Miracle-dz/UniFAR-FTUs huggingface dataset:
Minimizing the Data Transfer Time Using Multicore End-System Aware Flow Bifurcation

Data centers are being deployed in a wide variety of environments (cloud computing, scientific, financial, defense, etc.). When geographically distributed, these data centers must transmit and receive growing volumes of data. In order to avoid congestion in the public internet, most use high speed dedicated optical networks, which can be thought of as private highways for carrying data. In this work, we examined the impact of such high speed network traffic on a commodity multicore machine, and identified a number of scenarios that cause packet loss and degraded throughput due to an end-system inability to consume incoming data fast enough. We show that high speed single flow traffic nullifies the benefits of multicore systems and multiqueue NICs, and we propose an end-system aware flow bifurcation technique to optimize the data transfer time using rate based protocols. Using introspective end-system modeling, we determine the optimal number of parallel flows required to utilize the available bandwidth, and the optimal rate for each of the flows. We compare our approach with GridFTP, which is a widely used data transfer protocol in computational grids, and show that our approach performs better (particularly when the end-system losses are in the receive ring buffer.).
A Risk-Based Model Predictive Control Approach to Adaptive Interventions in Behavioral Health

This brief examines how control engineering and risk management techniques can be applied in the field of behavioral health through their use in the design and implementation of adaptive behavioral interventions. Adaptive interventions are gaining increasing acceptance as a means to improve prevention and treatment of chronic, relapsing disorders, such as abuse of alcohol, tobacco, and other drugs, mental illness, and obesity. A risk-based model predictive control (MPC) algorithm is developed for a hypothetical intervention inspired by Fast Track, a real-life program whose long-term goal is the prevention of conduct disorders in at-risk children. The MPC-based algorithm decides on the appropriate frequency of counselor home visits, mentoring sessions, and the availability of after-school recreation activities by relying on a model that includes identifiable risks, their costs, and the cost/benefit assessment of mitigating actions. MPC is particularly suited for the problem because of its constraint-handling capabilities, and its ability to scale to interventions involving multiple tailoring variables. By systematically accounting for risks and adapting treatment components over time, an MPC approach as described in this brief can increase intervention effectiveness and adherence while reducing waste, resulting in advantages over conventional fixed treatment. A series of simulations are conducted under varying conditions to demonstrate the effectiveness of the algorithm.
Ethnography, Communication and Support for Design

This paper reflects on our experiences in supporting communication between fieldworkers and the designers of cooperative systems. We have investigated the nature of this communication by using a tool orginally designed to support the representation of software designs to present emerging results of ethnographic material. In this paper we discuss the tool used (the DNP) and the experiences of using the toolkit in the context of design. Our particular focus is on the use of the tool to represents results from a study of a UK financial institution where a series of prototyping exercises was underway.
Blind source separation and sparse component analysis of overcomplete mixtures

We formulate conditions (k-SCA-conditions) under which we can represent a given (m/spl times/N)-matrix, X, (data set) uniquely (up to scaling and permutation) as a multiplication of m/spl times/n and n/spl times/N matrices, A and S, (often called mixing matrix or dictionary and source matrix, respectively), such that S is sparse of level n-m+k in the sense that each column of S has at least n-m+k zero elements. We call this the k-sparse component analysis problem (k-SCA). Conditions on a matrix, S, are presented such that the k-SCA-conditions are satisfied for the matrix X=AS, where A is an arbitrary matrix from some class. This is the blind source separation problem and the above conditions are called identifiability conditions. We present new algorithms for matrix identification (under k-SCA-conditions), and for source recovery (under identifiability conditions). The methods are illustrated with examples, showing good separation of the high-frequency part of mixtures of images after appropriate sparsification.
3D Timelapse Analysis of Muscle Satellite Cell Motility

Skeletal muscle repair and regeneration requires the activity of satellite cells, a population of myogenic stem cells scattered throughout the tissue and activated to proliferate and differentiate in response to myotrauma or disease. While it seems likely that satellite cells would need to navigate local muscle tissue to reach damaged areas, relatively little data on such motility exist, and most studies have been with immortalized cell lines. We find that primary satellite cells are significantly more motile than myoblast cell lines, and that adhesion to laminin promotes primary cell motility more than fourfold over other substrates. Using timelapse videomicroscopy to assess satellite cell motility on single living myofibers, we have identified a requirement for the laminin‐binding integrin α7β1 in satellite cell motility, as well as a role for hepatocyte growth factor in promoting directional persistence. The extensive migratory behavior of satellite cells resident on muscle fibers suggests caution when determining, based on fixed specimens, whether adjacent cells are daughters from the same mother cell. We also observed more persistent long‐term contact between individual satellite cells than has been previously supposed, potential cell‐cell attractive and repulsive interactions, and migration between host myofibers. Based on such activity, we assayed for expression of “pathfinding” cues, and found that satellite cells express multiple guidance ligands and receptors. Together, these data suggest that satellite cell migration in vivo may be more extensive than currently thought, and could be regulated by combinations of signals, including adhesive haptotaxis, soluble factors, and guidance cues. STEM CELLS 2009;27:2527–2538
The Pseudomonas syringae pv. tomato Type III Effector HopM1 Suppresses Arabidopsis Defenses Independent of Suppressing Salicylic Acid Signaling and of Targeting AtMIN7

