Miracle-dz/UniFAR-FTUs huggingface dataset:
Contact-Induced Mitochondrial Polarization Supports HIV-1 Virological Synapse Formation

ABSTRACT Rapid HIV-1 spread between CD4 T lymphocytes occurs at retrovirus-induced immune cell contacts called virological synapses (VS). VS are associated with striking T cell polarization and localized virus budding at the site of contact that facilitates cell-cell spread. In addition to this, spatial clustering of organelles, including mitochondria, to the contact zone has been previously shown. However, whether cell-cell contact specifically induces dynamic T cell remodeling during VS formation and what regulates this process remain unclear. Here, we report that contact between an HIV-1-infected T cell and an uninfected target T cell specifically triggers polarization of mitochondria concomitant with recruitment of the major HIV-1 structural protein Gag to the site of cell-cell contact. Using fixed and live-cell imaging, we show that mitochondrial and Gag polarization in HIV-1-infected T cells occurs within minutes of contact with target T cells, requires the formation of stable cell-cell contacts, and is an active, calcium-dependent process. We also find that perturbation of mitochondrial polarization impairs cell-cell spread of HIV-1 at the VS. Taken together, these data suggest that HIV-1-infected T cells are able to sense and respond to contact with susceptible target cells and undergo dynamic cytoplasmic remodeling to create a synaptic environment that supports efficient HIV-1 VS formation between CD4 T lymphocytes. IMPORTANCE HIV-1 remains one of the major global health challenges of modern times. The capacity of HIV-1 to cause disease depends on the virus's ability to spread between immune cells, most notably CD4 T lymphocytes. Cell-cell transmission is the most efficient way of HIV-1 spread and occurs at the virological synapse (VS). The VS forms at the site of contact between an infected cell and an uninfected cell and is characterized by polarized assembly and budding of virions and clustering of cellular organelles, including mitochondria. Here, we show that cell-cell contact induces rapid recruitment of mitochondria to the contact site and that this supports efficient VS formation and consequently cell-cell spread. Additionally, we observed that cell-cell contact induces a mitochondrion-dependent increase in intracellular calcium, indicative of cellular signaling. Taken together, our data suggest that VS formation is a regulated process and thus a potential target to block HIV-1 cell-cell spread.
What impacts skin color in digital photos?

Skin colors are important for a broad range of imaging applications to assure quality and naturalness. We discuss the impact of various metadata on skin colors in images, i.e. how does the presence of a metadata attribute influence the expected skin color distribution for a given image. For this purpose we employ a statistical framework to automatically build color models from image datasets crawled from the web. We assess both technical and semantic metadata and show that semantic metadata has a more significant impact. This suggests that semantic metadata holds important cues for processing of skin colors. Further we demonstrate that the refined skin color models from our automatic framework improve the accuracy of skin detection.
Model-distributed solution of regularized least-squares problem over sensor networks

We develop a fully-distributed iterative algorithm for finding a model-distributed least-squares solution of systems of linear equations over sensor networks. Here, model-distributed means the solution vector is distributed across the network rather than being replicated at each node. For this purpose, we devise a dual regularized least-squares problem via a suitable decomposition of the normal equations associated with the original problem. The resultant dual problem can be solved in a fully-decentralized and iterative manner by means of the diffusion-based Pareto optimization strategy. We verify the usefulness of the proposed algorithm via both theoretical analysis and numerical examples.
The Properties of Binding Sites of miR-619-5p, miR-5095, miR-5096, and miR-5585-3p in the mRNAs of Human Genes

The binding of 2,578 human miRNAs with the mRNAs of 12,175 human genes was studied. It was established that miR-619-5p, miR-5095, miR-5096, and miR-5585-3p bind with high affinity to the mRNAs of the 1215, 832, 725, and 655 genes, respectively. These unique miRNAs have binding sites in the coding sequences and untranslated regions of mRNAs. The mRNAs of many genes have multiple miR-619-5p, miR-5095, miR-5096, and miR-5585-3p binding sites. Groups of mRNAs in which the ordering of the miR-619-5p, miR-5095, miR-5096, and miR-5585-3p binding sites differ were established. The possible functional and evolutional properties of unique miRNAs are discussed.
Web-service for finding cloned files using b-bit minwise hashing

