Miracle-dz/UniFAR-FTUs huggingface dataset:
Natural polyphenols down-regulate universal stress protein in Mycobacterium tuberculosis: An in-silico approach

Universal stress protein (USP) is a novel target to overcome the tuberculosis resistance. Our present study enlightens the possibilities of some natural polyphenols as an antioxidant for USP. The study has shown some molecular simulations of some selected natural antioxidants with USP. We have considered USP (Rv1636) strain for homology modeling and the selected template was taken for the docking study. Curcumin, catechin, reservetrol has shown ARG 136 (1.8Å) hydrogen bonding and two ionic bonding with carboxyl group of curcumin with LEU 130 (3.3Å) and ASN 144 (3.4Å) respectively. INH was taken for the standard molecule to perform molecular simulation. It showed poor binding interaction with the target, that is, −5.18 kcal, and two hydrogen bonding with SER 140 (1.887Å), ARG 147 (2.064Å) respectively. The study indicates possible new generation curcumin analogue for future therapy to down-regulate USP.
Determination of Critical Conditions for Initiation of Dynamic Recrystallization by New Method

ABSTRACT Based on the stress versus strain relation for materials at high temperatures, a new method to determine critical conditions for initial dynamic recrystallization (DRX) was proposed by analyzing the stress versus strain curve in a double natural logarithm coordinates (Ln–Ln plot) directly. The critical conditions of initial DRX of a low carbon steel were determined by the new method and the resultant values were compared with those determined by previous methods. The results show that the normalized strains are 0.6491, 0.7026, and 0.7055, respectively, by using the corresponding curves and all of the values fall in the range of 0.6–0.85 proposed by Sellars. The normalized stress and strain determined by using the strain hardening rate versus stress curve have a good agreement with those determined by using the stress versus strain curve in an Ln–Ln plot.
Capturing Information Need by Learning User Context

Learning techniques can be applied to help information retrieval systems adapt to users' spe-ciic needs. They can be used to learn from user searches to improve subsequent searches. This paper describes the approach taken to learn about particular users' contexts in order to improve document ranking produced by a probabilistic information retrieval system. The approach is based on the argument that there is a pattern in user queries in that they tend to remain within a particular context over on-line sessions. This context, if approximated, can improve system performance. While it is not uncommon to link the evidence from one query to the next within a particular online session, the approach here groups the evidence over diierent sessions. The paper concentrates on the user-oriented evaluation method used in order to determine whether or not the approach improved information retrieval system performance .
Consistent Covariance Matrix Estimation in Probit Models with Autocorrelated Errors

Some recent time-series applications use probit models to measure the forecasting power of a set of variables. Correct inferences about the significance of the variables requires a consistent estimator of the covariance matrix of the estimated model coefficients. A potential source of inconsistency in maximum likelihood standard errors is serial correlation in the underlying disturbances, which may arise, for example, from overlapping forecasts. We discuss several practical methods for constructing probit autocorrelation-consistent standard errors, drawing on the generalized method of moments techniques of Hansen (1982), Newey-West (1987) and others, and we provide simulation evidence that these methods can work well.
Compact Video Code and Its Application to Robust Face Retrieval in TV-Series

We address the problem of video face retrieval in TV-Series which searches video clips based on the presence of specific character, given one video clip of his/hers. This is tremendously challenging because on one hand, faces in TV-Series are captured in largely uncontrolled conditions with complex appearance variations, and on the other hand retrieval task typically needs efficient representation with low time and space complexity. To handle this problem, we propose a compact and discriminative representation for the huge body of video data, named Compact Video Code (CVC). Our method first models the video clip by its sample (i.e., frame) covariance matrix to capture the video data variations in a statistical manner. To incorporate discriminative information and obtain more compact video signature, the high-dimensional covariance matrix is further encoded as a much lower-dimensional binary vector, which finally yields the proposed CVC. Specifically, each bit of the code, i.e., each dimension of the binary vector, is produced via supervised learning in a max margin framework, which aims to make a balance between the discriminability and stability of the code. Face retrieval experiments on two challenging TV-Series video databases demonstrate the competitiveness of the proposed CVC over state-of-the-art retrieval methods. In addition, as a general video matching algorithm, CVC is also evaluated in traditional video face recognition task on a standard Internet database, i.e., YouTube Celebrities, showing its quite promising performance by using an extremely compact code with only 128 bits.
A Framework for Classification of Resource Consolidation Management Problems

