Miracle-dz/UniFAR-FTUs huggingface dataset:
The Impact of Dynamic Channels on Functional Topology Skeletons

Parallel functional programs with implicit communication often generate purely hierarchical communication topologies during execution: communication only happens between parent and child processes. Hence, messages between siblings must be passed via the parent causing inefficiencies that can be avoided by direct communication between arbitrary processes. The Eden parallel functional language provides dynamic channels to implement arbitrary communication topologies. This paper analyses the impact of dynamic channels on Eden's topology skeletons, i.e. skeletons which define process topologies such as rings, toroids, or hypercubes. We compare topology skeletons with and without dynamic channels with respect to runtime and communication. Our case studies confirm that dynamic channels decrease the number of messages by up to 50% and substantially reduce runtime. Detailed analyses of EdenTV (Eden trace viewer) execution profiles reveal a bottleneck in the root process when only hierarchical channel connections are used and a better distribution of communications with dynamic channels.
The Repertoire and Dynamics of Evolutionary Adaptations to Controlled Nutrient-Limited Environments in Yeast

The experimental evolution of laboratory populations of microbes provides an opportunity to observe the evolutionary dynamics of adaptation in real time. Until very recently, however, such studies have been limited by our inability to systematically find mutations in evolved organisms. We overcome this limitation by using a variety of DNA microarray-based techniques to characterize genetic changes—including point mutations, structural changes, and insertion variation—that resulted from the experimental adaptation of 24 haploid and diploid cultures of Saccharomyces cerevisiae to growth in either glucose, sulfate, or phosphate-limited chemostats for ∼200 generations. We identified frequent genomic amplifications and rearrangements as well as novel retrotransposition events associated with adaptation. Global nucleotide variation detection in ten clonal isolates identified 32 point mutations. On the basis of mutation frequencies, we infer that these mutations and the subsequent dynamics of adaptation are determined by the batch phase of growth prior to initiation of the continuous phase in the chemostat. We relate these genotypic changes to phenotypic outcomes, namely global patterns of gene expression, and to increases in fitness by 5–50%. We found that the spectrum of available mutations in glucose- or phosphate-limited environments combined with the batch phase population dynamics early in our experiments allowed several distinct genotypic and phenotypic evolutionary pathways in response to these nutrient limitations. By contrast, sulfate-limited populations were much more constrained in both genotypic and phenotypic outcomes. Thus, the reproducibility of evolution varies with specific selective pressures, reflecting the constraints inherent in the system-level organization of metabolic processes in the cell. We were able to relate some of the observed adaptive mutations (e.g., transporter gene amplifications) to known features of the relevant metabolic pathways, but many of the mutations pointed to genes not previously associated with the relevant physiology. Thus, in addition to answering basic mechanistic questions about evolutionary mechanisms, our work suggests that experimental evolution can also shed light on the function and regulation of individual metabolic pathways.
Certified Complex Root Isolation via Adaptive Root Separation

We address the problem of root isolationfor polynomial systems: for an affine, zero-dimensional polynomial system of N equations inN variables, we describe an algorithm to encapsulate all complex solutions into disjoint regions, each containing precisely one solutio n (calledisolating regions). Our approach also computes the multiplicity of each solution. The main nov elty is a new approach to certify that a set of computed regions is indeed isolating. It s based on an adaptive root separation bound obtained from combining information about th e approximate location of roots and resultant calculus. Here we use simple subdivision method to determine the number of roots within certain regions. The resultant calculus only takes place ove r prime fields to avoid the disadvantageous coefficient growth in symbolic methods, without sac rificing the exactness of the output. The presented approach is complete for uniand bivariate syst ms, and in general applies in higher dimensions as well, possibly after a coordinate change.
The Effects of Feeding on Hematological and Plasma Biochemical Profiles in Green (Chelonia mydas) and Kemp's Ridley (Lepidochelys kempii) Sea Turtles

In mammals, lipemic blood from sampling too soon after an animal feeds can have substantial effects on biochemical values. Plasma biochemical values in reptiles may be affected by species, age, season, and nutritional state. However, fasting status is not routinely considered when sampling reptile blood. In this paper, we evaluated 2-hour postprandial blood collection in two sea turtle species to investigate the effects of feeding on hematological and plasma biochemical values. Feeding had no significant effects on hematological values in either species, nor did it have an effect on plasma biochemistry values in Kemp's ridley sea turtles. In postprandial green turtles, total protein, albumin, ALP, AST, ALT, amylase, and cholesterol increased significantly, and chloride decreased significantly. Although statistically significant changes were observed, the median percent differences between pre- and postprandial values did not exceed 10% for any of these analytes and would not likely alter the clinical interpretation.
Learning Convolutional Nonlinear Features for K Nearest Neighbor Image Classification

