Miracle-dz/UniFAR-FTUs huggingface dataset:
R5 HIV gp120‐mediated cellular contacts induce the death of single CCR5‐expressing CD4 T cells by a gp41‐dependent mechanism

The use of CXC chemokine receptor 4 (CXCR4) and CC chemokine receptor 5 (CCR5) by X4 and R5 human immunodeficiency virus (HIV) envelopes (Env) influences HIV cytopathicity. Here, we have evaluated the role of CCR5 and gp41 in Env‐induced cell death occurring during the contacts of uninfected, primary cells with MOLT cells infected with different R5 and X4 HIV isolates. As reported for X4‐Env, R5 HIV‐infected cells destroyed CD4 T cells expressing the appropriate coreceptor by inducing the formation of syncytia and the death of single target cells. Therefore, only the small (<10%) CCR5+ subset of primary CD4 T cells was sensitive to cellular presentation of R5‐Env, and CCR5–CD4 T cells showed complete resistance to R5‐Env‐mediated cell death. X4‐ and R5‐infected cells killed single primary cells by a common mechanism that was dependent on gp41 function and induced a rapid loss of mitochondrial membrane potential and plasma membrane integrity in target cells. Single‐cell death was not affected by the blockade of HIV replication in target cells or G‐protein signaling through CXCR4/CCR5. In contrast, caspase inhibition (Z‐Val‐Ala‐Asp‐fluoromethylketone) profoundly changed the outcome of cell‐to‐cell contacts by reducing the number of single dead CD4 T cells and increasing the rate of syncytium formation. In conclusion, X4 and R5 HIV Env share a common gp41‐dependent mechanism to kill CD4 T cells during cellular contacts. Env tropism and coreceptor expression but not differential killing mechanisms seem to govern the extent of cytopathic effects induced by HIV infection.
A new remarkable subterranean beetle of the Rhodopes: Paralovricia gen. n. beroni sp. n. belonging to Lovriciina new subtribe (Coleoptera, Carabidae, Trechinae, Bembidiini)

Abstract Paralovricia gen. n. beroni sp. n. , belonging to the new subtribe Lovriciina, is described from two caves in the Western Rhodopes (Bulgaria): Kraypatnata peshtera, near Smilyan Village (Smolyan Municipality) and Snezhanka, near Peshtera Town (Peshtera Municipality). Three currently known genera, Lovricia Pretner, 1979, Neolovricia Lakota, Jalžić & Moravec, 2009 and Paralovricia gen. n. represent a monophyletic unit supported by important synapomorphies that allows to propose the establishment of the new subtribe Lovriciina, characterized by the following characters: last maxillary palpomeres very long and narrow, basal angles of pronotum without seta, elytra without discal setae, elytral umbilicate series of nine pores in which the main pores are the 2nd, 6th and 9th, apical recurrent striole absent and mesotibial apex expanded outward. Its systematic position within the subfamily Trechinae (sensu Lorenz 2005) is discussed and Lovriciina is placed near Anillina. Key to the genera of the subtribe is proposed. Distribution data and zoogeographical hypotheses are discussed.
Mixed-ADC Massive MIMO Uplink in Frequency-Selective Channels

The aim of this paper is to investigate the recently developed mixed-analog-to-digital converter (ADC) architecture for frequency-selective channels. Multi-carrier techniques, such as orthogonal frequency division multiplexing, are employed to handle inter-symbol interference. A frequency-domain equalizer is designed for mitigating the inter-carrier interference introduced by the nonlinearity of one-bit quantization. For static single-input-multiple-output (SIMO) channels, a closed-form expression of the generalized mutual information (GMI) is derived, and based on which the linear frequency-domain equalizer is optimized. The analysis is then extended to ergodic time-varying SIMO channels with estimated channel state information, where numerically tight lower and upper bounds of the GMI are derived. The analytical framework is naturally applicable to the multi-user scenario, for both static and time-varying channels. Extensive numerical studies reveal that the mixed-ADC architecture with a small proportion of high-resolution ADCs does achieve a dominant portion of the achievable rate of ideal conventional architecture, and that it remarkably improves the performance as compared with one-bit massive multiple-input-multiple-output.
Cadmium-specific formation of metal sulfide 'Q-particles' by Klebsiella pneumoniae.

