Miracle-dz/UniFAR-FTUs huggingface dataset:
Chlamydia trachomatis Type III Secretion Proteins Regulate Transcription

ABSTRACT The Scc4 protein (CT663) of the pathogenic bacterium Chlamydia has been described as a type III secretion (T3S) chaperone as well as an inhibitor of RNA polymerase. To examine if these roles are connected, we first investigated physical interactions between Chlamydia trachomatis Scc4 and the T3S chaperone Scc1 and a T3S substrate, CopN. In a yeast 3-hybrid assay, Scc4, Scc1, and CopN were all required to detect an interaction, which suggests that these proteins form a trimolecular complex. We also detected interactions between any two of these three T3S proteins in a pulldown assay using only recombinant proteins. We next determined whether these interactions affected the function of Scc4 as an inhibitor of RNA transcription. Using Escherichia coli as a heterologous in vivo system, we demonstrated that expression of C. trachomatis Scc4 led to a drastic decrease in transcript levels for multiple genes. However, coexpression of Scc4 with Scc1, CopN, or both alleviated Scc4-mediated inhibition of transcription. Scc4 expression also severely impaired E. coli growth, but this growth defect was reversed by coexpression of Scc4 with Scc1, CopN, or both, suggesting that the inhibitory effect of Scc4 on transcription and growth can be antagonized by interactions between Scc4, Scc1, and CopN. These findings suggest that the dual functions of Scc4 may serve as a bridge to link T3S and the regulation of gene expression in Chlamydia. IMPORTANCE This study investigates a novel mechanism for regulating gene expression in the pathogenic bacterium Chlamydia. The Chlamydia type III secretion (T3S) chaperone Scc4 has been shown to inhibit transcription by RNA polymerase. This study describes physical interactions between Scc4 and the T3S proteins Scc1 and CopN. Furthermore, Chlamydia Scc1 and CopN antagonized the inhibitory effects of Scc4 on transcription and growth in a heterologous Escherichia coli system. These results provide evidence that transcription in Chlamydia can be regulated by the T3S system through interactions between T3S proteins.
Collaborative Data Dissemination Methods In VANETs For Identifying Road Conditions Zone Boundaries

Vehicle to vehicle communication (V2VC) is a modern approach to exchanging and generating traffic information with (yet to be realised) potential to improve road safety, driving comfort and traffic control. In this paper, we present a novel algorithm which is based on V2V communication, uses in-vehicle sensor information and, in collaboration with other vehicles’ sensor information, can detect road conditions and determine the geographical area where these road conditions exist e.g. an area where there is traffic density, unusual traffic behaviour, a range of weather conditions (raining), etc. The built-in automatic geographical restriction of the data collection, aggregation and dissemination mechanisms allows warning messages to be received by other cars not necessarily sharing the identified road conditions, which may then be used to inform them of the optimum route to take (to avoid bottlenecks or dangerous areas including accidents or congestion on their current routes). We propose two approaches in this paper that are simple, flexible and fast and do not rely on any kind of roadside infrastructure equipment. They will offer live road condition information channels at – almost – no cost to drivers and public/private traffic agencies and have the potential to become an indispensable part of any future intelligent traffic system (ITS).
The Sphingosine 1-Phosphate Receptor Agonist Fingolimod Increases Myocardial Salvage and Decreases Adverse Post-Infarction Left Ventricular Remodeling in a Porcine Model of Ischemia-Reperfusion

Icahn School of Medicine at Mount Sinai, Mount Sinai Heart, Zena and Michael A. Wiener Cardiovascular Institute, and Marie-Josée and Henry R. Kravis Center for Cardiovascular Health, New York, NY; Columbia University Medical Center, New York Presbyterian Hospital, New York, NY; Dept of Cardiology, Medical University of Vienna, Vienna, Austria; Center for Clinical Heart Research, Dept of Cardiology, Oslo University Hospital Ullevaal, Oslo, Norway
Moniliophthora perniciosa Necrosis- and Ethylene-Inducing Protein 2 (MpNep2) as a Metastable Dimer in Solution: Structural and Functional Implications

