Miracle-dz/UniFAR-FTUs huggingface dataset:
A fair packet scheduler to support QoS in HSDPA

Only best-effort traffic was supported by traditional packet switching networks, but newer applications need network services that allow an end-client to transport data with performance guarantees. The choice of packet-scheduling algorithm used at switching nodes is crucial in providing Quality of Service (QoS). This paper proposes a downlink packet scheduling algorithm for QoS provisioning in High Speed Downlink Packet Access (HSDPA) based UMTS networks. In HSDPA, a single logical channel is shared amongst multiple contending users. Besides better link utilization, scheduling disciplines seek to achieve fair allocation of this shared resource. However, these two criteria can potentially be in conflict. The scheduling algorithm proposed in this paper, Wireless Fair High Speed Scheduling, addresses this conflict. The basic idea is to allocate the wireless channel fairly amongst users, even during short time scales, according to their data rate requirements. Simulation results show that the proposed scheduling algorithm provides better link utilization, as well as long-term and short-term fairness amongst users, even under heavy load conditions.
A supervised machine learning algorithm for arrhythmia analysis

A new machine learning algorithm for the diagnosis of cardiac arrhythmia from standard 12 lead ECG recordings is presented. The algorithm is called VF15 for Voting Feature Intervals. VF15 is a supervised and inductive learning algorithm for inducing classification knowledge from examples. The input to VF15 is a training set of records. Each record contains clinical measurements, from ECG signals and some other information such as sex, age, and weight, along with the decision of an expert cardiologist. The knowledge representation is based on a recent technique called Feature Intervals, where a concept is represented by the projections of the training cases on each feature separately. Classification in VF15 is based on a majority voting among the class predictions made by each feature separately. The comparison of the VF15 algorithm indicates that it outperforms other standard algorithms such as Naive Bayesian and Nearest Neighbor classifiers.
Temporal lobe cortical pathology and inhibitory GABA interneuron cell loss are associated with seizures in multiple sclerosis

Background: Seizures are recognised in multiple sclerosis (MS), but their true incidence and the mechanism by which they are associated with MS is unclear. Objective: The objective of this paper is to determine the lifetime frequency of seizures in the United Kingdom MS Tissue Bank (UKMSTB) population and any pathological features associated with seizures. Methods: We evaluated 255 individuals from the UKMSTB. A subset underwent analysis of cortical thickness, grey matter lesion (GML) (type and number) and cortical neuronal numbers (total and GABAergic). Results: A total of 37/255 patients had seizures (14.5% lifetime incidence); in 47% they were associated with concurrent infection. In those with seizures, death and wheelchair use occurred earlier and in 59% seizures developed after 15 years of disease. Seizures were associated with Type 1 GMLs and reduced cortical thickness in the middle temporal gyrus. Localised selective GABAergic interneuron loss in layers IV and VI was related to GMLs but was not explained by the presence of inflammation or by mitochondrial dysfunction within Type I GMLs. Conclusion: We confirm that seizure frequency rises in MS. Type I GMLs in the temporal lobe underlie a loss of inhibitory interneurons in cortical layers IV and VI and these changes could together with concurrent infection enhance susceptibility to seizures.
Routing on spatiotemporal networks without global knowledge

The formulation of most shortest-path problems makes two simplifying assumptions: (1) the edge weights are deterministic, and (2) global knowledge of the network is available. I develop a decentralised routing algorithm providing en-route guidance for travellers without global knowledge on spatial networks with stochastic edge weights. The algorithm guides travellers using an estimation function that gauges cumulative arrival probability distributions based on the distance between nodes. The estimation function carries a notion of proximity between nodes and enables routing without global knowledge. I develop a new criterion to discriminate among these distributions and compare decentralised algorithms with centralised ones.
The Hand Sees Visual Periphery Better Than the Eye: Motor-Dependent Visual Motion Analyses