Learning low-dimensional feature representations is a crucial task in machine learning and computer vision. Recently the impressive breakthrough in general object recognition made by large scale convolutional networks shows that convolutional networks are able to extract discriminative hierarchical features in large scale object classification task. However, for vision tasks other than end-to-end classification, such as K Nearest Neighbor classification, the learned intermediate features are not necessary optimal for the specific problem. In this paper, we aim to exploit the power of deep convolutional networks and optimize the output feature layer with respect to the task of K Nearest Neighbor (kNN) classification. By directly optimizing the kNN classification error on training data, we in fact learn convolutional nonlinear features in a data-driven and task-driven way. Experimental results on standard image classification benchmarks show that the proposed method is able to learn better feature representations than other general end-to-end classification methods on kNN classification task.
Human-robot interactions in active sensor networks

This paper considers the modes of interaction between one or several human operators and an active sensor network-a fully decentralized network of sensors some or all of which have actuators and are in that sense active. The primary goal of this study is to investigate the conditions under which the human involvement will not jeopardize scalability of the overall system. Two aspects of human-robot interaction are considered: the ways in which the global view of the system may be conveyed to the operators, and how the operators may influence the behavior of the system during the course of its operation. The results of analysis favor peer-to-peer environment-centric interactions between the operators and the network whereby the humans act as extended sensors and communication nodes of the network itself. Experiments on an indoor active sensor network are described.
SIGN LANGUAGE RECOGNITION BASED ON ELECTROMYOGRAPHY (EMG) SIGNAL USING ARTIFICIAL NEURAL NETWORK (ANN)

EMG signal is a muscular signal. It can represent equally time & frequency domain. EMG provides measurement of muscular performance. Hence it is a direct representation of strength of health. It is used for identification & treatment tasks by comparing with normal person. EMG biofeedback can be instantaneous as compare to manual inspection. EMG signal used in management of prostheses & to improve the effectiveness of rehabilitation robotics. The motive of this paper is to describe the process of detecting different predefined hand gestures using artificial neural network (ANN). This different hand gestures used by deaf & dumb people to understand the things. The EMG sample signatures are extracted from the signals for all movement and then given to ANN for training & classification. A back-propagation (BP) network has been used for the recognition of sign, as it works well for different biosignal. The features like autoregression coefficient, fast Fourier transform, short time Fourier transform, wavelet transform coefficient, mean absolute value, root mean square, variance, standard deviation, Mean frequency, zero crossing and slope sign change are selected to train the neural network.
Automating the identification of variability realisation techniques from feature models

In Software Product Line Engineering (SPLE), feature modelling is frequently used to model commonalities and variabilities within a domain. A feature model captures an abstract view of a product line and it can serve as a starting point for software design and component implementation. Handling variability exposed within the feature model is an important problem in this context, and in this paper, we describe ongoing research aimed at automating the identification of variability realisation techniques from feature models
Thermal and Cold Spray: Recent Developments

Thermal spraying consists in a technology aiming at producing coatings whose thicknesses range from 10 μm to a few millimeters onto mechanical components to confer them specific and unique functional properties, such as wear and corrosion resistances, friction coefficient adaptation, thermal and electrical insulation, biocompatibility, repair, etc., among the principals. Thermal spraying consists in injecting in a viscous enthalpic jet (animated by a momentum) powder with particles which average size ranges from 0.01 to 100 μm. These particles are melted and simultaneously accelerated towards the surface of the part to be covered. They form, after impact, spreading and solidification, near-circular lamellae the stacking of which form the coating. Due to the versatility of the available processes exhibiting a wide range of enthalpic and momentum contents, virtually any kind of material exhibiting congruent melting behavior can be processed, from alloys and ceramics to polymers, ever since its melting temperature differs from its vaporization or decomposition temperature by at least 300 K and that it can be processed previously under the form of powder particles or wires. Thermal spray techniques offer the unique capability to manufacture a large variety of coatings on components of a large variety and geometry. However, thermal spraying constitutes a special process for which the coating service properties derive mostly from the structure and indirectly from the selection of the operating parameters. Very significant improvements over the past years permitted to diagnose the in-flight particle characteristics, mostly in terms of velocity and temperature. Recently, these new capabilities have made possible the development of on-line process controls. This should participate to a drastic increase in coating reliability. In convetntional thermal spraying processes, a pulverulent feedstock (i.e., powder particles) is injected within the plasma jet via a carrier gas. This approach does not permit to process small diameter particles; i.e., nano-sized particles, which could permit to form finely grained coatings. Replacing gas by liquid to carry particles offer the unique possibility to process nano-sized particles. Cold gas spraying may appear as an alternative process to reach the same goal. Indeed, thermal spray processes experienced very significant developments over the past years, opening new doors to manufacture coatings with a high reliability and superior properties. This papepr indend at presenting some of those developments.
In Vivo and In Vitro Development of the Protist Helicosporidium sp

