nils-herrmann/clean_scirepeval huggingface dataset:
N-body Networks: a Covariant Hierarchical Neural Network Architecture for Learning Atomic Potentials

We describe N–body networks, a neural network architecture for learning the behavior and properties of complex many body physical systems. Our specific application is to learn atomic potential energy surfaces for use in molecular dynamics simulations. Our architecture is novel in that (a) it is based on a hierarchical decomposition of the many body system into subsytems (b) the activations of the network correspond to the internal state of each subsystem (c) the “neurons” in the network are constructed explicitly so as to guarantee that each of the activations is covariant to rotations (d) the neurons operate entirely in Fourier space, and the nonlinearities are realized by tensor products followed by Clebsch–Gordan decompositions. As part of the description of our network, we give a characterization of what way the weights of the network may interact with the activations so as to ensure that the covariance property is maintained.
Brave New World: Uncovering Topical Dynamics in the ACL Anthology Reference Corpus Using Term Life Cycle Information

One of the main interests in the analysis of large document collections is to discover domains of discourse that are still actively developing, growing in interest and relevance, at a given point in time, and to distinguish them from those topics that are in stagnation or decline. The present paper describes a terminologically inspired approach to this kind of task. The inputs to the method are a corpus spanning several decades of research in computational linguistics and a set of single-word terms that frequently occur in that corpus. The diachronic development of these terms is modelled by means of term life cycle information, namely the parameters relative frequency and productivity. In a second step, k-means clustering is used to identify groups of terms with similar development patterns. The paper describes a mathematical approach to modelling term productivity and discusses what kind of information can be obtained from this measure. The results of the clustering experiment are promising and well motivate future research.
Realization of Kalman filter in GNU radio

The paper develops a basic idea pertaining to Kalman filters. The interest in Kalman filter is motivated by the wide variety of applications it provide. The Kalman filter is an iterative filter which considers a series of measurements (that contains statistical noise) over time, and then estimates the unknown variable. The primary concern is to design a block in GNU Radio for the operation of Kalman filtering. In this work, a block has been created and we explored the filtering algorithm using three different key in mechanisms — 1)a continuous signal dataset, 2)an open flight tracker dataset, 3)a generated dataset. The first mechanism include providing a continuous sinusoidal signal source to the filter block. Then, an open aircraft dataset used in tracking the position of flight was considered and had been fed to experiment the Kalman filter block. Further, a dataset generated by considering the practical possibilities of a giant moving object was input to the block. The result of all the three mechanisms confirm that there is an effective noise reduction in position tracking, on using Kalman filtering algorithm.
Chlamydia trachomatis infections: screening, diagnosis, and management.

Chlamydia trachomatis is a gram-negative bacterium that infects the columnar epithelium of the cervix, urethra, and rectum, as well as nongenital sites such as the lungs and eyes. The bacterium is the cause of the most frequently reported sexually transmitted disease in the United States, which is responsible for more than 1 million infections annually. Most persons with this infection are asymptomatic. Untreated infection can result in serious complications such as pelvic inflammatory disease, infertility, and ectopic pregnancy in women, and epididymitis and orchitis in men. Men and women can experience chlamydia-induced reactive arthritis. Treatment of uncomplicated cases should include azithromycin or doxycycline. Screening is recommended in all women younger than 25 years, in all pregnant women, and in women who are at increased risk of infection. Screening is not currently recommended in men. In neonates and infants, the bacterium can cause conjunctivitis and pneumonia. Adults may also experience conjunctivitis caused by chlamydia. Trachoma is a recurrent ocular infection caused by chlamydia and is endemic in the developing world.
Acquiring Forensic Evidence from Infrastructure-as-a-Service Cloud Computing: Exploring and Evaluating Tools, Trust, and Techniques

