Miracle-dz/UniFAR-FTUs huggingface dataset:
Extending the Nested Parallel Model to the Nested Dataflow Model with Provably Efficient Schedulers

The nested parallel (a.k.a. fork-join) model is widely used for writing parallel programs. However, the two composition constructs, i.e. "||" (parallel) and ";" (serial), that comprise the nested-parallel model are insufficient in expressing "partial dependencies" in a program. We propose a new dataflow composition construct "↝" to express partial dependencies in algorithms in a processor- and cache-oblivious way, thus extending the Nested Parallel (NP) model to the Nested Dataflow (ND) model. We redesign several divide-and-conquer algorithms ranging from dense linear algebra to dynamic-programming in the ND model and prove that they all have optimal span while retaining optimal cache complexity. We propose the design of runtime schedulers that map ND programs to multicore processors with multiple levels of possibly shared caches (i.e, Parallel Memory Hierarchies) and prove guarantees on their ability to balance nodes across processors and preserve locality. For this, we adapt space-bounded (SB) schedulers for the ND model. We show that our algorithms have increased "parallelizability" in the ND model, and that SB schedulers can use the extra parallelizability to achieve asymptotically optimal bounds on cache misses and running time on a greater number of processors than in the NP model. The running time for the algorithms in this paper is O((∑i=0h-1 Q*(t;σ⋅ Mi)⋅ Ci)/p) on a p-processor machine, where Q* is the parallel cache complexity of task t, Ci is the cost of cache miss at level-i cache which is of size Mi, and σ∈(0,1) is a constant.
Developmental victimology

Although research on the age–crime curve has made significant advances in the past few decades, the understanding of victimization has not benefited to the same degree. The present study examines the age–victim curve to explore victimization trajectories, which increases understanding of risks over time through different life pathways. Using data from the Offending, Crime and Justice Survey, a national longitudinal survey in England and Wales, trajectory modeling is used to estimate different violent victimization trajectories for people aged 10 to 29 over four years of data. Analyses indicate the presence of four distinct victimization trajectories, including: rarely victimized; young adult victims; childhood victims; and chronically victimized. Further analyses indicated that young adult victims often were connected to intimate partner violence, whereas childhood victims often were victimized by other students.
Distinguishing disturbance from perturbations in fire-prone ecosystems

Fire is a necessary ecosystem process in many biomes and is best viewed as a natural disturbance that is beneficial to ecosystem functioning. However, increasingly, we are seeing human interference in fire regimes that alters the historical range of variability for most fire parameters and results in vegetation shifts. Such perturbations can affect all fire regime parameters. Here, we provide a brief overview of examples where anthropogenically driven changes in fire frequency, fire pattern, fuels consumed and fire intensity constitute perturbations that greatly disrupt natural disturbance cycles and put ecosystems on a different trajectory resulting in type conversion. These changes are not due to fire per se but rather anthropogenic perturbations in the natural disturbance regime.
Social seeking declines in young adolescents

The desire to engage with others is an important motivational force throughout our lifespan. It is known that social behaviour and preferences change from childhood to adulthood, but whether this change is linked with any changes in social motivation is not known. We evaluated 255 typically developing participants from ages 4–20 years on a behavioural paradigm ‘Choose a Movie’ (CAM). On every trial, participants had a choice between viewing social or non-social movies presented with different levels of effort (key presses/screen touch required). Hence, participants chose not only the movie they would watch but also how much effort they would make. The difference between the effort levels of the chosen and not chosen stimuli helps in quantifying the motivation to seek it. This task could be used with all the age groups with minimal adaptations, allowing comparison between the groups. Results showed that children (4–8 years), older adolescents (12–16 years) and young adults (17–20 years) made more effort to look at social movies. Counterintuitively, this preference was not seen in young adolescents (around 9–12 years), giving a U-shaped developmental trajectory over the population. We present the first evidence for non-monotonic developmental change in social motivation in typical participants.
PREDICTING INJURY FROM FALLS IN OLDER ADULTS: COMPARISON OF VOLUNTARY STEP REACTION TIMES IN INJURED AND NONINJURED FALLERS—A PROSPECTIVE STUDY

declined, versus 14% of those who were not (Po.001). Tired people were more prone to decline in their level of physical activity (relative risk (RR) 5 3.6) and frequency of leaving the house (RR 5 3.6). There were no significant differences between tired and not tired subjects regarding the new onset of common comorbidities including diabetes mellitus, hypertension, ischemic heart disease, or depression.
Firefly-Inspired Synchronization in Swarms of Mobile Agents

