Miracle-dz/UniFAR-FTUs huggingface dataset:
Using surface electromyography to predict single finger forces

Surface electromyography (sEMG) of the forearm is an active research topic since the 1990s in the rehabilitation robotics/machine learning community, as it can be used to predict the hand posture and overall grip force. We hereby advance the state of the art by describing a multi-subject experiment in which sEMG is successfully used to predict simultaneous forces applied by a human subject at the fingertips, that is, when six voluntary muscle contractions (VMCs) are elicited (flexion of the little, ring, middle and index fingers, thumb rotation and thumb adduction). Using a multi-sensor setup sEMG activity of the forearm of a human subject and the forces exerted at the fingertips are measured; a Support Vector Machine is then used to associate sEMG signals and forces. Our results clearly show that sEMG can be used to predict the required forces with an error as small as 1.5% of the sensor range. Targeted positioning of the electrodes is not required. The prediction is uniformly accurate across all VMCs and all 12 subjects considered, and it is robust against subsampling. This result goes in the direction of enabling natural force/impedance control of a highly dexterous prosthetic hand over a continuous, infinite manifold of force configurations, rather than using posture classification like in the traditional approach.
Effects of Intracoronary Verapamil Administration in a Sheep Model of Acute Myocardial Ischemia and Reperfusion

We evaluated the efficacy of intracoronary administration of verapamil hydrochloride in reducing myocardial injury during acute ischemia and reperfusion. Ischemia was induced by 30% and 45% reductions of circumflex arterial blood flow for successive 2-hour periods. A reperfusion period (1 hour and 45 minutes) followed ischemia upon deflation of a pneumatic occluder. Verapamil (30 μg/kg) was slowly injected into the circumflex artery as a bolus 15 minutes after each blood flow reduction step. To prevent verapamil-induced decreases in heart rate, ventricular pacing was established at 170 beats/min before a baseline period and maintained throughout the protocol. Creatine kinase activities (international units per milligram protein) measured in samples obtained from posterior papillary muscles were 15 ± 1 (mean ± SEM) and 10 ± 2 for animals receiving verapamil or its saline vehicle, respectively (p<0.05). Quantitative morphometry was performed on left ventricular myocardium after staining with p-nitro blue tetrazolium. Intracoronary administration of verapamil reduced the extent of left ventricular infarction, as disclosed by positive tetrazolium staining of the tissue, from 34 ± 4% of the left ventricle in vehicle-treated animals to 21 ± 4% of the left ventricle in verapamil-treated animals (p<0.05). We conclude that intracoronary administration of verapamil reduced the extent of myocardial infarction acutely, independent of increases in blood flow through the circumflex coronary artery or decreases in heart rate. Administration of verapamil was not associated with decreases in ventricular afterload, the pressure-rate index, cardiac output, or the maximum rate of pressure development in the left ventricle. Verapamil treatment of animals subjected to ischemia was not associated with sustained elevations of left atrial pressure to values above those measured in animals receiving the vehicle.
Build-IT -- An Interactive Web Application for 3D Construction, Interior and Exterior Design

Using 3D building models is extremely helpful throughout the architecture engineering and construction (AEC) lifecycle. Such models coupled with virtual walk through can enable customers to decide and be satisfied with their dream building. Manually creating a polygonal 3D model of a set of floor plans is nontrivial and requires skill and time. This project introduces and reviews a mechanism for applying interior and exterior design constructs after the conversion of 2D drawings into 3D Building Information Model (BIM). This research demonstrates an automated 3D model reconstruction of real world object from an un-calibrated image sequence targeting the same scene, which can be used for interior and exterior design. There are many key techniques in 3D reconstruction from image sequences, including feature matching, fundamental matrix estimation, projective reconstruction, camera self-calibration, dense stereo matching and Euclidean reconstruction. The effectiveness of the algorithms was evaluated in the experiments with many real image sequences.
Biochemical, Mutational and In Silico Structural Evidence for a Functional Dimeric Form of the Ornithine Decarboxylase from Entamoeba histolytica