Understanding how Nep-like proteins (NLPs) behave during the cell cycle and disease progression of plant pathogenic oomycetes, fungi and bacteria is crucial in light of compelling evidence that these proteins play a role in Witches` Broom Disease (WBD) of Theobroma cacao, one of the most important phytopathological problems to afflict the Southern Hemisphere. The crystal structure of MpNep2, a member of the NLP family and the causal agent of WBD, revealed the key elements for its activity. This protein has the ability to refold after heating and was believed to act as a monomer in solution, in contrast to the related homologs MpNep1 and NPP from the oomyceteous fungus Phytophthora parasitica. Here, we identify and characterize a metastable MpNep2 dimer upon over-expression in Escherichia coli using different biochemical and structural approaches. We found using ultra-fast liquid chromatography that the MpNep2 dimer can be dissociated by heating but not by dilution, oxidation or high ionic strength. Small-angle X-ray scattering revealed a possible tail-to-tail interaction between monomers, and nuclear magnetic resonance measurements identified perturbed residues involved in the putative interface of interaction. We also explored the ability of the MpNep2 monomer to refold after heating or chemical denaturation. We observed that MpNep2 has a low stability and cooperative fold that could be an explanation for its structure and activity recovery after stress. These results can provide new insights into the mechanism for MpNep2′s action in dicot plants during the progression of WBD and may open new avenues for the involvement of NLP- oligomeric species in phytopathological disorders.
Robust Projective Dictionary Learning by Joint Label Embedding and Classification

In this paper, we propose a new discriminative dictionary learning framework, called robust Label Embedding Projective Dictionary Learning (LE-PDL), for data classification. LE-PDL can learn a discriminative dictionary and the blockdiagonal representations without using the l0-norm or l1-norm sparsity regularization, since the l0 or l1-norm constraint on the coding coefficients used in the existing DL methods makes the training phase time-consuming. To enhance the performance, we also consider label information of the dictionary atoms in the learning process of LE-PDL to encourage the intra-class atoms to deliver similar profiles and enforce the coefficient matrix to be block-diagonal. Besides, our LE-PDL also involves an underlying projection to bridge data with their coefficients by extracting special features from given data. Then, we can train a classifier based on the extracted features so that the classification and representation powers are jointly considered. So, the classification approach of our model is efficient, since it avoids the extra time-consuming sparse reconstruction process with trained dictionary for each new test data as most existing DL methods. Besides, a robust l2,1-norm is regularized on the classifier and the non-negative constraint is used for the coding coefficients to enhance the performance. Experimental results show the effectiveness of our formulation.
A TCAD and Spectroscopy Study of Dark Count Mechanisms in Single-Photon Avalanche Diodes

It is shown through dark count rate spectroscopy (DCRS) and TCAD-simulations that in single-photon avalanche diodes (SPADs), the majority of low dark count rate (DCR) devices in modern CMOS arrays are free of deep-level traps and that DCR can therefore be explained by saturation current and band-to-band tunneling (BTBT). The DCRS performed on the Megaframe 32 × 32 show that the activation energies for the high DCR devices are consistent with a single type of defect at ≈ 0.44 eV, thought to be the E-center, in differing electric fields. Calibrated TCAD-simulated reverse bias leakage currents are orders of magnitude lower than those measured due to the lack of parasitic leakage paths but give theoretical DCRS that are close to the measured values for four different SPAD designs and predict the voltage dependence at high fields. The coefficients for Kane's indirect tunneling model in the [100] direction are determined as A ≈ 2×1015 cm-3/s and B ≈ 2.39×107 V/cm through TCAD calibration, DCR measurement, and theory. It is found that indirect BTBT dominates the DCR of SPADs with low breakdown voltages.
Comparative Study of Parallel Suffix Arrays Algorithms

This paper presents results from experiments devised to evaluate the comparative performance of a number of parallel algorithms we have devised for Suffix Arrays. This is an indexing strategy for very large text databases which allows complex queries to be effected in an efficient way. We have parallelized this strongly sequential strategy and obtained performance results with actual implementations operating upon a cluster of PCs and benchmark work-loads.
Failure of fluconazole prophylaxis to reduce mortality or the requirement of systemic amphotericin B therapy during treatment for refractory acute myeloid leukemia

Invasive fungal infections have increasingly become a matter of concern with regard to patients receiving intensive myelosuppressive therapy for hematologic malignancies. Such infections, especially prolonged neutropenia systemic fungal infections, may contribute substantially to infectious complications and early death. Measures for early detection and effective prophylactic strategies using active and nontoxic antifungal agents are therefore urgently needed.
Learning 3D Deformation of Animals from 2D Images

Understanding how an animal can deform and articulate is essential for a realistic modification of its 3D model. In this paper, we show that such information can be learned from user‐clicked 2D images and a template 3D model of the target animal. We present a volumetric deformation framework that produces a set of new 3D models by deforming a template 3D model according to a set of user‐clicked images. Our framework is based on a novel locally‐bounded deformation energy, where every local region has its own stiffness value that bounds how much distortion is allowed at that location. We jointly learn the local stiffness bounds as we deform the template 3D mesh to match each user‐clicked image. We show that this seemingly complex task can be solved as a sequence of convex optimization problems. We demonstrate the effectiveness of our approach on cats and horses, which are highly deformable and articulated animals. Our framework produces new 3D models of animals that are significantly more plausible than methods without learned stiffness.
Population Dynamics of the Feral Pigeon in the Central Business District of Butte, Montana

