Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding the Optimal Power Allocation Structure in AF-Based MIMO Cooperative Networks with Multiple Relays

Cooperative networking is known to have significant potential in increasing network capacity and transmission reliability. Although there have been extensive studies on applying cooperative networking in multi-hop ad hoc networks, most works on cooperative network optimization are limited to the basic three-node relay scheme and single-antenna systems. These two limitations are interconnected and both due to a limited understanding of the optimal power allocation structure in MIMO cooperative networks (MIMO-CN). In this paper, we study in depth the structural properties of the optimal power allocation in MIMO-CN. More specifically, we show that the optimal power allocation at the source and each relay follows a matching structure in MIMO-CN. This result generalizes the power allocation result under the basic three-node setting to the multi-relay setting, for which the optimal power allocation structure has been heretofore unknown. We further quantify the performance gain due to cooperative relay and establish a connection between cooperative relay and pure relay. Finally, based on these structural insights, we reduce the MIMO-CN rate maximization problem to an equivalent scalar formulation. We then propose a global optimization method to solve this simplified and equivalent problem.
Statin Prevents Tissue Factor Expression in Human Endothelial Cells: Role of Rho/Rho-Kinase and Akt Pathways

Background—Tissue factor plays a pivotal role in thrombus formation in acute coronary syndromes. However, the regulatory mechanisms underlying tissue factor expression are poorly understood. Statins are effective in patients with acute coronary syndromes. Hence, the aim of this study was to clarify in human endothelial cells the signaling pathways of thrombin-induced tissue factor expression and potential inhibitory effects of statins. Methods and Results—In human aortic endothelial cells, simvastatin prevented tissue factor induction by thrombin (4 U/mL) in a concentration-dependent manner. The increase in tissue factor activity on the cell surface was also blocked by simvastatin. Simvastatin also prevented the upregulation of tissue factor expression and activity in human aortic smooth muscle cells. Mevalonate (100 &mgr;mol/L) reversed the inhibitory effect of simvastatin on tissue factor expression. Thrombin induced rapid activation of Rho A and p38 MAP kinase. The Rho-kinase inhibitor Y-27632 and the p38 MAP kinase inhibitor SB203580 prevented tissue factor induction. Akt was dephosphorylated by thrombin; the phosphoinositol 3-kinase inhibitor wortmannin enhanced its dephosphorylation as well as thrombin-induced tissue factor expression. Simvastatin prevented thrombin-induced Rho A activation but not p38 MAP kinase activation. Akt dephosphorylation by thrombin was blocked by both simvastatin and Y-27632. Conclusions—Endothelial tissue factor induction by thrombin is regulated by Rho/Rho-kinase, Akt, and p38 MAP kinase. Simvastatin prevents its induction through inhibition of Rho/Rho-kinase and activation of Akt. These findings provide new insights into the action of statins in acute coronary syndromes.
New light on the initial mass function of the Galactic halo globular clusters

We present new constraints on the initial mass spectrum of the Galactic Old Halo globular clusters. This has remained poorly known so far, as both an initial power-law mass spectrum and an initial lognormal mass function could have evolved into the presently observed globular cluster mass distribution, making the initial contribution of now lost low-mass objects ill-determined. Our approach consists of comparing the evolution with time of both the radial mass density profile and the number density profile of the globular cluster system. Using the analytical expression established by Vesperini & Heggie for the temporal evolution of the mass of a globular cluster on a circular orbit in a stable Galactic potential, we evolve the mass and number density profiles of many putative globular cluster systems, each starting with a different initial cluster mass spectrum and initial cluster space density. We then compare the modelled profiles with those of the Old Halo cluster system in order to investigate which system(s) provide(s) the best consistency with the data. Specifically, we build on the following points: (i) the presently observed mass density profile and number density profile of the Old Halo cluster system show the same shape; (ii) assuming that globular clusters were initially distributed the same way in mass at all galactocentric distances, the mass and number density profiles had also the same shape initially; and (iii) according to our simulations, the mass density profile remains well preserved, irrespective of the initial cluster mass spectrum, while the temporal evolution of its number counterpart depends sensitively on initial conditions. We show that to obtain a mass density profile and a number density profile that are identical in shape, both initially and after a Hubble time of evolution, the globular cluster system must have been depleted in low-mass objects from the beginning. We deduce that the initial distribution in mass of the globular clusters was either a lognormal mass function, similar to that today, or a power-law mass spectrum with a slope ≃−2 and truncated at large mass, say, around 105 M⊙. In contrast, a power-law mass spectrum with a similar slope but extending down to low cluster mass (i.e. a few thousand solar masses) seems to be ruled out.
Language and Tool Support for Model Checking of Fault-Tolerant Distributed Algorithms