Background Entamoeba histolytica is responsible for causing amoebiasis. Polyamine biosynthesis pathway enzymes are potential drug targets in parasitic protozoan diseases. The first and rate-limiting step of this pathway is catalyzed by ornithine decarboxylase (ODC). ODC enzyme functions as an obligate dimer. However, partially purified ODC from E. histolytica (EhODC) is reported to exist in a pentameric state. Methodology and Results In present study, the oligomeric state of EhODC was re-investigated. The enzyme was over-expressed in Escherichia coli and purified. Pure protein was used for determination of secondary structure content using circular dichroism spectroscopy. The percentages of α-helix, β-sheets and random coils in EhODC were estimated to be 39%, 25% and 36% respectively. Size-exclusion chromatography and mass spectrophotometry analysis revealed that EhODC enzyme exists in dimeric form. Further, computational model of EhODC dimer was generated. The homodimer contains two separate active sites at the dimer interface with Lys57 and Cys334 residues of opposite monomers contributing to each active site. Molecular dynamic simulations were performed and the dimeric structure was found to be very stable with RMSD value ∼0.327 nm. To gain insight into the functional role, the interface residues critical for dimerization and active site formation were identified and mutated. Mutation of Lys57Ala or Cys334Ala completely abolished enzyme activity. Interestingly, partial restoration of the enzyme activity was observed when inactive Lys57Ala and Cys334Ala mutants were mixed confirming that the dimer is the active form. Furthermore, Gly361Tyr and Lys157Ala mutations at the dimer interface were found to abolish the enzyme activity and destabilize the dimer. Conclusion To our knowledge, this is the first report which demonstrates that EhODC is functional in the dimeric form. These findings and availability of 3D structure model of EhODC dimer opens up possibilities for alternate enzyme inhibition strategies by targeting the dimer disruption.
Adapting Bronfenbrenner’s Bio-ecology Theory to Enhance Social Marketing

Social marketing has been criticised for mainly focusing on the individual and not wider environmental influences. This issue is being challenged by scholars of the domain who are now investigating the impact of incorporating ecological models within it. Bronfenbrenner’s bio-ecological theory is one that is widely used in other disciplines. This study utilises a mixed methods approach with a single case study: examining why individuals living with diabetes chose to attend (or not) a structured education course (the social marketing programme) in England. It examines the attitudes of the patients, healthcare professionals and administrators of the NHS. The research identified that many of the propositions held within the bio-ecological theory are highly relevant to social marketing: they provide a means of explaining the antecedents of why individuals chose to engage in behaviour change programmes. Further studies will be required to test the macro and time elements of the bio-ecology theory.
EEG Resting-State Large-Scale Brain Network Dynamics Are Related to Depressive Symptoms

Background The few previous studies on resting-state EEG microstates in depressive patients suggest altered temporal characteristics of microstates compared to those of healthy subjects. We tested whether resting-state microstate temporal characteristics could capture large-scale brain network dynamic activity relevant to depressive symptomatology. Methods To evaluate a possible relationship between the resting-state large-scale brain network dynamics and depressive symptoms, we performed EEG microstate analysis in patients with moderate to severe depression within bipolar affective disorder, depressive episode, and periodic depressive disorder, and in healthy controls. Results Microstate analysis revealed six classes of microstates (A-F) in global clustering across all subjects. There were no between-group differences in the temporal characteristics of microstates. In the patient group, higher symptomatology on the Montgomery-Åsberg Depression Rating Scale, a questionnaire validated as measuring severity of depressive episodes in patients with mood disorders, correlated with higher occurrence of microstate A (Spearman’s rank correlation, r = 0.70, p < 0.01). Conclusion Our results suggest that the observed interindividual differences in resting-state EEG microstate parameters could reflect altered large-scale brain network dynamics relevant to depressive symptomatology during depressive episodes. These findings suggest the utility of the microstate analysis approach in an objective depression assessment.
Emerging simulation approaches for micromachined devices