Klebsiella pneumoniae overcomes cadmium toxicity through the 'biotrans-formation' of cadmium ions into photoactive, nanometre-sized CdS particles deposited on the cell surface. The kinetics of particle formation during batch culture growth was monitored by electron microscopy (EM), energy-dispersive X-ray analysis and electronic absorption spectroscopy (EAS). During the deceleration phase of bacterial growth, the presence of CdS particles on the outer cell wall of K. pneumoniae (> or = 5 nm in diameter) was detected by EM. The size of these electron-dense particles continued to increase throughout the stationary phase of growth, with some of the particles reaching a diameter > 200 nm. The formation of the extracellular CdS particles contributed to around 3-4% of the total cell biomass. EAS undertaken on these extracellular 'bio-CdS' particles suggested that the large 'superparticles' observed by EM, e.g. 200 nm, were aggregates of smaller particles termed 'Q-particles', approximately 4 nm in diameter. Metal sulfide particles were not formed in batch cultures of K. pneumoniae grown in the presence of lead, zinc, mercury, copper or silver ions. Growth in the presence of lead ions resulted in the formation of extracellular electron-dense particles containing lead but not sulfide or phosphate. Intracellular phosphorus-containing electron-opaque particles were formed during growth in the presence of copper and mercury. Intracellular electron-dense particles were formed in the presence of zinc ions but these did not contain phosphorus. From these results it was thought that metal sulfide formation in K. pneumoniae showed some cadmium-specificity. When cadmium and zinc ions were both added to the growth medium, metal sulfide particles were formed that were predominantly composed of cadmium, e.g. 48.6% cadmium and 0.04% zinc. Similarly, when cadmium and lead ions were both present during growth only CdS particles formed. In both cases analysis of the cells by EAS confirmed the presence of CdS only. These observations suggest that the mechanism of CdS formation is unlikely to occur simply through a cadmium-induced release of hydrogen sulfide by the cells into the external environment. If hydrogen sulfide production was the mechanism of sulfide formation then metal sulfide particles containing lead and zinc ions in addition to cadmium ions should have been produced.
Scalable Region‐matching Motion Estimation Based on an Unsupervised Spatial Segmentation

In a video scene, motion estimation (ME) can be studied on a dense field (optical flow) or on image structures or regions. Image structures can be deduced from the motion itself or formerly deduced by a segmentation. A scheme of ME, funded on a Bayesian segmentation using a Potts‐Markov model, has lead to a “region‐matching” ME scheme. Bayesian segmentation has been operated, with the same model, in the wavelet domain and has shown an interesting gain in segmentation speed. In the present work we have synthesized both approaches to demonstrate a new scheme of region‐matching ME which uses the hierarchical property of the multiscale segmentation scheme. A bottom‐top ME is built from the hierarchical segmentation in the wavelet domain. We show that a hierarchical, region‐based, ME, can provide an interesting approach w.r. t. the necessity of ME robustness as well as its scalability, in a region (or object) ‐based compression scheme. This approach is to be compared with recent developments like the “structure from motion” (SfM) in [15], based on Bayesian inference and sequential Monte Carlo methods, and the “trace model” for object (face) detection and tracking in [12] (see also [13]).
On the Coverage and Detectability of Large-scale Wireless Sensor Networks

Advances in sensor and communication technologies have made it possible to manufacture small sensors with sensing, processing, and wireless communication capabilities in a costeffective fashion. A sensor network can be formed by deploying specialized sensors in the region of interest to perform certain sensing and networking tasks. Application scenarios of wireless sensor networks include battlefield surveillance, environment monitoring, and etc. Many of the above application scenarios involve a large number of sensors deployed in a vast geographical area. Coverage and detectability are two fundamental measures of the performance of a sensor network. In general, sensing coverage represents how well an area is monitored by sensors; and detectability represents the capability that a sensor network detects an object that moves through the network. Formal definitions of the coverage and detectability will be introduced shortly. Characterizations of these two measures present important implications to protocol design and performance of sensor networks. While most of previous related work on the sensor network coverage and detectability focuses on protocol design [1][2][3][4][5], the goal of our work is to define and characterize the coverage and detectability, and examine the implications of the results. To represent the coverage and detectability of a sensor network, we define the following quantities. Area coverage ( fa): the fraction of the geographical area that is in the sensing area of one or more sensors. The sensing area of a sensor is the area within which the sensor can provide a valid sensing measurement. This is usually represented by a circle centered at the sensor with a radius of the sensor’s sensing range. Node coverage fraction ( fn): the fraction of sensors whose sensing areas are fully covered by collections of other sensors. This quantity represents the redundancy level of sensors from a coverage perspective. It has a direct effect on the performance of energy-efficient protocols which turn off redundant sensors while preserving area coverage [1]. Detectability (pd): the probability that no path exists for an object to penetrate a large-scale sensor network from left to right or from top to bottom without being detected. An object is detected by a sensor if it enters the sensing area of the sensor. We consider the worst-case scenario for sensor networks and assume that an object can take arbitrary paths.
Elucidating Population Histories Using Genomic DNA Sequences