Recently, there has been growing interest in the synchronization of mobile pulse-coupled oscillators. We build on the work by Prignano et al. (Phys. Rev. Lett. 110, 114101) and show that agents that interact exclusively with others in their cone of vision can exhibit different synchronization regimes. Depending on their speed, synchronization emerges as a slow process through spreading of the local coherence, as a fast process where global synchronization dominates, or it is inhibited for a range of intermediate speeds. In addition, we show that, not only the speed of the agents, but also their angle and range of interaction can tune the appearance of this intermediate regime.
Die sozio-emotionale Entwicklung in den Begabtenklassen und ihren Parallelklassen

Schneider, Wolfgang [Hrsg. ]; Preckel, Franzis [Hrsg. ]; Stumpf, Eva [Hrsg. ]: Hochbegabtenforderung in der Sekundarstufe. Ergebnisse der PULSS-Studie zur Untersuchung der gymnasialen Begabtenklassen in Bayern und Baden-Wurttemberg. Frankfurt am Main 2014, S. 52-64. - (Karg Hefte: Beitrage zur Begabtenforderung und Begabungsforschung; 7) Padagogische Teildisziplin: Empirische Bildungsforschung; Schulpadagogik; als elektronischer Volltext verfugbar
Dilated cardiomyopathy produced by lamin A/C gene mutations

Lamin A/C gene (LMNA) associated cardiomyopathy is a form of dilated cardiomyopathy with poor prognosis and high mortality, and a rapid evolution toward end-stage heart failure and malignant ventricular arrhythmias associated with increased risk of sudden cardiac death. It is transmitted in a autosomal dominant manner and is characterized by age-dependent high penetrance and variable expression. Screening of first degree relatives of proband patients by means of clinical evaluation, electrocardiogram, echocardiography and genetic analysis is useful for the early diagnosis of the disease. Drug therapy and non-pharmacological measures in the early stages of the disease seem to improve the prognosis of these patients.
Accuracy of the Enlite 6-day glucose sensor with guardian and Veo calibration algorithms.

OBJECTIVE This study investigates the accuracy of a newly developed, next-generation subcutaneous glucose sensor, evaluated for 6-day use. RESEARCH DESIGN AND METHODS Seventy-nine subjects (53 men, 26 women) with type 1 diabetes and 18 subjects (14 men, four women) with type 2 diabetes completed a three-center, prospective, sensor accuracy study. The mean age for the group was 42.2±15.0 years (mean±SD), ranging from 18 to 71 years, with a mean glycosylated hemoglobin level of 7.6±1.5%, ranging from 5.5% to 14%. Subjects wore Enlite™ sensors (Medtronic Diabetes, Northridge, CA) in the abdominal and buttocks region for two separate 7-day periods and calibrated with a home-use blood glucose meter. Subjects participated in an in-clinic testing day where frequent sampled plasma glucose samples were acquired every 15 min for 10 h. Sensor data was retrospectively processed with Guardian(®) REAL-Time (Medtronic) and Paradigm(®) Veo™ (Medtronic) calibration routines, and accuracy metrics were calculated for each algorithm and sensor location. Physiological time lag for each measurement site was calculated. RESULTS Based on 6,404 plasma-sensor glucose paired points, the Enlite sensor with Veo calibration algorithm produced a mean absolute relative difference of 13.86% with 97.3% of points within the A+B zones of the Clarke error grid. Threshold-only alarms detected 90.1% of hypoglycemia and 90% of hyperglycemia. Mean time lag measured at the abdominal region was 7.94±6.48 min compared with 11.70±6.71 min (P<0.0001) at the buttocks area. CONCLUSIONS The Enlite sensor accurately measures glucose when compared with gold standard laboratory measurements over its 6-day use. Sensors placed in the buttocks region exhibited greater time lags than sensors placed in the abdomen.
Data mining with Random Forests as a methodology for biomedical signal classification

