Miracle-dz/UniFAR-FTUs huggingface dataset:
Challenges faced by learners who live in squatter camps: A case of one primary school in Rustenburg province of South Africa

Despite the increasing awareness of the importance of education worldwide, in South Africa there seem to be very little being done on the learners from low class especially those living in squatter camps. Yet home background is considered to be an essential aspect on the child’s educational achievement. Therefore the principal objective of this paper is to explore those factors that affect the learning of squatter camp learners and how they can be assisted in order to get equal educational access as others. Since the researchers want to find out the opinions, experiences, feelings, beliefs and attitudes of those who live in these squatter camps interpretive qualitative approach was used to analyse data collected through interviews, questionnaires, documentation analysis and observation. Data analysis and collection was done simultaneously for accuracy. The study employed case study design since data were collected from only one squatter camp from which one of the primary schools in Rustenburg draws its students and a sample of 54 participants was used which consisted of teachers, students and parents. Drawing from the findings the research revealed that pupils who live in squatter camps face a lot of challenges which contribute to their low academic performance, which are lack of school requirements such as books and proper uniform, descent accommodation and overcrowding which hinders them from doing their school work properly, land and noise pollution from the environment, parental level of education and anti social behaviours for example drug abuse and crime. The details of the findings are discussed and recommendations for further studies suggested as the paper progresses
Multiobjective Evolutionary Optimization Algorithm for Cognitive Radio Networks

Under Cognitive radio (CR), the Quality of Service (QoS) suffers from many dimensions or metrics of communication quality for improving spectrum utilization. To investigate this issue, this paper develops a methodology based on the multiobjective optimization model with genetic algorithms (GAs). The influence of evolving a radio defined by a chromosome is identified. The Multiobjective Cognitive Radio (MOCR) algorithm from genetically manipulating the chromosomes is proposed. Using adaptive component as an example, the bounds for the maximum benefit is predicted by a proposed model that considers Pareto front. To find a set of parameters that optimize the radio for user’s current needs, several solutions are presented. Simulation results show that MOCR is able to find a comparatively better spread of compromise solutions.
A coupled‐stability index for ENSO

Based on the simple framework of the recharge oscillator for El Niño‐Southern Oscillation (ENSO), this paper describes the formulation of a coupled stability index for the large‐scale tropical ocean‐atmosphere interactions in the equatorial Pacific region. This index, referred to as the Bjerknes (BJ) stability index, takes its negative contributions from the mean upwelling and thermal damping and its positive contributions from the thermocline, the zonal advection, and the Ekman feedbacks. The validity of the BJ stability index formula is tested through a detailed eigen‐analysis of an intermediate‐coupled model, which shows that the BJ stability index captures the dependence of growth rate of the leading coupled ENSO‐like mode on various climate conditions. The general formula of the BJ stability index may be useful for assessing the coupled stability of ENSO and its sensitivity to changes in tropical climate conditions.
Yang-Yang thermometry and momentum distribution of a trapped one-dimensional Bose gas

We describe the use of the exact Yang-Yang solutions for the one-dimensional Bose gas to enable accurate kinetic-energy thermometry based on the root-mean-square width of an experimentally measured momentum distribution. Furthermore, we use the stochastic projected Gross-Pitaevskii theory to provide a quantitative description of the full momentum distribution measurements of Van Amerongen et al. [Phys. Rev. Lett. 100, 090402 (2008)]. We find the fitted temperatures from the stochastic projected Gross-Pitaevskii approach are in excellent agreement with those determined by Yang-Yang kinetic-energy thermometry.
Red Cell Distribution Width in Relation to Incidence of Stroke and Carotid Atherosclerosis: A Population-Based Cohort Study

