follow-up was 9.5 months (6 - 24). The clinical evaluation found a mean VAS at last follow-up at 14/100 (0 - 30) and an average Oswestry score at the last follow-up at 88%. The initial average vertebral kyphosis went from 13° to 4° at the last follow-up with a correction loss of 1°, an absolute gain of 8°. No postoperative neurological complications were noted in our series. Conclusion: The implementation of a two-step therapeutic strategy with anterior reconstruction in Magerl’s lumbar spine or A3.3 thoracolumbar junction fractures allows effective and long-lasting correction of lumbar lordosis and thoracic kyphosis, and obtaining a balanced spine in the sagittal plane. Our functional results are close to normal, with low morbidity and a low complication rate.
Learning a Latent Space of Multitrack Measures

Discovering and exploring the underlying structure of multi-instrumental music using learning-based approaches remains an open problem. We extend the recent MusicVAE model to represent multitrack polyphonic measures as vectors in a latent space. Our approach enables several useful operations such as generating plausible measures from scratch, interpolating between measures in a musically meaningful way, and manipulating specific musical attributes. We also introduce chord conditioning, which allows all of these operations to be performed while keeping harmony fixed, and allows chords to be changed while maintaining musical "style". By generating a sequence of measures over a predefined chord progression, our model can produce music with convincing long-term structure. We demonstrate that our latent space model makes it possible to intuitively control and generate musical sequences with rich instrumentation (see this https URL for generated audio).
Lifelong Domain Word Embedding via Meta-Learning

Learning high-quality domain word embeddings is important for achieving good performance in many NLP tasks. General-purpose embeddings trained on large-scale corpora are often sub-optimal for domain-specific applications. However, domain-specific tasks often do not have large in-domain corpora for training high-quality domain embeddings. In this paper, we propose a novel lifelong learning setting for domain embedding. That is, when performing the new domain embedding, the system has seen many past domains, and it tries to expand the new in-domain corpus by exploiting the corpora from the past domains via meta-learning. The proposed meta-learner characterizes the similarities of the contexts of the same word in many domain corpora, which helps retrieve relevant data from the past domains to expand the new domain corpus. Experimental results show that domain embeddings produced from such a process improve the performance of the downstream tasks.
Invasive Software Testing: Mutating Target Programs to Diversify Test Exploration for High Test Coverage

Software testing techniques have advanced significantly over several decades; however, most of current techniques still test a target program as it is, and fail to utilize valuable information of diverse test executions on many variants of the original program in test generation. This paper proposes a new direction for software testing – Invasive Software Testing (IST). IST first generates a set of target program variants m1; :::;mn from an original target program p by applying mutation operations 1; :::; n. Second, given a test suite T, IST executes m1; :::;mn with T and records the test runs which increase test coverage compared to p with T. Based on the recorded information, IST generates guideposts for automated test generation on p toward high test coverage. Finally, IST generates test inputs on p with the guideposts and achieves higher test coverage. We developed DEMINER which implements IST for C programs through software mutation and concolic testing. Further, we showed the effectiveness of DEMINER on three real-world target programs Busybox-ls, Busybox-printf, and GNU-find. The experiment results show that the amount of the improved branch coverage by DEMINER is 24.7% relatively larger than those of the conventional concolic testing techniques on average.
A Multimedia Support Skills Intervention for Female Partners of Male Smokeless Tobacco Users: Use and Perceived Acceptability

Background UCare is a new multimedia (website+booklet) intervention for women who want their male partner to quit their use of smokeless tobacco. The intervention is based on research showing that perceived partner responsiveness to social support is highest when the supporter conveys respect, understanding, and caring in their actions. The website included both didactic and interactive features, with optional video components, and special activities to help women develop empathy for nicotine addiction. The booklet reinforced the website content, encouraged women to use the website, and served both as a physical reminder of the intervention and a convenient way to share the information with her partner. Objective The objective of this study was to describe the utilization and acceptability of a multimedia intervention among women seeking to support their partner in quitting smokeless tobacco. Lessons learned with respect to design considerations for online interventions are also summarized. Methods We present the evaluation of the intervention components’ use and usefulness in a randomized trial. Results In the randomized clinical trial, more than 250,000 visits were made to the website in a 2-year period, with the vast majority from mobile devices. Of the 552 women randomized to receive the intervention, 96.9% (535/552) visited the website at least once, and 30.8% (170/552) completed the core website component, “The Basics. ” About half of the women (287/552) used the interactive “Take Notes” feature, and 37% (204/552) used the checklists. Few women used the post-Basics features. At 6 weeks, 40.7% (116/285) reported reading the printed and mailed booklet. Website and booklet use were uncorrelated. User ratings for the website and booklet were positive overall. Conclusions Intervention website designers should consider that many users will access the program only once or twice, and many will not complete it. It is also important to distinguish between core and supplemental features and to consider whether the primary purpose is training or support. Furthermore, printed materials still have value. Trial Registration ClinicalTrials.gov NCT01885221; https://clinicaltrials.gov/ct2/show/NCT01885221 (Archived by WebCite at http://www.webcitation.org/6zdIgGGtx)
Ab Initio Protein Structure Prediction: Methods and challenges