Abstract As the contribution of specific parameters is not known and significant intersubject variability is expected, a decision system allowing adaptation for subject and environment conditions has to be designed to evaluate biomedical signal classification. A decision support system has to be trained in its desirable functionality prior to being used for patient monitoring evaluation. This paper describes a decision system based on data mining with Random Forests, allowing the adaptation for subject and environment conditions. This methodology may lead to specific system scoring by an artificial intelligence-supported patient monitoring evaluation system, which may help find a way of making decisions concerning future treatment and have influence on the quality of patients’ life.
Effect of Inert Annealing Gases on Morphology of Gold Nanoparticles Produced by Using Rapid Thermal Annealing

Metallic nanoparticles have various potential applications. Recent studies have showed that their morphology had a strong influence on their optical and electrical properties. In this work, rapid thermal annealing was used to produce gold nanoparticles on silicon substrates. Morphology control of the gold nanoparticles was made by changing inert annealing gases. Spherical gold nanoparticles were obtained with nitrogen while hemispherical gold nanoparticles were formed with argon.
Thresholds for warming‐induced growth decline at elevational tree line in the Yukon Territory, Canada

A few tree ring studies indicate recent growth declines at northern latitudes. The precise causes are not well understood. Here we identify a temperature threshold for decline in a tree ring record from a well‐established temperature‐sensitive site at elevational tree line in northwestern Canada. The positive ring width/temperature relationship has weakened such that a pre‐1965 linear model systematically overpredicts tree ring widths from 1965 to 1999. A nonlinear model shows an inverted U‐shaped relationship between this chronology and summer temperatures, with an optimal July–August average temperature of 11.3°C based on a nearby station. This optimal value has been consistently exceeded since the 1960s, and the concurrent decline demonstrates that even at tree line, trees can be negatively affected when temperatures warm beyond a physiological threshold. If warming continues without significant gains in effective precipitation, the large‐scale greening of recent decades could be replaced by large‐scale browning. Such browning could slow or reverse carbon uptake by northern forests.
Thrombospondin-1 Modulates the Angiogenic Phenotype of Human Cerebral Arteriovenous Malformation Endothelial Cells

BACKGROUND:The management of cerebral arteriovenous malformation (AVM) is challenging, and invasive therapies place vital intracranial structures at risk of injury. The development of noninvasive, pharmacologic approaches relies on identifying factors that mediate key angiogenic processes. Previous studies indicate that endothelial cells (ECs) derived from cerebral AVM (AVM-ECs) are distinct from control brain ECs with regard to important angiogenic characteristics. OBJECTIVE:To determine whether thrombospondin-1 (TSP-1), a potent angiostatic factor, regulates critical angiogenic features of AVM-ECs and to identify factors that modulate TSP-1 production in AVM-ECs. METHODS:EC proliferation, migration, and tubule formation were evaluated with bromodeoxyuridine incorporation, Boyden chamber, and Matrigel studies, respectively. TSP-1 and inhibitor of DNA binding/differentiation 1 (Id1) mRNA levels were quantified with microarray and quantitative real-time polymerase chain reaction analyses. TSP-1 protein expression was measured using Western blotting, immunohistochemical, and enzyme-linked immunosorbent assay techniques. The mechanistic link between Id1 and TSP-1 was established through small interfering RNA-mediated knockdown of Id1 in AVM-ECs followed by Western blot and enzyme-linked immunosorbent assay experiments assessing TSP-1 production. RESULTS:AVM-ECs proliferate faster, migrate more quickly, and form disorganized tubules compared with brain ECs. TSP-1 is significantly down-regulated in AVM-ECs. The addition of TSP-1 to AVM-EC cultures normalizes the rate of proliferation and migration and the efficiency of tubule formation, whereas brain ECs are unaffected. Id1 negatively regulates TSP-1 expression in AVM-ECs. CONCLUSION:These data highlight a novel role for TSP-1 in the pathobiology of AVM angiogenesis and provide a context for its use in the clinical management of brain AVMs.
Combining Manifest Contracts with State