Pseudomonas syringae pv tomato strain DC3000 (Pto) delivers several effector proteins promoting virulence, including HopM1, into plant cells via type III secretion. HopM1 contributes to full virulence of Pto by inducing degradation of Arabidopsis proteins, including AtMIN7, an ADP ribosylation factor-guanine nucleotide exchange factor. Pseudomonas syringae pv phaseolicola strain NPS3121 (Pph) lacks a functional HopM1 and elicits robust defenses in Arabidopsis thaliana, including accumulation of pathogenesis related 1 (PR-1) protein and deposition of callose-containing cell wall fortifications. We have examined the effects of heterologously expressed HopM1Pto on Pph-induced defenses. HopM1 suppresses Pph-induced PR-1 expression, a widely used marker for salicylic acid (SA) signaling and systemic acquired resistance. Surprisingly, HopM1 reduces PR-1 expression without affecting SA accumulation and also suppresses the low levels of PR-1 expression apparent in SA-signaling deficient plants. Further, HopM1 enhances the growth of Pto in SA-signaling deficient plants. AtMIN7 contributes to Pph-induced PR-1 expression. However, HopM1 fails to degrade AtMIN7 during Pph infection and suppresses Pph-induced PR-1 expression and callose deposition in wild-type and atmin7 plants. We also show that the HopM1-mediated suppression of PR-1 expression is not observed in plants lacking the TGA transcription factor, TGA3. Our data indicate that HopM1 promotes bacterial virulence independent of suppressing SA-signaling and links TGA3, AtMIN7, and other HopM1 targets to pathways distinct from the canonical SA-signaling pathway contributing to PR-1 expression and callose deposition. Thus, efforts to understand this key effector must consider multiple targets and unexpected outputs of its action.
Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor

By taking advantage of both k-NN which is highly accurate and K-means cluster which is able to reduce the time of classification, we can introduce Cluster-k-Nearest Neighbor as ”variable k”-NN dealing with the centroid or mean point of all subclasses generated by clustering algorithm. In general the algorithm of K-means cluster is not stable, in term of accuracy, for that reason we develop another algorithm for clustering our space which gives a higher accuracy than K-means cluster, less subclass number, stability and bounded time of classification with respect to the variable data size. We find between 96% and 99.7 % of accuracy in the classification of 6 different types of Time series by using K-means cluster algorithm and we find 99.7% by using the new clustering algorithm.
Indictment by Association: Once Is Not Enough

Early life infections with human bocavirus 1 (HBoV-1) are common, and the virus is readily detected in the upper respiratory tract, often during acute upper respiratory tract illness. Its etiological role in respiratory tract infections has been uncertain because of its presence in asymptomatic children and frequent concurrent detection of other respiratory viruses. Longitudinal cohort studies, in which sampling is done at intervals that include periods of illness and health, have begun to bring clarity to the story. In this issue of the Journal, Martin et al [1] performed noninvasive weekly sampling and collected health data during the first 2 years of life and provide substantial evidence that HBoV-1 is indeed a respiratory pathogen in young children. This story is an excellent example of the power of longitudinal cohort study designs in identifying etiologic roles for viruses that embody combinations of being highly prevalent, being able to reinfect previously exposed individuals and to persist for long periods in the infected host in the absence of symptoms, and, often, causing mild disease.
Structured Counterexamples for the Temporal Description Logic ALCCTL

A new algorithm for generating counterexamples for the temporal description logic ALCCTL is presented. ALCCTL is a decidable combination of the description logic ALC and computation tree logic CTL. It extends CTL by first order quantified expressions over unary and binary predicates. Predicates and quantified expressions are required for representing properties in application domains such as structured web documents and they are frequently used in software and hardware specifications which are verified by model checking. In the case of a specification violation, existing algorithms generate counterexamples that tend to be complex yet imprecise if specifications range over sets of objects. The presented algorithm is the first algorithm for generating counterexamples for a temporal description logic that considers first order predicates and quantification. The algorithm is sound and semi-complete for ALCCTL. The generated counterexamples are both more precise and comprehensible than counterexamples generated by the previous algorithms.
Taking ideas and discourse seriously: explaining change through discursive institutionalism as the fourth ‘new institutionalism’