Background Increased red cell distribution width (RDW) has been related to poor prognosis in patients with cardiovascular disease, and is a predictor of cardiovascular mortality in the general population. The purpose of the present study was to investigate if RDW is associated with increased incidence of stroke and its subtypes in individuals from the general population. Methods Red cell distribution width was measured in 26,879 participants (16,561 women and 10,318 men aged 45–73 years) without history of coronary events or stroke, from the population-based Malmö Diet and Cancer Study. Incidences of total stroke and stroke subtypes over a mean follow-up of 15.2 years were calculated in relation to sex-specific quartiles of RDW. The presence of carotid plaque and intima–media thickness, as assessed by ultrasound, was studied in relation to RDW in a randomly selected subcohort (n = 5,309). Results Incidences of total stroke (n = 1,869) and cerebral infarction (n = 1,544) were both increased in individuals with high RDW. Hazard ratios (HRs) in the highest compared to the lowest quartile were 1.31 for total stroke (95% confidence interval [CI]: 1.11–1.54, p for trend = 0.004) and 1.32 for cerebral infarction (95% CI: 1.10–1.58, p for trend = 0.004) after adjustment for stroke risk factors and hematological parameters. The adjusted HR for intracerebral hemorrhage (n = 230) was 1.44 (95% CI: 0.90–2.30) and the HR for subarachnoid hemorrhage (n = 75) was 0.94 (95% CI: 0.43–2.07), in the highest compared to the lowest quartile of RDW. Red cell distribution width was positively associated with intima–media thickness of the common carotid artery (p for trend = 0.011). Conclusions Red cell distribution width in the highest quartile was associated with increased incidence of total stroke and cerebral infarction. There was no significant association between RDW and incidence of intracerebral or subarachnoid hemorrhage.
Bayesian Analysis of Finite Poisson Mixtures

Finite Poisson mixtures are widely used to model overdispersed data sets for which the simple Poisson distribution is inadequate. Such data sets are very common in real applications. In this paper we investigate Bayesian estimation via MCMC for finite Poisson mixtures and we discuss some computational issues. The related problem of determining the number of components in a mixture is also treated. This problem is of particular interest since it can reveal the number of subpopulations comprising the entire population under study. We model the number of components k as a random quantity having itself a prior probability function and then we apply the Reversible Jump Markov Chain Monte Carlo (Green 1995) to estimate the number of components. A real data example dealing with a financial credit scoring system illustrates our methodology.
Cholesterol Depletion Impairs Vascular Reactivity to Endothelin-1 by Reducing Store-Operated Ca2+ Entry Dependent on TRPC1

Abstract— The reactivity of the vascular wall to endothelin-1 (ET-1) is influenced by cholesterol, which is of possible importance for the progression of atherosclerosis. To elucidate signaling steps affected, the cholesterol acceptor methyl-&bgr;-cyclodextrin (m&bgr;cd, 10 mmol/L) was used to manipulate membrane cholesterol and disrupt caveolae in intact rat arteries. In endothelium-denuded caudal artery, contractile responsiveness to 10 nmol/L ET-1 (mediated by the ETA receptor) was reduced by m&bgr;cd and increased by cholesterol. Neither ligand binding nor colocalization of ETA and caveolin-1 was affected by m&bgr;cd. Ca2+ inflow via store-operated channels after depletion of intracellular Ca2+ stores was reduced in m&bgr;cd-treated caudal arteries, as shown by Mn2+ quench rate and intracellular [Ca2+] response. Expression of TRPC1, 3, and 6 was detected by reverse transcriptase–polymerase chain reaction, and colocalization of TRPC1 with caveolin-1 was reduced by m&bgr;cd, as seen by immunofluorescence. Part of the contractile response to ET-1 was inhibited by Ni2+ (0.5 mmol/L) and by a TRPC1 blocking antibody. In the basilar artery, exhibiting less store-operated channel activity than the caudal artery, ET-1–induced contractions were insensitive to the TRPC1 blocking antibody and to m&bgr;cd. Increased store-operated channel activity in basilar arteries after organ culture correlated with increased sensitivity of ET-1 contraction to m&bgr;cd. These results suggest that cholesterol influences vascular reactivity to ET-1 by affecting the caveolar localization of TRPC1.
Fast view interpolation of stereo images using image gradient and disparity triangulation