Information pertaining to visual motion is used in the brain not only for conscious perception but also for various kinds of motor controls. In contrast to the increasing amount of evidence supporting the dissociation of visual processing for action versus perception, it is less clear whether the analysis of visual input is shared for characterizing various motor outputs, which require different kinds of interactions with environments. Here we show that, in human visuomotor control, motion analysis for quick hand control is distinct from that for quick eye control in terms of spatiotemporal analysis and spatial integration. The amplitudes of implicit and quick hand and eye responses induced by visual motion stimuli differently varied with stimulus size and pattern smoothness (e.g., spatial frequency). Surprisingly, the hand response did not decrease even when the visual motion with a coarse pattern was mostly occluded over the visual center, whereas the eye response markedly decreased. Since these contrasts cannot be ascribed to any difference in motor dynamics, they clearly indicate different spatial integration of visual motion for the individual motor systems. Going against the overly unified hierarchical view of visual analysis, our data suggest that visual motion analyses are separately tailored from early levels to individual motor modalities. Namely, the hand and eyes see the external world differently.
Don't Blink! Evaluating Training Paradigms for Overcoming the Attentional Blink

A lot of people show a decline in performance when they have to report a second target stimulus in a stream of distractor stimuli. Curiously, this decline only happens when the second target appears approximately 200-500ms after the first target. Recently, Choi, Chang, Shibata, Sasaki, and Watanabe (2012) have shown that a short, one-hour training can eliminate this “attentional blink”. Up to now, it is still unclear why this training works. In this paper, we have evaluated a range of different training paradigms to test several hypotheses about the mechanism behind the reduction of the attentional blink. Our results show that none of these training paradigms have a large training effect when administered in isolation. The training by Choi et al. (2012) outperforms them all. The most likely explanation for this effect are temporal expectations relative to the first target.
Playing for real: designing alternate reality games for teenagers in learning contexts

An Alternate Reality Game (ARG) is a form of transmedia storytelling that engages players in scavenger hunt-like missions to collectively uncover, interpret, and reassemble the fragments of a story that is distributed across multiple media, platforms, and locations. ARGs are participatory experiences, because players have a central role in reconstructing the storyline. Furthermore, players interact with the game as themselves, not via avatars. Although transmedia formats like ARGs have garnered increasing attention in entertainment and education, most have been targeted for adults 18 and older. Few studies have explored the design process of education-based ARGs for children. In this paper, we detail the design and implementation of an ARG for middle school students (13--15 years old). We describe the strategies we used to distribute story elements across various media and to encourage players to participate in an authentic inquiry process. We found that a "protagonist by proxy", or in-game character with whom players related closely, served as a strong motivator and a model for positive participation. We highlight student interactions and offer insights for designers who implement ARGs and similar immersive learning experiences.
Constructing educational quality in the Arab region: a bottom-up critique of regional educational governance

ABSTRACT The article challenges the deficit view in which education in the Arab region is portrayed by examining the process of educational regionalisation. It takes as its case study the Arab Regional Agenda for Improving Educational Quality in order to explore the construction of an educational quality space that uses data as a governance model. Drawing on critical theory and evidence collected from 70 interviews, I argue that such approaches promote globalised versions of what quality education means remaining blind to context. I suggest that improving educational quality in the region entails creating responsive approaches grounded in political and socio-economic contexts.
Hemagglutination and proteoglycan binding by the Lyme disease spirochete, Borrelia burgdorferi

The ability of the Lyme disease spirochete to attach to host components may contribute to its ability to infect diverse tissues. We present evidence that the Lyme disease spirochete expresses a lectin activity that promotes agglutination of erythrocytes and bacterial attachment to glycosaminoglycans. Among a diverse collection of 21 strains of Lyme disease spirochete, hemagglutinating activity was easily detected in all but 3 strains, and these three strains were noninfectious. The ability to agglutinate erythrocytes was associated with the ability of the spirochete to bind to the sulfated polysaccharide dextran sulfate and to mammalian cells. Soluble dextran sulfate was a potent inhibitor of both hemagglutination and attachment to mammalian cells, while dextran had no effect on either activity, suggesting that dextran sulfate may inhibit attachment by mimicking host cell glycosaminoglycans. Consistent with this, the spirochete bound to immobilized heparin, and soluble heparin inhibited bacterial adhesion to mammalian cells. The bacterium did not bind efficiently to Vero cells treated with heparinase or heparitinase or to mutant CHO cell lines that are deficient in proteoglycan synthesis. Sulfation of glycosaminoglycans was critical for efficient bacterial recognition, as Vero cells treated with an inhibitor of sulfation, or a mutant CHO cell line that produces undersulfated heparan sulfate, did not mediate maximal spirochetal binding. Binding of the spirochete to extracellular matrix also appeared to be dependent upon this attachment pathway. These findings suggest that a glycosaminoglycan-binding activity which can be detected by hemagglutination contributes to the attachment of the Lyme disease spirochete to host cells and matrix.
Surface Patches from Unorganized Space Curves