All three of the traditionally recognized new institutionalisms – rational choice, historical, and sociological – have increasingly sought to ‘endogenize’ change, which has often meant a turn to ideas and discourse. This article shows that the approaches of scholars coming out of each of these three institutionalist traditions who take ideas and discourse seriously can best be classified as part of a fourth ‘new institutionalism’ – discursive institutionalism (DI) – which is concerned with both the substantive content of ideas and the interactive processes of discourse in institutional context. It argues that this newest of the ‘new institutionalisms’ has the greatest potential for providing insights into the dynamics of institutional change by explaining the actual preferences, strategies, and normative orientations of actors. The article identifies the wide range of approaches that fit this analytic framework, illustrating the ways in which scholars of DI have gone beyond the limits of the traditional institutionalisms on questions of interests and uncertainty, critical junctures and incremental change, norms and culture. It defines institutions dynamically – in contrast to the older neo-institutionalisms’ more static external rule-following structures of incentives, path-dependencies, and cultural framing – as structures and constructs of meaning internal to agents whose ‘background ideational abilities’ enable them to create (and maintain) institutions while their ‘foreground discursive abilities’ enable them to communicate critically about them, to change (or maintain) them. But the article also points to areas for improvement in DI, including the theoretical analysis of processes of ideational change, the use of the older neo-institutionalisms for background information, and the incorporation of the power of interests and position into accounts of the power of ideas and discourse.
Episodic Memory: A Comparative Approach

Historically, episodic memory has been described as autonoetic, personally relevant, complex, context-rich, and allowing mental time travel. In contrast, semantic memory, which is theorized to be free of context and personal relevance, is noetic and consists of general knowledge of facts about the world. The field of comparative psychology has adopted this distinction in order to study episodic memory in non-human animals. Our aim in this article is not only to reflect on the concept of episodic memory and the experimental approaches used in comparative psychology to study this phenomenon, but also to provide a critical analysis of these paradigms. We conclude the article by providing new avenues for future research.
TrafficSense: Rich Monitoring of Road and Traffic Conditions us ing Mobile Smartphones

We consider the problem of monitoring road and traffic conditions in a city. Prior work in this area has required the deployment of dedicated sensors on vehicles and/or on the roadside, or the tracking of mobile phones by service providers. Furthermore, prior work has largely focused on the developed world, with its relatively simple traffic flow patterns. In fact, traffic flow in cities of the developing regions, which comprise much of the world, tends to be much more complex owing to varied road conditions (e.g., potholed roads), chaotic traffic (e.g., a lot of braking and honking), and a heterogeneous mix of vehicles (2-wheelers, 3-wheelers, cars, buses, etc.). To monitor road and traffic conditions in such a setting, we present TrafficSense, a system that performs rich sensing by piggybacking on smartphones that users carry around with them. In this paper, we focus specifically on the sensing component, which uses the accelerometer, microphone, GSM radio, and/or GPS sensors in these phones to detect potholes, bumps, braking, and honking. TrafficSense addresses several challenges including virtually reorienting the accelerometer on a phone that is at an arbitrary orientation, and performing honk detection and localization in an energy efficient manner. We also touch upon the idea of triggered sensing, where dissimilar sensors are used in tandem to conserve energy. We evaluate the effectiveness of the sensing functions in TrafficSense based on experiments conducted on the roads of Bangalore, with promising results.
From adorable to worthless: implicit and self‐report structure of highly evaluative personality descriptors

So‐called highly ‘evaluative’ personality judgments (e.g. describing someone as exceptional, odd, or vile,) are an integral component of people's daily judgments of themselves and others. However, little is known about the conceptual structure, psychological function, and personality‐relevance of these kinds of attribution. Two studies were conducted to explore the internal (i.e. implicit) and external (i.e. self‐report) structure of highly evaluative terms. Factor analyses of semantic‐similarity sortings and self‐reports on several representative samples of highly evaluative personality adjectives yielded internal and external structures that were very similar. Both types of structure included five dimensions representing distinction, worthlessness, depravity, unconventionality, and stupidity. The robustness of the uncovered dimensions across the two studies suggests that typically excluded highly evaluative personality terms, far from being behaviorally ambiguous and psychologically uninformative, allude to meaningful dispositions that people both implicitly understand and possess to different degrees. These findings also suggest that highly evaluative personality judgments are organized around the basic domains of morality (i.e. depravity), power (distinction and worthlessness), peculiarity (unconventionality), and intelligence (stupidity). We discuss the implications of our findings for the study of self‐ and other‐esteem processes, personality perception, and the Big Seven factor model of personality. Copyright © 2002 John Wiley & Sons, Ltd.
Optical Measurement of Stem Xylem Vulnerability1[OPEN]

