nils-herrmann/clean_scirepeval huggingface dataset:
Parameter Hub: a Rack-Scale Parameter Server for Distributed Deep Neural Network Training

Distributed deep neural network (DDNN) training constitutes an increasingly important workload that frequently runs in the cloud. Larger DNN models and faster compute engines are shifting DDNN training bottlenecks from computation to communication. This paper characterizes DDNN training to precisely pinpoint these bottlenecks. We found that timely training requires high performance parameter servers (PSs) with optimized network stacks and gradient processing pipelines, as well as server and network hardware with balanced computation and communication resources. We therefore propose PHub, a high performance multi-tenant, rack-scale PS design. PHub co-designs the PS software and hardware to accelerate rack-level and hierarchical cross-rack parameter exchange, with an API compatible with many DDNN training frameworks. PHub provides a performance improvement of up to 2.7x compared to state-of-the-art cloud-based distributed training techniques for image classification workloads, with 25% better throughput per dollar.
ProvUSB: Block-level Provenance-Based Data Protection for USB Storage Devices

Defenders of enterprise networks have a critical need to quickly identify the root causes of malware and data leakage. Increasingly, USB storage devices are the media of choice for data exfiltration, malware propagation, and even cyber-warfare. We observe that a critical aspect of explaining and preventing such attacks is understanding the provenance of data (i.e., the lineage of data from its creation to current state) on USB devices as a means of ensuring their safe usage. Unfortunately, provenance tracking is not offered by even sophisticated modern devices. This work presents ProvUSB, an architecture for fine-grained provenance collection and tracking on smart USB devices. ProvUSB maintains data provenance by recording reads and writes at the block layer and reliably identifying hosts editing those blocks through attestation over the USB channel. Our evaluation finds that ProvUSB imposes a one-time 850 ms overhead during USB enumeration, but approaches nearly-bare-metal runtime performance (90% of throughput) on larger files during normal execution, and less than 0.1% storage overhead for provenance in real-world workloads. ProvUSB thus provides essential new techniques in the defense of computer systems and USB storage devices.
Behavioral and functional analysis of mouse phenotype: SHIRPA, a proposed protocol for comprehensive phenotype assessment

For an understanding of the aberrant biology seen in mouse mutations and identification of more subtle phenotype variation, there is a need for a full clinical and pathological characterization of the animals. Although there has been some use of sophisticated techniques, the majority of behavioral and functional analyses in mice have been qualitative rather than quantitative in nature. There is, however, no comprehensive routine screening and testing protocol designed to identify and characterize phenotype variation or disorders associated with the mouse genome. We have developed the SHIRPA procedure to characterize the phenotype of mice in three stages. The primary screen utilizes standard methods to provide a behavioral and functional profile by observational assessment. The secondary screen involves a comprehensive behavioral assessment battery and pathological analysis. These protocols provide the framework for a general phenotype assessment that is suitable for a wide range of applications, including the characterization of spontaneous and induced mutants, the analysis of transgenic and gene-targeted phenotypes, and the definition of variation between strains. The tertiary screening stage described is tailored to the assessment of existing or potential models of neurological disease, as well as the assessment of phenotypic variability that may be the result of unknown genetic influences. SHIRPA utilizes standardized protocols for behavioral and functional assessment that provide a sensitive measure for quantifying phenotype expression in the mouse. These paradigms can be refined to test the function of specific neural pathways, which will, in turn, contribute to a greater understanding of neurological disorders.
A Model of Intercultural Communication Competence

chology Today, March. Sherif, C. W., Sherif, W., and Nebergall, R. (1965). Attitude and Altitude Change. Philadelphia: W. B. Saunders. Stewart, E. C., and Bennett, M. J. (1991). American Cultural Patterns. Yarmouth,  Tai, E. (1986). Modification of the Western Approach to Intercultural Communication for the Japanese Context. Unpublished master's thesis, Portland State University, Portland, Oregon. Thaler, A. (1970). Future Shock.  Bantam. Ursin, H. (1978). "Activation, Coping and Psychosomatics." In E. Baade, S. Levine, and H. Ursin (Eds ) Psychobiology of Stress: A Study of Coping Men.  A Model of Intercultural Communication Competence
Building secure healthcare services using OAuth 2.0 and JSON web token in IOT cloud scenario

