Miracle-dz/UniFAR-FTUs huggingface dataset:
Solving the TCP-Incast Problem with Application-Level Scheduling

Data center networks are characterized by high link speeds, low propagation delays, small switch buffers, and temporally clustered arrivals of many concurrent TCP flows fulfilling data transfer requests. However, the combination of these features can lead to transient buffer overflow and bursty packet losses, which in turn lead to TCP retransmission timeouts that degrade the performance of short-lived flows. This so-called TCP-incast problem can cause TCP throughput collapse. In this paper, we explore an application-level approach for solving this problem. The key idea of our solution is to coordinate the scheduling of short-lived TCP flows so that no data loss happens. We develop a mathematical model of lossless data transmission, and estimate the maximum good put achievable in data center networks. The results indicate non-monotonic good put that is highly sensitive to specific parameter configurations in the data center network. We validate our model using ns-2 network simulations, which show good correspondence with the theoretical results.
The outliers become a stampede as immunometabolism reaches a tipping point

Summary: Obesity and Type 2 diabetes mellitus (T2D) are characterized by pro‐inflammatory alterations in the immune system including shifts in leukocyte subset differentiation and in cytokine/chemokine balance. The chronic, low‐grade inflammation resulting largely from changes in T‐cell, B‐cell, and myeloid compartments promotes and/or exacerbates insulin resistance (IR) that, together with pancreatic islet failure, defines T2D. Animal model studies show that interruption of immune cell‐mediated inflammation by any one of several methods almost invariably results in the prevention or delay of obesity and/or IR. However, anti‐inflammatory therapies have had a modest impact on established T2D in clinical trials. These seemingly contradictory results indicate that a more comprehensive understanding of human IR/T2D‐associated immune cell function is needed to leverage animal studies into clinical treatments. Important outstanding analyses include identifying potential immunological checkpoints in disease etiology, detailing immune cell/adipose tissue cross‐talk, and defining strengths/weaknesses of model organism studies to determine whether we can harness the promising new field of immunometabolism to curb the global obesity and T2D epidemics.
Particle Swarm Optimization Combined with Molecular Force and Its Application for Parameter Estimation

Parameter estimation is the critical part of system identification and regression analysis and it relates to the application and promotion of nonlinear model. The parameter estimation problem of nonlinear model is transformed into an unconstrained multi-dimensional function optimization problem. The particle swarm optimization algorithm based on the molecular force (MPSO), which is enlightened by molecular kinetic theory, is used to solve this problem, just taking the asymptotic regression model for example which is widespread in natural sciences and social sciences. There are real data and random sample data in the experiments. The random sample data is applied to analyze the impact of dimensions of parameter estimation and sampling interval on the algorithm performance, and experimental results show that MPSO algorithm is an effective nonlinear model parameter estimation method.
An Overview of Predictors for Intrinsically Disordered Proteins over 2010–2014

The sequence-structure-function paradigm of proteins has been changed by the occurrence of intrinsically disordered proteins (IDPs). Benefiting from the structural disorder, IDPs are of particular importance in biological processes like regulation and signaling. IDPs are associated with human diseases, including cancer, cardiovascular disease, neurodegenerative diseases, amyloidoses, and several other maladies. IDPs attract a high level of interest and a substantial effort has been made to develop experimental and computational methods. So far, more than 70 prediction tools have been developed since 1997, within which 17 predictors were created in the last five years. Here, we presented an overview of IDPs predictors developed during 2010–2014. We analyzed the algorithms used for IDPs prediction by these tools and we also discussed the basic concept of various prediction methods for IDPs. The comparison of prediction performance among these tools is discussed as well.
A Security Architecture for Wireless Mesh Network

Wireless Mesh Network (WMN) is characterized as rapid deployment and self-organizing, multi-hop network. It is regarded as commodity application of mobile ad hoc network. The wireless and distributed nature of WMNs and the bad security environment bring a great challenge to securing wireless mesh networks. Most schemes proposed recently are developed from security schemes of wireless local networks. Few of the previous work proposes security solutions from a system architectural view. In this paper, we propose security architecture for wireless mesh networks, which is layered as network model, trust model and security operations. Three main security technologies applied in this architecture and relationships among them are analyzed in detail.
Scalable approach for mining association rules from structured XML data

XML has become the standard for data representation on the web. This expansion in reputation has prompted the need for a technique to access XML documents. Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data
A Bipartite , Di erential IDDQ Testable Static RAM