The paper proposes a fast view interpolation method based on image gradient and disparity triangulation. The image gradient is used to select the node points for triangulation and each node point is evaluated by its matching errors and cross correspondence of the disparity values. To model the abrupt changes of disparity on the object boundaries, new node points are added along the image gradient direction. In addition, some node points are removed by consideration of unreliable matching conditions. To construct the intermediate-view images, Delaunay triangulation and image warping are performed. The experimental results show that the proposed algorithm is fast and overcomes the drawbacks of previous methods.
MULTI-SCALE ROAD EXTRACTION USING LOCAL AND GLOBAL GROUPING CRITERIA

In this paper we combine two approaches for road extraction. The first approach makes use of multiple scales to detect roads segments and employs local grouping criteria and also context information to extract the road network. This approach is suitable for aerial imagery with a resolution of 0.2–0.5 m. The second approach was designed to extract roads from satellite imagery and can be applied to resolutions of 2–5 m. It fuses lines extracted from different channels for road extraction and exploits especially the connectivity properties of roads, i.e., global network criteria for road extraction. By combining the two approaches we can reduce the effort for selecting appropriate parameters, because both help each other to get rid of some individual deficiencies. In addition, the evaluation of the extracted road network showed significant improvements compared to the results we get by applying each approach on its own.
Toll-Like Receptor 4 Mediates the Antitumor Host Response Induced by a 55-Kilodalton Protein Isolated from Aeginetia indica L., a Parasitic Plant

ABSTRACT A 55-kDa protein named AILb-A, isolated from the seed extract of Aeginetia indica L. , a parasitic plant, induces a Th1-type T-cell response and elicits a marked antitumor effect in tumor-bearing mice. In the present study, we examined the role of Toll-like receptors (TLRs), which have been implicated in pathogen-induced cell signaling, in AILb-A-induced immune responses. In the luciferase assay using a nuclear factor (NF)-κB-dependent reporter plasmid, AILb-A induced NF-κB activation in the cells transfected with TLR4, but not with those transfected with the TLR2 gene, in a dose-dependent manner. TLR4-mediated NF-κB activation induced by AILb-A but not by lipopolysaccharide (LPS) was also observed under serum-free conditions. In in vitro experiments using human peripheral blood mononuclear cells, AILb-A-induced cytokine production was markedly inhibited by anti-TLR4 but not by anti-CD14 antibody, while LPS-induced, TLR4-mediated cytokine production was inhibited by anti-CD14 as well as anti-TLR4 antibodies. Cytokine production, killer cell activities, maturation of dendritic cells, phosphorylation of mitogen-activated protein kinases, and nuclear translocation of interferon-regulatory factor 3 induced by AILb-A were severely impaired in TLR4-deficient but not TLR2-deficient mice. Transfection of TLR4-deficient mouse-derived macrophages with the TLR4 expression plasmid led AILb-A to induce cytokines. Finally, the antitumor effect of AILb-A was also impaired in TLR4-deficient and TLR4-mutated mice. These findings suggest that TLR4 mediates antitumor immunity induced by the plant-derived protein AILb-A.
Spanning Tree Method for Minimum Communication Costs In Grouped Virtual MapReduce Cluster

Today, MapReduce and virtual cluster are sharp swords for this big data and cloud computing era. To combine these two emerging technologies, it brings feasible-scalability, easy-management, fast-deployment and high-efficiency with the system. As every sword has two sides, the I/O bottleneck of virtualization technologies may seriously impacts on the performance of MapReduce cluster which deals with I/O-intensive applications. In this paper, we analyze the combination advantages and disadvantages of virtualization technology of MapReduce cluster. We also analyze the communication model for both of them and build a communication costs model. Then, we propose a novel algorithm of minimum-weight spanning tree to construct a lower communication costs virtual MapReduce cluster. With the help of constructing minimum-weight spanning tree, we find out a method to select local-master and group the cluster. Theoretical simulation and experiment results demonstrate that our method can greatly reduce communication costs. The performance improvement is up to ~40.4% respectively
Software Effort Estimation using Machine Learning Techniques with Robust Confidence Intervals

