Miracle-dz/UniFAR-FTUs huggingface dataset:
Synergistic Attenuation of Vesicular Stomatitis Virus by Combination of Specific G Gene Truncations and N Gene Translocations

ABSTRACT A variety of rational approaches to attenuate growth and virulence of vesicular stomatitis virus (VSV) have been described previously. These include gene shuffling, truncation of the cytoplasmic tail of the G protein, and generation of noncytopathic M gene mutants. When separately introduced into recombinant VSV (rVSV), these mutations gave rise to viruses distinguished from their “wild-type” progenitor by diminished reproductive capacity in cell culture and/or reduced cytopathology and decreased pathogenicity in vivo. However, histopathology data from an exploratory nonhuman primate neurovirulence study indicated that some of these attenuated viruses could still cause significant levels of neurological injury. In this study, additional attenuated rVSV variants were generated by combination of the above-named three distinct classes of mutation. The resulting combination mutants were characterized by plaque size and growth kinetics in cell culture, and virulence was assessed by determination of the intracranial (IC) 50% lethal dose (LD50) in mice. Compared to virus having only one type of attenuating mutation, all of the mutation combinations examined gave rise to virus with smaller plaque phenotypes, delayed growth kinetics, and 10- to 500-fold-lower peak titers in cell culture. A similar pattern of attenuation was also observed following IC inoculation of mice, where differences in LD50 of many orders of magnitude between viruses containing one and two types of attenuating mutation were sometimes seen. The results show synergistic rather than cumulative increases in attenuation and demonstrate a new approach to the attenuation of VSV and possibly other viruses.
A 50-dB image-rejection SiGe-HBT based low noise amplifier in 24-GHz band

An image-rejection low-noise amplifier (LNA) based on 0.18-μm SiGe BiCMOS technology was developed in order to create a 24GHz-band RF receiver front-end. Its high image-rejection ratio (IRR) in the quasi-millimeter-wave frequency region is due to the use of a notch feedback circuit. The LNA has a 14-dB gain at an operating frequency of 27.2 GHz and an IRR greater than 50 dB IRR at an image frequency of 21.6 GHz. While its IIP3 is −14 dBm, its power consumption with a 1.2-V power supply is also low, 7.9 mW.
Phase-Weighted Stacking Applied to Low-Frequency Earthquakes

Abstract We apply phase‐weighted stacking (PWS) to the analysis of low‐frequency earthquakes (LFEs) in the Parkfield, California, region and central Cascadia. The technique uses the coherence of the instantaneous phase among the stacked signals to enhance the signal‐to‐noise ratio (SNR) of the stack. We find that for picking LFE arrivals for the Parkfield, California, region and for LFE template formation in central Cascadia, PWS is extremely effective. For LFEs in the Parkfield, California, region, PWS yields many more usable phases than standard linear stacking; and, for LFE detection in Cascadia, PWS produces templates with much higher SNR than linear stacking.
Progressive haptic and visual guidance for training in a virtual dynamic task

This paper presents the design and implementation of a novel progressive haptic guidance scheme and a similar visual guidance scheme for acquisition of a dynamic motor skill. The paper compares the schemes' performance to each other and to practice alone without any form of guidance. The target-hitting task is represented in a visual and haptic virtual environment and implemented in a training protocol that lasts eleven sessions over a two-month period. The progressive guidance controller employs as inputs two expertise-based performance measures, trajectory error and input frequency. The analysis of the experimental results demonstrates that while guidance is active, haptic guidance outperforms both visual guidance and practice alone (no guidance) until late in the protocol when all three groups saturate at the same level of performance. The results fail to show significant differences in training outcomes because the performance of all participants saturates toward the end of the protocol. The key implication of the experimental findings is that visual and haptic guidance presented in a progressive manner have no detrimental effects on performance. Our results confirm that haptic guidance, based on skill component measures, is effective early in the training protocol when participants are only beginning to understand the components of the task but should be progressively removed to avoid possible negative dependence on the guidance.
Secrecy enhancement of block ciphered systems with deliberate noise in Non-coherent scenario

