nils-herrmann/clean_scirepeval huggingface dataset:
World of Bits: An Open-Domain Platform for Web-Based Agents

While simulated game environments have greatly accelerated research in reinforcement learning, existing environments lack the open-domain realism of tasks in computer vision or natural language processing, which operate on artifacts created by humans in natural, organic settings. To foster reinforcement learning research in such settings, we introduce the World of Bits (WoB), a platform in which agents complete tasks on the Internet by performing low-level keyboard and mouse actions. The two main challenges are: (i) to curate a diverse set of natural webbased tasks, and (ii) to ensure that these tasks have a well-defined reward structure and are reproducible despite the transience of the web. To tackle this, we develop a methodology in which crowdworkers create tasks defined by natural language questions and provide demonstrations of how to answer the question on real websites using keyboard and mouse; HTTP traffic is cached to create a reproducible offline approximation of the website. Finally, we show that agents trained via behavioral cloning and reinforcement learning can complete a range of web-based tasks.
Occupational therapy interventions for work-related injuries and conditions of the forearm, wrist, and hand: a systematic review.

A systematic review of the literature related to effective occupational therapy interventions in rehabilitation of individuals with work-related forearm, wrist, and hand injuries and illnesses was conducted as part of the Evidence-Based Literature Review Project of the American Occupational Therapy Association. This review provides a comprehensive overview and analysis of 36 studies that addressed many of the interventions commonly used in hand rehabilitation. Findings reveal that the use of occupation-based activities has reasonable yet limited evidence to support its effectiveness. This review supports the premise that many client factors can be positively affected through the use of several commonly used occupational therapy-related modalities and methods. The implications for occupational therapy practice, research, and education and limitations of reviewed studies are also discussed.
Night-to-Day Image Translation for Retrieval-based Localization

Visual localization is a key step in many robotics pipelines, allowing the robot to (approximately) determine its position and orientation in the world. An efficient and scalable approach to visual localization is to use image retrieval techniques. These approaches identify the image most similar to a query photo in a database of geo-tagged images and approximate the query’s pose via the pose of the retrieved database image. However, image retrieval across drastically different illumination conditions, e.g. day and night, is still a problem with unsatisfactory results, even in this age of powerful neural models. This is due to a lack of a suitably diverse dataset with true correspondences to perform end-to-end learning. A recent class of neural models allows for realistic translation of images among visual domains with relatively little training data and, most importantly, without ground-truth pairings. In this paper, we explore the task of accurately localizing images captured from two traversals of the same area in both day and night. We propose ToDayGAN – a modified imagetranslation model to alter nighttime driving images to a more useful daytime representation. We then compare the daytime and translated night images to obtain a pose estimate for the night image using the known 6-DOF position of the closest day image. Our approach improves localization performance by over 250% compared the current state-of-the-art, in the context of standard metrics in multiple categories.
Design and implementation of anti-theft module for ATM machine

Frauds related to the ATM (Automatic Teller Machine) are increasing day by day which is a serious issue. ATM security is used to provide protection against these frauds. Though security is provided for ATM machine, cases of robberies are increasing. Previous technologies provide security within machines for secure transaction, but machine is not neatly protected. The ATM machines are not safe since security provided traditionally were either by using RFID reader or by using security guard outside the ATM. This security is not sufficient because RFID card can be stolen and can be misused for robbery as well as watchman can be blackmailed by the thief. So there is a need to propose new technology which can overcome this problem. This paper proposes a system which aims to design real-time monitoring and controlling system. The system is implemented using Raspberry Pi and fingerprint module which make the system more secure, cost effective and stand alone. For controlling purpose, Embedded Web Server (EWS) is designed using Raspberry Pi which serves web page on which video footage of ATM center is seen and controlled. So the proposed system removes the drawback of manual controlling camera module and door also this system is stand alone and cost effective.
Modelling bone tissue fracture and healing : a review q

This paper reviews the available literature on computational modelling in two areas of bone biomechanics: fracture and healing. Bone is a complex material, with a multiphasic, heterogeneous and anisotropic microstructure. The processes of fracture and healing can only be understood in terms of the underlying bone structure and its mechanical role. Bone fracture analysis attempts to predict the failure of musculoskeletal structures by several possible mechanisms under different loading conditions. However, as opposed to structurally inert materials, bone is a living tissue that can repair itself. An exciting new field of research is being developed to better comprehend these mechanisms and the mechanical behaviour of bone tissue. One of the main goals of this work is to demonstrate, after a review of computational models, the main similarities and differences between normal engineering materials and bone tissue from a structural point of view. We also underline the importance of computational simulations in biomechanics due to the difficulty of obtaining experimental or clinical results.
A two-phase heat spreader for cooling high heat flux sources