Manifest contracts combine the rich specifications and runtime checking of higher-order contracts [11] with a static type discipline. Conventional type systems prevent simple errors, like calling a boolean as a function, but manifest contracts can prevent more complex errors. For example, we could give the sqrt function the very precise type {x:Float | x ≥ 0} → {y:Float | |x − y| < }, where subset types like {x:Float | x ≥ 0} refer to those floating-point numbers x such that x ≥ 0. Extending types with contract-like specifications in code yield powerful reasoning principles [5, 22] and better abstractions [14]. Sound manifest contract systems enjoy an inversion principle, invaluable for reasoning about parameters in function bodies:
Synchronization inspired data mining

Advances of modern technologies produce huge amounts of data in various fields, increasing the need for efficient and effective data mining tools to uncover the information contained implicitly in the data. This thesis mainly aims to propose innovative and solid algorithms for data mining from a novel perspective: synchronization. Synchronization is a prevalent phenomenon in nature that a group of events spontaneously come into co-occurrence with a common rhythm through mutual interactions. The mechanism of synchronization allows controlling of complex processes by simple operations based on interactions between objects. The first main part of this thesis focuses on developing the innovative algorithms for data mining. Inspired by the concept of synchronization, this thesis presents Sync (Clustering by Synchronization), a novel approach to clustering. In combination with the Minimum Description Length principle (MDL), it allows discovering the intrinsic clusters without any data distribution assumptions and parameters setting. In addition, relying on the dierent dynamic behaviors of objects during the process towards synchronization,the algorithm SOD (Synchronization-based Outlier Detection) is further proposed. The outlier objects can be naturally flagged by the denition of Local Synchronization Factor (LSF). To cure the curse of dimensionality in clustering,a subspace clustering algorithm ORSC is introduced which automatically detects clusters in subspaces of the original feature space. This approach proposes a weighted local interaction model to ensure all objects in a common cluster, which accommodate in arbitrarily oriented subspace, naturally move together. In order to reveal the underlying patterns in graphs, a graph partitioning approach RSGC (Robust Synchronization-based Graph Clustering) is presented. The key philosophy of RSGC is to consider graph clustering as a dynamic process towards synchronization. Inherited from the powerful concept of synchronization, RSGC shows several desirable properties that don't exist in other competitive methods. For all presented algorithms, their efficiency and eectiveness are thoroughly analyzed. The benets over traditional approaches are further demonstrated by evaluating them on synthetic as well as real-world data sets. Not only the theory research on novel data mining algorithms, the second main part of the thesis focuses on brain network analysis based on Diusion Tensor Images (DTI). A new framework for automated white matter tracts clustering is rst proposed to identify the meaningful ber bundles in the Human Brain by combining ideas from time series mining with density-based clustering. Subsequently, the enhancement and variation of this approach is discussed allowing for a more robust, efficient, or eective way to find hierarchies of ber bundles. Based on the structural connectivity network, an automated prediction framework is proposed to analyze and understand the abnormal patterns in patients of Alzheimer's Disease.
Infrastructure for 3D model reconstruction of marine structures

3D model reconstruction of marine structures, such as dams, oilrigs, and sea caves, is both important and challenging. An important application includes structural inspection. Manual inspection of marine structures is tedious and even a small oversight can have severe consequences for the structure and the people around it. A robotic system that can construct 3D models of marine structures would hopefully reduce the chances of oversight, and hence improve the safety of marine environment. Due to the water currents and wakes, developing a robotic system to construct 3D models of marine structures is a challenge, as it is difficult for a robot to reach the desired scan configurations and take a scan of the environment while remaining stationary. This paper presents our preliminary work in developing a robotic and software system for construction of 3D models of marine structures. We have successfully tested our system in a sea water environment in the Singapore Straits.
INDUCTION OF SKIN RESISTANCE TO VACCINIA VIRUS IN RABBITS BY VACCINIA-SOLUBLE EARLY ANTIGENS

