Miracle-dz/UniFAR-FTUs huggingface dataset:
The Acute and Enduring Consequences of Exposure to Violence on Youth Mental Health and Aggression

The bulk of “neighborhood effects” research examines the impact of neighborhood conditions cross-sectionally. However, it is critical to understand whether the effects of neighborhood context are situational and whether they endure over time. In this study, we take seriously the notion that there are enduring consequences of exposure to deleterious neighborhood conditions. Using a rich set of longitudinal data on adolescents from the Project on Human Development in Chicago Neighborhoods, we estimate the effect of exposure to violence on both internalizing (depression and anxiety) and externalizing problems (aggression). We find that exposure to violence has both an acute and enduring effect on aggression, yet no effect on anxiety-depression, net of individual, family, peer, and neighborhood influences. Part of the enduring effect of violence exposure is explained by changes in social cognitions brought on by the exposure, yet much of the relationship remains to be explained by other causal mechanisms.
Directional initial access for millimeter wave cellular systems

Communication in millimeter (mmWave) bands seems an evermore promising prospect for new generation cellular systems. However, due to high isotropic pathloss at these frequencies the use of directional antennas becomes mandatory. Directivity complicates many system design issues that are trivial in current cellular implementations. One such issue is initial access, i.e., the establishment of a link-layer connection between a UE and a base station. Based on different combinations of beamforming architectures and transmission modes, we present a series of design options for initial access in mmWave and compare them in terms of delay performance. We show that the use of digital beamforming for initial access will expedite the whole process significantly. Also, we argue that low quantization digital beamforming can more than compensate for high power consumption.
Unsupervised Relation Extraction by Mining Wikipedia Texts Using Information from the Web

This paper presents an unsupervised relation extraction method for discovering and enhancing relations in which a specified concept in Wikipedia participates. Using respective characteristics of Wikipedia articles and Web corpus, we develop a clustering approach based on combinations of patterns: dependency patterns from dependency analysis of texts in Wikipedia, and surface patterns generated from highly redundant information related to the Web. Evaluations of the proposed approach on two different domains demonstrate the superiority of the pattern combination over existing approaches. Fundamentally, our method demonstrates how deep linguistic patterns contribute complementarily with Web surface patterns to the generation of various relations.
Understanding Gesture Expressivity through Muscle Sensing

Expressivity is a visceral capacity of the human body. To understand what makes a gesture expressive, we need to consider not only its spatial placement and orientation but also its dynamics and the mechanisms enacting them. We start by defining gesture and gesture expressivity, and then we present fundamental aspects of muscle activity and ways to capture information through electromyography and mechanomyography. We present pilot studies that inspect the ability of users to control spatial and temporal variations of 2D shapes and that use muscle sensing to assess expressive information in gesture execution beyond space and time. This leads us to the design of a study that explores the notion of gesture power in terms of control and sensing. Results give insights to interaction designers to go beyond simplistic gestural interaction, towards the design of interactions that draw on nuances of expressive gesture.
Towards Commoditised Near Infrared Spectroscopy

Near Infrared Spectroscopy (NIRS) is a sensing technique in which near infrared light is transmitted into a sample, followed by light absorbance measurements at various wavelengths. This technique enables the inference of the inner chemical composition of the scanned sample, and therefore can be used to identify or classify objects. In this paper, we describe how to facilitate the use of NIRS by non- expert users in everyday settings. Our work highlights the key challenges of placing NIRS devices in the hands of non-experts. We develop a system to mitigate these challenges, and evaluate it in a user study. We show how NIRS technology can be successfully utilised by untrained users in an unsupervised manner through a special enclosure and an accompanying smartphone app. Finally, we discuss potential future developments of commoditised NIRS.
A Secure Routing Protocol for Cluster-Based Wireless Sensor Networks Using Group Key Management

