Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Enhancement Architecture of VoIP Applications in Multiprotocol Label Switching Networks

In recent years, Voice over IP (VoIP) has impacted global telecommunications and networking tremendously. Traffic engineering and Quality of Service (QoS) guarantees for VoIP services pose a challenge for network researchers and designers. The repeated use of Internet Protocol shortest path towards the same destination may lead to unbalanced traffic situations and degraded network performance. Therefore, load balancing and link utilization become the critical functions in Internet Protocol routing for providing Quality of Service assurance for VoIP application. The aim of this work is to employ Multiprotocol Label Switching Network as a traffic engineering tool to enhance the QoS for VoIP applications. To achieve this, an effective Multiprotocol Label Switching Network load balancing architecture is developed that classifies the Internet traffic flows, routes the flows into multiple paths. Flow arrival rate, packet loss rate and delay are measured and taken as the input parameters and compared with the threshold values to identify the VoIP flow. Network load status is calculated by estimating the average buffer occupancy value and multipath routing is triggered when the network load is high to enhance the QoS. The investigated performance measures like throughput, delay and packet loss are reported to show the efficiency of the proposed technique for effective VoIP flows.
Detecting the Defective Nodes in Wireless Sensor Networks Using the Nonlinear Consensus of Median

A local algorithm is proposed and analyzed to monitor the health of a wireless sensor network. Our previous algorithm, the average consensus-based algorithm, works based on the mean estimator. Therefore, it fails to detect the defective nodes in the presence of large outliers. However, the algorithm proposed in this paper works based on the median estimator, and is able to detect the defective nodes, even in the presence of a large number of outliers. To calculate the median in a distributed scheme, a nonlinear consensus algorithm is proposed. By applying the nonlinear consensus algorithm, all the nodes in the network compute the median iteratively, using only local communications. We show that the proposed algorithm is more robust than the previous algorithms in this area and outperforms all of them. The simulation results verify the effectiveness of the proposed algorithm in calculating the median in a distributed scheme and in detecting the defective nodes in the network.
Gas flux to the atmosphere from mud volcanoes in eastern Romania

Gas flux measurements have for the first time been taken from vents and soil of eastern Romania mud volcanoes, the largest geological structures in Europe releasing methane into the atmosphere. In the quiescent phase, the methane emission from single vents is up to 28 t yr−1. Diffuse soil microseepage is of the order of 102−105 mg m−2 day−1. A total output of at least 1200 tonnes of CH4 per year can be conservatively estimated over the area investigated alone (∼ 2.3 km2). Helium fluxes are up to five orders of magnitude higher than the average flux in a stable continental area, pointing to a close link between mud volcanoes and crustal degassing through faults crossing the deep hydrocarbon reservoirs. These data represent a key contribution towards refining global CH4‐emission estimates, which indicate mud volcanoes as a significant and unavoidable source of greenhouse gases for the atmosphere.
Numerical analysis and computations of a high accuracy time relaxation fluid flow model

We present a numerical study based on continuous finite element analysis for a time relaxation regularization of Navier–Stokes equations. This regularization is based on filtering and deconvolution. We study the convergence of the regularized equations using a fully discretized filter and deconvolution algorithm. Velocity and pressure error estimates and the L 2 Aubin–Nitsche lift technique are proved for the equilibrium problem, and this analysis is accompanied by the velocity error estimate for the time-dependent problem, too. Thus, optimal error estimates in L 2 and H 1 norms are derived and followed by their computational verification. Also, computational results of the vortex street are presented for the two-dimensional cylinder benchmark flow problem. Maximum drag and lift coefficients and difference in pressure between the front and back of the cylinder at the final time were investigated as well, showing that the time relaxation regularization can attain the benchmark values.
Oseba: Optimization for Selective Bulk Analysis in Big Data Processing