A two-phase heat spreader has been developed for cooling high heat flux sources in high-power lasers, high-intensity light-emitting diodes (LEDs), and semiconductor power devices. The heat spreader uses a passive mechanism to cool heat sources with fluxes as high as 5 W/mm2 without requiring any active power consumption for the thermal solution. The prototype is similar to a vapor chamber in which water is injected into an evacuated, air-tight shell. The shell consists of an evaporator plate, a condenser plate and an adiabatic section. The heat source is made from aluminum nitride, patterned with platinum. The heat source contains a temperature sensor and is soldered to a copper substrate that serves as the evaporator. Tests were performed with several different evaporator microstructures at different heat loads. A screen mesh was able to dissipate heat loads of 2 W/mm2, but at unacceptably high evaporator temperatures. For sintered copper powder with a 50 µm particle diameter, a heat load of 8.5 W/mm2 was supported, without the occurrence of dryout. A sintered copper powder surface coated with multi-walled carbon nanotubes (CNT) that were rendered hydrophilic showed a lowered thermal resistance for the device.
Desynchronization: Synthesis of Asynchronous Circuits From Synchronous Specifications

Asynchronous implementation techniques, which measure logic delays at runtime and activate registers accordingly, are inherently more robust than their synchronous counterparts, which estimate worst case delays at design time and constrain the clock cycle accordingly. Desynchronization is a new paradigm to automate the design of asynchronous circuits from synchronous specifications, thus, permitting widespread adoption of asynchronicity without requiring special design skills or tools. In this paper, different protocols for desynchronization are first studied, and their correctness is formally proven using techniques originally developed for distributed deployment of synchronous language specifications. A taxonomy of existing protocols for asynchronous latch controllers, covering, in particular, the four-phase handshake protocols devised in the literature for micropipelines, is also provided. A new controller that exhibits provably maximal concurrency is then proposed, and the performance of desynchronized circuits is analyzed with respect to the original synchronous optimized implementation. Finally, this paper proves the feasibility and effectiveness of the proposed approach by showing its application to a set of real designs, including a complete implementation of the DLX microprocessor architecture
Optimization of energy-constrained wireless powered communication networks with heterogeneous nodes

In this paper, we study wireless networks where nodes have two energy sources, namely a battery and radio frequency (RF) energy harvesting circuitry. We formulate two optimization problems with different objective functions, namely maximizing the sum throughput and maximizing the minimum throughput, for enhanced fairness. Furthermore, we show the generality of the proposed system model through characterizing the conditions under which the two formulated optimization problems can be reduced to the corresponding problems of different known wireless networks, namely, conventional wireless networks (battery-powered) and wireless powered communications networks (WPCNs) with only RF energy harvesting nodes. In addition, we introduce WPCNs with two types of nodes, with and without RF energy harvesting capability, in which the nodes without RF energy harvesting are utilized to enhance the sum throughput, even beyond WPCNs with all energy harvesting nodes. We establish the convexity of all formulated problems which opens room for efficient solution using standard techniques. Our numerical results show that the two types of wireless networks, namely WPCNs with only RF energy harvesting nodes and conventional wireless networks, are considered, respectively, as lower and upper bounds on the performance of the generalized problem setting in terms of the maximum sum throughput and the maxmin throughput. Moreover, the results reveal new insights and throughput-fairness trade-offs unique to our new problem setting. Index Terms Cellular networks, green communications, RF energy harvesting, convex optimization, numerical results. ar X iv :1 60 3. 01 11 5v 1 [ cs .I T ] 3 M ar 2 01 6
Modeling the Dropbox client behavior

Cloud storage systems are currently very popular, generating a large amount of traffic. Indeed, many companies offer this kind of service, including worldwide providers such as Dropbox, Microsoft and Google. These companies, as well as new providers entering the market, could greatly benefit from knowing typical workload patterns that their services have to face in order to develop more cost-effective solutions. However, despite recent analyses of typical usage patterns and possible performance bottlenecks, no previous work investigated the underlying client processes that generate workload to the system. In this context, this paper proposes a hierarchical two-layer model for representing the Dropbox client behavior. We characterize the statistical parameters of the model using passive measurements gathered in 3 different network vantage points. Our contributions can be applied to support the design of realistic synthetic workloads, thus helping in the development and evaluation of new, well-performing personal cloud storage services.
Plasticity in the Working Memory System: Life Span Changes and Response to Injury.