We expose and explore technical and trust issues that arise in acquiring forensic evidence from infrastructure-as-aservice cloud computing and analyze some strategies for addressing these challenges. First, we create a model to show the layers of trust required in the cloud. Second, we present the overarching context for a cloud forensic exam and analyze choices available to an examiner. Third, we provide for the first time an evaluation of popular forensic acquisition tools including Guidance EnCase and AccesData Forensic Toolkit, and show that they can successfully return volatile and non-volatile data from the cloud. We explain, however, that with those techniques judge and jury must accept a great deal of trust in the authenticity and integrity of the data from many layers of the cloud model. In addition, we explore four other solutions for acquisition—Trusted Platform Modules, the management plane, forensics as a service, and legal solutions, which assume less trust but require more cooperation from the cloud service provider. Our work lays a foundation for future development of new acquisition methods for the cloud that will be trustworthy and forensically sound. Our work also helps forensic examiners, law enforcement, and the court evaluate confidence in evidence from the cloud.
Distance-Preserving Subgraphs of Interval Graphs

We consider the problem of finding small distance-preserving subgraphs of undirected, unweighted interval graphs with k terminal vertices. We prove the following results. 1. Finding an optimal distance-preserving subgraph is NP-hard for general graphs. 2. Every interval graph admits a subgraph with O(k) branching vertices that approximates pairwise terminal distances up to an additive term of +1. 3. There exists an interval graph Gint for which the +1 approximation is necessary to obtain the O(k) upper bound on the number of branching vertices. In particular, any distance-preserving subgraph of Gint has Ω(k log k) branching vertices. 4. Every interval graph admits a distance-preserving subgraph with O(k log k) branching vertices, i.e. the Ω(k log k) lower bound for interval graphs is tight. 5. There exists an interval graph such that every optimal distance-preserving subgraph of it has O(k) branching vertices and Ω(k log k) branching edges, thereby providing a separation between branching vertices and branching edges. The O(k) bound for distance-approximating subgraphs follows from a näıve analysis of shortest paths in interval graphs. Gint is constructed using bit-reversal permutation matrices. The O(k log k) bound for distance-preserving subgraphs uses a divide-and-conquer approach. Finally, the separation between branching vertices and branching edges employs Hansel’s lemma [Han64] for graph covering.
Enhancing Cognition with Video Games: A Multiple Game Training Study

Previous evidence points to a causal link between playing action video games and enhanced cognition and perception. However, benefits of playing other video games are under-investigated. We examined whether playing non-action games also improves cognition. Hence, we compared transfer effects of an action and other non-action types that required different cognitive demands.



We instructed 5 groups of non-gamer participants to play one game each on a mobile device (iPhone/iPod Touch) for one hour a day/five days a week over four weeks (20 hours). Games included action, spatial memory, match-3, hidden- object, and an agent-based life simulation. Participants performed four behavioral tasks before and after video game training to assess for transfer effects. Tasks included an attentional blink task, a spatial memory and visual search dual task, a visual filter memory task to assess for multiple object tracking and cognitive control, as well as a complex verbal span task. Action game playing eliminated attentional blink and improved cognitive control and multiple-object tracking. Match-3, spatial memory and hidden object games improved visual search performance while the latter two also improved spatial working memory. Complex verbal span improved after match-3 and action game training.



Cognitive improvements were not limited to action game training alone and different games enhanced different aspects of cognition. We conclude that training specific cognitive abilities frequently in a video game improves performance in tasks that share common underlying demands. Overall, these results suggest that many video game-related cognitive improvements may not be due to training of general broad cognitive systems such as executive attentional control, but instead due to frequent utilization of specific cognitive processes during game play. Thus, many video game training related improvements to cognition may be attributed to near-transfer effects.
Working after a stroke: survivors' experiences and perceptions of barriers to and facilitators of the return to paid employment.

This paper examines respondents' relationship with work following a stroke and explores their experiences including the perceived barriers to and facilitators of a return to employment.



Our qualitative study explored the experiences and recovery of 43 individuals under 60 years who had survived a stroke. Participants, who had experienced a first stroke less than three months before and who could engage in in-depth interviews, were recruited through three stroke services in South East England. Each participant was invited to take part in four interviews over an 18-month period and to complete a diary for one week each month during this period.