In this survey paper, we describe and contrast three different approaches for extending circuit simulation to include micromachined devices. The most commonly used method, that of using physical insight to develop parameterized macromodels, is presented first. The issues associated with fitting the parameters to simulation data while incorporating design attribute dependencies are considered. The numerical model order reduction approach to macromodeling is presented second, and some of the issues associated with fast solvers and model reduction are summarized. Lastly, we describe the recently developed circuit-based approach for simulating micromachined devices, and describe the design hierarchy and the use of a catalog of parts.
Learning-based Rule-Extraction from Support Vector Machines

In recent years, support vector machines (SVMs) have shown good performance in a number of application areas, including text classification. However, the success of SVMs comes at a cost - an inability to explain the process by which a learning result was reached and why a decision is being made. Rule-extraction from SVMs is important for the acceptance of this machine learning technology, especially for applications such as medical diagnosis. It is crucial for the users to understand how the system makes a decision. In this paper, a novel approach for rule-extraction from support vector machines is presented. This approach handles rule-extraction as a learning task, which proceeds in two steps. The first is to use the labeled patterns from a data set to train an SVM. The second step is to use the generated model to predict the label (class) for an extended data set or different, unlabeled data set. The resulting patterns are then used to train a decision tree learning system and to extract the corresponding rule sets. The output rule sets are verified against available knowledge for the domain problem (e.g. a medical expert), and other classification techniques, to assure correctness and validity of rules.
Fair Decentralized Congestion and Awareness Control for Vehicular Networks

Challenges surrounding 802.11p vehicular networks have become more apparent in recent years within the research community. The exchange of periodical beacons on the control channel is mandatory to support higher layer applications such as active safety applications. However, the nature of such wireless vehicular networks imposes a lot of serious problems, especially the risk that the radio channel becomes quickly saturated. Thus, congestion control and awareness control are crucial mechanisms to control the load and ensure that each vehicle is able to communicate with its most relevant neighbours respectively. In this paper, we tackle jointly congestion and awareness control by taking into consideration 2-hops influence, hidden-terminals, SINR, received power, and a fair bandwidth indicator measuring the performance distribution among a coalition of vehicles in a highly volatile vehicular network. A two-steps proactive distributed algorithm called TPA&plus;IAB is proposed to improve the fair bandwidth utilization. Each step of the algorithm achieves a distinct goal: Intelligent Adaptive Beaconing (IAB) is in charge of controlling the congestion while the Transmit Power Adaptation (TPA) is in charge of controlling which neighbour should be part of a coalition with respect to down-link channel qualities. Different from awareness control algorithms which assume an optimal channel model, here a more realistic model is used to estimate dynamically the best communication range based on a non-deterministic propagation model. Realistic simulations with NS-3 show that the solution presented outperforms the well-known D-FPAV algorithm in non-homogeneous graphs.
International Arab Conference on Information Technology ( ACIT ' 2016 ) Coupling of Geographic Location-based Service and Routing for Wireless Sensor Networks

Geographic Routing Protocols use location information when they need to route packets. Obviously, location information is maintained by Location-based Services provided by network nodes in a distributed way. Routing and location services are very related but are used separately. Therefore, the overhead of the location-based service is not considered when we evaluate the geographic routing overhead. Our aim is to combine routing protocols with location-based services in order to reduce communication establishment latency and routing overhead. To reduce the location overhead, we propose a combination of GPSR (Greedy Perimeter Stateless Routing) and Location-based Services (Grid and Hierarchical Location Services (GLS/HLS)). GPSR takes care of routing packets and GLS or HLS are called to get destination position when the target’s node position is unknown or is not fresh enough. In order to implement this concept, we have proposed a patch over the NS-2 simulator which mixes GPSR, GLS and HLS according to our proposal. We have undertaken a set of experimentations and we have considered two performance criteria, the location overhead (number of sent location requests and the consumed location bandwidth) and the network performances (i.e., the packet delivery ratio and the average latency).
On tree-based convergecasting in wireless sensor networks