I DDQ or current testing has emerged in the last few years as an eeective technique for detecting certain classes of faults in high density IC's. In this paper a testable design that enhances the I DDQ testability of static random access memories (SRAMs) for oo-line testing is proposed. To achieve high accuracy and a test speed approaching the system operational speed, the memory is partitioned for comparison of I DDQ values. Parallel write/read operations are used to activate possible faults, while quiescent power supply currents from two blocks are compared.
Hadoop scalable Video Transcoding technique in cloud environment

Nowadays video is being produced and consumed in more component representation formats, more device types and over a variety of networks than ever. Transmission of video through network takes more time. So Video Transcoding is a very important factor when the video is moved between various heterogeneous clients in the cloud environment. Transcoding is a process of translating one coded form of video into another. However most of the time transcoding becomes computationally intensive and time consuming process. This proposed cloud system has four of the video compression standards such as Low Quality Encoding, Standard Quality Encoding, High Quality Encoding and High Definition. These standards achieve better compression performance with Quality. In general compression process takes more time. Map Reduce is used for managing a work in a considerable short period of time. This in turn helps in faster and efficient video transcoding. These Four standards are embedded into the Hadoop Distributed File System implementation and trial runs were done. Using the HDFS Map Reduce functionality, the video is splited using 64 MB blocks (Segments of Streams) and processed separately for maintaining efficiency in a time based aspect.
Lipophosphoglycans from Leishmania amazonensis Strains Display Immunomodulatory Properties via TLR4 and Do Not Affect Sand Fly Infection

The immunomodulatory properties of lipophosphoglycans (LPG) from New World species of Leishmania have been assessed in Leishmania infantum and Leishmania braziliensis, the causative agents of visceral and cutaneous leishmaniasis, respectively. This glycoconjugate is highly polymorphic among species with variation in sugars that branch off the conserved Gal(β1,4)Man(α1)-PO4 backbone of repeat units. Here, the immunomodulatory activity of LPGs from Leishmania amazonensis, the causative agent of diffuse cutaneous leishmaniasis, was evaluated in two strains from Brazil. One strain (PH8) was originally isolated from the sand fly and the other (Josefa) was isolated from a human case. The ability of purified LPGs from both strains was investigated during in vitro interaction with peritoneal murine macrophages and CHO cells and in vivo infection with Lutzomyia migonei. In peritoneal murine macrophages, the LPGs from both strains activated TLR4. Both LPGs equally activate MAPKs and the NF-κB inhibitor p-IκBα, but were not able to translocate NF-κB. In vivo experiments with sand flies showed that both stains were able to sustain infection in L. migonei. A preliminary biochemical analysis indicates intraspecies variation in the LPG sugar moieties. However, they did not result in different activation profiles of the innate immune system. Also those polymorphisms did not affect infectivity to the sand fly.
A minimax search algorithm for robust continuous speech recognition

In this paper, we propose a novel implementation of a minimax decision rule for continuous density hidden Markov-model-based robust speech recognition. By combining the idea of the minimax decision rule with a normal Viterbi search, we derive a recursive minimax search algorithm, where the minimax decision rule is repetitively applied to determine the partial paths during the search procedure. Because of the intrinsic nature of a recursive search, the proposed method can be easily extended to perform continuous speech recognition. Experimental results on Japanese isolated digits and TIDIGITS, where the mismatch between training and testing conditions is caused by additive white Gaussian noise, show the viability and efficiency of the proposed minimax search algorithm.
On Linear Stability Analysis of High-Order Finite-Difference Methods

In order to produce the desired global order of accuracy, high-order finite-dierence methods require suitably accurate stable boundary schemes. Various tools can be helpful in providing insight into the stability of numerical boundary schemes, including spectra, pseudospectra, and the singular value decomposition. In this paper, these tools are applied to several dierent discretizations of the linear convection equation which display various types of instability. Pseudospectra are seen to be a convenient and eective means of detecting instabilities. The same instabilities can also be revealed by either the spectrum or the spectrum of the associated circulant matrix resulting from the assumption of periodic boundary conditions. Finally, the singular value decomposition is shown to be a good indicator of the cause of the instability.
Effect of Authentic Leadership on Organisation Commitment: Mediating Role of Job Satisfaction

Having committed employees is beneficent and sometimes essential for an organization. The current study investigates the mediating role of the job satisfaction in the relationship between authentic leadership and the organizational commitment. The participants of this study were 300 job holders working in different industries in Lahore, Pakistan. The Hayes’s Process showed full mediation. In this study, factor analysis (EFA/CFA) was conducted and different dimensions of all variables were witnessed, 3 new dimensions of organizational commitment and authentic leadership and job satisfaction become unidimensional by deleting a few items. The results of the factor analysis study also support the proposed hypotheses of the study. Moreover, the job satisfaction is better predictor of organizational commitment. When the leaders are authentic and well behaved with their employees, they become more satisfied and want to stay with the organization in future.
Interlaced to progressive scan conversion Using fuzzy edge-based line average algorithm