The precision and reliability of the estimation of the effort of software projects is very important for the competitiveness of software companies. Good estimates play a very important role in the management of software projects. Most methods proposed for effort estimation, including methods based on machine learning, provide only an estimate of the effort for a novel project. In this paper we introduce a method based on machine learning which gives the estimation of the effort together with a confidence interval for it. In our method, we propose to employ robust confidence intervals, which do not depend on the form of probability distribution of the errors in the training set. We report on a number of experiments using two datasets aimed to compare machine learning techniques for software effort estimation and to show that robust confidence intervals can be successfully built.
Defeating Jamming With the Power of Silence: A Game-Theoretic Analysis

The timing channel is a logical communication channel in which information is encoded in the timing between events. Recently, the use of the timing channel has been proposed as a countermeasure to reactive jamming attacks performed by an energy-constrained malicious node. In fact, while a jammer is able to disrupt the information contained in the attacked packets, timing information cannot be jammed, and therefore, timing channels can be exploited to deliver information to the receiver even on a jammed channel. Since the nodes under attack and the jammer have conflicting interests, their interactions can be modeled by means of game theory. Accordingly, in this paper, a game-theoretic model of the interactions between nodes exploiting the timing channel to achieve resilience to jamming attacks and a jammer is derived and analyzed. More specifically, the Nash equilibrium is studied in terms of existence, uniqueness, and convergence under best response dynamics. Furthermore, the case in which the communication nodes set their strategy and the jammer reacts accordingly is modeled and analyzed as a Stackelberg game, by considering both perfect and imperfect knowledge of the jammer's utility function. Extensive numerical results are presented, showing the impact of network parameters on the system performance.
PGCapping: Exploiting power gating for power capping and core lifetime balancing in CMPs

Optimizing the performance of a chip multiprocessor (CMP) within a power cap has recently received a lot of attention. However, most existing solutions rely solely on DVFS, which is anticipated to have only limited actuation ranges in the future. Power gating shuts down idling cores in a CMP, such that more power can be shifted to the cores that run applications for better CMP performance. However, current preliminary studies on integrating the two knobs focus on deciding the power gating and DVFS levels in a tightly coupled fashion, with much less attention given to the direction of decoupled designs. By decoupling the two knobs that may interfere with each other, individual knob management algorithms can be less complex and more efficient to take advantage of the characteristics of different knobs. This paper proposes PGCapping, a decoupled design to integrate power gating with DVFS for CMP power capping. To fully utilize the power headroom that is reserved through power gating, PGCapping enables per-core overclocking on turned-on cores that run sequential applications. However, per-core overclocking may make some cores age much faster than others and thus become the reliability bottleneck in the whole system. Therefore, PGCapping also uses power gating to balance the core lifetimes. Our empirical results on a hardware testbed show that the proposed scheme achieves up to 42.0% better average application performance than five state-of-the-art power capping baselines for realistic multi-core applications, i.e., a mixed group of PARSEC and SPEC CPU2006 benchmarks. Furthermore, our extensive simulation results with real-world traces demonstrate that a lightweight lifetime balancing algorithm (based on power gating) can increase the CMP lifetime by 9.2% on average.
Partnership for Advanced Computing in Europe Massively Parallel Algorithm for Multiple Sequence Alignment Based on Artificial Bee Colony