In this paper we propose an encoding-encryption approach to take advantage of intentional noise introduced in ciphertexts for a block cipher working in CFB or CBC mode. First of all, we provide a rigorous analysis of the impacts of channel degradation on block ciphered systems. We show that the overall channel can be modeled as a Finite State Markov Chain (FSMC) with symmetric channels associated in each state, whose underlying non-coherent Shannon capacity is derived and computed. Despite Eve's efforts in modifying her linear crytanalysis given the intercepted noisy ciphertexts, there is still a non-negligible probability of having possible failures in her attack. We essentially create a wiretap channel in application layer that is a degraded version of the main channel and measure security of the system in terms of secrecy capacity and show that it depends on the deliberately introduced bit error rate. In addition, Alice can accordingly adjust cross over probability of the channel to maximize secrecy rate. This secrecy rate can be achieved by wiretap channel coding over multiple frames in application layer if the delay in system is bearable.
Virtual worlds, real traffic: interaction and adaptation

Metaverses such as Second Life (SL) are a relatively new type of Internet application. Their functionality is similar to online 3D games but differs in that users are able to construct the environment their avatars inhabit and are not constrained by predefined goals. From the network perspective metaverses are similar to games in that timeliness is important but differ in that their traffic is much less regular and requires more bandwidth This paper contributes to our understanding of metaverse traffic by validating previous studies and offering new insights. In particular we analyse the relationships between application functionality, SL's traffic control system and the wider network environment. Two sets of studies have been carried out: one of the traffic generated by a hands-on workshop which used SL; and a follow up set of controlled experiments to clarify some of the findings from the first study. The interplay between network latency, SL's traffic throttle settings, avatar density, and the errors in the client's estimation of avatar positions are demonstrated. These insights are of particular interest to those designing traffic management schemes for metaverses and help explain some of the oddities in the current user experience.
An Activity Based Perspective for Information Systems Research

A semiconductor package for use in fiber optics systems is disclosed wherein optical performance is enhanced by a lens between a fiber segment and the photoactive area of the semiconductor. The lens is spaced a predetermined distance from the fiber by a layer of elastomer. During assembly of the package, the fiber provides a convenient means for handling the lens.
Effect of relaying on capacity improvement in wireless local area networks

Wireless relay nodes can improve the capacity of wireless networks. In this work, we integrate wireless relay nodes into the infrastructure of a wireless local area network (WLAN). In particular, we investigate the effect of different relay strategies and optimal utilization of a fixed number of immobile relay nodes, which maximizes the expected throughput capacity of the network. We study how the number of relay nodes, the range of users, transmission power, path loss exponent, and traffic characteristics affect the optimal relay node placement and expected throughput capacity of the network. Our results show that a time-division relay strategy can far outperform a receive-and-retransmit relay strategy. Furthermore, for a wide range of system parameters, optimally placed relay nodes can significantly increase the network expected throughput capacity.
Transposable elements and small RNAs contribute to gene expression divergence between Arabidopsis thaliana and Arabidopsis lyrata

Transposable elements (TEs) are often the primary determinant of genome size differences among eukaryotes. In plants, the proliferation of TEs is countered through epigenetic silencing mechanisms that prevent mobility. Recent studies using the model plant Arabidopsis thaliana have revealed that methylated TE insertions are often associated with reduced expression of nearby genes, and these insertions may be subject to purifying selection due to this effect. Less is known about the genome-wide patterns of epigenetic silencing of TEs in other plant species. Here, we compare the 24-nt siRNA complement from A. thaliana and a closely related congener with a two- to threefold higher TE copy number, Arabidopsis lyrata. We show that TEs—particularly siRNA-targeted TEs—are associated with reduced gene expression within both species and also with gene expression differences between orthologs. In addition, A. lyrata TEs are targeted by a lower fraction of uniquely matching siRNAs, which are associated with more effective silencing of TE expression. Our results suggest that the efficacy of RNA-directed DNA methylation silencing is lower in A. lyrata, a finding that may shed light on the causes of differential TE proliferation among species.
Use of traditional medicine in middle-income countries: a WHO-SAGE study