An optical method is shown to accurately measure the vulnerability of stem xylem to cavitation during water stress. The vulnerability of plant water transport tissues to a loss of function by cavitation during water stress is a key indicator of the survival capabilities of plant species during drought. Quantifying this important metric has been greatly advanced by noninvasive techniques that allow embolisms to be viewed directly in the vascular system. Here, we present a new method for evaluating the spatial and temporal propagation of embolizing bubbles in the stem xylem during imposed water stress. We demonstrate how the optical method, used previously in leaves, can be adapted to measure the xylem vulnerability of stems. Validation of the technique is carried out by measuring the xylem vulnerability of 13 conifers and two short-vesseled angiosperms and comparing the results with measurements made using the cavitron centrifuge method. Very close agreement between the two methods confirms the reliability of the new optical technique and opens the way to simple, efficient, and reliable assessment of stem vulnerability using standard flatbed scanners, cameras, or microscopes.
The Asian Pharmacoepidemiology Network (AsPEN): promoting multi‐national collaboration for pharmacoepidemiologic research in Asia

Centre for Pharmacoepidemiology, Karolinska Institutet, Stockholm, Sweden Medical Research Collaborating Center, Seoul National University Hospital/Seoul National University College of Medicine, Seoul, South Korea Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, USA Department of Medicine, Division of Pharmacoepidemiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA Department of Medical Informatics, School of Medicine, Hamamatsu University, Shizuoka, Japan Department of Pharmacoepidemiology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan Institute of Clinical Pharmacy and Pharmaceutical Sciences, and Health Outcome Research Center, National Cheng Kung University, Tainan, Taiwan Department of Preventative Medicine, College of Medicine, Seoul National University, Seoul, South Korea Korea Institute of Drug Safety and Risk Management, Seoul, South Korea Quality Use of Medicines and Pharmacy Research Centre, Sansom Institute for Health Research, University of South Australia, Adelaide, Australia Duke Clinical Research Institute, Durham, NC, USA Division of Clinical Pharmacology, Department of Laboratory Medicine, Karolinska Institutet, Stockholm, Sweden Karolinska University Hospital, Stockholm, Sweden Institute of Environmental Medicine, Seoul National University Medical Research Center, Seoul, South Korea Department of Pharmacy Practice and Administration, Ernest Mario School of Pharmacy, Rutgers University, Piscataway, NJ, USA
A modular and flexible system for activity recognition and smart home control based on nonobtrusive sensors

This work describes a modular open source AAL framework for event recognition and smart home control. Various integrated tools simplify the configuration task, the personalization as well as the learning of activity models by a novel approach. Flexibility, standard compliant interfaces as well as the ability to transfer the system into new environments with little efforts have a strong focus. The paper describes the system architecture and the algorithms used.
A cost-effective VLSI architecture for anisotropic texture filtering in limited memory bandwidth

Texture mapping is one of the techniques that express realism in three-dimensional (3-D) graphics. To produce high-quality images, various anisotropic filtering methods have been proposed for texture mapping. These methods require more texels than isotropic (trilinear) filtering method. In spite of increases to texture memory bandwidth, however, texture memory bandwidth is still a bottleneck of texture-filtering hardware. Consequently, an exact filtering method is required for good-quality images in a limited texture memory bandwidth. In this paper, we propose anisotropic texture filtering based on edge functions. Our method proposes an exact footprint-shape approximation with edge functions for generating weights. For real-time filtering, the weight plays a key role in effective filtering of the restricted texels loaded from memory. The normalized value of the edge function gives the distance relative to the contribution of texels to a final intensity. Calculating a Gaussian filter using this normalized value, generates a good weight. The quality of rendered images is superior to other anisotropic filtering methods with the same restricted number of texels. For images of the same quality, our method requires less than half the texels of other methods. Consequently, the improvement in performance is more than twice that of other methods. With low hardware overheads, our method can be implemented at a reasonable cost. In practice, the algorithm is demonstrated through VLSI implementation. The hardware, which is described by verilog and synthesized with a 0.35-/spl mu/m 3.3-V standard cell library, is operated at 100 MHz and it generates 100 M texture-filtered RGB pixel-color values per second.
Mobile User Interface Using a Robust Fingertip Detection Algorithm for Complex Lighting and Background Conditions

This paper proposes the robust fingertip detection method using the Adaboost algorithm under dynamic lighting conditions and against complicated backgrounds for a finger-gesture-based mobile-user interface system. The proposed system is composed of two modules. First, the fingertip detection method is composed of two pre-processing phases using color and gradient information, AND an operation phase, and fingertip region detection using the Adaboost algorithm as sequential steps. Second, a user interacts with a mobile application by using finger gestures with the point change that are detected by the Adaboost algorithm. As a result, the proposed fingertip detection method is very effective under varying lighting conditions and against complex backgrounds, and mobile applications can be controlled by the proposed finger gesturebased mobile user interface system.