Selective bulk analyses, such as statistical learning on temporal/spatial data, are fundamental to a wide range of contemporary data analysis. However, with the increasingly larger data-sets, such as weather data and marketing transactions, the data organization/access becomes more challenging in selective bulk data processing with the use of current big data processing frameworks such as Spark or keyvalue stores. In this paper, we propose a method to optimize selective bulk analysis in big data processing and referred to as Oseba. Oseba maintains a super index for the data organization in memory to support fast lookup through targeting the data involved with each selective analysis program. Oseba is able to save memory as well as computation in comparison to the default data processing frameworks.
The Complexity and Effectiveness of Prediction Algorithms

Abstract The problem of predicting an arbitrary sequence x 1 x 2 x 3 · · · is considered with x t + 1 being predicted from an analysis of the word x 1 x 2 · · · x t . There are no presumptions concerning the probability structure on this process. The relation between prediction effectiveness and Kolmogorov complexity is established. Then the Hausdorff dimension of sets of sequences for which effective methods of prediction exist is estimated. The prediction method which is asymptotically superior to other arbitrary ones realized by finite automata is constructed.
Resources and infrastructure for the delivery of antiretroviral therapy at primary health care facilities in the Free State Province, South Africa

There are concerns as to whether South Africa's public health system has sufficient resources, human and otherwise, to ensure universal access to antiretroviral treatment (ART). We report on public sector implementation of the Comprehensive Care Management and Treatment (CCMT) programme in the Free State Province, South Africa, in particular whether the primary health care (PHC) infrastructure was able to mobilise the necessary inputs to effectively provide ART, without undermining other services within facilities. A longitudinal study was conducted of the first 16 PHC facilities accredited to provide ART in the province. The facilities were visited on three occasions over 2 years, involving both structured and open-ended interviews with professional and lay staff, and observations of available resources. The resources assessed were staffing, space, essential equipment, drug supplies and laboratory systems. Approximately one-fifth (20%) of professional nurses were allocated to the CCMT programme in the facilities, although the overall number of professional nurses increased by only 14%. This process resulted in some displacement of professional nurses towards the CCMT Programme away from other services in the facilities. However, this could have been partially compensated for by task shifting towards community health workers and the appointment of additional support staff. Staff were largely positive about the programme. Drug supplies, availability of equipment and laboratory systems, although good at the baseline, improved further over the period of observation. The lack of adequate space to accommodate the new programme was a frequently reported problem. Overall, our assessment is that the PHC infrastructure in the Free State's public health system is capable of implementing and benefiting from the CCMT programme. Nevertheless, constraints in the availability of professional staff threaten future implementation of both the CCMT and other PHC programmes.
The Concept of Standardized Ileal Amino Acid Digestibilities: Principles and Application in Feed Ingredients for Piglets

In this review, the terminology that is used to describe ileal amino acid (AA) digestibilities in piglet feed ingredients is defined. If one accepts that the determination of AA digestibilities should be based on the ileal analysis method, one should consider that ileal digesta contains variable amounts of endogenous crude protein (CP), which originates mainly from digestive secretions, sloughed-off epithelial cells and mucins. The ileal endogenous CP and AA losses are separated into basal ileal endogenous CP and AA losses (IAAL B ), which are not influenced by the feed ingredient composition, and specific ileal endogenous CP and AA losses (IAAL S ), which are induced by feed ingredient characteristics such as level and type of fiber and anti-nutritional factors (ANF). Depending how ileal endogenous CP and AA losses are considered in the measurement of CP and AA digestibilities, digestibility values are expressed as apparent (AID), standardized (SID), or true (TID) ileal digestibilities of CP and AA. The main concern associated with the use of AID values in diet formulation for pigs is that they are not additive in mixtures of feed ingredients. Consequently, the concept of standardized ileal CP and AA digestibilities was introduced by correcting AID values for basal ileal endogenous CP and AA losses (IAAL B ). The correction for both IAAL B and IAAL s yields TID values, however, routine procedures to measure IAAL s are not yet available. In principle, SID values should be preferred, because they represent the fundamental properties of the feed ingredient. There exist only few reports on SID of CP and AA in feedstuffs frequently used in piglet nutrition. These include soybeans (SB), soybean meal (SBM), soy proteins (SP), soy protein concentrate (SPC), soy protein isolate (SPI), corn gluten (CG), wheat gluten (WG), pea protein (PeaP), potato protein (PotP), fish meal (FM) and whey proteins (WP), but the results obtained are inconsistent. Differences in SID values within feed ingredients may, at least in part, be attributed to different processing conditions or inherent differences of the assay feed ingredients. Moreover, there is some evidence that the determination of SID values and IAAL B in piglets may be confounded by the dietary CP level of the assay diet, age and (or) body weight (BW), the level of feed intake or the methodological approach used to determine IAAL B .
A Computer-Based Screening Method for Distress in Patients With Multiple Sclerosis: A Feasibility Study