Wireless sensor networks routing protocols always neglect security problem at the designing step, while plenty of solutions of this problem exist, one of which is using key management. Researchers have proposed many key management schemes, but most of them were designed for flat wireless sensor networks, which is not fit for cluster-based wireless sensor networks (e.g. LEACH). In this paper, we investigate adding security to cluster-based routing protocols for wireless sensor networks which consisted of sensor nodes with severely limited resources, and propose a security solution for LEACH, a protocol in which the clusters are formed dynamically and periodically. Our solution uses improved random pair-wise keys (RPK) scheme, an optimized security scheme that relys on symmetric-key methods; is lightweight and preserves the core of the original LEACH. Simulations show that security of RLEACH has been improved, with less energy consumption and lighter overhead.
A framework for rapid system-level exploration, synthesis, and programming of multimedia MP-SoCs

In this paper, we present the Daedalus framework, which allows for traversing the path from sequential application specification to a working MP-SoC prototype in FPGA technology with the (parallelized) application mapped onto it in only a matter of hours. During this traversal, which offers a high degree of automation, guidance is provided by Daedalus' integrated system-level design space exploration environment. We show that Daedalus offers remarkable potentials for quickly experimenting with different MP-SoC architectures and exploring system-level design options during the very early stages of design. Using a case study with a Motion-JPEG encoder application, we illustrate Daedalus' design steps and demonstrate its efficiency.
Gaussian mixture diffusion

Most state-of-the-art denoising algorithms employ a patch-based approach by enforcing a local model or prior, such as self similarity, sparse representation, or Gaussian Mixture Model (GMM). While applying these models, these algorithms implicitly build a notion of similarity between the image pixels. This can be formulated as an image-adaptive linear-filter which is then used to denoise or restore the degraded image. In this work we focus on such a filter emerging from the GMM, study its properties and construct a graph Laplacian from it. Focusing on a variational denoising formulation, we incorporate a graph-based regularization term by leveraging the corresponding GMM Laplacian. The resulting algorithm extends and improves the non-local diffusion algorithm by replacing the Non-Local Means kernel with a GMM one. Our results indicate that this approach, termed Gaussian Mixtures Diffusion (GMD), consistently improves over both the original GMM scheme and the non-local diffusion algorithm. Furthermore, GMD is competitive or even better than the state-of-the-art method of EPLL.
RXP-E: A Connexin43-Binding Peptide That Prevents Action Potential Propagation Block

Gap junctions provide a low-resistance pathway for cardiac electric propagation. The role of GJ regulation in arrhythmia is unclear, partly because of limited availability of pharmacological tools. Recently, we showed that a peptide called “RXP-E” binds to the carboxyl terminal of connexin43 and prevents chemically induced uncoupling in connexin43-expressing N2a cells. Here, pull-down experiments show RXP-E binding to adult cardiac connexin43. Patch-clamp studies revealed that RXP-E prevented heptanol-induced and acidification-induced uncoupling in pairs of neonatal rat ventricular myocytes. Separately, RXP-E was concatenated to a cytoplasmic transduction peptide (CTP) for cytoplasmic translocation (CTP–RXP-E). The effect of RXP-E on action potential propagation was assessed by high-resolution optical mapping in monolayers of neonatal rat ventricular myocytes, containing ≈20% of randomly distributed myofibroblasts. In contrast to control experiments, when heptanol (2 mmol/L) was added to the superfusate of monolayers loaded with CTP–RXP-E, action potential propagation was maintained, albeit at a slower velocity. Similarly, intracellular acidification (pHi 6.2) caused a loss of action potential propagation in control monolayers; however, propagation was maintained in CTP–RXP-E–treated cells, although at a slower rate. Patch-clamp experiments revealed that RXP-E did not prevent heptanol-induced block of sodium currents, nor did it alter voltage dependence or amplitude of Kir2.1/Kir2.3 currents. RXP-E is the first synthetic molecule known to: (1) bind cardiac connexin43; (2) prevent heptanol and acidification-induced uncoupling of cardiac gap junctions; and (3) preserve action potential propagation among cardiac myocytes. RXP-E can be used to characterize the role of gap junctions in the function of multicellular systems, including the heart.
Adaptive Filesystem Compression for Embedded Systems