Author(s): Richardson, Cody; Capoccia, Stella; Hart, Julie | Abstract: The purpose of this study was to gather information on the feral pigeon population living in the central business district (CBD) of Butte, MT. Pigeons in the CBD have historically been part of the urban landscape and have contributed to local biodiversity. We report on an aspect of a larger study that was initiated to address complaints from business owners concerning damage caused by pigeons. To better understand feral pigeon population dynamics, we used live trapping, marking with leg bands, and survey transects to study the pigeons’ distribution, habitat selection, and dispersal. Our results thus far indicate minimal dispersal between colonies. Two individuals have shown dispersal movements of up to 6.1 km from the tagging site. Transect surveys revealed an average of 173.3 birds present, with a maximum count of 254 and minimum of 101.
Trace Element and Isotope Geochemistry of the Northern and Central Tongan Islands with an Emphasis on the Genesis of High Nb/Ta Signatures at the Northern Volcanoes of Tafahi and Niuatoputapu

We present a new comprehensive isotope and trace element dataset for north and central Tongan lavas including high-precision High Field Strength Element measurements. The emphasis of our study is on lavas from the northernmost volcanic islands of Tafahi and Niuatoputapu that exhibit unique compositions compared with other Tongan volcanoes, in particular elevated high-precision Nb/Ta ratios as high as similar to 28. These lavas are extremely depleted in incompatible, fluid-immobile elements such as Ti, Zr, Sc and Yb, suggesting about 6% depletion of their mantle wedge source relative to average upper mantle prior to 20-30% partial melting. The extremely depleted mantle wedge was re-enriched in highly incompatible elements including Nb and Ta from the subducting slab. Three slab components-fluids from altered oceanic crust, pelagic sediments, and Louisville Seamount Chain lavas-have contributed to the source region of the magmas. A fluid from the subducted Louisville lavas has been added after the other two slab components and has radiogenic Pb-206/Pb-204. Components from the altered oceanic crust and Louisville sea-mounts exhibit little Nb/Ta fractionation, as demonstrated by the nearly uniform and mid-ocean ridge basalt-like Nb/Ta ratios. We suggest that the apparently large slab fluid flux beneath Tafahi and Niuatoputapu results from focused flow through subducting Louisville Seamount crust that had no or little sediment cover, allowing the fluids to pass through the subducting lithosphere more efficiently. Thus, the high Nb/Ta ratios indicate that the Louisville-derived fluids had probably equilibrated with residual rutile. Our results imply that significant amounts of Nb and Ta can be mobilized from distinct subducting oceanic lithologies-a process that may probably also operate beneath other island arcs. We propose a model in which the appearance of the subducted seamount signatures some 3-4Myr after their actual subduction is explained by storage in shallow metasomatized lithospheric mantle. This relic Louisville seamount signature is subsequently reactivated and added to transiting magmas 4 Myr later. This reactivation may result from slab rollback of the subducting Pacific plate towards the east. Our new temporal and spatial model also provides a viable explanation for the conundrum of the occurrence of Louisville signatures even though the Louisville seamount chain is, at present, being subducted several hundred kilometres further south.
CEDAR: a core-extraction distributed ad hoc routing algorithm

CEDAR is an algorithm for QoS routing in ad hoc network environments. It has three key components: (a) the establishment and maintenance of a self-organizing routing infrastructure called the core for performing route computations, (b) the propagation of the link-state of stable high-bandwidth links in the core through increase/decrease waves, and (c) a QoS route computation algorithm that is executed at the core nodes using only locally available state. But preliminary performance evaluation shows that CEDAR is a robust and adaptive QoS routing algorithm that reacts effectively to the dynamics of the network while still approximating link-state performance for stable networks.
Personality and Social Psychology Bulletin Nezlek / Multilevel Random Coefficient Analyses Multilevel Random Coefficient Analyses of Event-and Interval-contingent Data in Social and Personality Psychology Research