Model checking is a successful formal verification technique; however, its application to fault-tolerant distributed algorithms is still not common practice. One major reason for this is that model checking requires non-negligible users¿ efforts in representing the algorithm to be verified in the input language of a model checker. To alleviate this problem we propose an approach which encompasses (i) a language for concisely describing fault-tolerant distributed algorithms and (ii) a translator from the proposed language to PROMELA, the input language of the SPIN model checker. To demonstrate the feasibility of our approach, we show the results of an experiment where we described and verified several algorithms for consensus, a well-known distributed agreement problem.
A dynamic channel selection algorithm for the classification of EEG and EMG data

The multichannel nature of EEG and EMG data poses a big challenge to the development of automatic EEG/EMG analysis and classification systems. Due to the “curse of dimensionality” problem, the analysis and classification of several channels may not lead to the desired performance. Accordingly, a number of algorithms have been proposed to identify small “static” subsets of channels that are capable of differentiating between samples of different classes. However, the identification of small subsets of relevant channels may not always be possible, where for certain applications the smaller the number of channels the less chance that sufficient information is provided. We propose in this paper a dynamic channel selection algorithm that identifies a channel (or a subset of channels) for each time segment of the signal that is relevant to the class of that particular time segment. To achieve this, we embraced the dynamic classifier selection methodology, and particularly the multiple classifier behaviour approach. Each EEG/EMG channel can be chosen to represent a certain unseen time segment of the signal based on the performance, or local accuracy, of its nearest neighbours in the set of training time segments. Results obtained using EEG data of a four-class alertness state classification problem reveal that the proposed approach is capable of achieving competitive performance compared to a traditional static channel selection based method. The algorithm also produced very encouraging results when used to classify EMG data collected from nine transradial amputees performing six classes of movements.
Creating and Maintaining Curated View Databases

The process of building a new database relevant to some eld of study in biology involves transforming, integrating, and cleansing multiple external data sources, as well as adding new material and annotations. For example, EpoDB is a database created at the University of Pennsylvania Center for Bioinformatics. It was designed to study gene regulation during di erentiation and development of vertebrate red blood cells. In building EpoDB, data relevant to red blood cells were extracted from GenBank, SWISS-PROT, TRRD (transcriptional regulation data), and GERD (expression levels data). Once extracted, the data were cleansed of errors using a semi-automated approach. Cleansed data were then integrated, and additional information or annotations entered either automatically or manually to the integrated view. Databases such as EpoDB can be thought of as secondary or derived \value-added" databases. They are proliferating in the biomedical world. In the database community, they are also called warehouses, or materialized views due to the fact that they extract and integrate data from existing databases. Creating and maintaining these view databases raise a number of problems:
On reducing packet latencies in ad hoc networks

The ad hoc on-demand distance vector (AODV) is an on-demand routing protocol designed specifically for mobile, ad hoc networks. But the packet latencies with AODV can be very high, >100 ms on average, especially when the network load is low and node mobility is high. To mitigate this effect, we have enhanced AODV with a proactive technique, which lets receiver nodes broadcast periodic 'beacons' throughout the network to keep routing entries in other nodes current. Using simulations we show that beacons reduce the packet latencies by a factor of 2-3. The routing packets transmitted are also reduced as the beacons obviate the need for some route discovery processes.
Unconstrained Impedance Control Using a Compact Series Elastic Actuator

Series elastic actuators offer high fidelity force control with inherent low impedance above their controllable frequency bandwidth. As a result they well suited for interaction with humans, in which safety is paramount. Their high force fidelity suggests that they may be a suitable for impedance control, in which the interaction between motion and force is controlled. The authors model the unconstrained actuator, and perform tests to evaluate the ability of series elastic actuators to mimic different stiffness. Series elastic actuators are found to be adequate for unconstrained impedance control at input frequencies below 3 Hz
WebFilter: A High-throughput XML-based Publish and Subscribe System

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Physiological and Mechanical Response to Soccer-Specific Intermittent Activity and Steady-State Activity

The aim of this study was to quantify response to a soccer-specific intermittent (INT) treadmill protocol based on notational analysis of match-play. Ten male semiprofessional football players (age 24.7 ± 4.4 yr, body mass 77.1 ± 8.3 kg, VO2max 63.0 ± 4.8 ml·kg·min−1) completed the 90 minute INT protocol and a steady-state (SS) protocol eliciting the same distance covered. Physiological (heart rate [HR], ratings of perceived exertion [RPE], blood lactate concentration, salivary cortisol concentration) and mechanical (electromyography [EMG] of biceps femoris and rectus femoris) responses were obtained at 15 minute intervals throughout each protocol. The physiological and mechanical responses were typically greater during the INT protocol than during the SS protocol, tending to increase as a function of exercise duration. The INT activity profile induces cumulative mechanical load on the musculoskeletal system. The increased incidence of injury toward the latter stages of match-play is attributed to compromised movement mechanics, rather than physiological strain.
Automatic Tripartite Classification of Intransitive Verbs