In 1993, Cliff Jolly suggested that rather than debating species definitions and classifications, energy would be better spent investigating multidimensional patterns of variation and gene flow among populations. Until now, however, genetic studies of wild primate populations have been limited to very small portions of the genome. Access to complete genome sequences of humans, chimpanzees, macaques, and other primates makes it possible to design studies surveying substantial amounts of DNA sequence variation at multiple genetic loci in representatives of closely related but distinct wild primate populations. Such data can be analyzed with new approaches that estimate not only when populations diverged but also the relative amounts and directions of subsequent gene flow. These analyses will reemphasize the difficulty of achieving consistent species and subspecies definitions by revealing the extent of variation in the amount and duration of gene flow accompanying population divergences.
Differential Nested Lattice Encoding for Consensus Problems

In this paper we consider the problem of transmitting quantized data while performing an average consensus algorithm. Average consensus algorithms are protocols to compute the average value of all sensor measurements via near neighbors communications. The main motivation for our work is the observation that consensus algorithms offer the perfect example of network communications where there is an increasing correlation between the data exchanged, as the system updates its computations. Henceforth, it is possible to utilize previously exchanged data and current side information to reduce significantly the demands of quantization bit rate for a certain precision. We analyze the case of a network with a topology built as that of a random geometric graph and with links that are assumed to be reliable at a constant bit rate. Numerically we show that in consensus algorithms, increasing number of iterations does not have the effect of increasing the error variance. Thus, we conclude that noisy recursions lead to a consensus if the data correlation is exploited in the messages source encoders and decoders. We briefly state the theoretical results which are parallel to our numerical experiments.
A study of the Sunyaev–Zel'dovich increment using archival SCUBA data

In a search for evidence of the short wavelength increment in the Sunyaev–Zel'dovich (SZ) effect, we have analysed archival galaxy cluster data from the Submillimetre Common User Bolometer Array (SCUBA) on the James Clerk Maxwell Telescope, resulting in the most complete pointed survey of clusters at 850 μm to date. SCUBA's 850-μm passband overlaps the peak of the SZ increment. The sample consists of 44 galaxy clusters in the range 0 < z < 1.3. Maps of each of the clusters have been made and sources have been extracted; as an ancillary product, we generate the most thorough galaxy cluster point source list yet from SCUBA. 17 of these clusters are free of obvious active galactic nuclei (AGN) and have data deep enough to provide interesting measurements of the expected SZ signal. Specialized analysis techniques are employed to extract the SZ effect signal from these SCUBA data, including using SCUBA's short wavelength band as an atmospheric monitor and fitting the long wavelength channel to a model of the spatial distribution of each cluster's SZ effect. By explicitly excising the exact cluster centre from our analysis, we demonstrate that emission from galaxies within the cluster does not contaminate our measurement. The SZ amplitudes from our measurements are consistently higher than the amplitudes inferred from low-frequency measurements of the SZ decrement.
AAL systems and services for end users: Are the AT models and frameworks suitable for prescription and selection?

The complexity inherent to Ambient Assisted Living raises some of issues not yet quiet solved within similar fields like Assistive Technology, namely those related with prescription and selection. This paper aims to identify models of frameworks for the prescription of AT that may serve as a foundation to develop comprehensive models for the selection, prescription and counselling process of ALL solutions. A systematic literature search was conducted in Pubmed, Eric and CiteSeerX databases using a predefined strategy. The relevant literature extracted was screened and a list of models and frameworks was elaborated. Seven models or frameworks were included for analyses. It was possible to find ICF components in all of the models or frameworks. The results showed a shift between the models from the end of last century, based in an instrumental description of components involved to a predictive end users behaviour concern. Future work should deepen the conceptual issues about the selection, prescription and counselling process of AAL systems and services.
${Q}$-Learning Algorithms for Constrained Markov Decision Processes With Randomized Monotone Policies: Application to MIMO Transmission Control

This paper presents novel Q-learning based stochastic control algorithms for rate and power control in V-BLAST transmission systems. The algorithms exploit the supermodularity and monotonic structure results derived in the companion paper. Rate and power control problem is posed as a stochastic optimization problem with the goal of minimizing the average transmission power under the constraint on the average delay that can be interpreted as the quality of service requirement of a given application. Standard Q-learning algorithm is modified to handle the constraints so that it can adaptively learn structured optimal policy for unknown channel/traffic statistics. We discuss the convergence of the proposed algorithms and explore their properties in simulations. To address the issue of unknown transmission costs in an unknown time-varying environment, we propose the variant of Q-learning algorithm in which power costs are estimated in online fashion, and we show that this algorithm converges to the optimal solution as long as the power cost estimates are asymptotically unbiased
SDAF: A Secure Data Aggregation Framework for Wireless Sensor Networks