Working memory acts as a key bridge between perception, long-term memory, and action. The brain regions, connections, and neurotransmitters that underlie working memory undergo dramatic plastic changes during the life span, and in response to injury. Early life reliance on deep gray matter structures fades during adolescence as increasing reliance on prefrontal and parietal cortex accompanies the development of executive aspects of working memory. The rise and fall of working memory capacity and executive functions parallels the development and loss of neurotransmitter function in frontal cortical areas. Of the affected neurotransmitters, dopamine and acetylcholine modulate excitatory-inhibitory circuits that underlie working memory, are important for plasticity in the system, and are affected following preterm birth and adult brain injury. Pharmacological interventions to promote recovery of working memory abilities have had limited success, but hold promise if used in combination with behavioral training and brain stimulation. The intense study of working memory in a range of species, ages and following injuries has led to better understanding of the intrinsic plasticity mechanisms in the working memory system. The challenge now is to guide these mechanisms to better improve or restore working memory function.
An adaptive ontology mapping approach with neural network based constraint satisfaction

1 1 This paper has been revised and extended from the authors' previous work [23][24][25].  Ontology mapping seeks to find semantic correspondences between similar elements of different ontologies. It is a key challenge to achieve semantic interoperability in building the Semantic Web. This paper proposes a new generic and adaptive ontology mapping approach, called the PRIOR+, based on propagation theory, information retrieval techniques and artificial intelligence. The approach consists of three major modules, i.e., the IR-based similarity generator, the adaptive similarity filter and weighted similarity aggregator, and the neural network based constraint satisfaction solver. The approach first measures both linguistic and structural similarity of ontologies in a vector space model, and then aggregates them using an adaptive method based on their harmonies, which is defined as an estimator of performance of similarity. Finally to improve mapping accuracy the interactive activation and competition neural network is activated, if necessary, to search for a solution that can satisfy ontology constraints. The experimental results show that harmony is a good estimator of f-measure; the harmony based adaptive aggregation outperforms other aggregation methods; neural network approach significantly boosts the performance in most cases. Our approach is competitive with top ranked systems on benchmark tests at OAEI campaign 2007, and performs the best on real cases in OAEI benchmark tests.
Moderating role of trait aggressiveness in the effects of violent media on aggression.

Three studies were conducted to test the hypothesis that high trait aggressive individuals are more affected by violent media than are low trait aggressive individuals. In Study 1, participants read film descriptions and then chose a film to watch. High trait aggressive individuals were more likely to choose a violent film to watch than were low trait aggressive individuals. In Study 2, participants reported their mood before and after the showing of a violet or nonviolent videotape. High trait aggressive individuals felt more angry after viewing the violent videotape than did low trait aggressive individuals. In Study 3, participants first viewed either a violent or a nonviolent videotape and then competed with an "opponent" on a reaction time task in which the loser received a blast of unpleasant noise. Videotape violence was more likely to increase aggression in high trait aggressive individuals than in low trait aggressive individuals.
Survey of Non-Rigid Registration Tools in Medicine

We catalogue available software solutions for non-rigid image registration to support scientists in selecting suitable tools for specific medical registration purposes. Registration tools were identified using non-systematic search in Pubmed, Web of Science, IEEE Xplore® Digital Library, Google Scholar, and through references in identified sources (n = 22). Exclusions are due to unavailability or inappropriateness. The remaining (n = 18) tools were classified by (i) access and technology, (ii) interfaces and application, (iii) living community, (iv) supported file formats, and (v) types of registration methodologies emphasizing the similarity measures implemented. Out of the 18 tools, (i) 12 are open source, 8 are released under a permissive free license, which imposes the least restrictions on the use and further development of the tool, 8 provide graphical processing unit (GPU) support; (ii) 7 are built on software platforms, 5 were developed for brain image registration; (iii) 6 are under active development but only 3 have had their last update in 2015 or 2016; (iv) 16 support the Analyze format, while 7 file formats can be read with only one of the tools; and (v) 6 provide multiple registration methods and 6 provide landmark-based registration methods. Based on open source, licensing, GPU support, active community, several file formats, algorithms, and similarity measures, the tools Elastics and Plastimatch are chosen for the platform ITK and without platform requirements, respectively. Researchers in medical image analysis already have a large choice of registration tools freely available. However, the most recently published algorithms may not be included in the tools, yet.
Fabrications and Applications of Stimulus-Responsive Polymer Films and Patterns on Surfaces: A Review