Background In multiple sclerosis (MS) patients, symptoms of anxiety, depression, pain, and cognitive impairment are highly prevalent and contribute to lower wellbeing. As these physical and psychological symptoms of distress often stay unnoticed, regular screening could offer possibilities to identify and refer impaired patients to appropriate care. Objective The aim of our study was to pilot a new computer-based method in 43 MS patients to efficiently screen for a variety of psychological and physical symptoms of distress. Methods Data on feasibility and psychological and physical distress (anxiety, depression, fatigue, physical disability, cognitive functioning) were collected via a touch screen computer. Referral to psychosocial care and rehabilitation was retrospectively checked. Results The results demonstrated that most patients (35/40, 88%) considered the screening meaningful and the system easily usable (37/40, 93%). Average completion time of the screening was below 8 minutes. Many patients (35/40, 88%) had elevated distress levels, of whom the majority was referred. Conclusions These findings imply that computer-based screening for MS-related distress incorporated in clinical care is feasible and aids to identify psychological or physical needs. A randomized controlled trial with follow-up should address whether this screening method could be more effective than routine care, and whether it can improve costs and efficiency of care.
Polish Household Consumption of Tobacco and Alcohol: A Censored System

The addictive nature of tobacco and alcohol suggests that it is more appropriate to model these consumption as a system. We expand Heckman’s sample selection model into a censored system (or multivariate sample selection model) to analyze household tobacco and alcohol consumption. We use a pooled cross sectional data of 77,043 observations from Polish Household Survey data in the period of 2005 to 2008 and apply full information maximum likelihood estimation. Empirical investigation indicates that the decisions to smoke and drink as well as their expenditure levels are indeed, respectively, positively correlated. We examine the effects of demographic, socio-economic factors and outmigration, a special issue in Poland, on the consumption decisions and expenditure on tobacco and alcohol. Findings provide insights for the reduction and prevention of tobacco and alcohol use.
Heuristic Procedure for the Assembly Line Balancing Problem With Postural Load Smoothness

This paper presents a heuristic procedure for assigning assembly tasks to workstations where both productivity and ergonomics issues are considered concurrently. The procedure uses Kilbridge and Wester’s algorithm to obtain an initial task-workstation assignment solution which minimizes the balance delay of an assembly line. A task reassignment algorithm was applied to improve the initial solution by exchanging assembly tasks, which smooth postural load among workers, between workstations. A composite index of variation was used to measure the effectiveness of the task-workstation assignment solution. On the basis of clothes assembling, it was found that the task-workstation assignment solution with a minimum composite index of variation can be obtained with relatively equal weights in balance delay and postural load.
Cognitive Brain Mapping for Better or Worse

Cognitive brain mapping is a neuroscience fad, with hundreds of reports published each month. Such popularity requires careful attention to experimental design and data analysis in order to minimize false findings. In my view, cognitive brain mapping consists of procedures that allow such troublesome items as data-dredging and confirmation bias to affect study outcomes. This article discusses these issues and makes suggestions for enhancing the validity and reliability of the findings.
Advanced (Measurement) Applications of Curriculum-Based Measurement in Reading