OAuth 2.0 is a delegated authorization framework enabling secure authorization for applications running on various kinds of platforms. In healthcare services, OAuth allows the patient (resource owner) seeking real time clinical care to authorize automatic monthly payments from his bank account (resource server) without the patient being required to supply his credentials to the clinic (client app). OAuth 2.0 achieves this with the help of tokens issued by an authorization server which enables validated access to a protected resource. To ensure security, access tokens have an expiry time and are short-lived. So the clinical app may use a refresh token to obtain a new access token to cash monthly payments for rendering real time health care services. Refresh tokens need secure storage to ensure they are not leaked, since any malicious party can use them to obtain new access and refresh tokens. Since OAuth 2.0 has dropped signatures and relies completely on SSL/TLS, it is vulnerable to phishing attack when accessing interoperable APIs. In this paper, we develop an approach that combines JSON web token (JWT) with OAuth 2.0 to request an OAuth access token from authorization server when a client wishes to utilize a previous authentication and authorization. Experimental evaluation confirms that the proposed scheme is practically efficient, removes secure storage overhead by removing the need to have or store refresh token, uses signature and prevents different security attacks which is highly desired in health care services using an IOT cloud platform.
Close partner as sculptor of the ideal self: behavioral affirmation and the Michelangelo phenomenon.

This work incorporates concepts from the behavioral confirmation tradition, self tradition, and interdependence tradition to identify an interpersonal process termed the Michelangelo phenomenon. The Michelangelo phenomenon describes the means by which the self is shaped by a close partner's perceptions and behavior. Specifically, self movement toward the ideal self is described as a product of partner affirmation, or the degree to which a partner's perceptions of the self and behavior toward the self are congruent with the self's ideal. The results of 4 studies revealed strong associations between perceived partner affirmation and self movement toward the ideal self, using a variety of participant populations and measurement methods. In addition, perceived partner affirmation--particularly perceived partner behavioral affirmation--was strongly associated with quality of couple functioning and stability in ongoing relationships.
Food cravings in food addiction: exploring a potential cut-off value of the Food Cravings Questionnaire-Trait-reduced

The Food Cravings Questionnaires are among the most often used measures for assessing the frequency and intensity of food craving experiences. However, there is a lack of studies that have examined specific cut-off scores that may indicate pathologically elevated levels of food cravings.



Receiver-Operating-Characteristic analysis was used to determine sensitivity and specificity of scores on the Food Cravings Questionnaire-Trait-reduced (FCQ-T-r) for discriminating between individuals with (n = 43) and without (n = 389) "food addiction" as assessed with the Yale Food Addiction Scale 2.0.



A cut-off score of 50 on the FCQ-T-r discriminated between individuals with and without "food addiction" with high sensitivity (85%) and specificity (93%).



FCQ-T-r scores of 50 and higher may indicate clinically relevant levels of trait food craving.
Sleep Dynamic Therapy for Cerro Grande Fire evacuees with posttraumatic stress symptoms: a preliminary report.

Sleep disturbance is common among disaster survivors with posttraumatic stress symptoms but is rarely addressed as a primary therapeutic target. Sleep Dynamic Therapy (SDT), an integrated program of primarily evidence-based, nonpharmacologic sleep medicine therapies coupled with standard clinical sleep medicine instructions, was administered to a large group of fire evacuees to treat posttraumatic insomnia and nightmares and determine effects on posttraumatic stress severity.



The trial was an uncontrolled, prospective pilot study of SDT for 66 adult men and women, 10 months after exposure to the Cerro Grande Fire. SDT was provided to the entire group in 6, weekly, 2-hour sessions. Primary and secondary outcomes included validated scales for insomnia, nightmares, posttraumatic stress, anxiety, and depression, assessed at 2 pretreatment baselines on average 8 weeks apart, weekly during treatment, posttreatment, and 12-week follow-up.



Sixty-nine participants completed both pretreatment assessment, demonstrating small improvement in symptoms prior to starting SDT. Treatment and posttreatment assessments were completed by 66 participants, and 12-week follow-up was completed by 59 participants. From immediate pretreatment (second baseline) to posttreatment, all primary and secondary scales decreased significantly (all p values < .0001) with consistent medium-sized effects (Cohen's d = 0.29 to 1.09), and improvements were maintained at follow-up. Posttraumatic stress disorder subscales demonstrated similar changes: intrusion (d = 0.56), avoidance (d = 0.45), and arousal (d = 0.69). Fifty-three patients improved, 10 worsened, and 3 reported no change in posttraumatic stress.