In the past two decades, we have witnessed significant progress in developing high performance stimuli-responsive polymeric materials. This review focuses on recent developments in the preparation and application of patterned stimuli-responsive polymers, including thermoresponsive layers, pH/ionic-responsive hydrogels, photo-responsive film, magnetically-responsive composites, electroactive composites, and solvent-responsive composites. Many important new applications for stimuli-responsive polymers lie in the field of nano- and micro-fabrication, where stimuli-responsive polymers are being established as important manipulation tools. Some techniques have been developed to selectively position organic molecules and then to obtain well-defined patterned substrates at the micrometer or submicrometer scale. Methods for patterning of stimuli-responsive hydrogels, including photolithography, electron beam lithography, scanning probe writing, and printing techniques (microcontact printing, ink-jet printing) were surveyed. We also surveyed the applications of nanostructured stimuli-responsive hydrogels, such as biotechnology (biological interfaces and purification of biomacromoles), switchable wettability, sensors (optical sensors, biosensors, chemical sensors), and actuators.
Relations between neighborhood factors, parenting behaviors, peer deviance, and delinquency among serious juvenile offenders.

The present study examined relations among neighborhood structural and social characteristics, parenting practices, peer group affiliations, and delinquency among a group of serious adolescent offenders. The sample of 14-18-year-old boys (N=488) was composed primarily of economically disadvantaged, ethnic-minority youth living in urban communities. The results indicate that weak neighborhood social organization is indirectly related to delinquency through its associations with parenting behavior and peer deviance and that a focus on just 1 of these microsystems can lead to oversimplified models of risk for juvenile offending. The authors also find that community social ties may confer both pro- and antisocial influences to youth, and they advocate for a broad conceptualization of neighborhood social processes as these relate to developmental risk for youth living in disadvantaged communities.
Generalized frequency division multiplexing: Analysis of an alternative multi-carrier technique for next generation cellular systems

Generalized frequency division multiplexing (GFDM) is a new concept that can be seen as a generalization of traditional OFDM. The scheme is based on the filtered multi-carrier approach and can offer an increased flexibility, which will play a significant role in future cellular applications. In this paper we present the benefits of the pulse shaped carriers in GFDM. We show that based on the FFT/IFFT algorithm, the scheme can be implemented with reasonable computational effort. Further, to be able to relate the results to the recent LTE standard, we present a suitable set of parameters for GFDM.
SCface – surveillance cameras face database

In this paper we describe a database of static images of human faces. Images were taken in uncontrolled indoor environment using five video surveillance cameras of various qualities. Database contains 4,160 static images (in visible and infrared spectrum) of 130 subjects. Images from different quality cameras should mimic real-world conditions and enable robust face recognition algorithms testing, emphasizing different law enforcement and surveillance use case scenarios. In addition to database description, this paper also elaborates on possible uses of the database and proposes a testing protocol. A baseline Principal Component Analysis (PCA) face recognition algorithm was tested following the proposed protocol. Other researchers can use these test results as a control algorithm performance score when testing their own algorithms on this dataset. Database is available to research community through the procedure described at www.scface.org .
The determinants of crowdfunding success: A semantic text analytics approach

In the era of the Social Web, crowdfunding has become an increasingly more important channel for entrepreneurs to raise funds from the crowd to support their startup projects. Previous studies examined various factors such as project goals, project durations, and categories of projects that might influence the outcomes of the fund raising campaigns. However, textual information of projects has rarely been studied for analyzing crowdfunding successes. The main contribution of our research work is the design of a novel text analytics-based framework that can extract latent semantics from the textual descriptions of projects to predict the fund raising outcomes of these projects. More specifically, we develop the Domain-Constraint Latent Dirichlet Allocation (DC-LDA) topic model for effective extraction of topical features from texts. Based on two real-world crowdfunding datasets, our experimental results reveal that the proposed framework outperforms a classical LDA-based method in predicting fund raising success by an average of 11% in terms of F1 score. The managerial implication of our research is that entrepreneurs can apply the proposed methodology to identify the most influential topical features embedded in project descriptions, Corresponding author at: School of Information, Renmin University of China, Beijing, 100872, P.R. China.