 Abstract—Wireless sensor networks (WSNs) are constrained in terms of memory, computation, communication, and energy. To reduce communication overhead and energy expenditure in (WSNs), data aggregation is used. Data aggregation is a very important technique, but it gives extra opportunity to the adversary to attack the network, inject false messages into the network and trick the base station to accept false aggregation results. This paper presents a secure data aggregation framework (SDAF) for (WSNs). The goal of the framework is to ensure data integrity and data confidentiality. SDAF uses two types of keys. Base station shares a unique key with each sensor node that is used for integrity and the aggregator shares a unique key with each sensor node (within that cluster) that is used for data confidentiality. Sensor nodes calculate a message authentication code (MAC) of the sensed data using shared key with base station, which verifies the MAC for message integrity. Sensor nodes encrypt the sensed data using shared key with aggregator, which ensures data confidentiality. Proposed framework has low communication overhead as the redundant packets are dropped at the aggregators.
Graph wavelet applied to human brain connectivity

The graph theory is increasingly used and provides powerful tools for studying complex biological networks problems. They were able to characterize the small-worldness of the brain connectivity network and were accurate enough to observe topological differences between healthy and diseased brain graphs. However, these methods relied on topological characteristics implying that differences could be observed between two groups only if corresponding graphs topologies were different.
Energy-Efficient TDMA-Based MAC Protocol for Wireless Body Area Networks

Body Area Networks (BAN) are a specific type of Network structure. They are spread over a very small area and their available power is heavily constrained. Hence it is useful to have gateway points in the network, such as nodes carried around the belt, that are less power constrained and can be used for network coordination. This network structure can result in very low transmission power/range for the sensors and effective TDMA timing control. This paper presents an energy-efficient MAC protocol for communication within the Wireless Body Area Network. The protocol takes advantage of the fixed nature of the Body Area Network to implement a TDMA strategy with very little communication overhead, long sleep times for the sensor transceivers and robustness to communication errors. The protocol is implemented on the Analog Devices ADF7020 RF transceivers.
Teaching Software Architecture Quality based on run-time metrics

1 Renato Manzan de Andrade, Computing Engineering a nd Digital Systems Department Polytechnic School of the University of São Paulo São Paulo – SP, 05508-900, Brazil, renato.manzan@poli.usp. br 2 Reginaldo Arakaki, Computing Engineering and Digi tal Systems Department Polytechnic School of the University of São Paulo São Paulo – SP, 05508900, Brazil, reginaldo.arakaki@poli.usp. br Abstract Software architecture is strongly related to sys tem quality, since it drives the whole development proc ess. In large systems, the achievement of qualities such as functionality, efficiency, reliability, and maintai nability depends more on the overall software architecture t han on code-level practices. It is cost effective to try t o determine, before a system is built, whether it will satisfy i ts desired qualities. By these reasons, evaluating software ar chitecture quality has become one of the most important decisi ons in the software development cycle. To support this de cision, many software architecture evaluation methods with distinct goals and approaches have emerged in the last few y ears. These methods can assist the developer in creating a software architecture that will have a potential to fulfill the requirements on the system. Although software archi te ture is part of Software Engineering undergraduate curri lum, in many cases software architecture quality classes do not explicit clearly the importance of this issue. Stud ents have strong programming skills, but very seldom know architectural quality concepts and their influences on software quality, costs and maintenance. This paper describes a practical approach to teach software ar chitecture quality based on run-time metrics and presents the application of this approach in an advanced softwar e laboratory undergraduate discipline.
Gaussian process quadratures in nonlinear sigma-point filtering and smoothing

This paper is concerned with the use of Gaussian process regression based quadrature rules in the context of sigma-point-based nonlinear Kalman filtering and smoothing. We show how Gaussian process (i.e., Bayesian or Bayes-Hermite) quadratures can be used for numerical solving of the Gaussian integrals arising in the filters and smoothers. An interesting additional result is that with suitable selections of Hermite polynomial covariance functions the Gaussian process quadratures can be reduced to unscented transforms, spherical cubature rules, and to Gauss-Hermite rules previously proposed for approximate nonlinear Kalman filter and smoothing. Finally, the performance of the Gaussian process quadratures in this context is evaluated with numerical simulations.
Embodied Communication between Human and Artifacts

In this paper, we focus on embodiment aspects of communication between human and single function artifact. Communication with embodiment media between human and artifact is difficult because of the difference of embodiment. We discuss a bottom up process and top down process of designing a common understand of embodiment media between human and artifact. keywords: human-artifact communication, embodiment