Miracle-dz/UniFAR-FTUs huggingface dataset:
Non-strict cache coherence: exploiting data-race tolerance in emerging applications

Software distributed shared memory (DSM) platforms on networks of workstations tolerate large network latencies by employing one of several weak memory consistency models. Data-race tolerant applications, such as Genetic Algorithms (GAs), Probabilistic Inference, etc., offer an additional degree of freedom to tolerate network latency: they do not synchronize shared memory references, and behave correctly when supplied outdated shared data. However, these algorithms often have a high communication-to-computation ratio and can flood the network with messages in the presence of large message delays. We study the performance of controlled asynchronous implementations of these algorithms via the use of our previously proposed blocking Global Read memory access primitive. Global Read implements non-strict cache coherence by guaranteeing to return to the reader a shared datum value from within a specified staleness range. Experiments on an IBM SP2 multicomputer with an Ethernet show significant performance improvements for controlled asynchronous implementations. On a lightly loaded Ethernet network, most of the GA benchmarks see 30% to 40% improvement over the best competitor for 2 to 16 processors, while two of the Probabilistic Inference benchmarks see more than 80% improvement for 2 processors. As the network load increases, the benefits of non-strict cache coherence increase significantly.
Characteristics of Alternating Current Corona Discharge Pulses and Its Radio Interference Level in a Coaxial Wire-Cylinder Gap

Alternating current (ac) corona discharge characteristics are studied by using a small corona cage with different applied ac voltages, where the corona cage is located in a 5-m anechoic chamber to avoid the external electromagnetic interference. Characteristic parameters of ac corona pulses are analyzed statistically, such as peak values of primary and secondary pulses in positive half cycle, the interval of secondary pulses, average amplitude, and repetition frequency in both half cycles. Then, the experimental results are explained by using discharge physical mechanism. Besides, the radio interference (RI) current of typical frequencies are measured simultaneously, and the relationship between pulses and 0.5-MHz RI current is discussed.
Mediated Leader Effects: The Impact of Newspapers’ Portrayal of Party Leadership on Electoral Support

Conventional wisdom holds that party leaders matter in democratic elections. As very few voters have direct contact with party leaders, media are voters’ primary source of information about these leaders and, thus, the likely origin of leader effects on party support. Our study focuses on these supposed electoral effects of the media coverage of party leaders. We examine the positive and negative effects of specific leadership images in Dutch newspapers on vote intentions. To this end, we combine an extensive automated content analysis of leadership images in the media with a panel data set, the Dutch 1Vandaag Opinion Panel (1VOP), consisting of more than fifty thousand unique respondents and 110 waves of interviews conducted between September 2006 and September 2012. The results confirm that media coverage of party leaders’ character traits affects voters: Positive mediated leadership images increase support for the leader’s party, while negative images decrease this support. However, this influence is not unconditional: During campaign periods, positive leadership images have a stronger effect, while negative images no longer have an impact on subsequent vote intentions.
What works in implementation of integrated care programs for older adults with complex needs? A realist review

Abstract Purpose A realist review of the evaluative evidence was conducted on integrated care (IC) programs for older adults to identify key processes that lead to the success or failure of these programs in achieving outcomes such as reduced healthcare utilization, improved patient health, and improved patient and caregiver experience. Data sources International academic literature was searched in 12 indexed, electronic databases and gray literature through internet searches, to identify evaluative studies. Study selection Inclusion criteria included evaluative literature on integrated, long-stay health and social care programs, published between January 1980 and July 2015, in English. Data extraction Data were extracted on the study purpose, period, setting, design, population, sample size, outcomes, and study results, as well as explanations of mechanisms and contextual factors influencing outcomes. Results of data synthesis A total of 65 articles, representing 28 IC programs, were included in the review. Two context-mechanism-outcome configurations (CMOcs) were identified: (i) trusting multidisciplinary team relationships and (ii) provider commitment to and understanding of the model. Contextual factors such as strong leadership that sets clear goals and establishes an organizational culture in support of the program, along with joint governance structures, supported team collaboration and subsequent successful implementation. Furthermore, time to build an infrastructure to implement and flexibility in implementation, emerged as key processes instrumental to success of these programs. Conclusions This review included a wide range of international evidence, and identified key processes for successful implementation of IC programs that should be considered by program planners, leaders and evaluators.
Rac1-mediated membrane raft localization of PI3K/p110β is required for its activation by GPCRs or PTEN loss

