nils-herrmann/clean_scirepeval huggingface dataset:
Governance of an Enterprise Social Intranet Implementation: The Statkraft Case

Recent studies demonstrate that the implementation of enterprise social systems (ESSs) will transfer organizations into new paradigm of social business which results in enormous economic returns and competitive advantage. Social business creates a completely new way of working and organizing characterised by social collaboration, intrinsic knowledge sharing, voluntarily mass participation, just name a few. Thus, implementation of ESSs should tackle the uniqueness of the new way of working and organizing. However, there is a shortage of knowledge about implementation of these large enterprise systems. The purpose of this paper is to study governance model of ESSs implementation. A case study is conducted to investigate the implementation of the social intranet called the ‘Stream’ at Statkraft, which is a world-leading energy company in Norway. The governance model of ‘Stream’ emphasizes the close cooperation and accountability between corporate communication, human resources and IT, which implies paradigm shift in governance of implementing ESSs. Benefits and challenges in the implementation are also identified. Based on the knowledge and insights gained in the study, recommendations are proposed to assist the company in improving governance of ESSs implementation. The study contributes knowledge/know-how on governance of ESSs implementation.
The pathogenesis of rheumatoid arthritis.

From the College of Medical, Veterinary, and Life Sciences, University of Glasgow, Glasgow, United Kingdom (I.B.M.); and the Department of Internal Medicine 3, University of Erlangen–Nuremberg, Erlangen, Germany (G.S.). Address reprint requests to Dr. McInnes at the College of Medical, Veterinary, and Life Sciences, University of Glasgow, Level 4, Sir Graeme Davis Bldg., 120 University Pl., Glasgow G12 8QQ, United Kingdom, or at iain.mcinnes@glasgow.ac.uk; or to Dr. Schett at the Department of Internal Medicine 3, University of Erlangen–Nuremberg, Krankenhausstr. 12, 91054 Erlangen, Germany, or at georg.schett@uk-erlangen.de.
Predictors of Relationship Satisfaction in Online Romantic Relationships

Based on traditional theories of interpersonal relationship development and on the hyperpersonal communication theory, this study examined predictors of relationship satisfaction for individuals involved in online romantic relationships. One hundredfourteen individuals (N1⁄4114) involved in online romantic relationships, and who had only engaged in computer-mediated communication (CMC) with their partners, completed an online questionnaire about their relationships. Intimacy, trust, and communication satisfaction were found to be the strongest predictors of relationship satisfaction for individuals involved in online romances. Additionally, perceptions of relationship variables differed depending on relationship length and time spent communicating. Implications for interpersonal and hyperpersonal communication theories, and future investigation of online relationships, are discussed.
The psychology of globalization.

The influence of globalization on psychological functioning is examined. First, descriptions of how globalization is occurring in various world regions are presented. Then the psychological consequences of globalization are described, with a focus on identity issues. Specifically, it is argued that most people worldwide now develop a bicultural identity that combines their local identity with an identity linked to the global culture; that identity confusion may be increasing among young people in non-Western cultures as a result of globalization; that some people join self-selected cultures to maintain an identity that is separate from the global culture; and that a period of emerging adulthood increasingly extends identity explorations beyond adolescence, through the mid- to late twenties.
Visual comparison for information visualization

Data analysis often involves the comparison of complex objects. With the ever increasing amounts and complexity of data, the demand for systems to help with these comparisons is also growing. Increasingly, information visualization tools support such comparisons explicitly, beyond simply allowing a viewer to examine each object individually. In this paper, we argue that the design of information visualizations of complex objects can, and should, be studied in general, that is independently of what those objects are. As a first step in developing this general understanding of comparison, we propose a general taxonomy of visual designs for comparison that groups designs into three basic categories, which can be combined. To clarify the taxonomy and validate its completeness, we provide a survey of work in information visualization related to comparison. Although we find a great diversity of systems and approaches, we find that all designs are assembled from the building blocks of juxtaposition, superposition, and explicit encodings. This initial exploration shows the power of our model, and suggests future challenges in developing a general understanding of comparative visualization and facilitating the development of more comparative visualization tools.
A Theoretical Basis for a Biopharmaceutic Drug Classification: The Correlation of in Vitro Drug Product Dissolution and in Vivo Bioavailability