It is frequently stated in the scientific literature, official reports and the press that 80% of Asian and African populations use traditional medicine (TM) to meet their healthcare needs; however, this statistic was first reported in 1983. This study aimed to update knowledge of the prevalence of TM use and the characteristics of those who access it, to inform health policy-makers as countries seek to fulfil the WHO TM strategy 2014–23 and harness TM for population health. Prevalence of reported use of TM was studied in 35 334 participants of the WHO-SAGE, surveyed 2007–10. TM users were compared with users of modern healthcare in univariate and multivariate analyses. Characteristics examined included age, sex, geography (urban/rural), income quintile, education, self-reported health and presence of specific chronic conditions. This study found TM use was highest in India, 11.7% of people reported that their most frequent source of care during the previous 3 years was TM; 19.0% reported TM use in the previous 12 months. In contrast <3% reported TM as their most frequent source of care in China, Ghana, Mexico, Russia and South Africa; and <2% reported using TM in the previous year in Ghana, Mexico, Russia and South Africa. In univariate analyses, poorer, less educated and rural participants were more likely to be TM-users. In the China multivariate analysis, rurality, poor self-reported health and presence of arthritis were associated with TM use; whereas diagnosed diabetes, hypertension and cataracts were less prevalent in TM users. In Ghana and India, lower income, depression and hypertension were associated with TM use. In conclusion, TM use is less frequent than commonly reported. It may be unnecessary, and perhaps futile, to seek to employ TM for population health needs when populations are increasingly using modern medicine.
An open router virtualization framework using a programmable forwarding plane

Network virtualization promises to spur innovation and add flexibility to the Future Internet infrastructure. Routers supporting virtualization allow the deployment of concurrent virtual networks, and can be employed to consolidate resources and improve energy efficiency in data centers. The closed nature of commercial router systems poses a significant problem for research in the field of virtual network architectures. On the other hand, the performance of software-based, open routing solutions is typically limited. In this work we outline an open router virtualization framework utilizing OpenFlow enabled hardware as a fast, programmable forwarding plane.
1-D Dirac Equation, Klein Paradox and Graphene

Solutions of the one dimensional Dirac equation with piece-wise constant potentials are presented using standard methods. These solutions show that the Klein Paradox is non-existent and represents a failure to correctly match solutions across a step potential. Consequences of this exact solution are studied for the step potential and a square barrier. Characteristics of massless Dirac states and the momentum linear band energies for Graphene are shown to have quite different current and momentum properties.
Congestion Domain Boundaries in Resilient Packet Rings

In June 2004, the IEEE approved a new standard for Resilient Packet Rings (RPR). The standard is maintained in the 802 LAN/MAN Standards Committee, and is designated the standard number 802.17. In this paper, we analyze and discuss performance aspects of the Resilient Packet Ring fairness mechanism. We explain that, if the ring is not configured correctly, the fairness mechanism fails to stabilize at a fair division of bandwidth between the active nodes. We present a novel addition to the fairness algorithm, and show that with this modification, RPR reaches a stable state with more optimal parameter settings. We also show that our proposed modification gives shorter convergence time for the Resilient Packet Ring fairness algorithm.
ProtoNet 6.0: organizing 10 million protein sequences in a compact hierarchical family tree