Recent 3D sketch tools produce networks of three‐space curves that suggest the contours of shapes. The shapes may be non‐manifold, closed three‐dimensional, open two‐dimensional, or mixed. We describe a system that automatically generates intuitively appealing piecewise‐smooth surfaces from such a curve network, and an intelligent user interface for modifying the automatically chosen surface patches. Both the automatic and the semi‐automatic parts of the system use a linear algebra representation of the set of surface patches to track the topology. On complicated inputs from ILoveSketch [ BBS08 ], our system allows the user to build the desired surface with just a few mouse‐clicks.
The Association between Individual SNPs or Haplotypes of Matrix Metalloproteinase 1 and Gastric Cancer Susceptibility, Progression and Prognosis

Background The single nucleotide polymorphisms (SNPs) in matrix metalloproteinase 1(MMP-1)play important roles in some cancers. This study examined the associations between individual SNPs or haplotypes in MMP-1 and susceptibility, clinicopathological parameters and prognosis of gastric cancer in a large sample of the Han population in northern China. Methods In this case–controlled study, there were 404 patients with gastric cancer and 404 healthy controls. Seven SNPs were genotyped using the MALDI-TOF MS system. Then, SPSS software, Haploview 4.2 software, Haplo.states software and THEsias software were used to estimate the association between individual SNPs or haplotypes of MMP-1 and gastric cancer susceptibility, progression and prognosis. Results Among seven SNPs, there were no individual SNPs correlated to gastric cancer risk. Moreover, only the rs470206 genotype had a correlation with histologic grades, and the patients with GA/AA had well cell differentiation compared to the patients with genotype GG (OR=0.573; 95%CI: 0.353–0.929; P=0.023). Then, we constructed a four-marker haplotype block that contained 4 common haplotypes: TCCG, GCCG, TTCG and TTTA. However, all four common haplotypes had no correlation with gastric cancer risk and we did not find any relationship between these haplotypes and clinicopathological parameters in gastric cancer. Furthermore, neither individual SNPs nor haplotypes had an association with the survival of patients with gastric cancer. Conclusions This study evaluated polymorphisms of the MMP-1 gene in gastric cancer with a MALDI-TOF MS method in a large northern Chinese case-controlled cohort. Our results indicated that these seven SNPs of MMP-1 might not be useful as significant markers to predict gastric cancer susceptibility, progression or prognosis, at least in the Han population in northern China.
A CDMA Data Measurement and Analysis Tool

We present DQoS (Data Quality-of-Service), a tool for measuring and analyzing CDMA data services. For a wireless connection, DQoS collects traces at its two endpoints and at multiple layers including application, IP, TCP, PPP and physical layers. It then synchronizes these traces and aggregates the information to produce graphical plots that illustrate throughput, latencies, protocol (e.g. TCP) behavior and bad events. DQoS provides a comprehensive view of the connection performance from an end-to-end perspective. It allows us to correlate behaviors at different network layers and troubleshoot potential problems. We have been using DQoS internally at Lucent Technologies for testing and performance validation. DQoS requires no instrumentation internally within the wireless network. Therefore, it can also be used for comparing different CDMA technologies (e.g. EVDO vs UMTS) as well as networks operated by different service providers.
Vision based Vehicle Tracking using a high angle camera