A wireless sensor network (WSN) consists of sensors implanted in an environment for collecting and transmitting data regarding changes in the environment based on the requests from a controlling device (called base station) using wireless communication. WSNs are being used in medical, military, and environment monitoring applications. Broadcast (dissemination of information from a central node) and convergecast (gathering of information towards a central node) are important communication paradigms across all application domains. Most sensor applications involve both convergecasting and broadcasting. The time taken to complete either of them has to be kept minimal. This can be accomplished by constructing an efficient tree for both broadcasting as well as convergecasting and allocating wireless communication channels to ensure collision-free communication. There exist several works on broadcasting in multihop radio networks (a.k.a. ad hoc networks), which can also be used for broadcasting in WSNs. These algorithms construct a broadcast tree and compute a schedule for transmitting and receiving for each node to achieve collision-free broadcasting. In this paper, we show that we need a new algorithm for applications, which involve both convergecasting and broadcasting since the broadcast tree may not be efficient for convergecasting. So we propose a heuristic algorithm (convergecasting tree construction and channel allocation algorithm (CTCCAA)), which constructs a tree with schedules assigned to nodes for collision free convergecasting. The algorithm is capable of code allocation (direct sequence spread spectrum (DSSS)/ frequency hopping spread spectrum (FHSS)), in case multiple codes are available, to minimize the total duration required for convergecasting. We also show that the same tree can be used for broadcasting and is as efficient as a tree exclusively constructed for broadcasting.
K-Core Decomposition of Large Networks on a Single PC

Studying the topology of a network is critical to inferring underlying dynamics such as tolerance to failure, group behavior and spreading patterns. k-core decomposition is a well-established metric which partitions a graph into layers from external to more central vertices. In this paper we aim to explore whether k-core decomposition of large networks can be computed using a consumer-grade PC. We feature implementations of the "vertex-centric" distributed protocol introduced by Montresor, De Pellegrini and Miorandi on GraphChi and Webgraph. Also, we present an accurate implementation of the Batagelj and Zaversnik algorithm for k-core decomposition in Webgraph. With our implementations, we show that we can efficiently handle networks of billions of edges using a single consumer-level machine within reasonable time and can produce excellent approximations in only a fraction of the execution time. To the best of our knowledge, our biggest graphs are considerably larger than the graphs considered in the literature. Next, we present an optimized implementation of an external-memory algorithm (EMcore) by Cheng, Ke, Chu, and Ozsu. We show that this algorithm also performs well for large datasets, however, it cannot predict whether a given memory budget is sufficient for a new dataset. We present a thorough analysis of all algorithms concluding that it is viable to compute k-core decomposition for large networks in a consumer-grade PC.
Design and Implementation of a Graphical Visualization Tool for NCS

A core goal for neuroscientists is to understand the physiological processes behind memory, learning, and cognition. By developing computational models of the brain, scientists can simulate how neurons interact with each other and study these interactions more closely. However, these simulations often require technical expertise to create and can be difficult to analyze due to a lack of comprehensive visualization tools. NeoCortical View, or NCV for short, aims to solve these problems by providing a simple, convenient graphical interface for managing virtual brain models. NCV interacts with the NeoCortical Simulator (NCS) developed by the Brain Computation Laboratory at the University of Nevada, Reno (UNR), allowing users to build models, distribute simulations across available hardware, and view the current live network state in 3D. NCV provides an intuitive and extensible simulation platform with a reduced learning curve, abstracting away the complex setup and analysis of neural simulations and allowing neuroscientists to focus on neuroscience.
Point mutation of adenosine triphosphate-binding motif generated rigor kinesin that selectively blocks anterograde lysosome membrane transport