Abstract We describe the discovery and developmental features of a Helicosporidium sp. isolated from the black fly Simulium jonesi. Morphologically, the helicosporidia are characterized by a distinct cyst stage that encloses three ovoid cells and a single elongate filamentous cell. Bioassays have demonstrated that the cysts of this isolate infect various insect species, including the lepidopterans, Helicoverpa zea, Galleria mellonella, and Manduca sexta, and the dipterans, Musca domestica, Aedes taeniorhynchus, Anopheles albimanus, and An. quadrimaculatus. The cysts attach to the insect peritrophic matrix prior to dehiscence, which releases the filamentous cell and the three ovoid cells. The ovoid cells are short-lived in the insect gut with infection mediated by the penetration of the filamentous cell into the host. Furthermore, these filamentous cells are covered with projections that anchor them to the midgut lining. Unlike most entomopathogenic protozoa, this Helicosporidium sp. can be propagated in simple nutritional media under defined in vitro conditions, providing a system to conduct detailed analysis of the developmental biology of this poorly known taxon. The morphology and development of the in vitro produced cells are similar to that reported for the achorophyllic algae belonging to the genus Prototheca.
A navigation mesh for dynamic environments

Games and simulations frequently model scenarios where obstacles move, appear, and disappear in an environment. A city environment changes as new buildings and roads are constructed, and routes can become partially blocked by small obstacles many times in a typical day. This paper studies the effect of using local updates to repair only the affected regions of a navigation mesh in response to a change in the environment. The techniques are inspired by incremental methods for Voronoi diagrams. The main novelty of this paper is that we show how to maintain a 2D or 2.5D navigation mesh in an environment that contains dynamic polygonal obstacles. Experiments show that local updates are fast enough to permit real‐time updates of the navigation mesh. Copyright © 2012 John Wiley & Sons, Ltd.
Moraxella catarrhalis‐dependent tonsillar B cell activation does not lead to apoptosis but to vigorous proliferation resulting in nonspecific IgM production

The respiratory pathogen Moraxella catarrhalis has a high affinity for human IgD and is mitogenic for peripheral blood B lymphocytes. Moraxella IgD‐binding protein, which is a multifunctional outer membrane protein with adhesive properties, is responsible for the interaction. Previous experiments with the Ig‐binding B cell superantigens protein A and protein L from Staphylococcus aureus and Peptostreptococcus magnus, respectively, have suggested that nonimmune BCR cross‐linking induces B cell apoptosis through the intrinsic pathway. The goal of this study was to characterize early and late B cell events in the presence of M. catarrhalis in comparison with S. aureus. Despite an increased phosphatidyl serine translocation as revealed by Annexin V binding in flow cytometry analyses, neither M. catarrhalis nor S. aureus induced activation‐associated apoptotic cell death in purified human tonsillar B cells. In contrast, a vigorous B cell proliferation, as quantified using thymidine incorporation and CFSE staining, was observed. An increased expression of an array of surface proteins (i.e., CD19, CD21, CD40, CD45, CD54, CD69, CD86, CD95, and HLA‐DR) and IgM production was found upon activation with M. catarrhalis. In conclusion, M. catarrhalis‐dependent B cell activation does not result in apoptosis but in cell division and nonspecific IgM synthesis, suggesting that the bacterial interaction with tonsillar B cells serves to redirect the early adaptive immune response.
New avenues for treating emotional memory disorders: towards a reconsolidation intervention for posttraumatic stress disorder

The discovery that fear memories may change upon retrieval, a process referred to as memory reconsolidation, opened avenues to develop a revolutionary new treatment for emotional memory disorders. Reconsolidation is a two-phase process in which retrieval of a memory initiates a transient period of memory destabilization, followed by a protein synthesis-dependent restabilization phase. This reconsolidation window offers unique opportunities for amnesic agents to interfere with the process of memory restabilization, thereby weakening or even erasing the emotional expression from specific fear memories. Here we present four uncontrolled case descriptions of patients with symptoms of posttraumatic stress disorder (PTSD) who received a reconsolidation intervention. The intervention basically involves a brief reactivation of the trauma memory aimed to trigger memory destabilization, followed by the intake of one pill of 40 mg propranolol HCl (i.e. a noradrenergic beta-blocker) that should disrupt the process of memory restabilization. We present three cases who showed a steep decline of fear symptoms after only one or two intervention sessions. To illustrate that the translation from basic science to clinical practice is not self-evident, we also present a description of a noneffective intervention in a relatively complex case. Even though the reconsolidation intervention is very promising, the success of the treatment depends on whether the memory reactivation actually triggers memory reconsolidation. Obviously the uncontrolled observations described here warrant further study in placebo-controlled designs.
A Coupling-based Complexity Metric for Remote Component-based Software Systems Toward Maintainability Estimation