A biopharmaceutics drug classification scheme for correlating in vitro drug product dissolution and in vivo bioavailability is proposed based on recognizing that drug dissolution and gastrointestinal permeability are the fundamental parameters controlling rate and extent of drug absorption. This analysis uses a transport model and human permeability results for estimating in vivo drug absorption to illustrate the primary importance of solubility and permeability on drug absorption. The fundamental parameters which define oral drug absorption in humans resulting from this analysis are discussed and used as a basis for this classification scheme. These Biopharmaceutic Drug Classes are defined as: Case 1. High solubility-high permeability drugs, Case 2. Low solubility-high permeability drugs,  High solubility-low permeability drugs, and Case 4. Low solubility-low permeability drugs. Based on this classification scheme, suggestions are made for setting standards for in vitro drug dissolution testing methodology which will correlate with the in vivo process. This methodology must be based on the physiological and physical chemical properties controlling drug absorption. This analysis points out conditions under which no in vitro-in vivo correlation may be expected e.g. rapidly dissolving low permeability drugs. Furthermore, it is suggested for example that for very rapidly dissolving high solubility drugs, e.g. 85% dissolution in less than 15 minutes, a simple one point dissolution test, is all that may be needed to insure bioavailability. For slowly dissolving drugs a dissolution profile is required with multiple time points in systems which would include low pH, physiological pH, and surfactants and the in vitro conditions should mimic the in vivo processes. This classification scheme provides a basis for establishing in vitro-in vivo correlations and for estimating the absorption of drugs based on the fundamental dissolution and permeability properties of physiologic importance.
Algorithmic bias amplifies opinion polarization: A bounded confidence model

The flow of information reaching us via the online media platforms is optimized not by the information content or relevance but by popularity and proximity to the target. This is typically performed in order to maximise platform usage. As a side effect, this introduces an algorithmic bias that is believed to enhance polarization of the societal debate. To study this phenomenon, we modify the well-known continuous opinion dynamics model of bounded confidence in order to account for the algorithmic bias and investigate its consequences. In the simplest version of the original model the pairs of discussion participants are chosen at random and their opinions get closer to each other if they are within a fixed tolerance level. We modify the selection rule of the discussion partners: there is an enhanced probability to choose individuals whose opinions are already close to each other, thus mimicking the behavior of online media which suggest interaction with similar peers. As a result we observe: a) an increased tendency towards polarization, which emerges also in conditions where the original model would predict convergence, and b) a dramatic slowing down of the speed at which the convergence at the asymptotic state is reached, which makes the system highly unstable. Polarization is augmented by a fragmented initial population. 1 ar X iv :1 80 3. 02 11 1v 1 [ ph ys ic s. so cph ] 6 M ar 2 01 8
Side-Channel Attacks on Everyday Applications : Distinguishing Inputs with F LUSH + R ELOAD

Side channel attacks are typically used to break implementations of cryptography. Recently, side-channel attacks are being discovered in more general settings that violate user privacy. We build on this work by showing that the FLUSH+RELOAD L3 cache side channel from Yuval Yarom and Katrina Falkner  can be used to distinguish between inputs to non-cryptographic programs on multi-user systems. We describe how input-distinguishing attacks can be discovered automatically (with human assistance) and we present three concrete attacks. Our first attack is against the Links command-line web browser. We show that an attacker can determine which of the top 100 Wikipedia pages the user visited (correct 94% of the time). Our second attack is against the Poppler PDF rendering library. We show that an attacker can determine which of a set of 127 PDFs were rendered by Poppler (correct 98% of the time). Finally, we show how an attacker can determine whether the TrueCrypt volume a user just mounted contained a hidden volume or not (correct above 80% of the time, but the attack only works on one of our two test systems).
Visual secret sharing scheme for (k, n) threshold based on QR code with multiple decryptions

In this paper, a novel visual secret sharing (VSS) scheme based on QR code (VSSQR) with (k, n) threshold is investigated. Our VSSQR exploits the error correction mechanism in the QR code structure, to generate the bits corresponding to shares (shadow images) by VSS from a secret bit in the processing of encoding QR. Each output share is a valid QR code that can be scanned and decoded utilizing a QR code reader, which may reduce the likelihood of attracting the attention of potential attackers. Due to different application scenarios, two different recovered ways of the secret image are given. The proposed VSS scheme based on QR code can visually reveal secret image with the abilities of stacking and XOR decryptions as well as scan every shadow image, i.e., a QR code, by a QR code reader. The secret image could be revealed by human visual system without any computation based on stacking when no lightweight computation device. On the other hand, if the lightweight computation device is available, the secret image can be revealed with better visual quality based on XOR operation and could be lossless revealed when sufficient shares are collected. In addition, it can assist alignment for VSS recovery. The experiment results show the effectiveness of our scheme.
Electronic media use and adolescent health and well-being: cross-sectional community study.