The purpose of this article is to provide a commentary on the current state of several measurement issues pertaining to curriculum-based measures of reading (R-CBM1). We begin by providing an overview of the utility of R-CBM, followed by a presentation of five specific measurements considerations: (a) the reliability of R-CBM oral reading fluency (ORF), (b) issues pertaining to form effects, (c) the generalizability of scores from R-CBM, (d) measurement error, and (e) linearity of growth in R-CBM. We then conclude with a presentation of the purpose for this issue and broadly introduce the articles in the special issue. Because ORF is one of the most common measures of R-CBM, much of the review is focused on this particular type of assessment; however, the issues presented extend to other assessments of R-CBM.
Poly(ADP‐ribose)polymerase activity is reduced in circulating mononuclear cells from type 2 diabetic patients

Poly(ADP‐ribose)polymerase (PARP‐1), a nuclear enzyme activated by DNA strand breaks, is involved in DNA repair, aging, inflammation, and neoplastic transformation. In diabetes, reactive oxygen and nitrogen species occurring in response to hyperglycemia cause DNA damages and PARP‐1 activation. Because circulating mononuclear cells (MNCs) are involved in inflammation mechanisms, these cells were chosen as the experimental model to evaluate PARP‐1 levels and activity in patients with type 2 diabetes. MNCs were isolated from 25 diabetic patients (18 M, 7 F, age, 63.5 ± 10.2 years, disease duration 17.7 ± 8.2 years) and 11 age and sex matched healthy controls. PARP‐1 expression and activity were analyzed by semi‐quantitative PCR, Western and activity blot, and immunofluorescence microscopy. PARP‐1‐mRNA expression was increased in MNCs from all diabetic patients versus controls (P < 0.01), whereas PARP‐1 content and activity were significantly lower in diabetic patients (P < 0.0001). To verify whether low PARP‐1 levels and activity were due to a proteolytic effect of caspase‐3 like, the latter activation was measured by a fluorimetric assay. Caspase‐3 activity in MNCs was significantly higher in diabetic patients versus control subjects (P < 0.0001). The different PARP‐1 behavior in MNCs from patients with type 2 diabetes could therefore be responsible for the abnormal inflammation and infection responses in diabetes. © 2005 Wiley‐Liss, Inc.
Study design for genetic analysis in the Jackson Heart Study.

OBJECTIVE This paper describes the preparation of genetic materials and the recruitment and initial characterization of a nested Family Study within the Jackson Heart Study (JHS) METHODS: Genomic DNA was prepared from all consenting JHS participants. In addition, family members of a subset of JHS participants were recruited to the JHS Family Study to allow heritability and linkage analyses and family-based association studies. Family Study participants completed the same questionnaires, measures, and procedures as all other JHS participants and provided blood samples for lymphocyte cryopreservation and transformation. RESULTS DNA samples were obtained from 4726 JHS participants, including 1499 members of 291 families. In the family cohort, estimated heritabilities of body mass index, selected lipid levels, and blood pressure are highly significant, supporting the validity of the sample. DISCUSSION The JHS data and genetic materials (DNA and cryopreserved cells) offer valuable opportunities to identify susceptibility alleles for common complex diseases by positional and candidate gene approaches.
Random forest FLAIR reconstruction from T1, T2, and PD-weighted MRI

Fluid Attenuated Inversion Recovery (FLAIR) is a commonly acquired pulse sequence for multiple sclerosis (MS) patients. MS white matter lesions appear hyperintense in FLAIR images and have excellent contrast with the surrounding tissue. Hence, FLAIR images are commonly used in automated lesion segmentation algorithms to easily and quickly delineate the lesions. This expedites the lesion load computation and correlation with disease progression. Unfortunately for numerous reasons the acquired FLAIR images can be of a poor quality and suffer from various artifacts. In the most extreme cases the data is absent, which poses a problem when consistently processing a large data set. We propose to fill in this gap by reconstructing a FLAIR image given the corresponding T1-weighted, T2-weighted, and PD-weighted images of the same subject using random forest regression. We show that the images we produce are similar to true high quality FLAIR images and also provide a good surrogate for tissue segmentation.
Molecular and Biochemical Characterization of CTX-M-131 , a Natural Asp 240 Gly Variant Derived from CTX-M-2 , Produced by a Providencia rettgeri Clinical Strain in São Paulo , Brazil