We aimed to understand how spatial compartmentalization in the plasma membrane might contribute to the functions of the ubiquitous class IA phosphoinositide 3-kinase (PI3K) isoforms, p110α and p110β. We found that p110β localizes to membrane rafts in a Rac1-dependent manner. This localization potentiates Akt activation by G-protein-coupled receptors (GPCRs). Thus genetic targeting of a Rac1 binding-deficient allele of p110β to rafts alleviated the requirement for p110β-Rac1 association for GPCR signaling, cell growth and migration. In contrast, p110α, which does not play a physiological role in GPCR signaling, is found to reside in nonraft regions of the plasma membrane. Raft targeting of p110α allowed its EGFR-mediated activation by GPCRs. Notably, p110β dependent, PTEN null tumor cells critically rely upon raft-associated PI3K activity. Collectively, our findings provide a mechanistic account of how membrane raft localization regulates differential activation of distinct PI3K isoforms and offer insight into why PTEN-deficient cancers depend on p110β. DOI: http://dx.doi. org/10.7554/eLife.17635. 001
Long noncoding RNA ENSRNOG00000037522 is involved in the podocyte epithelial-mesenchymal transition in diabetic rats

Diabetic nephropathy (DN) is one of the most common complications associated with type I and II diabetes mellitus. Long noncoding RNAs (lncRNAs) have been implicated in various physiological and pathological processes, and recent evidence has demonstrated that they are involved in the process of the epithelial-mesenchymal transition (EMT). In the present study, the potential functions of lncRNA ENSRNOG00000037522 during the EMT process in DN were investigated. The results identified that the level of the lncRNA ENSRNOG00000037522 was significantly increased in kidney tissues collected from rats with streptozocin (STZ)-induced DN accompanied by impairment of the glomerular podocytes. It was further demonstrated that the silencing of lncRNA ENSRNOG00000037522 by small interfering RNA transfection partially restored the podocyte function. In addition, knockdown of lncRNA ENSRNOG00000037522 repaired the damage to the podocytes via regulating vimentin, podocalyxin-like 1 and nephrin expression. In conclusion, the current results demonstrated that lncRNA ENSRNOG00000037522 serves a pivotal role in the podocyte EMT in DN.
New Perspectives on Droop Control in AC MicroGrid

—Virtual impedance, angle droop and frequency droop control play important roles in maintaining system stability, and load sharing among distributed generators (DGs) in microgrid. These approaches have been developed into three totally independent concepts, but present strong relevance. In this letter, their similarities and differences are significantly revealed. Some new findings are established as follows: 1) angle droop control is intrinsically a virtual impedance method; 2) virtual impedance method can also be regarded as a special frequency droop control with a power derivative feedback; 3) the combination of virtual impedance method and frequency droop control is equivalent to the proportional–derivative (PD) type frequency droop, which is introduced to enhance the power oscillation damping. As a whole, these analogous relationships provide the new insight into the design of these three controllers.
Action-grounded push affordance bootstrapping of unknown objects

When it comes to learning how to manipulate objects from experience with minimal prior knowledge, robots encounter significant challenges. When the objects are unknown to the robot, the lack of prior object models demands a robust feature descriptor such that the robot can reliably compare objects and the effects of their manipulation. In this paper, using an experimental platform that gathers 3-D data from the Kinect RGB-D sensor, as well as push action trajectories from a tracking system, we address these issues using an action-grounded 3-D feature descriptor. Rather than using pose-invariant visual features, as is often the case with object recognition, we ground the features of objects with respect to their manipulation, that is, by using shape features that describe the surface of an object relative to the push contact point and direction. Using this setup, object push affordance learning trials are performed by a human and both pre-push and post-push object features are gathered, as well as push action trajectories. A self-supervised multi-view online learning algorithm is employed to bootstrap both the discovery of affordance classes in the post-push view, as well as a discriminative model for predicting them in the pre-push view. Experimental results demonstrate the effectiveness of self-supervised class discovery, class prediction and feature relevance determination on a collection of unknown objects.
An Exploration of Factors Associated With Ageist Stereotype Threat in a Medical Setting

Objectives Experiencing stereotype threat in a medical setting may be triggered by routine clinical activities, and may be detrimental to healthcare processes and outcomes. This study estimated the prevalence of, and identified factors associated with, reporting ageist stereotype threat in a medical setting using a nationally representative dataset. Methods Participants were community-dwelling adults aged 50 and older who had visited the doctor at least once in the past 2 years (n = 1,662). We analyzed data from the Health and Retirement Study using multivariate logistic regression. Results 8.31% of participants felt worry or fear that they were judged by medical staff because of their age. Previous experiences of age discrimination (adjusted odds ratio [AOR] = 2.47, p < .01), poorer self-perceptions of aging (AOR = 1.34, p < .05), and having greater control over one's health (AOR = 0.84, p < .05) were associated with reporting stereotype threat because of age. Discussion Future research should investigate if measures to reduce age discrimination and to improve self-perceptions of aging and individual control over health protect against experiencing ageist stereotype threat in healthcare settings.
Episodic Simulation of Future Events