Much effort in the current literature has been put towards methods and implementations to solve Resource Consolidation Management (RCM) problems in the cloud setting. A vast number of proposed solutions appears to be designed for different variants of the RCM problem. This makes the comparison of approaches challenging. We propose a new framework that facilitates mapping RCM solutions to their RCM problem definitions. Our framework allows a solution to be assigned to its RCM problem definition by means of answering a set of questions specific to RCM problems. Our framework can be used to (1) specify problem descriptions, (2) establish optimal solutions and providing theoretical benchmarks, (3) provide a platform allowing formal complexity analysis of RCM problems and (4) facilitate a healthy discussion about the essence of RCM and evaluations of different solutions. We show how our proposed framework can be applied in form of case studies depicting four approaches from the literature.
On General Equilibrium Effects and Contingent Claim Valuation of Financial Assets ∗

This paper studies the extent of the error that is made in standard contingent claim analysis, which underlies modern asset pricing theories and real option theory within a two-period general equilibrium model with incomplete markets. It is well-known that in mean-variance, or CARA-normal economies the introduction of new assets leaves the prices of existing assets, relative to the bond, unchanged. Simulations show that contingent claim valuation remains a good predictor of a new asset’s equilibrium price in CRRA-lognormal economies with habit formation. Present value, however, performs badly. Equilibria are computed via a differentially implementable homotopy.
Lamb wave detection and source location using fiber Bragg gratin rosettes

We describe a novel fiber-optic system that is able to detect both ultrasonic Lamb waves and the location of their source. The aim of the system is to detect damage in structures such as those found in aerospace applications. Our system involves the use of fiber Bragg gratings, which may be either bonded to the surface of the material or embedded within it in order to detect the linear strain component produced by the acoustic waves. Interrogation of the Bragg gratings is carried out using a laser, which is tuned to the wavelength that gives the maximum sensitivity on the grating response curve. An amplitude modulated signal is produced by the interaction of the Lamb wave with the grating. The well defined directional properties of the Bragg grating (compared to the isotropic response of the more commonly used piezoceramic disc transducers) are used to determine the direction of propagation of the acoustic waves by mounting three of the gratings in a rosette configuration. Two suitably spaced rosettes are used to locate the source of the ultrasound by taking the intersection of the directions given by each rosette. This will become important when we extend the technique to include the study of the use of changes in the propagation properties of Lamb waves as a method of damage detection. We will present both theoretical and practical results on the interaction of the Lamb waves with the grating and the extraction of directional information from the response of the rosettes.
Unix Memory Allocations are Not Poisson

In multitasking operating systems, requests for free memory are traditionally modeled as a stochastic counting process with independent, exponentially-distributed interarrival times because of the analytic simplicity such Poisson models afford. We analyze the distribution of several million unix page commits to show that although this approach could be valid over relatively long timespans, the behavior of the arrival process over shorter periods is decidedly not Poisson. We find that this result holds regardless of the originator of the request: unlike network packets, there is little difference between system- and user-level page-request distributions. We believe this to be due to the bursty nature of page allocations, which tend to occur in either small or extremely large increments. Burstiness and persistent variance have recently been found in self-similar processes in computer networks, but we show that although page commits are both bursty and possess high variance over long timescales, they are probably not self-similar. These results suggest that altogether different models are needed for fine-grained analysis of memory systems, an important consideration not only for understanding behavior but also for the design of online control systems.
THE DESIGN OF BLOCK-BASED MASHUP TOOL FOR END- USERS MASHUP APPLICATIONS DEVELOPMENT

A mashup application is a web application that combines contents from several sources into an integrated web experience A mashup tool is a software tool to assist users in developing web mashup application. Most of these tools are developed by employing end-users development approaches such as scripting, wire, widget, spreadsheet, and Programming by Demonstration. However, although these tools are based on end-users development approaches, they are still difficult to be used by most of end-users since they require end-users to have some programming background. In this paper, we present the design of Whip mashup tool. The aim of this mashup tool is to allow end-users to develop web mashup application easily by using Block-Based Software Development approach. This development approach enables end-users to develop software or web applications by combining several programming blocks together.
A Low-Cost Storage Server for Movie on Demand Databases

With recent advances in storage and network technology it is now possible to provide movie on demand (MOD) service, eliminating the inflexibility inherent in todays broadcast cable systems. A MOD server is a computer sy5 tern that stores movies in compressed digital form and provides support for different portions of compressed movie data to be accessed and transmitted concurrently. In this paper, we present a low-cost storage architecture for a MOD server that relies principally on disks. The high bandwidths of disks in conjunction with a clever strategy for striping movies on them is utilized in order to enable simultaneous access and transmission of “certain” different portions of a movie. We also present a wide range of schemes for implementing VCRlike functions.
Effect of Sonication Time and Particle Volume Fraction on Thermal Conductivity of Alumina Nanofluids