In silico biological sequence processing is a key task in molecular biology. This scientific area requires powerful computing resources for exploring large sets of biological data. Parallel in silico simulations based on methods and algorithms for analysis of biological data using high-performance distributed computing is essential for accelerating the research and reducing the investment. Multiple sequence alignment is a widely used method for biological sequence processing. The goal of this method is DNA and protein sequences alignment. This paper presents an innovative parallel algorithm MSA_BG for multiple alignment of biological sequences that is highly scalable and locality aware. The MSA_BG algorithm we describe is iterative and is based on the concept of Artificial Bee Colony metaheuristics and the concept of algorithmic and architectural spaces correlation. The metaphor of the ABC metaheuristics has been constructed and the functionalities of the agents have been defined. The conceptual parallel model of computation has been designed and the algorithmic framework of the designed parallel algorithm constructed. Experimental simulations on the basis of parallel implementation of MSA_BG algorithm for multiple sequences alignment on heterogeneouc compact computer cluster and supercomputer BlueGene/P have been carried out for the case study of the influenza virus variability investigation. The performance estimation and profiling analyses have shown that the parallel system is well balanced both in respect to the workload and machine size.
Effective Analysis of C Programs by Rewriting Variability

Context. Variability-intensive programs (program families) appear in many application areas and for many reasons today. Different family members, called variants, are derived by switching statically configurable options (features) on and off, while reuse of the common code is maximized. Inquiry. Verification of program families is challenging since the number of variants is exponential in the number of features. Existing single-program analysis and verification tools cannot be applied directly to program families, and designing and implementing the corresponding variability-aware versions is tedious and laborious. Approach. In this work, we propose a range of variability-related transformations for translating program families into single programs by replacing compile-time variability with run-time variability (non-determinism). The obtained transformed programs can be subsequently analyzed using the conventional off- the-shelf single-program analysis tools such as type checkers, symbolic executors, model checkers, and static analyzers. Knowledge. Our variability-related transformations are outcome-preserving, which means that the relation between the outcomes in the transformed single program and the union of outcomes of all variants derived from the original program family is equality. Grounding. We show our transformation rules and their correctness with respect to a minimal core imperative language IMP. Then, we discuss our experience of implementing and using the transformations for efficient and effective analysis and verification of real-world C program families. Importance. We report some interesting variability-related bugs that we discovered using various state-of-the-art single-program C verification tools, such as Frama-C, Clang, LLBMC.
A kaleidoscopic approach to surround geometry and reflectance acquisition

We describe a system for acquiring reflectance fields of objects without moving parts and without a massively parallel hardware setup. Our system consists of a set of planar mirrors which serve to multiply a single camera and a single projector into a multitude of virtual counterparts. Using this arrangement, we can acquire reflectance fields with an average angular sampling rate of about 120+ view/light pairs per surface point. The mirror system allows for freely programmable illumination with full directional coverage. We employ this setup to realize a 3D acquisition system that employs structured illumination to capture the unknown object geometry, in addition to dense reflectance sampling. On the software side, we combine state-of-the-art 3D reconstruction algorithms with a reflectance sharing technique based on non-negative matrix factorization in order to reconstruct a joint model of geometry and reflectance. We demonstrate for a number of test scenes that the kaleidoscopic approach can acquire complex reflectance properties faithfully. The main limitation is that the multiplexing approach limits the attainable spatial resolution, trading it off for improved directional coverage.
Struggling for meaning in the Dutch infrastructure sector: An interpretative analysis of political-executive decision making practices concerning infrastructure development in the Netherlands

An interpretative analysis of political-executive decision making practices concerning infrastructure development in the Netherlands Decision-making concerning future infrastructural developments in the Netherlands is often perceived as problematic, taking too much time and producing suboptimal outcomes. These problems are partly ascribed to the practices of Ministers, Provincial Delegates and Alderpersons during infrastructural decision-making. However, the actual decision-making practices of these political-executives remain enigmatic and difficult to grasp. This study develops an alternative view on these practices based on a meaning making perspective. Political-executives tell powerful stories which frame infrastructural developments according to their own interests. Together they have to negotiate a mutual story which gives common meaning to a potential development, enabling them to make a legitimate decision.