Source code reuse is a common practice in software development. Since industrial developers may accidentally reuse source files developed by open source software, clone detection tools are used to detect open source files in their closed source project. To execute a clone detection, developers need a database of existing open source software. While a web-service providing clone detection using a centralized database is likely useful, industrial developers are not allowed to submit their source code to a public server on the Internet. To solve the problem, we employ b-bit minwise hashing technique that enables to estimate similarity of documents using only hash values of the documents. Using the method, we implemented a file-clone detection web service; it takes as input a hash value of a source file and returns a list of similar source files in existing open source software. Our hash comparison method is efficient, although an estimated similarity may have a margin of error.
III-nitride blue and ultraviolet photonic crystal light emitting diodes

We present results on enhancement of 460 nm blue and 340 nm UV optical power output in III-nitride light emitting diodes (LEDs) using photonic crystals (PCs) under current injection. Triangular arrays of the PCs with diameter/periodicity of 300/700 nm were patterned using electron-beam lithography and inductively coupled plasma dry etching. The total power at 20 mA of 300×300 μm2 unpackaged LED chips revealed an increase by 63% and 95% for the blue and UV LEDs, respectively, as a result of the PC formation. Possible ways for further improving enhancement of light extraction using PCs are discussed.
Sparse Optimization with Least-Squares Constraints

The use of convex optimization for the recovery of sparse signals from incomplete or compressed data is now common practice. Motivated by the success of basis pursuit in recovering sparse vectors, new formulations have been proposed that take advantage of different types of sparsity. In this paper we propose an efficient algorithm for solving a general class of sparsifying formulations. For several common types of sparsity we provide applications, along with details on how to apply the algorithm, and experimental results.
SecURe DPR: Secure update preventing replay attacks for dynamic partial reconfiguration

Dynamic partial reconfiguration is a growing need for SRAM FPGA-based embedded systems. This feature allows reconfiguring parts of the FPGA while others continue to run. But it may introduce security breaches affecting FPGA configuration. In this paper, a secure protocol to ensure confidentiality, integrity, authenticity and up-to-dateness is described and applied to dynamic partial reconfiguration. Two common threat models are addressed for industrially-driven use cases. The implementation can perform both secure update and reconfiguration without significantly affecting performances.
An integrated, probabilistic model for improved seasonal forecasting of agricultural crop yield under environmental uncertainty

We present a novel forecasting method for generating agricultural crop yield forecasts at the seasonal and regional-scale, integrating agroclimate variables and remotely-sensed indices. The method devises a multivariate statistical model to compute bias and uncertainty in forecasted yield at the Census of Agricultural Region (CAR) scale across the Canadian Prairies. The method uses robust variable-selection to select the best predictors within spatial subregions. Markov-Chain Monte Carlo (MCMC) simulation and random forest-tree machine learning techniques are then integrated to generate sequential forecasts through the growing season. Cross-validation of the model was performed by hindcasting/backcasting it and comparing its forecasts against available historical data (1987-2011) for spring wheat (Triticum aestivum L.). The model was also validated for the 2012 growing season by comparing its forecast skill at the CAR, provincial and Canadian Prairie region scales against available statistical survey data. Mean percent departures between wheat yield forecasted were under-estimated by 1-4 % in mid-season and over-estimated by 1 % at the end of the growing season. This integrated methodology offers a consistent, generalizable approach for sequentially forecasting crop yield at the regional-scale. It provides a statistically robust, yet flexible way to concurrently adjust to data-rich and data-sparse situations, adaptively select different predictors of yield to changing levels of environmental uncertainty, and to update forecasts sequentially so as to incorporate new data as it becomes available. This integrated method also provides additional statistical support for assessing the accuracy and reliability of model-based crop yield forecasts in time and space.
Classifying Human Leg Motions with Uniaxial Piezoelectric Gyroscopes

This paper provides a comparative study on the different techniques of classifying human leg motions that are performed using two low-cost uniaxial piezoelectric gyroscopes worn on the leg. A number of feature sets, extracted from the raw inertial sensor data in different ways, are used in the classification process. The classification techniques implemented and compared in this study are: Bayesian decision making (BDM), a rule-based algorithm (RBA) or decision tree, least-squares method (LSM), k-nearest neighbor algorithm (k-NN), dynamic time warping (DTW), support vector machines (SVM), and artificial neural networks (ANN). A performance comparison of these classification techniques is provided in terms of their correct differentiation rates, confusion matrices, computational cost, and training and storage requirements. Three different cross-validation techniques are employed to validate the classifiers. The results indicate that BDM, in general, results in the highest correct classification rate with relatively small computational cost.
Aiding the choice of a voting procedure for a business decision problem