In this paper, we introduce a tripartite scheme for the classification of intransitive verbs for Hindi and claim it to be a more suitable model of classification than the classical binary unaccusative/unergative classification. We develop a multi-class SVM classifier based model for automatic classification of intransitive verbs into proposed tripartite classes. We rank the unaccusative diagnostic tests for Hindi based on their authenticity in attesting an intransitive verb under unaccussative class. We show that the use of the ranking score in the feature of the classifier improves the efficiency of the classification model even with a small amount of data. The empirical result illustrates the fact that judicious use of linguistic knowledge builds a better classification model than the one that is purely statistical.
Can We Reduce Bias in the Recruiting Process and Diversify Pools of Candidates by Using Different Types of Words in Job Descriptions

Intuitively, we all know diversity matters in recruiting and leadership development. McKinsey research points out that companies in the top quartile for racial and ethnic diversity are 35% more likely to have financial returns above their respective national industry medians. Strategic diversity recruitment is a way to effectively send talent through the recruitment pipeline, but it is crucial to mitigate bias. A candidate’s first interaction with employers is often through a job post that includes the job description and responsibilities. Without examining potential unconscious biases, job postings can include language that might deter a certain pool of candidates from applying, thus reducing the diversity of candidates. Through our research, we identified the beneficial use of gender fair language and flexible and inclusive wording in job advertisement and postings.
Decentralized energy management system for charging and discharging of plug-in electric vehicles

We propose a decentralized management of the charging and discharging process of plug-in electric vehicles (PEVs). By simply switching a PEV during charging, discharging, or in an off-mode, certain quality of services to a PEV owner can be maximized. Most importantly, circuit-level capacity constraints on power grids can be maintained simultaneously. However, the optimal PEV state decision problem requires an exhaustive search of all possible combinations of PEV states, which can become computationally prohibitive when the number of PEVs is very large. Therefore, we employ the convex relaxation optimization method to solve the PEV state decision problem. Moreover, we also develop a decentralized optimization algorithm that can solve the PEV state decision problem in a decentralized fashion, where charging, discharging, and off-mode are made locally by each sub-aggregator. The simulation results indicate that the proposed PEV energy management system can obtain the same final state-of-charge of the batteries as that obtained by uncontrolled cases, however, the effect of PEV charging on the power system is significantly mitigated.
Urdu compound Character Recognition using feed forward neural networks

Urdu compound Character Recognition is a scarcely developed area and requires robust techniques to develop as Urdu being a family of Arabic script is cursive, right to left in nature and characters change their shapes and sizes when they are placed at initial, middle or at the end of a word. The developed system consists of two main modules segmentation and classification. In the segmentation phase pixels strength is measured to detect words in a sentence and joints of characters in a compound/connected word for segmentation. In the next phase these segmented characters are feeded to a trained Neural Network for classification and recognition, where Feed Forward Neural Network is trained on 56 different classes of characters each having 100 samples. The main purpose of the system is to test the algorithm developed for segmentation of compound characters. The prototype of the system has been developed in Matlab, currently achieves 70% accuracy on the average
Nogo-A Inhibits Neurite Outgrowth and Cell Spreading with Three Discrete Regions

Nogo-A is a potent neurite growth inhibitor in vitro and plays a role both in the restriction of axonal regeneration after injury and in structural plasticity in the CNS of higher vertebrates. The regions that mediate inhibition and the topology of the molecule in the plasma membrane have to be defined. Here we demonstrate the presence of three different active sites: (1) an N-terminal region involved in the inhibition of fibroblast spreading, (2) a stretch encoded by the Nogo-A-specific exon that restricts neurite outgrowth and cell spreading and induces growth cone collapse, and (3) a C-terminal region (Nogo-66) with growth cone collapsing function. We show that Nogo-A-specific active fragments bind to the cell surface of responsive cells and to rat brain cortical membranes, suggesting the existence of specific binding partners or receptors. Several antibodies against different epitopes on the Nogo-A-specific part of the protein as well as antisera against the 66 aa loop in the C-terminus stain the cell surface of living cultured oligodendrocytes. Nogo-A is also labeled by nonmembrane-permeable biotin derivatives applied to living oligodendrocyte cultures. Immunofluorescent staining of intracellular, endoplasmic reticulum-associated Nogo-A in cells after selective permeabilization of the plasma membrane reveals that the epitopes of Nogo-A, shown to be accessible at the cell surface, are exposed to the cytoplasm. This suggests that Nogo-A could have a second membrane topology. The two proposed topological variants may have different intracellular as well as extracellular functions.
Histological changes in testes of rats treated with testosterone, nandrolone, and stanozolol