A vehicle tracking and grouping algorithm is presented in this work using Lukas-Kanade Tracking technique. Every frame of the sequence is downsampled to improve efficiency. A section of the highway is marked to establish a detection zone where the detection and tracking of the features take place. For every frame a background subtraction is done and only the foreground pixels inside the detection zone are kept; features will be specified only for these pixels, grouped and tracked until the vehicle leaves the detection zone, we also store the amount of vehicles that had entered the zone. Feature points computed in the downsampled frames are later displayed in the original size images of the sequence.
All That Glisters is Not Gold - Genes, Transgenesis and Behavior

1. Genetic background. ES cells are most commonly made from mouse strains (such as 129) that harbour a mutation or mutations, so far unknown, that permit the outgrowth and proliferation of cells from the early embryo. ES cells are reported to have been prepared from other strains, including BL/6, but these have not been widely used. There are also potential problems of strain typing that could confound the issue (Simpson et al., 1997). Because 129 mice perform poorly on a variety of tests, transgenic mice are routinely backcrossed to a more robust strain (e.g. BL/6). This presents a problem because the control mice will tend to have the BL/6 allele (and flanking BL/6 genes) where modified or knockout mice will contain the 129 allele. This may explain, in part, irreproducibility of some transgenic experiments (Routtenberg, 1995; Gerlai, 1996; Lathe, 1997).
Security Risk Management by Qualitative Vulnerability Analysis

Security risk assessment in the requirements phase is challenging because risk factors, such as probability and damage of attacks, are not always numerically measurable or available in the early phases of development. This makes the selection of proper security solutions problematic because mitigating impacts and side-effects of solutions are not often quantifiable. In the early development phases, analysts need to assess risks in the absence of numerical measures or deal with a mixture of quantitative and qualitative data. We propose a risk analysis process which intertwines security requirements engineering with a vulnerability-centric and qualitative risk analysis method. The proposed method is qualitative and vulnerability-centric, in the sense that by identifying and analyzing common vulnerabilities the probability and damage of risks are evaluated qualitatively. We also propose an algorithmic decision analysis method that considers risk factors and alternative security solutions, and helps analysts select the most cost-effective solution. The decision analysis method enables making a decision when some of the available data is qualitative.
New Phases of Near-Extremal Branes on a Circle

We study the phases of near-extremal branes on a circle, by which we mean near-extremal branes of string theory and M-theory with a circle in their transverse space. We find a map that takes any static and neutral Kaluza-Klein black hole, i.e. any static and neutral black hole on Minkowski-space times a circle M^d x S^1, and map it to a corresponding solution for a near-extremal brane on a circle. The map is derived using first a combined boost and U-duality transformation on the Kaluza-Klein black hole, transforming it to a solution for a non-extremal brane on a circle. The resulting solution for a near-extremal brane on a circle is then obtained by taking a certain near-extremal limit. As a consequence of the map, we can transform the neutral non-uniform black string branch into a new non-uniform phase of near-extremal branes on a circle. Furthermore, we use recently obtained analytical results on small black holes in Minkowski-space times a circle to get new information about the localized phase of near-extremal branes on a circle. This gives in turn predictions for the thermal behavior of the non-gravitational theories dual to these near-extremal branes. In particular, we give predictions for the thermodynamics of supersymmetric Yang-Mills theories on a circle, and we find a new stable phase of (2,0) Little String Theory in the canonical ensemble for temperatures above its Hagedorn temperature.
Ombitasvir, paritaprevir co-dosed with ritonavir, dasabuvir, and ribavirin for hepatitis C in patients co-infected with HIV-1: a randomized trial.