The immunological role of vaccinia-soluble early antigen was examined in rabbits. The antigens were prepared from HeLa cells infected with a conditional lethal mutant of vaccinia virus, which induces in these cells early antigens including those responsible for surface immunofluorescence of infected cells, but not viral DNA and late protein syntheses. Immunization of rabbits with the antigens in Freund's complete adjuvant induced complement-fixing antibody but neither detectable circulating neutralizing antibody nor any detectable level of inhibitory substance or interferon in the skin of the animals. When immunized animals were inoculated intradermally with vaccinia virus, multiplication of virus in the skin was greatly inhibited, being accompanied by an earlier appearance as well as an accelerated wane of the local reactions. The resistance could not be transferred passively by the serum of immunized animals to normal rabbits. Immunization of rabbits with the antigens without the adjuvant not only failed to inhibit but, contrariwise, enhanced the multiplication of intradermally inoculated vaccinia virus, inducing heavy skin lesions and exalted virus multiplication.
2016 Fifth International Conference on Recent Trends in Information Technology Efficient Detection Tracking of Multiple Moving Objects in Temporal Domain

ņIn video surveillance the moving object detection and tracking are important research area of computer vision. Tracking moving objects in a real time environment is not easy because of continual deformation of objects during movement. The moving item has many attributes in both temporal and spatial spaces. In the spatial area, objects vary in size while in temporal area they vary in moving speed. To track multiple object in video with optimal window size the Decomposition with Temporal Domain (DTD) is proposed. Thus the moving objects are detected and tracked until it disappears or losses it motion. The proposed strategy can identify and track objects all the while. It reduces the False Alarms Rate (FAR) and increases True Positive Rate (TPR). Moving items with various speeds and sizes are tracked with their optimal window size and the possible shadow is eliminated by the multi frame difference method. The proposed method is compared with Kalman filter and Optical Flow (OF) of Lucas-Kanade method using probabilistic approaches such as FAR and TPR performance is analyzed. Different test results have affirmed the legitimacy and adequacy of the proposed technique. I. INTRODUCTION The detection of moving objects and tracking of the objects in video surveillance is a primitive and vital task that captivated an increasing level as concentration in computer vision. Efficient algorithm is needed to track multiple moving objects in complex background. Each and every object has different size and scale have to track individual object efficiently with optimal window size. In order to support effective video surveillance, an automatic monitoring system has to be developed.In visual surveillance multiple cameras, attempts to detect, recognize and track those objects from image sequences, and also importantly to understand and describe object behaviors. The main aim of anvisual surveillance is to reduce the human effort whenthe number of cameras exceed the capability of human operators to monitor them by developingcomputer vision algorithms.Visual surveillance devices used to monitor the people, gathering informationand events in outdoor as well as indoor environments. Visual surveillance innovations, CCD cameras, warm cameras and night vision gadgets are the most
Temporal and antigenic analysis of dengue virus serotype 1 genome polyprotein sequences

Dengue virus poses a significant health threat. The new emerging strains continue to cause annual epidemics. In this paper, we report results of an analysis of dengue virus serotype 1 (DV1) genome polyprotein sequences in the context of time and geographical distribution. We studied the clustering of 60 DV1 genome polyprotein sequences of different geographical distributions, reported in the past 30 years, to identify geographic and temporal patterns of genetic and antigenic variation. Our analysis showed distinct clustering of sequences into two main geographical regions: i Western and South Pacific and South-East Asian region (with three distinct sub-clusters) and ii South American region. The results provide evidence suggesting temporal changes of the isolated strains. In addition, our analysis indicated that potential T-cell epitope hotspots within DV1 are shifting with time and recurrent epidemics, resulting in disappearing of some hotspots and emerging of new hotspots.