Increasingly, social and personality psychologists are conducting studies in which data are collected simultaneously at multiple levels, with hypotheses concerning effects that involve multiple levels of analysis. In studies of naturally occurring social interaction, data describing people and their social interactions are collected simultaneously. This article discuses how to analyze such data using random coefficient modeling. Analyzing data describing day-today social interaction is used to illustrate the analysis of event-contingent data (when specific events trigger or organize data collection), and analyzing data describing reactions to daily events is used to illustrate the analysis of interval-contingent data (when data are collected at intervals). Different analytic strategies are presented, the shortcomings of ordinary least squares analyses are described, and the use of multilevel random coefficient modeling is discussed in detail. Different modeling techniques, the specifics of formulating and testing hypotheses, and the differences between fixed and random effects are also considered. The use of nonexperimental methods in social and personality psychology has increased dramatically over the past two decades, and much of this research has concerned day-today experience and other naturally occurring phenomena. Many studies of such phenomena produce multilevel data structures in which observations are collected simultaneously at multiple levels, and this article describes the use of multilevel random coefficient modeling to analyze data generated in studies of naturally occurring phenomena. An important way to classify studies of naturally occurring phenomena is the basis used to structure the data, and two types of data structures , event and interval contingent, predominate the study of naturally occurring phenomena in social and personality psychology. In event-contingent data structures , a specific type of event triggers (or organizes) data collection, whereas in interval-contingent structures, data are collected at intervals, such as every day. A wide variety of events and various intervals can be used to organize data collection, and it is beyond the scope of this article to discuss the analysis of each of these different data structures. In light of this, the analysis of event-contingent data is discussed in terms of the study of day-today social interaction, and the analysis of interval-contingent data is discussed in terms of the study of reactions to daily events. These topics were chosen because they are popular topics among social and personality psychologists that are frequently studied with multilevel designs. In studies of day-today social interaction, each person describes the social interactions (i.e., events) that occur over …
Cobra: fine-grained malware analysis using stealth localized-executions

Fine-grained code analysis in the context of malware is a complex and challenging task that provides insight into malware code-layers (polymorphic/metamorphic), its data encryption/decryption engine, its memory layout etc., important pieces of information that can be used to detect and counter the malware and its variants. Current research in fine-grained code analysis can be categorized into static and dynamic approaches. Static approaches have been tailored towards malware and allow exhaustive fine-grained malicious code analysis, but lack support for self-modifying code, have limitations related to code-obfuscations and face the undecidability problem. Given that most if not all malware employ self-modifying code and code-obfuscations, poses the need to analyze them at runtime using dynamic approaches. However, current dynamic approaches for fine-grained code analysis are not tailored specifically towards malware and lack support for multithreading, self-modifying/self-checking code and are easily detected and countered by ever-evolving anti-analysis tricks employed by malware. To address this problem, we propose a powerful dynamic fine-grained malicious code analysis framework, codenamed Cobra, to combat malware that are becoming increasingly hard to analyze. Our goal is to provide a stealth, efficient, portable and easy-to-use framework supporting multithreading, self-modifying/self-checking code and any form of code obfuscation in both user- and kernel-mode on commodity operating systems. Cobra cannot be detected or countered and can be dynamically and selectively deployed on malware specific code-streams while allowing other code-streams to execute as is. We also illustrate the framework utility by describing our experience with a tool employing Cobra to analyze a real-world malware
Neural Correlates of Response Inhibition and Conflict Control on Facial Expressions

Response inhibition and conflict control on affective information can be regarded as two important emotion regulation and cognitive control processes. The emotional Go/Nogo flanker paradigm was adopted and participant’s event-related potentials (ERPs) were analyzed to investigate how response inhibition and conflict control interplayed. The behavioral findings revealed that participants showed higher accuracy to identify happy faces in congruent condition relative to that in incongruent condition. The electrophysiological results manifested that response inhibition and conflict control interplayed during the detection/conflict monitoring stage, and Nogo-N2 was more negative in the incongruent trials than the congruent trials. With regard to the inhibitory control/conflict resolution stage, Nogo responses induced greater frontal P3 and parietal P3 responses than Go responses did. The difference waveforms of N2 and parietal P3 showed that response inhibition and conflict control had distinct processes, and the multiple responses requiring both conflict control and response inhibition processes induced stronger monitoring and resolution processes than conflict control. The current study manifested that response inhibition and conflict control on emotional information required separable neural mechanisms during emotion regulation processes.
Information Dissemination and Fairness Perceptions: The Case of Inland Revenue Board Malaysia

This paper highlights how information dissemination or information sharing between the authority (in this case, is the Inland Revenue Board Malaysia - IRBM) and the community at large would to certain extent influence their perceptions on the fairness of the income tax system. Specifically, this paper investigates perceptions of individual taxpayers on the fairness of the income tax system in Malaysia and how such perceptions were formed, by applying a mixed method (through survey and interview). The survey involved 852 respondents while the interview sessions were conducted on 30 participants. The descriptive analysis and thematic analysis were carried out on survey data and interview data, respectively. Survey results indicate that taxpayers generally perceive the income tax system as fair. The interviews, on the other hand, showed that taxpayers were not happy with government spending of tax revenue. Such view was actually resulted from the lack of information disclosed by the IRBM on how they have used the taxpayers’ money. Taxpayers believed if such dissemination of information has taken place, their views on IRBM’s credibility may have been improved.