This article focuses on the neural and cognitive processes that support imagining or simulating future events, a topic that has recently emerged in the forefront of cognitive neuroscience. We begin by considering concepts of simulation from a number of areas of psychology and cognitive neuroscience in order to place our use of the term in a broader context. We then review neuroimaging, neuropsychological, and cognitive studies that have examined future‐event simulation and its relation to episodic memory. This research supports the idea that simulating possible future events depends on much of the same neural machinery, referred to here as a core network, as does remembering past events. After discussing several theoretical accounts of the data, we consider applications of work on episodic simulation for research concerning clinical populations suffering from anxiety or depression. Finally, we consider other aspects of future‐oriented thinking that we think are related to episodic simulation, including planning, prediction, and remembering intentions. These processes together comprise what we have termed “the prospective brain,” whose primary function is to use past experiences to anticipate future events.
Adipose-derived stem cells in orthopaedic pathologies

Introduction To examine the current literature regarding the clinical application of adipose-derived stem cells (ADSCs) for the management of orthopaedic pathologies. Sources of data MEDLINE,SCOPUS, CINAHL and EMBASE (1950 to April 14, 2017) were searched by two independent investigators for articles published in English. Reviews, meta-analyses, expert opinions, case reports, mini case series and editorials were excluded. Furthermore, we excluded animal studies, cadaveric studies and in vitro studies. Areas of agreement ADSCs seem to produce excellent clinical results. However, the length and modalities of follow-up in the different conditions are extremely variable. Nevertheless, it appears that the use of adipose-derived stem cells is associated with subjective and objective clinical improvements and minimal complication rates. Areas of controversy None of the studies identified is a randomized double-blinded trial, and most of the selected studies present major limitations, and different methods, confounding the results of our review. Growing points It is necessary to conduct more and better studies to ascertain whether ADSCs really play a role in orthopaedic surgery with particular attention to ADSCs harvesting method, type of administration and the conditions treated. Areas timely for developing research The current literature regarding the use of ADSCs for orthopaedic pathologies is limited. At present, long-term safety is the biggest challenge of ADSCs based regenerative medicine. Level of evidence Level IV-Study of Level I, II, III, IV.
STT-MRAM for embedded memory applications from eNVM to last level cache

Spin-Transfer-Torque Magnetic Random Access Memory (STT-MRAM) is emerging as a leading candidate for a variety of embedded memory applications ranging from embedded NVM to working memory and last level cache. In this paper, we review recent breakthroughs that have brought perpendicular STT-MRAM to the cusp of mass production.
An error-tuned model for sensorimotor learning

Current models of sensorimotor control posit that motor commands are generated by combining multiple modules which may consist of internal models, motor primitives or motor synergies. The mechanisms which select modules based on task requirements and modify their output during learning are therefore critical to our understanding of sensorimotor control. Here we develop a novel modular architecture for multi-dimensional tasks in which a set of fixed primitives are each able to compensate for errors in a single direction in the task space. The contribution of the primitives to the motor output is determined by both top-down contextual information and bottom-up error information. We implement this model for a task in which subjects learn to manipulate a dynamic object whose orientation can vary. In the model, visual information regarding the context (the orientation of the object) allows the appropriate primitives to be engaged. This top-down module selection is implemented by a Gaussian function tuned for the visual orientation of the object. Second, each module's contribution adapts across trials in proportion to its ability to decrease the current kinematic error. Specifically, adaptation is implemented by cosine tuning of primitives to the current direction of the error, which we show to be theoretically optimal for reducing error. This error-tuned model makes two novel predictions. First, interference should occur between alternating dynamics only when the kinematic errors associated with each oppose one another. In contrast, dynamics which lead to orthogonal errors should not interfere. Second, kinematic errors alone should be sufficient to engage the appropriate modules, even in the absence of contextual information normally provided by vision. We confirm both these predictions experimentally and show that the model can also account for data from previous experiments. Our results suggest that two interacting processes account for module selection during sensorimotor control and learning.
Errata for Three Papers (2004-05) on Fixed-Priority Scheduling with Self-Suspensions

The purpose of this article is to (i) highlight the flaws in three previously published works [Audsley, 2004a; Audsley, 2004b; Bletsas, 2005] on the worst-case response time analysis for tasks with self-suspensions and (ii) provide straightforward fixes for those flaws, hence rendering the analysis safe.
HEVC intra features for human detection

Object detection relies on appropriate features extracted from images or video. Typically, features are extracted in the pixel domain, after full decoding. In this paper, we introduce a set of features derived from HEVC Intra coding syntax elements — block size, intra prediction modes, and transform coefficient levels — which enable human detection without full bitstream decoding. When used with a properly trained linear Support Vector Machine (SVM), the proposed features achieve competitive accuracy on human detection with widely used Histogram of Oriented Gradients (HOG) features over a range of Quantization Parameter (QP) values.
Genetic drift and selection in many-allele range expansions