CTX-M-131 is a natural Asp240Gly variant from the CTX-M-2 group detected in a Providencia rettgeri clinical strain from Brazil. Molecular analysis showed that blaCTX-M-131 was inserted in a complex class 1 integron harbored by a 112-kb plasmid, which has not been previously described as a platform for CTX-M-encoding genes with the Asp240Gly mutation. Steady-state kinetic parameters showed that the enzyme has a typical cefotaximase catalytic profile and an enhanced activity against ceftazidime.
Detection of unhealthy region of plant leaves and classification of plant leaf diseases using texture features

P lant diseases have turned into a dilemma as it can cause significant reduction in both quality and quantity of agricultural products. Automatic detection of plant diseases is an essential research topic as it may prove benefits in monitoring large fields of crops, and thus automatically detect the symptoms of diseases as soon as they appear on plant leaves. The proposed system is a software solution for automatic detection and classification of plant leaf diseases. The developed processing scheme consists of four main steps, first a color transformation structure for the input RGB image is created, then the green pixels are masked and removed using specific threshold value followed by segmentation process, the texture statistics are computed for the useful segments, finally the extracted features are passed through the classifier. The proposed algorithm’s efficiency can successfully detect and classify the examined diseases with an accuracy of 94%. Experimental results on a database of about 500 plant leaves confirm the robustness of the proposed approach. Keywords: HSI, c olor c o-occurrence m atrix, t exture, SVM, p lant leaf diseases
Functional Diversification of Acyl-Coenzyme A Oxidases in Jasmonic Acid Biosynthesis and Action1[W][OA]

The biosynthesis of jasmonic acid (JA) in plant peroxisomes requires the action of acyl-coenzyme A oxidase (ACX). Among the five expressed members (ACX1–5) of the ACX gene family in Arabidopsis (Arabidopsis thaliana), only ACX1 is known to serve a role in JA production. Here, we used transgenic promoter-reporter lines to show that ACX1 is highly expressed in mature and germinating pollen, stem epidermal cells, and other tissues in which jasmonate-signaled processes occur. Wound-induced JA accumulation was reduced in a mutant that is defective in ACX1 and was abolished in a mutant that is impaired in both ACX1 and its closely related paralog, ACX5. The severe JA deficiency in acx1/5 double mutants was accompanied by decreased resistance to the leaf-eating insect Trichoplusia ni. The double mutant also showed reduced pollen viability and fecundity. Treatment of acx1/5 plants with JA restored both protection against T. ni larvae and normal seed set. Unexpectedly, acx1/5 plants accumulated JA in response to infection by the necrotrophic fungal pathogen Alternaria brassicicola. In contrast to mutants that are impaired in jasmonate perception or early steps of the JA biosynthetic pathway, acx1/5 plants maintained resistance to A. brassicicola infection. These results indicate that ACX1/5-mediated JA synthesis is essential for resistance to chewing insects and male reproductive function and further suggest that other ACX isozymes contribute to JA production in response to A. brassicicola challenge. Thus, different types of biotic stress may induce JA synthesis via distinct enzymatic routes.
Neuromorophic vision sensing and processing

Conventional machine vision faces a fundamental latency-power tradeoff, where decreasing latency means increasing frame rate and power consumption. The communication by spikes in the brain provides the inspiration for developments of event-based vision sensors and processing, which could avoid this tradeoff entirely. This paper provides a personal perspective on developments of event-based vision sensors, algorithms, and applications over the period 2002–2016.