De-interlacing methods realize the interlaced to progressive conversion required in many applications. Among them, intra-field methods are widely used for their good trade off between performance and computational cost. In particular, the ELA algorithm is well-known for its advantages in reconstructing the edges of the images, although it degrades the image quality where the edges are not clear. The algorithm proposed in this paper uses a simple fuzzy system which models heuristic rules to improve the KLA rules. It can be implemented easily in software and hardware since the increase in computational cost is very low. Simulation results are included to illustrate the advantages of the proposed fuzzy ELA algorithm in de-interlacing non noisy and noisy images.
Evolutionary improvement of search queries and its parameters

The formulation of user queries is an important part of the information retrieval process. In the complex environment of the World Wide Web and other large data collections, it is often not easy for the users to express their information needs in an optimal way. In this paper, we investigate evolutionary algorithms (in particular genetic programming) as a tool for the optimization of user queries and seek for its good settings.
Getting on track: aligning the achievement gap conversation with ethical educational practice

ABSTRACT Research developments on tracking as an educational practice have led to a renewed need to investigate the ways it is conceptualized and operationalized. This article addresses the educational practice of tracking, how it impacts K-12 achievement, its potential for exacerbating inequities, and the ethics of separating students within intellectual spaces. The purpose is to illuminate the common practice of tracking and associated effects through a critical race lens. Research on tracking informs us of the deleterious effects for and on African American students, who comprise the largest population in lower track classes. The findings also shed light on why African American students attend school at the same rate or higher, yet remain the least prepared among their similarly situated peers, for higher educational opportunities. Because the achievement and opportunity gaps remain deeply entrenched in U.S. schooling, student experience, law, policy, ethics, teacher quality and curriculum access, are considered concurrently. The evidence supports the need for detracking policies to improve the equitable distribution and overall levels of student well-being and academic achievement.
Serum secreted frizzled-related protein 5 levels differentially decrease in patients with hepatitis B virus-associated chronic infection and hepatocellular carcinoma

The aim of this study was to investigate the characteristics of serum secreted frizzled-related protein 5 (SFRP5), an inhibitor of Wnt signaling, in hepatitis B virus (HBV)-associated infections and hepatocellular carcinoma (HCC) patients. Serum SFRP5 levels were detected in 147 patients with HBV-associated chronic infection or HCC. Compared with the non-HBV-infected and non-HCC group, the HBV-associated chronic infection and HCC groups exhibited decreased serum SFRP5 levels. A significant inverse correlation between serum SFRP5 levels and HBV DNA levels was identified in the HBV-associated chronic infection and HCC groups. Furthermore, SFRP5 levels differentially decreased in patients with HBV-associated diseases, in a manner which was dependent on liver disease status. Compared with patients exhibiting HBV-associated chronic infection, patients with HCC were found to exhibit lower serum SFRP5 levels. The results of the present study indicated that patients with HBV-associated liver infection and HCC exhibited significantly deceased serum SFRP5 levels, which were found to negatively correlate with HBV DNA levels. Serum SFRP5 levels may present a biomarker for the severity of HBV-associated liver infection, and the risk of HCC initiation and progression.
Summary and Recommendations from the National Cancer Institute’s Clinical Trials Planning Meeting on Novel Therapeutics for Non-Muscle Invasive Bladder Cancer

The NCI Bladder Cancer Task Force convened a Clinical Trials Planning Meeting (CTPM) Workshop focused on Novel Therapeutics for Non-Muscle Invasive Bladder Cancer (NMIBC). Meeting attendees included a broad and multi-disciplinary group of clinical and research stakeholders and included leaders from NCI, FDA, National Clinical Trials Network (NCTN), advocacy and the pharmaceutical and biotech industry. The meeting goals and objectives were to: 1) create a collaborative environment in which the greater bladder research community can pursue future optimally designed novel clinical trials focused on the theme of molecular targeted and immune-based therapies in NMIBC; 2) frame the clinical and translational questions that are of highest priority; and 3) develop two clinical trial designs focusing on immunotherapy and molecular targeted therapy. Despite successful development and implementation of large Phase II and Phase III trials in bladder and upper urinary tract cancers, there are no active and accruing trials in the NMIBC space within the NCTN. Disappointingly, there has been only one new FDA approved drug (Valrubicin) in any bladder cancer disease state since 1998. Although genomic-based data for bladder cancer are increasingly available, translating these discoveries into practice changing treatment is still to come. Recently, major efforts in defining the genomic characteristics of NMIBC have been achieved. Aligned with these data is the growing number of targeted therapy agents approved and/or in development in other organ site cancers and the multiple similarities of bladder cancer with molecular subtypes in these other cancers. Additionally, although bladder cancer is one of the more immunogenic tumors, some tumors have the ability to attenuate or eliminate host immune responses. Two trial concepts emerged from the meeting including a window of opportunity trial (Phase 0) testing an FGFR3 inhibitor and a second multi-arm multi-stage trial testing combinations of BCG or radiotherapy and immunomodulatory agents in patients who recur after induction BCG (BCG failure).
Implications of the universal temperature profile for galaxy clusters