In the study of motor proteins, the molecular mechanism of mechanochemical coupling, as well as the cellular role of these proteins, is an important issue. To assess these questions we introduced cDNA of wild-type and site-directed mutant kinesin heavy chains into fibroblasts, and analyzed the behavior of the recombinant proteins and the mechanisms involved in organelle transports. Overexpression of wild-type kinesin significantly promoted elongation of cellular processes. Wild-type kinesin accumulated at the tips of the long processes, whereas the kinesin mutants, which contained either a T93N- or T93I mutation in the ATP-binding motif, tightly bound to microtubules in the center of the cells. These mutant kinesins could bind to microtubules in vitro, but could not dissociate from them even in the presence of ATP, and did not support microtubule motility in vitro, thereby indicating rigor-type mutations. Retrograde transport from the Golgi apparatus to the endoplasmic reticulum, as well as lysosome dispersion, was shown to be a microtubule-dependent, plus-end- directed movement. The latter was selectively blocked in the rigor- mutant cells, although the microtubule minus-end-directed motion of lysosomes was not affected. We found the point mutations that make kinesin motor in strong binding state with microtubules in vitro and showed that this mutant causes a dominant effect that selectively blocks anterograde lysosome membrane transports in vivo.
Hydrophobic sequences target and anchor perilipin A to lipid droplets Published, JLR Papers in Press, September 1, 2004. DOI 10.1194/jlr.M400291-JLR200

Perilipins regulate triacylglycerol storage and hydrolysis in adipocytes. The central 25% of the perilipin A sequence, including three hydrophobic sequences (H1, H2, and H3) and an acidic region, targets and anchors perilipins to lipid droplets. Thus, we hypothesized that H1, H2, and H3 are targeting and anchoring motifs. We now show that deletion of any single hydrophobic sequence or combinations of H1 and H3 or H2 and H3 does not prevent targeting of the mutated perilipin to lipid droplets. In contrast, mutated perilipin lacking H1 and H2 showed reduced targeting, whereas perilipin lacking H1, H2, and H3 targeted poorly to lipid droplets; thus, H3 is a weak targeting signal and either H1 or H2 is required for optimal targeting. Complete elimination of perilipin targeting was observed only when all three hydrophobic sequences were deleted in combination with either the acidic region or N-terminal sequences predicted to form amphipathic β-strands. Unlike intact perilipin A, mutated perilipin lacking either H1 and H2 or H1, H2, and H3 was released from lipid droplets after alkaline carbonate treatment, suggesting that these forms are loosely associated with lipid droplets. The three hydrophobic sequences play a major role in targeting and anchoring perilipins to lipid droplets.
Resveratrol Promotes Foot Ulcer Size Reduction in Type 2 Diabetes Patients

Objective. The effect of a proprietary formulation of trans-resveratrol (t-RSV) on manifestations of diabetic foot syndrome (DFS) was studied in type 2 diabetic patients with newly diagnosed diabetic foot ulcers. Method. Placebo-controlled, examiner-blinded, parallel-group randomized controlled pilot clinical trial (ACTRN Clinical Trial Registry number 12610000629033) involving 24 patients with DFS (15 males and 9 females, average age of 56.4 ± 9.1 years) divided into the placebo and RSV-treatment groups was performed. 50 mg of t-RSV or placebo capsules was given to each patient twice a day over a 60-day time period. Results. Reduction in the parameters reflecting diabetic ulcer size was more profound in the RSV group as compared to placebo. RSV-treated patients also had a marginally improved performance in the foot pressure test. A statistically significant decline in the plasma fibrinogen level, but not CRP, was also found in the RSV-treated patients. Some improvement in the plasma lipid profile and fasting glucose levels were not related to RSV-treatment, since they have been seen on both the RSV and placebo groups, revealing the effectiveness of medical supervision and education in the newly diagnosed patients with DFS. Conclusion. t-RSV supplementation promotes reduction of the foot ulcer size and reduces plasma fibrinogen level in type 2 diabetic patients.