In an uncontrolled pilot study, chronic sleep symptoms in fire disaster evacuees were treated with SDT, which was associated with substantive and stable improvements in sleep disturbance, posttraumatic stress, anxiety, and depression 12 weeks after initiating treatment.
Asymmetric Actor Critic for Image-Based Robot Learning

Deep reinforcement learning (RL) has proven a powerful technique in many sequential decision making domains. However, Robotics poses many challenges for RL, most notably training on a physical system can be expensive and dangerous, which has sparked significant interest in learning control policies using a physics simulator. While several recent works have shown promising results in transferring policies trained in simulation to the real world, they often do not fully utilize the advantage of working with a simulator. In this work, we exploit the full state observability in the simulator to train better policies which take as input only partial observations (RGBD images). We do this by employing an actor-critic training algorithm in which the critic is trained on full states while the actor (or policy) gets rendered images as input. We show experimentally on a range of simulated tasks that using these asymmetric inputs significantly improves performance. Finally, we combine this method with domain randomization and show real robot experiments for several tasks like picking, pushing, and moving a block. We achieve this simulation to real world transfer without training on any real world data. Videos of these experiments can be found at www.goo.gl/b57WTs.
NeuroPlace: making sense of a place

The ability to detect mental states, whether relaxation or stressed, would be useful in categorizing places according to their impact on our brains and many other domains. Newly available, affordable and dry-electrode devices make electroencephalography headsets (EEG) feasible to use outside the lab, for example in open spaces and shopping malls. The purpose of this pervasive experimental manipulation is to analyze brain signals in order to label outdoor places according to how users perceive them with a focus on ---relaxing and ---stressful mental states. That is, when the user is experiencing tranquil brain waves or not when visiting a particular place. This paper demonstrates the potential of exploiting the temporal structure of EEG signals in making sense of outdoor places. The EEG signals induced by the place stimuli are analyzed and exploited to distinguish what we refer to as a place signature.
A nonlinear impact: evidences of causal effects of social media on market prices

We provide empirical evidence that suggests social media and stock markets have a nonlinear causal relationship. We take advantage of an extensive data set composed of social media messages related to DJIA index components. By using information-theoretic measures to cope for possible nonlinear causal coupling between social media and stock markets systems, we point out stunning differences in the results with respect to linear coupling. Two main conclusions are drawn: First, social media significant causality on stocks’ returns are purely nonlinear in most cases; Second, social media dominates the directional coupling with stock market, an effect not observable within linear modeling. Results also serve as empirical guidance on model adequacy in the investigation of sociotechnical and financial systems.
Failure to Demonstrate That Playing Violent Video Games Diminishes Prosocial Behavior

Past research has found that playing a classic prosocial video game resulted in heightened prosocial behavior when compared to a control group, whereas playing a classic violent video game had no effect. Given purported links between violent video games and poor social behavior, this result is surprising. Here our aim was to assess whether this finding may be due to the specific games used. That is, modern games are experienced differently from classic games (more immersion in virtual environments, more connection with characters, etc.) and it may be that playing violent video games impacts prosocial behavior only when contemporary versions are used.



Experiments 1 and 2 explored the effects of playing contemporary violent, non-violent, and prosocial video games on prosocial behavior, as measured by the pen-drop task. We found that slight contextual changes in the delivery of the pen-drop task led to different rates of helping but that the type of game played had little effect. Experiment 3 explored this further by using classic games. Again, we found no effect.



We failed to find evidence that playing video games affects prosocial behavior. Research on the effects of video game play is of significant public interest. It is therefore important that speculation be rigorously tested and findings replicated. Here we fail to substantiate conjecture that playing contemporary violent video games will lead to diminished prosocial behavior.
Latent Semantic Analysis Parameters for Essay Evaluation using Small-Scale Corpora