Remote-component-based software systems (CBS) must provide high maintainability to support operation over long periods of time and correspond to changes in enterprise requirements/environments. Measurements of the degree of complexity of a system are one technique for evaluating maintainability. However, conventional complexity metrics are unable to reflect the overall complexity of the system, because they do not incorporate a procedure to account for characteristics of CBS. To help maintenance work proceed smoothly, we propose a new metric that measures the coupling-based complexity of CBS by abstracting the target system's structure through a step-wise process and taking into consideration the characteristics of remote components. Our metric can be applied to CBS based on the Enterprise JavaBeans component architecture. As a result of experimental evaluations, it is found that our metric better reflects the maintainability than conventional metrics. It is also found that our metric is nonredundant with existing metrics such as coupling factor.
Grid current regulation of a three-phase voltage source inverter with an LCL input filter

Many grid connected power electronic systems, such as STATCOMs, UPFCs and distributed generation system interfaces, use a voltage source inverter (VSI) connected to the supply network through a filter. This filter, typically a series inductance, acts to reduce the switching harmonics entering the distribution network. An alternative filter is a LCL network, which can achieve reduced levels of harmonic distortion at lower switching frequencies and with less inductance, and therefore has potential benefits for higher power applications. However, systems incorporating LCL filters require more complex control strategies and are not commonly presented in literature. This paper proposes a robust strategy for regulating the grid current entering a distribution network from a three-phase VSI system connected via an LCL filter. The strategy integrates an outer loop grid current regulator with inner capacitor current regulation to stabilise the system. A synchronous frame PI current regulation strategy is used for the outer grid current control loop. Linear analysis, simulation and experimental results are used to verify the stability of the control algorithm across a range of operating conditions. Finally, expressions for "harmonic impedance" of the system are derived to study the effects of supply voltage distortion on the harmonic performance of the system.
Turbo Parsers: Dependency Parsing by Approximate Variational Inference

We present a unified view of two state-of-the-art non-projective dependency parsers, both approximate: the loopy belief propagation parser of Smith and Eisner (2008) and the relaxed linear program of Martins et al. (2009). By representing the model assumptions with a factor graph, we shed light on the optimization problems tackled in each method. We also propose a new aggressive online algorithm to learn the model parameters, which makes use of the underlying variational representation. The algorithm does not require a learning rate parameter and provides a single framework for a wide family of convex loss functions, including CRFs and structured SVMs. Experiments show state-of-the-art performance for 14 languages.
Detecting structure in parity binary sequences

In this article, we investigate the possible existence of error-detection/correction mechanisms in the genetic machinery by means of a recently proposed coding strategy. On this basis, we numerically code exons, creating binary parity strings and successively we study their dependence structure by means of rigorous statistical methods (moving block bootstrap, and a new entropy-based method). The results show that parity sequences display complex dependence patterns enforcing the hypothesis of the existence of deterministic error-correction mechanisms grounded on this particular parity coding.
On testing the source compatibility in Java

When software components evolve, they change interfaces, which may break backward compatibility. We present a tool that facilitates checking whether a new version of component is source compatible with a previous version. This tool figures out the component interface and generates the client code that uses the component interface to maximum extent. If the generated client compiles against the new component interface, those two versions are more or less compatible. The tool can be useful for API authors.
A standard file format for data from DNA sequencing instruments.

There are now a number of machines for determining DNA sequences. These devices are currently of two types: those such as the Applied Biosystems 373A and the Pharmacia A.L. F. which interpret the sequences of samples as they run on gels within the machine, and those, such as the Bio-Rad and Amersham readers that scan and analyse conventional autoradiographs. Both types of machine can produce their data in the form of traces which represent the band intensity of each of the four base types at each position in the sequence. At present all the machines write files in different formats. We describe a machine independent format for storing data derived from automatic sequencing machines. Files in this format can store the derived sequence, the traces and a set of confidence measures for each base. We have adopted the format as the standard for our sequence handling software.