IMPORTANCE Patients co-infected with human immunodeficiency virus (HIV) and hepatitis C virus (HCV) are at high risk for liver disease progression. However, interferon-based treatments for HCV infection have significant toxicities, limiting treatment uptake. OBJECTIVE To assess the all-oral 3 direct-acting antiviral (3D) regimen of ombitasvir, paritaprevir (co-dosed with ritonavir [paritaprevir/r]), dasabuvir, and ribavirin in HCV genotype 1-infected adults with HIV-1 co-infection, including patients with cirrhosis. DESIGN, SETTING, AND PARTICIPANTS TURQUOISE-I is a randomized, open-label study. Part 1a of this pilot study was conducted at 17 sites in the United States and Puerto Rico between September 2013 and August 2014 and included 63 patients with HCV genotype 1 and HIV-1 co-infection who were HCV treatment-naive or had history of prior treatment failure with peginterferon plus ribavirin therapy. The study allowed enrollment of patients, including those with cirrhosis, with a CD4+ count of 200/mm3 or greater or CD4+ percentage of 14% or more and plasma HIV-1 RNA suppressed while taking a stable atazanavir- or raltegravir-inclusive antiretroviral regimen. INTERVENTIONS Ombitasvir/paritaprevir/r, dasabuvir, and ribavirin for 12 or 24 weeks of treatment as randomized. MAIN OUTCOMES AND MEASURES The primary assessment was the proportion of patients with sustained virologic response (HCV RNA <25 IU/mL) at posttreatment week 12 (SVR12). RESULTS Among patients receiving 12 or 24 weeks of 3D and ribavirin, SVR12 was achieved by 29 of 31 (94%; 95% CI, 79%-98%) and 29 of 32 patients (91%; 95% CI, 76%-97%), respectively. Of the 5 patients who did not achieve SVR, 1 withdrew consent, 2 had confirmed virologic relapse or breakthrough, and 2 patients had clinical history and phylogenetic evidence consistent with HCV reinfection. The most common treatment-emergent adverse events were fatigue (48%), insomnia (19%), nausea (18%), and headache (16%). Adverse events were generally mild, with none reported as serious or leading to discontinuation. No patient had a confirmed HIV-1 breakthrough of 200 copies/mL or greater during treatment. CONCLUSIONS AND RELEVANCE In this open-label, randomized uncontrolled study, treatment with the all-oral, interferon-free 3D-plus-ribavirin regimen resulted in high SVR rates among patients co-infected with HCV genotype 1 and HIV-1 whether treated for 12 or 24 weeks. Further phase 3 studies of this regimen are warranted in patients with co-infection. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT01939197.
MRM-Lasso: A Sparse Multiview Feature Selection Method via Low-Rank Analysis

Learning about multiview data involves many applications, such as video understanding, image classification, and social media. However, when the data dimension increases dramatically, it is important but very challenging to remove redundant features in multiview feature selection. In this paper, we propose a novel feature selection algorithm, multiview rank minimization-based Lasso (MRM-Lasso), which jointly utilizes Lasso for sparse feature selection and rank minimization for learning relevant patterns across views. Instead of simply integrating multiple Lasso from view level, we focus on the performance of sample-level (sample significance) and introduce pattern-specific weights into MRM-Lasso. The weights are utilized to measure the contribution of each sample to the labels in the current view. In addition, the latent correlation across different views is successfully captured by learning a low-rank matrix consisting of pattern-specific weights. The alternating direction method of multipliers is applied to optimize the proposed MRM-Lasso. Experiments on four real-life data sets show that features selected by MRM-Lasso have better multiview classification performance than the baselines. Moreover, pattern-specific weights are demonstrated to be significant for learning about multiview data, compared with view-specific weights.
Static Noise Margin Analysis of Various SRAM Topologies

the present time, great emphasis has been given to the design of low-power and high performance memory circuits. As an SRAM is a critical component in both high-performance processors and hand-held portable devices. So the ever-increasing levels of on-chip integration of SRAM, offers serious design challenges in terms of power requirement and cell stability. There is a significant increase in the sub-threshold leakage due to its exponential relation to the threshold voltage, and gate leakage due to the reducing gate-oxide thickness. In order to minimize the leakage current, the supply voltage is reduced drastically which reduces the threshold voltage of the cell.This reduces the threshold voltage of the cell which results in reduction of the Static Noise Margin (SNM) of the cell and affect the data stability of the cell, seriously. In this work, the solutions for theses two problems, in the conventional 6T SRAM Cell has been explored.