Some previous studies (e.g. that carried out by Van Bruggen et al. in 2004) have pointed to a need for additional research in order to firmly establish the usefulness of LSA (latent semantic analysis) parameters for automatic evaluation of academic essays. The extreme variability in approaches to this technique makes it difficult to identify the most efficient parameters and the optimum combination. With this goal in mind, we conducted a high spectrum study to investigate the efficiency of some of the major LSA parameters in small-scale corpora. We used two specific domain corpora that differed in the structure of the text (one containing only technical terms and the other with more tangential information). Using these corpora we tested different semantic spaces, formed by applying different parameters and different methods of comparing the texts. Parameters varied included weighting functions (Log-IDF or Log-Entropy), dimensionality reduction (truncating the matrices after SVD to a set percentage of dimensions), methods of forming pseudo-documents (vector sum and folding-in) and measures of similarity (cosine or Euclidean distances). We also included two groups of essays to be graded, one written by experts and other by non-experts. Both groups were evaluated by three human graders and also by LSA. We extracted the correlations of each LSA condition with human graders, and conducted an ANOVA to analyse which parameter combination correlates best. Results suggest that distances are more efficient in academic essay evaluation than cosines. We found no clear evidence that the classical LSA protocol works systematically better than some simpler version (the classical protocol achieves the best performance only for some combinations of parameters in a few cases), and found that the benefits of reducing dimensionality arise only when the essays are introduced into semantic spaces using the folding-in method. Address correspondence to: José Antonio León,  Autónoma de Madrid, Campus de Cantoblanco, 28049 Madrid,   joseantonio.leon@uam.es Journal of Quantitative Linguistics 2010, Volume 17, Number 1, pp. 1–29 DOI: 10.1080/09296170903395890 0929-6174/10/17010001 2010 Taylor & Francis
DESIGN OF INTERNAL MODEL CONTROLLER-BASED PID CONTROLLER

The Internal Model Control (IMC) is a transparent framework for designing and tuning the controller. The proportional-integral (PI) and proportional-integral derivative (PID) controllers have ability to meet most of the control objectives and this led to their widespread acceptance in the control industry. In this paper the IMC-based PID controller is designed. IMC-based PID tuning method is a trade-off between closed-loop performance and robustness to model inaccuracies achieved with a single tuning parameter λ. The IMC-PID controller shows good set-point tracking property. In this paper, Robust stability synthesis of a class of uncertain parameter varying firstorder time-delay systems is presented. The output response characteristics using IMC based PID controller along with characteristics using automatic PID tuner are compared. The performance of IMC based PID for both stable, unstable as well as for the processes with time delay is studied and discussed. Various Order reduction techniques are utilized to reduce higher order polynomial into smaller order transfer function. This paper presents results of the implementation of an Internal Model Control (IMC) based PID controller for the level control application to meet robust performance and to achieve the set point tracking and disturbance rejection.
Virtual View Generation for 3D Digital Video

systems use digital models to provide interactive viewing. We present a 3D digital video system that attempts to provide the same capabilities for actual performances such as dancing. Recreating the original dynamic scene in 3D, the system allows photorealistic interactive playback from arbitrary viewpoints using video streams of a given scene from multiple perspectives. V irtual reality can become a medium of great usefulness in entertainment and education if it can incorporate recordings of actual events. While much work has gone into creating synthetic environments that correspond to counterparts in the real world, few have attempted to incorporate real people and events into such environments. To achieve this, an event of interest must be truthfully captured by real-time sensors such as video. From this recording, faithful digital replications must then be created such that the original performances can be presented using standard computer graphics methods and viewed from arbitrary perspectives. We present a system for generating and replaying photorealistic 3D digital video sequences of real events and performances. 3D video embodies the truthfulness of video recordings and the inter-activity of 3D graphics . This system employs Multiple Perspective Interactive Video (MPI-Video), 1 an infrastructure for the analysis and management of, and interactive access to, multiple video cameras monitoring a dynamically evolving scene such as a football game. The problem of virtual view creation, or view synthesis or interpolation of real scenes, has received increasing attention in recent years. Current approaches divide into two classes: image-based and model-based. Image-domain methods employ warping or morphing techniques to interpolate intermediate views from real images. Model-based methods first recover the geometry of the real scene; the resulting 3D model can then be rendered from desired viewpoints. Our method belongs to the latter class. Image-based methods The best-known image-domain method is Apple's QuickTime VR. 2 By capturing the 360-degree views (cylindrical panoramic images) of an environment from a fixed position, you can interactively adjust view orientation by rendering the corresponding portion of the panorama. Other approaches use image warping. Chen and Williams 3 determined camera transformations with pixel correspondences, then used morphing to generate intermediate views. Skerjanc and Liu 4 used known camera positions to obtain depth information and generate virtual views. Chang and Zakhor 5 obtained depth information by using an uncalibrated camera that " scans " a stationary scene and transforms points on camera image planes onto the plane of the …