Embedded system secondary storage size is often constrained, yet storage demands are growing as a result of increasing application complexity and storage of personal data and multimedia flies. Filesystem compression offers a solution. This paper formalizes the problem of automatic filesystem compression using multiple compression algorithms. The average latency of on-line file accesses is optimized under a constraint on filesystem capacity. Our solution is based on predictive control. Predicted latency implications are used to solve the file compression state selection problem using a multiple choice knapsack problem formulation. This approach is evaluated on filesystem traces and compared with other efficient heuristics. Our approach results in 34.1% reduction in file access latency compared to a straight-forward heuristic that decompresses frequently-accessed files and compresses least recently used files with more aggressive compression algorithms. It reduces file access latency by 67.7% compared to uniformly compressing files to the shallowest level required to meet storage capacity constraints.
Optimising Tree Edit Distance with Subtrees for Textual Entailment

This paper introduces a method for improving tree edit distance (TED) for textual entailment. We explore two ways of improving TED: we extend the standard TED to use edit operations that apply to subtrees as well as to single nodes; and we use the ‘artificial bee colony’ algorithm (ABC) to estimate the cost of edit operations for single nodes and subtrees and to determine thresholds. The preliminary results of the current work for checking entailment between two texts are encouraging compared with the common bag-ofwords, string edit distance and standard TED algorithms.
Bacteria within the Gastrointestinal Tract Microbiota Correlated with Improved Growth and Feed Conversion: Challenges Presented for the Identification of Performance Enhancing Probiotic Bacteria

Identification of bacteria associated with desirable productivity outcomes in animals may offer a direct approach to the identification of probiotic bacteria for use in animal production. We performed three controlled chicken trials (n = 96) to investigate caecal microbiota differences between the best and poorest performing birds using four performance measures; feed conversion ratio (FCR), utilization of energy from the feed measured as apparent metabolisable energy, gain rate (GR), and amount of feed eaten (FE). The shifts in microbiota composition associated with the performance measures were very different between the three trials. Analysis of the caecal microbiota revealed that the high and low FCR birds had significant differences in the abundance of some bacteria as demonstrated by shifts in microbiota alpha and beta diversity. Trials 1 and 2 showed significant overall community shifts, however, the microbial changes driving the difference between good and poor performers were very different. Lachnospiraceae, Ruminococcaceae, and Erysipelotrichaceae families and genera Ruminococcus, Faecalibacterium and multiple lineages of genus Clostridium (from families Lachnospiraceae, Ruminococcaceae, and Erysipelotrichaceae) were highly abundant in good FCR birds in Trial 1. Different microbiota was associated with FCR in Trial 2; Catabacteriaceae and unknown Clostridiales family members were increased in good FCR and genera Clostridium (from family Clostridiaceae) and Lactobacillus were associated with poor FCR. Trial 3 had only mild microbiota differences associated with all four performance measures. Overall, the genus Lactobacillus was correlated with feed intake which resulted in poor FCR performance. The genus Faecalibacterium correlated with improved FCR, increased GR and reduced FE. There was overlap in phylotypes correlated with improved FCR and GR, while different microbial cohorts appeared to be correlated with FE. Even under controlled conditions different cohorts of birds developed distinctly different microbiotas. Within the different trial groups the abundance of certain bacterial groups correlated with productivity outcomes. However, with different underlying microbiotas there were different bacteria correlated with performance. The challenge will be to identify probiotic bacteria that can reliably deliver favorable outcomes from diverse microbiotas.
Multiuser communications over frequency selective wired channels and applications to the powerline access network