Since all voting procedures have some serious drawbacks that lead to undesirable outcomes under some circumstances, we aim to characterize decision settings that make certain performance criteria particularly pertinent, while at the same time rendering other criteria largely irrelevant. The settings are distinguishable in terms of the goals of group choice as well as of the assumptions one can reasonably impose on the individuals participating. In business organization the mcdm group decision process, considering final aggregation of DMs preference, usually uses voting procedure. However, a specific decision problem has to be accounted for in this situation. This problem consists of choosing the voting procedure. In this paper we assume that this decision should be made by the DMs with some methodological and technical aiding given by an analyst, using a specific decision model. Therefore, this paper presents some features related to an mcdm model for aiding the choice of a voting procedure for a business organization decision problem.
Very low-voltage digital-audio ΔΣ modulator with 88-dB dynamic range using local switch bootstrapping

A 1-V 1-mW 14-bit /spl Delta//spl Sigma/ modulator in a standard CMOS 0.35-/spl mu/m technology is presented. Special attention has been given to device reliability and power consumption in a switched-capacitor implementation. A locally bootstrapped symmetrical switch that avoids gate dielectric overstress is used in order to allow rail-to-rail signal switching. The switch constant overdrive also enhances considerably circuit linearity. Modulator coefficients of a single-loop third-order topology have been optimized for low power. Further reduction in the power consumption is obtained through a modified two-stage opamp. Measurement results show that for an oversampling ratio of 100, the modulator achieves a dynamic range of 88 dB, a peak signal-to-noise ratio of 87 dB and a peak signal-to-noise-plus-distortion ratio of 85 dB in a signal bandwidth of 25 kHz.
Carbon Monoxide Promotes Respiratory Hemoproteins Iron Reduction Using Peroxides as Electron Donors

The physiological role of the respiratory hemoproteins (RH), hemoglobin and myoglobin, is to deliver O2 via its binding to their ferrous (FeII) heme-iron. Under variety of pathological conditions RH proteins leak to blood plasma and oxidized to ferric (FeIII, met) forms becoming the source of oxidative vascular damage. However, recent studies have indicated that both metRH and peroxides induce Heme Oxygenase (HO) enzyme producing carbon monoxide (CO). The gas has an extremely high affinity for the ferrous heme-iron and is known to reduce ferric hemoproteins in the presence of suitable electron donors. We hypothesized that under in vivo plasma conditions, peroxides at low concentration can assist the reduction of metRH in presence of CO. The effect of CO on interaction of metRH with hydrophilic or hydrophobic peroxides was analyzed by following Soret and visible light absorption changes in reaction mixtures. It was found that under anaerobic conditions and low concentrations of RH and peroxides mimicking plasma conditions, peroxides served as electron donors and RH were reduced to their ferrous carboxy forms. The reaction rates were dependent on CO as well as peroxide concentrations. These results demonstrate that oxidative activity of acellular ferric RH and peroxides may be amended by CO turning on the reducing potential of peroxides and facilitating the formation of redox-inactive carboxyRH. Our data suggest the possible role of HO/CO in protection of vascular system from oxidative damage.
Analysis and optimization of packaged inductively degenerated common-source low-noise amplifiers with ESD protection

The effects of packaging in inductively degenerated common-source low-noise amplifiers (LNAs) with electrostatic discharge (ESD) protection are studied and the performance of the packaged LNA is optimized. Equations describing the input impedance, transconductance, voltage gain, and noise figure (NF) of the packaged amplifier are derived and the effects of the LNA input matching network, package, and ESD parasitics on these amplifier quantities are highlighted. From the equations, several design guidelines for the packaged LNA are obtained and a systematic approach for the ESD-protected LNA optimization is deduced. It is also shown that, in the presence of an equivalent parallel package parasitic capacitance C/sub p/, the NF in a well-optimized LNA is easily dominated by the losses of the input-matching network instead of the active device noise. Based on the theoretical results, a packaged inductively degenerated common-source LNA with ESD protection is designed in a 0.13-/spl mu/m CMOS process. The amplifier provides a forward gain (S/sub 21/) of almost 18 dB at 2 GHz with an NF of 1.6 dB while consuming 8.4 mW from a 1.2-V supply.
Towards machine diagnostics on chip

Failures of critical factory equipment are one of the main reasons for production stoppages and a regular maintenance schedule is required to ensure continuous operation of production line. However, regular maintenance can be both costly and inefficient. Vibrations are present in all machinery with moving parts and it had always been regarded as an indicator of the health and condition of rotating machinery. With advances in technology, what used to be a mechanic's hunch can now be measured and with reasonable accuracy. This paper present a proof-of-concept implementation of machine diagnostic on chip using an intelligent wireless sensor node, capable of processing and analyzing vibration signals from Micro-electromechanical (MEMS) sensors. Special design considerations were also made to allow the wireless sensor node to be reconfigurable and modular at both the hardware and software level. A custom fixed-point library was implemented to tackle accuracy issues in dealing with small numbers without the use of floating point numbers in resource scarce platforms.
Cloud Based Localization for Mobile Robot in Outdoors