Abstract : The objective of this task was to use analytical modeling to determine thermal conductivity enhancement of nanofluid samples, with overall particle volume fraction, from 1% to 5%, at 70 W and 100 W. The highest thermal conductivity enhancement and maximum number of nanoparticle clusters were observed for different overall particle volume fractions and sonication times, at 70 W and 100 W. The second conclusion was, at both power levels, 4% volume fraction yielded nanofluids with highest thermal conductivity enhancement. For thermal conductivity enhancement from 16% to 35%, the maximum cluster size was on the order of 200 nm, while, for thermal conductivity enhancements from 135% to 173%, the maximum cluster size was restricted to 500 nm. Thermal conductivity enhancements in excess of 100% of the base fluid were achieved when the optimum overall particle volume fraction is 4%.
SICS: Valence annotation based on seeds in word space

This paper reports on a experiment to identify the emotional loading (the "valence") of news headlines. The experiment reported is based on a resource-thrifty approach for valence annotation based on a word-space model and a set of seed words. The model was trained on newsprint, and valence was computed using proximity to one of two manually defined points in a high-dimensional word space --- one representing positive valence, the other representing negative valence. By projecting each headline into this space, choosing as valence the similarity score to the point that was closer to the headline, the experiment provided results with high recall of negative or positive headlines. These results show that working without a high-coverage lexicon is a viable approach to content analysis of textual data.
Early Healing Events after Periodontal Surgery: Observations on Soft Tissue Healing, Microcirculation, and Wound Fluid Cytokine Levels

Early wound healing after periodontal surgery with or without enamel matrix derivative/biphasic calcium phosphate (EMD/BCP) was characterized in terms of soft tissue closure, changes of microcirculation, and expression of pro- and anti-inflammatory cytokines in gingival crevicular fluid/wound fluid (GCF/WF). Periodontal surgery was carried out in 30 patients (18 patients: application of EMD/BCP for regeneration of bony defects; 12 patients: surgical crown lengthening (SCL)). Healthy sites were observed as untreated controls. GCF/WF samples were collected during two post-surgical weeks. Flap microcirculation was measured using laser Doppler flowmetry (LDF). Soft tissue healing was evaluated after two weeks. GCF/WF levels of interleukin 1β (IL-1β), tumour necrosis factor (TNF-α), IL-6, and IL-10 were determined using a multiplex immunoassay. Surgery caused similar reductions of flap microcirculation followed by recovery within two weeks in both EMD/BCP and SCL groups. GCF/WF and pro-inflammatory cytokine levels were immediately increased after surgery, and returned only partially to baseline levels within the two-week observation period. Levels of IL-10 were temporarily reduced in all surgical sites. Flap dehiscence caused prolonged elevated levels of GCF/WF, IL-1β, and TNF-α. These findings show that periodontal surgery triggers an immediate inflammatory reaction corresponding to the early inflammatory phase of wound healing, and these inflammation measures are temporary in case of maintained closure of the flap. However, flap dehiscence causes prolonged inflammatory exudation from the periodontal wound. If the biological pre-conditions for periodontal wound healing are considered important for the clinical outcome, care should be taken to maintain primary closure of the flap.
Modelling the mechanical response of urushi lacquer subject to a change in relative humidity

A hygromechanical model has been developed to simulate the in-service behaviour of the natural lacquer urushi, using a phenomenological description of viscoelasticity. The material and mechanical properties were determined as a function of the relative humidity (RH), and the relationship between RH and moisture content was determined. These properties served as inputs to a finite-element-based model that was then tested against experimental measurements of the depth-averaged stresses in a thin layer of urushi deposited on a substrate and exposed to changes in the environmental conditions. Good agreement was seen between the predicted and measured behaviour. The validated model was used to investigate the spatial and temperature variation of stress in urushi films subjected to cyclic environmental conditioning.
Noise Robust Voice Activity Detection Based on Switching Kalman Filter

This paper addresses the problem of voice activity detection (VAD) in noisy environments. The VAD method proposed in this paper is based on a statistical model approach, and estimates statistical models sequentially without a priori knowledge of noise. Namely, the proposed method constructs a clean speech / silence state transition model beforehand, and sequentially adapts the model to the noisy environment by using a switching Kalman filter when a signal is observed. In this paper, we carried out two evaluations. In the first, we observed that the proposed method significantly outperforms conventional methods as regards voice activity detection accuracy in simulated noise environments. Second, we evaluated the proposed method on a VAD evaluation framework, CENSREC-1-C. The evaluation results revealed that the proposed method significantly outperforms the baseline results of CENSREC-1-C as regards VAD accuracy in real environments. In addition, we confirmed that the proposed method helps to improve the accuracy of concatenated speech recognition in real environments.
Using Multi-objective Optimization for Automated Graph Drawing