Proteins represent approximately 20% of a eukaryotic cell’s weight, that is, the largest percentage after water [1]. They are involved in the most critical functions: Structural proteins are an organism’s basic building blocks; enzymes, the largest class, are known to be involved in 4000 biochemical reactions [2]; and transmembrane proteins are essential in the cellular environment’s maintenance. A protein is a linear sequence of amino acids (AAs) which generally folds in a high-speed spontaneous process into a unique three-dimensional conformation; this conformation typically represents a global energy minimum [3]. A protein’s lack of structure, or misfold, may be harmful since a protein’s biological function is highly related to its three-dimensional structure. Indeed, it has been shown that many serious diseases like Alzheimer’s, Parkinson’s, Creutzfeldt–Jakob disease, cystic fibrosis, and many cancers are linked to protein misfolding [4]; see Figure 32.1. Thus, predicting the native structure of some proteins may not only contribute to a better understanding of the biochemistry of diseases but also have an invaluable contribution in drug design. Consequently, predicting a final structure from a sequence of AAs has been qualified as deciphering “the second half of the genetic code” and referred to the “holy grail of molecular biology” [5]. This quest has attracted researchers from many disciplines, including biology, biochemistry, biophysics, and computer science. It is estimated that about 100,000 different structures of proteins can be found in the human body [6]. However, fewer than 10% of them have been discovered so far [7]. Since experimental techniques for protein structure determination [i.e., X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy] are very expensive and time consuming, there is a great incentive in generating such knowledge via computational means. Protein structure prediction (PSP) aims at predicting computationally the three-dimensional (3D)
The Essential Element Manganese, Oxidative Stress, and Metabolic Diseases: Links and Interactions

Manganese (Mn) is an essential element that is involved in the synthesis and activation of many enzymes and in the regulation of the metabolism of glucose and lipids in humans. In addition, Mn is one of the required components for Mn superoxide dismutase (MnSOD) that is mainly responsible for scavenging reactive oxygen species (ROS) in mitochondrial oxidative stress. Both Mn deficiency and intoxication are associated with adverse metabolic and neuropsychiatric effects. Over the past few decades, the prevalence of metabolic diseases, including type 2 diabetes mellitus (T2MD), obesity, insulin resistance, atherosclerosis, hyperlipidemia, nonalcoholic fatty liver disease (NAFLD), and hepatic steatosis, has increased dramatically. Previous studies have found that ROS generation, oxidative stress, and inflammation are critical for the pathogenesis of metabolic diseases. In addition, deficiency in dietary Mn as well as excessive Mn exposure could increase ROS generation and result in further oxidative stress. However, the relationship between Mn and metabolic diseases is not clear. In this review, we provide insights into the role Mn plays in the prevention and development of metabolic diseases.
Saline as a vehicle control does not alter ventilation in male CD‐1 mice

Saline (0.9% NaCl) is used in clinical and research settings as a vehicle for intravenous drug administration. While saline is a standard control in mouse studies, there are reports of hyperchloremic metabolic acidosis in high doses. It remains unknown if metabolic acidosis occurs in mice and/or if compensatory increases in breathing frequency and tidal volume accompany saline administration. It was hypothesized that saline administration alters blood pH and the pattern of breathing in conscious CD‐1 male mice exposed to air or hypoxia (10% O2, balanced N2). Unrestrained barometric plethysmography was used to quantify breathing frequency (breaths/min; bpm), tidal volume (VT; mL/breath/10 g body weight (BW)), and minute ventilation (VE; mL/min/10 g BW) in two designs: (1) 11‐week‐old mice with no saline exposure (n = 11) compared to mice with 7 days of 0.9% saline administration (intraperitoneal, i.p.; 10 mL/kg body mass; n = 6). and (2) 17‐week‐old mice tested before (PRE) and after 1 day (POST1, n = 6) or 7 days (POST7, n = 5) of saline (i.p.; 10 mL/kg body mass). There were no differences when comparing frequency, VT, or VE between groups for either design with room air or hypoxia exposures. Hypoxia increased frequency, VT, and VE compared to room air. Moreover, conscious blood sampling showed no differences in pH, paCO2, paO2, or HCO3− in mice without or with 7 days of saline. These findings reveal no differences in ventilation following 1 and/or 7 days of saline administration in mice. Therefore, the use of 0.9% saline as a control is supported for studies evaluating the control of breathing in mice.
Synthesis, Characterization and Dry Sliding Wear Behavior of In-situ Formed TiAl3 Precipitate Reinforced A356 Alloy Produced by Mechanical Alloying Method

In this present study, the effect of in-situ formed TiAl3 and AlTiSi intermetallic phases within A356 aluminum alloy on the dry sliding wear behaviors was investigated. The TiAl3 and AlTiSi intermetallic phases were obtained by synthesizing A356 aluminum alloy containing 6% titanium for different times (1, 4, 8 and 16h). The cold pressed samples were sintered in an argon atmosphere at 530 °C for one hour (10 °C/min.) and then cooled in the furnace. The sintered samples were synthesized at 550 °C for different times (1, 4, 8 and 16h), and the in-situ aluminum matrix composites (AMCs) were produced. Wear tests of the AMCs were performed under 30 N load and at 1 ms-1sliding speed for five different sliding distances. As the result of the studies performed, formation of in-situ TiAl3 and AlTiSi intermetallic phases were detected. With the increase in synthesizing time, the porosity in the structure was found to be reduced. In addition, it was observed that the densities and hardness of the composites increased depending on the synthesizing time. The wear test results revealed that increasing hardness values of A356 + 6% Ti AMCs decreased the weight loss.