Cloud Robotics is the application of the cloud computing concept to the robot. It utilizes modern cloud computing infrastructure to distribute computing resources and datasets. A cloud based localization technique is proposed in this paper to allow the robot to identify its location relative to a road network map in the cloud. The update of the road network map and the extraction of the robot-terrain inclination model (RTI model) are running in the cloud. A particle filter localization is achieved on the mobile robot based on the local RTI model sent from the cloud. Experiments were carried out for validation of the proposed cloud based localization technique. Preliminary results show that this method could be potentially applicable to long-term autonomous.
Exploring the Maintenance Process through the Defect Management in the Open Source Projects - Four Case Studies

While Open Source Software are becoming evermore widespread and used these days, their maintenance is coming important issue. Earlier studies have shown that defect and version management systems are rich and valuable sources for evaluation of maintenance but they have not studied the use of separate management system for support and feature request. Therefore, in this research we study defect reports, support and feature requests of Open Source Software projects through four case studies from SourceForge. Results showed that most of the case studies used actively those systems but discussion forums were even more active. Although reports and requests were submitted, most of them did not cause any changes or further actions because they were closed shortly as duplicates, invalid or without any resolution.
Multiservice Optical Packet Switched Networks: Modeling, Performance Evaluation and QoS Mechanisms in a Mesh Slotted Architecture

Optical Packet Switching (OPS) technologies are among the most promising solutions for Next Generation Network architectures. Resource contention resolution and Quality of Service (QoS) management mechanisms have been developed in order to remedy the lack of optical buffering and implement multi-service support in OPS networks. In this paper we propose an analytical model for the access and core nodes of a multiservice mesh network architecture which operates in a synchronous slotted transmission mode. The proposed model captures the effect of the client traffic matrix and considers a priority-based multi-service support. Moreover, we elaborate two resource management mechanisms: Cumulative Credits Mechanism (CCM) and Distributed Deflection Routing (DDR). The former solves inter-class fairness issues at the access nodes and the latter optimizes the resource contention resolution in the core of the network. We use our analytical model to show the interest of the developed mechanisms. The results obtained by the proposed model are validated and analyzed through several simulation scenarios.
Nerve Growth Factor Induces Transcription of the p21 WAF1/CIP1 and Cyclin D1 Genes in PC12 Cells by Activating the Sp1 Transcription Factor

The PC12 pheochromocytoma cell line responds to nerve growth factor (NGF) by gradually exiting from the cell cycle and differentiating to a sympathetic neuronal phenotype. We have shown previously (Yan and Ziff, 1995) that NGF induces the expression of the p21 WAF1/CIP1/Sdi1 (p21) cyclin-dependent kinase (Cdk) inhibitor protein and the G1phase cyclin, cyclin D1. In this report, we show that induction is at the level of transcription and that the DNA elements in both promoters that are required for NGF-specific induction are clusters of binding sites for the Sp1 transcription factor. NGF also induced a synthetic promoter with repeated Sp1 sites linked to a core promoter, and a plasmid regulated by a chimeric transactivator in which the Gal4 DNA binding domain is fused to the Sp1 transactivation domain, indicating that this transactivation domain is regulated by NGF. Epidermal growth factor, which is a weak mitogen for PC12, failed to induce any of these promoter constructs. We consider a model in which the PC12 cell cycle is arrested as p21 accumulates and attains inhibitory levels relative to Cdk/cyclin complexes. Sustained activation of p21 expression is proposed to be a distinguishing feature of the activity of NGF that contributes to PC12 growth arrest during differentiation
Wideband speech and audio coding using gammatone filter banks

Considerable research attention has been directed towards speech and audio coding algorithms capable of producing high quality coded speech and audio, however few of these use signal representations which account for temporal as well as spectral detail. This paper presents a new technique for 16 kHz wideband speech and audio coding, whereby analysis and synthesis are performed using a linear phase gammatone filter bank. The outputs of these critical band filters are processed to obtain a series of pulse trains that represent neural firing. Auditory masking is then applied to reduce the number of pulses, producing a more compact time-frequency parameterization. The critical band gains and pulse amplitudes and positions are then coded using a combination of non-uniform quantization, arithmetic coding and vector quantization. This coding paradigm produces high quality coded speech and audio, is based upon well-known models of the auditory system, is highly scalable, and has moderate complexity.