ProtoNet 6.0 (http://www.protonet.cs.huji.ac.il) is a data structure of protein families that cover the protein sequence space. These families are generated through an unsupervised bottom–up clustering algorithm. This algorithm organizes large sets of proteins in a hierarchical tree that yields high-quality protein families. The 2012 ProtoNet (Version 6.0) tree includes over 9 million proteins of which 5.5% come from UniProtKB/SwissProt and the rest from UniProtKB/TrEMBL. The hierarchical tree structure is based on an all-against-all comparison of 2.5 million representatives of UniRef50. Rigorous annotation-based quality tests prune the tree to most informative 162 088 clusters. Every high-quality cluster is assigned a ProtoName that reflects the most significant annotations of its proteins. These annotations are dominated by GO terms, UniProt/Swiss-Prot keywords and InterPro. ProtoNet 6.0 operates in a default mode. When used in the advanced mode, this data structure offers the user a view of the family tree at any desired level of resolution. Systematic comparisons with previous versions of ProtoNet are carried out. They show how our view of protein families evolves, as larger parts of the sequence space become known. ProtoNet 6.0 provides numerous tools to navigate the hierarchy of clusters.
Moon Phases, Mood and Stock Market Returns

We employ recent data from 59 international emerging and mature stock markets to provide new evidence of a lunar cycle (full and new moon) effect on their stock market returns. Using a threshold generalised autoregressive conditional heteroscedasticity (TGARCH) model, we further examine the linkages between efficient-market theory, calendar-related effects and investors’ mood resulting from moon phases. The empirical results show significant full moon effects in six markets, and significant new moon effects in eight markets. In line with the theory, we report significant positive effect of new moon on stock market returns in five cases (UK, Switzerland, Bangladesh, Chile and Cyprus), while a negative effect of full moon is reported for the case of Jordan only. In addition, we find that lunar effects are strongly influenced by the calendar anomalies (Monday effect and January effect); several markets—mostly emerging markets—show evidence of full/new moon effects as well as Monday/January effects (Bangladesh, Brazil, Chile, Tunisia, Belgium, Cyprus). Further, we prove that the lunar phases are stronger outside America. These findings are recommended to investors, financial managers and analysts dealing with international stock indices. JEL Classification: G02, G14, G15
A Novel Open Source Morphology Using GPU Processing With LTU-CUDA

A mathematical morphology is used as a tool for extracting image components that are useful in the representation and description of region shape. The mathematical morphology operations of dilation, erosion, opening, and closing are important building blocks of many other image processing algorithms. The data parallel programming provides an opportunity for performance acceleration using highly parallel processors such as GPU. NVIDIA CUDA architecture offers relatively inexpensive and powerful framework for performing these operations. However the generic morphological erosion and dilation operation in CUDA NPP library is relatively naive, but it provides impressive speed ups only for a limited range of structuring element sizes. The vHGW algorithm is one of the fastest for computing morphological operations on a serial CPU. This algorithm is compute intensive and can be accelerated with the help of GPU. This project implements vHGW algorithm for erosion and dilation independent of structuring element size has been implemented for different types of structuring elements of an arbitrary length and along arbitrary angle on CUDA programming environment with GPU hardware as GeForce GTX 480. The results show maximum performance gain of 20 times than the conventional serial implementation of algorithm in terms of execution time.
Kernel Auto-Regressive Model with eXogenous Inputs for Nonlinear Time Series Prediction

In this paper we present a novel approach for nonlinear time series prediction using kernel methods. The kernel methods such as support vector machine (SVM) and support vector regression (SVR) deal with nonlinear problems assuming independent and identically distributed (i.i.d.) data, without explicit notion of time. However, the problem of prediction necessitates temporal information. In this regard, we propose a novel time series modeling technique, kernel auto-regressive model with exogenous inputs (KARX) and associated estimation methods. Amongst others the advantage of KARX model compared to the widely used nonlinear auto-regressive exogenous (NARX) model (which is implemented using artificial neural network (ANN)) is, implicit nonlinear mapping and better regularization capability. In this work, we make use of Kalman recursions instead of quadratic programming which is generally used in kernel methods. Also, we employ online estimation schemes for estimating model noise parameters. The efficacy of the approach is demonstrated on artificial time series as well as real world time series acquired from aircraft engines
A Computer Application for 3D Craniofacial Reconstruction and Automatic Skull-Photo Identification