A Genetic Algorithm (GA) is the process of constructing an optimization problem in which several objectives can be optimized at the same time. In this paper, Strength Pareto Evolutionary Algorithm (SPEA), a GA based multi-objective optimization technique, has been applied to a graph drawing (GD) problem. In this paper a measure (force equalization) which contributes to production of nicely drawing is introduced by a GA. We show that using the introduced objective and keeping the Pareto optimal solutions of the GD process in a pool, the following advantage can be achieved: A single run of the GA process leads to several suboptimal solutions which provide the user with a selection right; to choose the most effective drawing.
Applying Semantic Analysis to Feature Execution Traces

Recently there has been a revival of interest in feature analysis of software systems. Approaches to feature location have used a wide range of techniques such as dynamic analysis, static analysis, information retrieval and formal concept analysis. In this paper we introduce a novel approach to analyze the execution traces of features using Latent Semantic Indexing (LSI). Our goal is twofold. On the one hand we detect similarities between features based on the content of their traces, and on the other hand we categorize classes based on the frequency of the outgoing invocations involved in the traces. We apply our approach on two case studies and we discuss its benefits and drawbacks.
Differential Drug Resistance Acquisition in HIV-1 of Subtypes B and C

Background Subtype C is the most prevalent HIV-1 subtype in the world, mainly in countries with the highest HIV prevalence. However, few studies have evaluated the impact of antiretroviral therapy on this subtype. In southern Brazil, the first developing country to offer free and universal treatment, subtypes B and C co-circulate with equal prevalence, allowing for an extensive evaluation of this issue. Methods and Findings Viral RNA of 160 HIV-1+ patients was extracted, and the protease and reverse transcriptase genes were sequenced, subtyped and analyzed for ARV mutations. Sequences were grouped by subtype, and matched to type (PI, NRTI and NNRTI) and time of ARV exposure. Statistical analyses were performed to compare differences in the frequency of ARV-associated mutations. There were no significant differences in time of treatment between subtypes B and C groups, although they showed distinct proportions of resistant strains at different intervals for two of three ARV classes. For PI, 26% of subtype B strains were resistant, compared to only 8% in subtype C (p = 0.0288, Fisher's exact test). For NRTI, 54% of subtype B strains were resistant versus 23% of subtype C (p = 0.0012). Differences were significant from 4 years of exposure, and remained so until the last time point analyzed. The differences observed between both subtypes were independent of time under rebound viremia in cases of virologic failure and of the number of HAART regimens used by treated patients. Conclusions Our results pointed out to a lower rate of accumulation of mutations conferring resistance to ARV in subtype C than in subtype B. These findings are of crucial importance for current initiatives of ARV therapy roll-out in developing countries, where subtype is C prevalent.
Silicon nitride microclips for the kinematic location of optic fibres in silicon V-shaped grooves

Flexible silicon nitride clips are used to hold single mode optical fibres in position in grooves etched in silicon substrates to connect either subsurface or surface mounted optical components. The fabrication process for the buried fibre connector requires only one lithographic step, and a silicon substrate coated with a 3 m thick silicon nitride film. The light coupled between two single mode optic fibres buried in the same V groove has been measured as a function of the separation of the ends of the fibres. The Young's modulus and mechanical properties of silicon nitride from various sources have been measured using the clips. In another process using two lithographic steps a clipped fibre is made having the fibre core level with the silicon surface or up to 20 m above it, and the tolerances are sufficiently tight for optical system manufacture. Light coupling has been demonstrated between a semiconductor laser and a fibre. The clip technology is versatile and tolerant of lateral and angular misalignments during insertion. Fabrication and mechanical design rules for the silicon nitride clip technology are summarized, and possible applications in fibre connection, waveguide sensor and telecommunication systems are discussed.
OLMRP: Hierarchical Outflow Load-balancing Multicast Routing Protocol for Congestion Control in Ad hoc Networks

This paper, proposes a new multicast routing protocol for mobile ad hoc networks that handles the congestion to improve the Quality of routing service. Part of the proposed protocol introduced a MAC layer level solution called Group Level Multicasting (GLM) that effectively handles the multicasting at one hop level mesh or tree. The proposed model controls the congestion in hierarchical order to minimize the resource utilization. Limited bandwidth and a high degree of mobility require that routing protocols for ad hoc networks be adaptive, trouble-free, and energy saving. This paper proposed a new Hierarchical Outflow Loadbalancing Multicast Routing Protocol (OLMRP) for Ad hoc networks, which handles congestion state. OLMR is capable to adapt a mesh or tree structure with enhanced similar resilience against mobility. OLMRP utilizes GLM to reduce the overhead of route failure recovery, improve route efficiency and reduce data transmissions. The simulation results show that OLMR handles congestion with reduced control overhead in various environments,also the improved packet delivery ratio.