At the time of their stroke a minority of our sample (12, 28% of the original sample) were not actively involved in the labour market and did not return to the work during the period that they were involved in the study. Of the 31 participants working at the time of the stroke, 13 had not returned to work during the period that they were involved in the study, six returned to work after three months and nine returned in under three months and in some cases virtually immediately after their stroke. The participants in our study all valued work and felt that working, especially in paid employment, was more desirable than not working. The participants who were not working at the time of their stroke or who had not returned to work during the period of the study also endorsed these views. However they felt that there were a variety of barriers and practical problems that prevented them working and in some cases had adjusted to a life without paid employment. Participants' relationship with work was influenced by barriers and facilitators. The positive valuations of work were modified by the specific context of stroke, for some participants work was a cause of stress and therefore potentially risky, for others it was a way of demonstrating recovery from stroke. The value and meaning varied between participants and this variation was related to past experience and biography. Participants who wanted to work indicated that their ability to work was influenced by the nature and extent of their residual disabilities. A small group of participants had such severe residual disabilities that managing everyday life was a challenge and that working was not a realistic prospect unless their situation changed radically. The remaining participants all reported residual disabilities. The extent to which these disabilities formed a barrier to work depended on an additional range of factors that acted as either barriers or facilitator to return to work. A flexible working environment and supportive social networks were cited as facilitators of return to paid employment.



Participants in our study viewed return to work as an important indicator of recovery following a stroke. Individuals who had not returned to work felt that paid employment was desirable but they could not overcome the barriers. Individuals who returned to work recognized the barriers but had found ways of managing them.
COMMENT MINING, POPULARITY PREDICTION, AND SOCIAL NETWORK ANALYSIS by

...........................................................................................................................7 Chapter 1: Introduction ................................................................................................8 1.1. 9 1.2.  Thesis Outline ..........................................................................................................11 Chapter 2 : Background ...............................................................................................13 2.1. Social Networks .......................................................................................................13 2.2. Implicit versus Explicit Social Network Formations ...............................................14 2.3. Social Network Analysis versus Dynamic Network Analysis .................................15 2.4. Related Research ......................................................................................................16 2.5. Social Bookmarking and Digg Network ..................................................................18 Chapter 3: User Characterization ..............................................................................21 3.1. Network Description and Statistics ..........................................................................21 3.2. Degree Distribution ..................................................................................................22 3.3. Egonet Analysis .......................................................................................................23 3.4. User Membership Analysis ......................................................................................27 Chapter 4: Comparative Analysis of Network Formations .....................................31 4.
Remembering our past: functional neuroanatomy of recollection of recent and very remote personal events.

Functional magnetic resonance imaging was used to study brain regions implicated in retrieval of memories that are decades old. To probe autobiographical memory, family photographs were selected by confederates without the participant's involvement, thereby eliminating many of the variables that potentially confounded previous neuroimaging studies. We found that context-rich memories were associated with activity in lingual and precuneus gyri independently of their age. By contrast, retrosplenial cortex was more active for recent events regardless of memory vividness. Hippocampal activation was related to the richness of re-experiencing (vividness) rather than the age of the memory per se. Remote memories were associated with distributed activation along the rostrocaudal axis of the hippocampus whereas activation associated with recent memories was clustered in the anterior portion. This may explain why circumscribed lesions to the hippocampus disproportionately affect recent memories. These findings are incompatible with theories of long-term memory consolidation, and are more easily accommodated by multiple-trace theory, which posits that detailed memories are always dependent on the hippocampus.
Multi-sensors Data Fusion Based on Arduino Board and XBee Module Technology

In this study, a variety of environmental monitoring, the Arduino sensing value retrieved and transmitted using the XBee wireless signal transmission to the monitoring client computer, information and data are displayed in the interface program Visual C # on, instant catch data sequentially stored in the database. In addition, when sensing value beyond the set threshold is the exception warning, Visual C # displays a warning and sends control signals transmitted to the wireless relay module control electrical appliances to make the switch, improve the environment. For example, when soil moisture deficits, Sprinklers open sprinkler function, to achieve our demands. The future will add another function, when the user is not in the scene, by the application using the Eclipse smartphone over the wireless network, the client computer to connect to the monitor interface program Visual C #, see real-time data, user need not be present also can watch, real data can be viewed through a smartphone, more convenient. This study has several experiments by a number of experimental analysis, combined with Arduino and XBee applied to a variety of situations: Plant care environment monitoring system, can be constructed of a variety of different wireless sensing applications allow users to do by the results of This research further WSN technological development and innovation.
Community Detection in Multi-Dimensional Networks