We study the X-ray cluster gas density distribution in hydrostatic equilibrium using the universal temperature profile obtained from recent simulations involving only gravitational processes. If this temperature profile is an indicator of the influence of gravitational processes alone on the intracluster medium (ICM), then the comparison of various X-ray parameters expected from this profile and the observed data would point towards any additional physics that may be required. We compare the entropy at 0.1 R 2 0 0 and R 5 0 0 , the scaled entropy profile, the gas fraction at 0.3 R 2 0 0 and the gas fraction profile with recent observations and we discuss the implications of this temperature profile in light of these data. We find that the entropy imparted to the gas from gravitational processes alone is larger than previously thought. The entropy at R 5 0 0 for rich clusters is consistent with the data, whereas the entropy at 0.1 R 2 0 0 is still less than the observed values. We also find that the gas fraction in the inner region of clusters, expected from gravitational processes alone, is smaller than previously thought but larger than the observed data. It does show a trend with the emission-weighted temperature ((T)) as shown by the data. We therefore find that the role of any additional non-gravitational process influencing the physical state of ICM would have to be revised in light of these findings.
Implementation of vision-based real time helipad detection system

This paper presents vision-based helipad detection algorithm and implementation of embedded landing system for an UAV (Unmanned Aerial Vehicle). The helipad detection algorithm includes various image processing processes and feature recognition methods. It is essential for the embedded system that the detection algorithm should be simple and accurate. We propose optimized image processing algorithm and simple morphological algorithm to implement an embedded system for detecting the international standard helipad. First, we perform image preprocessing includes filtering, thresholding and labeling. After image preprocessing, we perform feature extraction of the helipad. Second, the size and position calculation of the detected helipad is performed. Third, the size and position information of helipad is transmitted via communication port. In these processes, we can estimate the position information of the UAV by using the size and the position of helipad in the aerial moving image. In experiment, we use aerial moving image photographed by coaxial rotor helicopter and save the detected helipad to SD-card to demonstrate the accuracy and real time processing capabilities. The experimental results show that proposed embedded system has features of real time and reliable accuracy.
Job Instability and Earnings and Income Consequences: Evidence from SIPP: 1983-1995

Transitory fluctuations in earnings have adverse consequences for the poor because of limited ability to smooth consumption. This paper investigates job instability and its consequences on earnings and income using 5 SIPP panels spanning 1983-1995. The paper discusses results for married men, the standard group for most studies, and for unmarried women, a group with welfare policy significance. The paper first looks at earnings fluctuations measured as a transitory coefficient of variation and then at job turnover. The less educated have greater relative earnings fluctuations and more turnover. For the age group 20-59 there is no apparent trend in instability for any education group. The paper then looks at the earnings and income consequences of both job loss and job changes. The earnings consequences of job change appear to improve for the less educated in the 90s, but there is no trend in income consequences. Family income shows greater relative transitory fluctuation than personal earnings due largely to earnings of other family members.
Spectroscopy of the brightest optical counterparts of X-ray sources in the direction of M 31 and M 33

Context. Recent surveys of the Local Group spiral Galaxies M 31 and M 33 with XMM-Newton yielded a large number of X-ray sources. Aims. As part of the effort to identify and classify the objects responsible for this X-ray emission, we have obtained optical spectra of the brightest optical counterparts of the identified X-ray sources, using the 1.3 m Skinakas Telescope. Most of these objects are foreground star candidates. The purpose of the present study is to confirm this identification and to explore the compatibility between the optical spectral classification and the observed X-ray properties of the sources. Methods. We have obtained optical spectra for the 14 brightest optical counterparts of X-ray sources identified by XMM-Newton in the direction of M 31 and for 21 optical counterparts in the direction of M 33, using the 1.3 m Skinakas telescope in Crete, Greece. Results. All of the M 31 sources and all but one of the M 33 sources were confirmed to be foreground stars, of spectral types between A and M. One of the stars is a late M dwarf with H,, emission, a flare star, also displaying strong X-ray variability. One of the M 33 sources (lying within the D25 ellipse) corresponds to a previously known background galaxy, LEDA 5899.