The low-voltage power distribution network is considered today as a serious candidate to provide residential customers with a high-speed access to communication services such as Internet. Outdoor Power-Line Communications (PLC) systems represent an alternative to the other classical 'last-mile solutions' such as ADSL, cable modems, or wireless access systems. We developed an accurate powerline channel simulation tool based on the Multiconductor Transmission Line theory. This tool is able to predict the end-to-end channel responses on the basis of the multiconductor cable structure and the network topology. Then the issue of optimal resource allocation in a multiuser environment was addressed in the light of the Multiuser Information Theory. Simultaneously active users are in competition for the limited resources that are the power (constrained by electro-magnetic compatibility restrictions) and the bandwidth (in the range of 1 to 10 MHz for outdoor PLC). The concept of multiuser balanced capacity was introduced to characterize the optimal resource allocation providing the maximum data rates with fairness constraints among the subscribers. The optimal PLC system was shown to require the shaping of the signal spectrum in the transmitters, and successive decoding in the receiver. A generic multiple access scheme based on Filter Banks (FB) was proposed, which offers the required spectral shaping with limited degrees of freedom. Classical multiple-access techniques (TDMA, CDMA, OFDMA) can be obtained by selecting the appropriate FB. The Minimum-Mean-Square-Error Decision-Feedback Joint Detector was shown to approach the performance of the optimal successive decoding receiver. Finally, the robustness of the proposed system against channel estimation and timing synchronization errors was addressed. The problem of multiuser timing synchronization was introduced, and practical multiuser timing error detectors were proposed.
Perception and Signaling of Strigolactones

Strigolactones (SLs), a recently discovered class of phytohormones, are important regulators of plant growth and development. While the biosynthetic pathway of these molecules is well documented, until recently there was not much known about the molecular mechanisms underlying SL perception and signal transduction in plants. Certain aspects of their perception and signaling, including the hormone-mediated interaction between receptor and F-box protein, degradation of suppressor proteins and activation of transcription factors, are also found in other phytohormones. However, some of SL signaling features seem to be specific for the SL signaling pathway. These include the enzymatic activity of the SL receptor and its destabilization caused by SLs. This review summarizes the current knowledge about SL signaling pathway in plants.
Modeling and Simulation of Microcode-based Built-In Self Test for Multi-Operation Memory Test Algorithms

As embedded memory area on-chip is increasing and memory density is growing, newer test algorithms like March SS are defined to detect newly developing faults. These new March algorithms contain multiple operations per March element. This paper presents a microcoded BIST architecture which can implement these new March tests having number of operations per element according to the growing needs of embedded memory testing. This is shown by implementing March SS Test and testing for new faults including Write Disturb Fault (WDF), Transition Coupling Fault (Cft), Deceptive Read Disturb Coupling Fault (Cfdrd), which established tests like March C- are not capable of detecting. Verilog HDL code of this architecture is written and synthesized using Xilinx ISE 8.2i. Verification of the architecture is done by testing Mentor’s ModelSim.
Surface proteins of Setaria cervi induce inflammation in macrophage through Toll‐like receptor 4 (TLR4)‐mediated signalling pathway

Lymphatic filariasis is a vectorborne parasitic disease that results in morbidities, disabilities and socio‐economic loss each year globally. Inflammatory consequences associated with any form of filariasis have drawn special attention. However, the molecular insight behind the inflammation of host macrophage (MФ) is considered as one of the shaded areas in filarial research. Herein, major emphasis was given to study the signalling pathway of MФ inflammation induced by surface proteins (SPs) of filarial parasite through in vitro and in vivo approaches. Twenty‐four hours of in vitro stimulation of Raw MФs with endotoxin‐free SPs of Setaria cervi resulted in the secretion of pro‐inflammatory cytokines (TNF‐α and IL‐1β) that revealed induction of inflammation, which was found to be elicited from classical NF‐кB activation. Moreover, this NF‐кB activation was found to be signalled from TLR4 and mediated by the downstream signalling intermediates, viz. MyD88, pTAK1 and NEMO. In vivo studies in adult Wistar rats, experimentally injected with SPs, clearly supported the outcomes of in vitro experiments by showing higher degree of inflammation rather classical activation of the peritoneal MФs. Therefore, SPs from S. cervi cuticle could be responsible for the induction of pro‐inflammatory response in MФ, which appears to be propagated through TLR4‐NF‐кB route.
Entropy Index in Quantitative EEG Measurement for Diagnosis Accuracy