The pervasiveness of Web 2.0 and social networking sites has enabled people to interact with each other easily through various social media. For instance, popular sites like Del.icio.us, Flickr, and YouTube allow users to comment on shared content (bookmarks, photos, videos), and users can tag their favorite content. Users can also connect with one another, and subscribe to or become a fan or a follower of others. These diverse activities result in a multi-dimensional network among actors, forming group structures with group members sharing similar interests or affiliations. This work systematically addresses two challenges. First, it is challenging to effectively integrate interactions over multiple dimensions to discover hidden community structures shared by heterogeneous interactions. We show that representative community detection methods for single-dimensional networks can be presented in a unified view. Based on this unified view, we present and analyze four possible integration strategies to extend community detection from single-dimensional to multi-dimensional networks. In particular, we propose a novel integration scheme based on structural features. Another challenge is the evaluation of different methods without ground truth information about community membership. We employ a novel cross-dimension network validation procedure to compare the performance of different methods. We use synthetic data to deepen our understanding, and real-world data to compare integration strategies as well as baseline methods in a large scale. We study further the computational time of different methods, normalization effect during integration, sensitivity to related parameters, and alternative community detection methods for integration. Lei Tang, Xufei Wang, Huan Liu Computer Science and Engineering, Arizona State University, Tempe, AZ 85287, USA E-mail: {L.Tang, Xufei.Wang, Huan.Liu@asu.edu} Report Documentation Page Form Approved OMB No. 0704-0188 Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. 1. REPORT DATE 2010 2. 2010 to 00-00-2010 4.  Community Detection in Multi-Dimensional Networks 5a.
THE HIERARCHICAL RELATIONSHIP OF WORDS : SUPERORDINATE , HYPONYM AND SUBORDINATE

The terms superordinate, hyponym, and subordinate designate the hierarchical taxonomic relationship of words. They also represent categories and concepts. This relationship is a subject of interest for anthropology, cognitive psychology, psycholinguistics, linguistic semantics, and cognitive linguistics. Taxonomic hierarchies are essentially classificatory systems, and they are supposed to reflect the way that speakers of a language categorize the world of experience. A well-formed taxonomy offers an orderly and efficient set of categories at different levels of specificity (Cruse 2000:180). However, the terms and levels of taxonomic hierarchy used in each discipline vary. This makes it difficult to carry out cross-disciplinary readings on the hierarchical taxonomy of words or categories, which act as an interface in these cognitive-based cross-disciplinary ventures. Not only words— terms and concepts differ but often the nature of the problem is compounded as some terms refer to differing word classes, categories and concepts at the same time. Moreover, the lexical relationship of terms among these lexical hierarchies is far from clear. As a result two lines of thinking can be drawn from the literature: (1) technical terms coined for the hierarchical relationship of words are conflicting and do not reflect reality or environment, and (2) the relationship among these hierarchies of word levels and the underlying principles followed to explain them are uncertain except that of inclusion.
Barriers of commercial power generation using biomass gasi fi cation gas : A review

Gasification is one of the promising technologies to convert biomass to gaseous fuels for distributed power generation. However, the commercial exploitation of biomass energy suffers from a number of logistics and technological challenges. In this review, the barriers in each of the steps from the collection of biomass to electricity generation are highlighted. The effects of parameters in supply chain management, pretreatment and conversion of biomass to gas, and cleaning and utilization of gas for power generation are discussed. Based on the studies, until recently, the gasification of biomass and gas cleaning are the most challenging part. For electricity generation, either using engine or gas turbine requires a stringent specification of gas composition and tar concentration in the product gas. Different types of updraft and downdraft gasifiers have been developed for gasification and a number of physical and catalytic tar separation methods have been investigated. However, the most efficient and popular one is yet to be developed for commercial purpose. In fact, the efficient gasification and gas cleaning methods can produce highly burnable gas with less tar content, so as to reduce the total consumption of biomass for a desired quantity of electricity generation. According to the recent report, an advanced gasification method with efficient tar cleaning can significantly reduce the biomass consumption, and thus the logistics and biomass pretreatment problems can be ultimately reduced. & 2013 Elsevier Ltd. All rights reserved.