We experimentally and numerically investigate the evolutionary dynamics of four competing strains of E. coli with differing expansion velocities in radially expanding colonies. We compare experimental measurements of the average fraction, correlation functions between strains, and the relative rates of genetic domain wall annihilations and coalescences to simulations modeling the population as a one-dimensional ring of annihilating and coalescing random walkers with deterministic biases due to selection. The simulations reveal that the evolutionary dynamics can be collapsed onto master curves governed by three essential parameters: (1) an expansion length beyond which selection dominates over genetic drift; (2) a characteristic angular correlation describing the size of genetic domains; and (3) a dimensionless constant quantifying the interplay between a colony’s curvature at the frontier and its selection length scale. We measure these parameters with a new technique that precisely measures small selective differences between spatially competing strains and show that our simulations accurately predict the dynamics with no additional fitting. Our results suggest that that the random walk model can act as a useful predictive tool when describing the evolutionary dynamics of range expansions composed of an arbitrary number of competing alleles with different fitnesses. Author summary Population expansions occur naturally during the spread of invasive species and have played a role in our evolutionary history when many of our ancestors expanded out of Africa. We use a colony of bacteria expanding into unoccupied, nutrient-rich territory on an agar plate as a model system to explore how an expanding population’s spatial structure impacts its evolutionary dynamics. Spatial structure is present in expanding microbial colonies because daughter cells migrate only a small distance away from their mothers each generation. Generally, the constituents of expansions occurring in nature and in the lab have different genetic compositions (genotypes, or alleles if a single gene differs), each instilling different fitnesses, which compete to proliferate at the frontier. Here, we show that a random-walk model can accurately predict the dynamics of four expanding strains of E. coli with different fitnesses; each strain represents a competing allele. Our results can be extended to describe any number of competing genotypes with different fitnesses in a naturally occurring expansions. Our model can also be used to precisely measure small selective differences between spatially competing genotypes in controlled laboratory settings.
Stimulating at the right time: phase-specific deep brain stimulation

See Moll and Engel (doi:10.1093/aww308) for a scientific commentary on this article. Brain regions dynamically engage and disengage with one another to execute everyday actions from movement to decision making. Pathologies such as Parkinson’s disease and tremor emerge when brain regions controlling movement cannot readily decouple, compromising motor function. Here, we propose a novel stimulation strategy that selectively regulates neural synchrony through phase-specific stimulation. We demonstrate for the first time the therapeutic potential of such a stimulation strategy for the treatment of patients with pathological tremor. Symptom suppression is achieved by delivering stimulation to the ventrolateral thalamus, timed according to the patient’s tremor rhythm. Sustained locking of deep brain stimulation to a particular phase of tremor afforded clinically significant tremor relief (up to 87% tremor suppression) in selected patients with essential tremor despite delivering less than half the energy of conventional high frequency stimulation. Phase-specific stimulation efficacy depended on the resonant characteristics of the underlying tremor network. Selective regulation of neural synchrony through phase-locked stimulation has the potential to both increase the efficiency of therapy and to minimize stimulation-induced side effects.
Implementing a National Tractor Safety Program: Using “Whole System in a Room” to Mobilize Partners and Implement Solutions

ABSTRACT Fatalities due to tractor overturns have long plagued the US farm community. Constituting 20% of agricultural fatalities, tractor overturns contribute significantly to high rates of fatal injuries. In the past, many efforts have been directed toward reducing tractor overturns, with one successful US-based program offering rebates to farmers who retrofit their tractors with rollover protective structures (ROPS). In an effort to expand the program, the National Tractor Safety Coalition was formed. This coalition hosted a “Whole System in the Room” workshop to bring 50 stakeholders together. During this workshop, participants worked together to identify a common vision for the future of tractor safety and ROPS programs and commit to action. At the close of the workshop, coalition members set out to begin work on 100 short- and long-term commitments to begin implementing a National ROPS Rebate Program.
Review of Power Sharing Control Strategies for Islanding Operation of AC Microgrids

1 Abstract – Microgrid is a new concept for future energy distribution system that enables renewable energy integration. It generally consists of multiple distributed generators (DGs) that are usually interfaced to the grid through power inverters. For the islanding operation of AC microgrids, two important tasks are to share the load demand among multiple parallel connected inverters proportionately and maintain the voltage and frequency stabilities. This paper reviews and categorizes various approaches of power sharing control principles. Simultaneously, the control schemes are graphically illustrated. Moreover, various control approaches are compared in terms of their respective advantages and disadvantages. Finally, the paper presents the future trends.