Electroencephalogram (EEG) remains the most immediate, simple, and rich source of information for understanding phenomena related to brain electrical activities. It is certainly a source of basic and interesting information to be extracted using specific and appropriate techniques. The most important aspect in processing EEG signals is to use less co-lateral assets and instrumentation in order to carried out a possible diagnosis; this is the approach of early diagnosis. Advanced estimate spectral analysis can reveal new information encompassed in EEG signals by means of specific parameters or indices. The research proposes a multidimensional approach with a combined use of decimated signal diagonalization (DSD) as basis from which it is possible to work by finding appropriate signal windows for revealing expected information and overcoming signal processing limitations encountered in quantitative EEG. Important information, about the state of the patient under observation, must be extracted from calculated DSD bispectrum. For this aim, it is useful to define an assessment index about the dynamic process associated with the analyzed signal. This information is measured by means of entropy, since the degree of order/disorder of the recorded EEG signal will be reflected in the obtained DSD bispectrum. The general advantage of multidimensional approach is to reveal eventual stealth frequencies “in space and in time” giving a topological vision to be correlated to physical areas which these frequencies emerge from. Long term and sleeping EEG recorded are analyzed, and the results obtained are of interest for an accurate diagnosis of the patient's clinical condition.
Mining Software Repositories with iSPAROL and a Software Evolution Ontology

One of the most important decisions researchers face when analyzing the evolution of software systems is the choice of a proper data analysis/exchange format. Most existing formats have to be processed with special programs written specifically for that purpose and are not easily extendible. Most scientists, therefore, use their own data-base(s) requiring each of them to repeat the work of writing the import/export programs to their format. We present EvoOnt, a software repository data exchange format based on the Web Ontology Language (OWL). EvoOnt includes software, release, and bug-related information. Since OWL describes the semantics of the data, EvoOnt is (1) easily extendible, (2) comes with many existing tools, and (3) allows to derive assertions through its inherent Description Logic reasoning capabilities. The paper also shows iSPARQL -our SPARQL-based Semantic Web query engine containing similarity joins. Together with EvoOnt, iSPARQL can accomplish a sizable number of tasks sought in software repository mining projects, such as an assessment of the amount of change between versions or the detection of bad code smells. To illustrate the usefulness of EvoOnt (and iSPARQL), we perform a series of experiments with a real-world Java project. These show that a number of software analyses can be reduced to simple iSPARQL queries on an EvoOnt dataset.
Analysis of various DRAM devices from power consumption's perspective

DRAM has become a crucial component in terms of system power consumption as the size of main memory increases. To improve power efficiency of DRAM devices, we need to analyze characteristics of DRAM behavior from power consumption's perspective. In this paper, we analyze the characteristics of various DRAM devices from major vendors under real system operating environment. As the size of the DRAM increases, power consumption due to activate, precharge and burst operations remains about the same, but that due to background and refresh operations increases steadily. Especially, power consumption due to the refresh operation for 3D stacked DRAMs increases by 91% at high temperatures, which strongly implies that the refresh operation will become more crucial for DRAMs in the future.
A weighted STOI intelligibility metric based on mutual information

It is known that the information required for the intelligibility of a speech signal is distributed non-uniformly in time. In this paper we propose WSTOI, a modified version of STOI, a speech intelligibility metric. With WSTOI the contribution of each time-frequency cell is weighted by an estimate of its intelligibility content. This estimate is equal to the mutual information between two hypothetical signals at either end of a simplified model of human communication. Listening tests show that the modification improves the prediction accuracy of STOI at all performance levels on both long and short utterances. An improvement was observed across all tested noise types and suppression algorithms.