Background: Anabolic androgenic steroids (AAS) is being used in medical treatments, but AAS also was identified to have the risks of adverse effects towards patients and consumers health. Objective: Present study was conducted to observe the effects of testosterone, nandrolone, and stanozolol (forms of AAS) intake during onset of puberty on the rat testicular histology. Materials and Methods: Juvenile male Sprague-Dawley (SD) rats (n=42) were divided into seven groups and were injected subcutaneously with medium dose of polyethylene glycol-200 (PEG-200) (control), testosterone, nandrolone, and stanozolol for six weeks (PND 41-87). The animals were weighed daily and sacrificed on PND 88. Testes were removed, weighed, and prepared for histological assessment and finally specimens were observed under microscope. Results: The results showed an insignificant increase in mean daily body weight with highest and lowest body weight gained was of 177.6±1.69 gr and 140.0±12.26 gr respectively. There was significant decrease in the testes absolute weight (p≤0.01) in all experimental groups except in the nandrolone 2.5 mg/kg/week treated group. Testicular histology of rats treated with AAS also showed slight changes in the uniformity of arrangements of seminiferous tubules. Conclusion: Data from present study suggests that AAS have been initiating the adverse effects on testicular normal functions in rats during onset of puberty.
A natural killer cell granule protein that induces DNA fragmentation and apoptosis

We report the purification from a rat natural killer (RNK) large granular lymphocyte leukemia of a 32-kD granule protein that induces rapid DNA fragmentation and apoptosis. The protein, which we have called "fragmentin," was capable of causing DNA from intact YAC-1 cells to be cleaved into oligonucleosomal-sized fragments and producing severe chromatin condensation within 1 h. Amino acid sequence of tryptic peptides indicated that fragmentin was highly homologous to the NK and T cell granule serine proteases RNK protease 1 and mouse cytotoxic T cell protease I (CCPI)/granzyme B. Preincubation with the serine esterase inhibitor 3,4-dichloroisocoumarin blocked fragmentin- induced DNA damage, but had no effect on cytolysin. Fragmentin activity against four lymphoma target cells was completely dependent on the presence of cytolysin. Fragmentin produced rapid membrane damage as well as DNA fragmentation at nonlytic cytolysin doses, suggesting that fragmentin activity was not limited to its effects on the nucleus. Fragmentin and cytolysin activity were completely inhibited by EGTA, indicating the process was Ca2+ dependent. A role for cytolysin in endocytosis of fragmentin was suggested by the observation that treatment of YAC-1 with cytochalasin B or sodium azide and 2- deoxyglucose blocked DNA fragmentation but not cytolysin activity. A 30- kD N alpha-CBZ-L-lysine thiobenzyl esterase, which copurified with fragmentin, was inactive on its own but was able to synergistically amplify the DNA damage induced by fragmentin in the presence of cytolysin. Fragmentin activity was not dependent on protein synthesis, as cycloheximide treatment of YAC-1 cells did not prevent DNA damage. We postulate that fragmentin is the molecular mediator of NK cell- mediated DNA fragmentation and apoptosis.
A Lagrangian Gauss-Newton-Krylov Solver for Mass- and Intensity-Preserving Diffeomorphic Image Registration

We present an efficient solver for diffeomorphic image registration problems in the framework of Large Deformations Diffeomorphic Metric Mappings (LDDMM). We use an optimal control formulation, in which the velocity field of a hyperbolic PDE needs to be found such that the distance between the final state of the system (the transformed/transported template image) and the observation (the reference image) is minimized. Our solver supports both stationary and non-stationary (i.e., transient or time-dependent) velocity fields. As transformation models, we consider both the transport equation (assuming intensities are preserved during the deformation) and the continuity equation (assuming mass-preservation). We consider the reduced form of the optimal control problem and solve the resulting unconstrained optimization problem using a discretize-then-optimize approach. A key contribution is the elimination of the PDE constraint using a Lagrangian hyperbolic PDE solver. Lagrangian methods rely on the concept of characteristic curves. We approximate these curves using a fourth-order Runge-Kutta method. We also present an efficient algorithm for computing the derivatives of the final state of the system with respect to the velocity field. This allows us to use fast Gauss-Newton based methods. We present quickly converging iterative linear solvers using spectral preconditioners that render the overall optimization efficient and scalable. Our method is embedded into the image registration framework FAIR and, thus, supports the most commonly used similarity measures and regularization functionals. We demonstrate the potential of our new approach using several synthetic and real world test problems with up to 14.7 million degrees of freedom.