Human identification from a skull is a critical process in legal and forensic medicine, especially when no other means are available. Traditional clay-based methods attempt to generate the human face, in order to identify the corresponding person. However, these reconstructions lack of objectivity, since they depend on the practitioner. On the other hand, superimposition of a skull with antemortem photographs is another popular method for suggesting individual identification; nevertheless, it is a costly process in terms of time if many photographs have to be analyzed. This paper presents two Human identification techniques. First one is an objective 3D craniofacial reconstruction method, without using any facial template. The only information required is the 3D image of the skull, age, gender and Body Mass Index of the individual. The second technique is an automated skull-photo superimposition method which calculates the matching degree of a large number of photos with a skull.
Emotion Perception Time Analysis for Variable Facial Expression

Gupta S. , Biswal R. , and Gupta S. , (2018). Toward Computational Model of Emotion from Individual Difference in Perceiving Facial Expressions. Psychological Studies,Springer, 16(3), 266-275, DOI: 10.1007/s12646-018-0459-5 Lucey, P., Cohn, J. F. , Kanade, T. , Saragih, J., Ambadar, Z. , & Matthews, I. (2010). The extended cohnkanade dataset (ck+): A complete dataset for action unit and emotion-specified expression. In 2010 ieee computer society conference on computer vision and pattern recognition-workshops (p. 94-101).
Quantization Index Modulation audio watermarking system using a psychoacoustic model

We propose a system in which the watermark message is embedded into audio signal by means of Quantization Index Modulation (QIM) scheme. However, the method is sensitive to gain scaling attack. We use a value-metric scaling invariant method called Rational Dither Modulation (RDM) to cope with this problem. At the same time, we exploit the psychoacoustic model to improve the audio signal's perceptual quality after the watermark embedding procedure. In comparison of the traditional QIM which use a fixed quantization step, our method adjusts the quantization step with psychoacoustic model adaptively. Experimental results show that our watermarking scheme is robust against common signal processing attacks while keeping the watermarked audio a high perceptual quality.
Molecular Pathways of Protein Synthesis Inhibition during Brain Reperfusion: Implications for Neuronal Survival or Death

Protein synthesis inhibition occurs in neurons immediately on reperfusion after ischemia and involves at least alterations in eukaryotic initiation factors 2 (eIF2) and 4 (eIF4). Phosphorylation of the α subunit of eIF2 [eIF2(αP)] by the endoplasmic reticulum transmembrane eIF2α kinase PERK occurs immediately on reperfusion and inhibits translation initiation. PERK activation, along with depletion of endoplasmic reticulum Ca2+ and inhibition of the endoplasmic reticulum Ca2+-ATPase, SERCA2b, indicate that an endoplasmic reticulum unfolded protein response occurs as a consequence of brain ischemia and reperfusion. In mammals, the upstream unfolded protein response components PERK, IRE1, and ATF6 activate prosurvivial mechanisms (e.g., transcription of GRP78, PDI, SERCA2b) and proapoptotic mechanisms (i.e., activation of Jun N-terminal kinases, caspase-12, and CHOP transcription). Sustained eIF2(αP) is proapoptotic by inducing the synthesis of ATF4, the CHOP transcription factor, through “bypass scanning” of 5‘ upstream open-reading frames in ATF4 messenger RNA; these upstream open-reading frames normally inhibit access to the ATF4 coding sequence. Brain ischemia and reperfusion also induce μ-calpain–mediated or caspase-3–mediated proteolysis of eIF4G, which shifts message selection to m7G-cap–independent translation initiation of messenger RNAs containing internal ribosome entry sites. This internal ribosome entry site–mediated translation initiation (i.e., for apoptosis-activating factor-1 and death-associated protein-5) can also promote apoptosis. Thus, alterations in eIF2 and eIF4 have major implications for which messenger RNAs are translated by residual protein synthesis in neurons during brain reperfusion, in turn constraining protein expression of changes in gene transcription induced by ischemia and reperfusion. Therefore, our current understanding shifts the focus from protein synthesis inhibition to the molecular pathways that underlie this inhibition, and the role that these pathways play in prosurvival and proapoptotic processes that may be differentially expressed in vulnerable and resistant regions of the reperfused brain.