To describe time adolescents spend using electronic media (television, computer, video games, and telephone); and to examine associations between self-reported health/well-being and daily time spent using electronic media overall and each type of electronic media.



Design-Cross-sectional data from the third (2005) wave of the Health of Young Victorians Study, an Australian school-based population study. Outcome Measures-Global health, health-related quality of life (HRQoL; KIDSCREEN), health status (Pediatric Quality of Life Inventory 4.0; PedsQL), depression/anxiety (Kessler-10), and behavior problems (Strengths and Difficulties Questionnaire). Duration of electronic media use averaged over 1 to 4 days recalled with the Multimedia Activity Recall for Children and Adolescents (MARCA) computerized time-use diary. Analysis-Linear and logistic regression; adjusted for demographic variables and body mass index z score.



A total of 925 adolescents (mean +/- standard deviation age, 16.1+/-1.2 years) spent, on average, 3 hours 16 minutes per day using electronic media (television, 128 minutes per day; video games, 35; computers, 19; telephone, 13). High overall electronic media use was associated with poorer behavior, health status, and HRQoL. Associations with duration of specific media exposures were mixed; there was a favorable association between computer use (typing/Internet) and psychological distress, whereas high video game use was associated with poorer health status, HRQoL, global health, and depression/anxiety. Television and telephone durations were not associated with any outcome measure.



Despite television's associations with obesity, time spent in other forms of media use appear more strongly related to adolescent health and well-being. This study supports efforts to reduce high video game use and further exploration of the role of computers in health enhancement.
Topological Centrality and Its Applications

Recent development of network structure analysis shows that it plays an important role in characterizing complex system of many branches of sciences. Different from previous network centrality measures, this paper proposes the notion of topological centrality (TC) reflecting the topological positions of nodes and edges in general networks, and proposes an approach to calculating the topological centrality. The proposed topological centrality is then used to discover communities and build the backbone network. Experiments and applications on research network show the significance of the proposed approach. Index Terms —Network structure, Centrality, Community, e-Science
Recovering time-varying networks of dependencies in social and biological studies.

A plausible representation of the relational information among entities in dynamic systems such as a living cell or a social community is a stochastic network that is topologically rewiring and semantically evolving over time. Although there is a rich literature in modeling static or temporally invariant networks, little has been done toward recovering the network structure when the networks are not observable in a dynamic context. In this article, we present a machine learning method called TESLA, which builds on a temporally smoothed l(1)-regularized logistic regression formalism that can be cast as a standard convex-optimization problem and solved efficiently by using generic solvers scalable to large networks. We report promising results on recovering simulated time-varying networks and on reverse engineering the latent sequence of temporally rewiring political and academic social networks from longitudinal data, and the evolving gene networks over >4,000 genes during the life cycle of Drosophila melanogaster from a microarray time course at a resolution limited only by sample frequency.
Why Machine Ethics?

Machine ethics isn't merely science fiction; it's a topic that requires serious consideration, given the rapid emergence of increasingly complex autonomous software agents and robots. Machine ethics is an emerging field that seeks to implement moral decision-making faculties in computers and robots. We already have semiautonomous robots and software agents that violate ethical standards as a matter of course. In the case of AI and robotics, fearful scenarios range from the future takeover of humanity by a superior form of AI to the havoc created by endlessly reproducing nanobots
Ontology-Based Integrated Information Platform for Digital City

Information integration develops toward semantic integration on the Semantic Web. Ontology facilitates the integration of heterogeneous data sources by resolving semantic heterogeneity among them. In this paper, we propose the system architecture of integrated information platform for digital city based on ontology, including three main layers: distributed heterogeneous data source layer, information integration layer, and application system layer. Its core is the information integration layer including the ontology server and the integrated database. Then, the domain ontology model for digital city is presented. Furthermore, we realize the semantic information retrieval according to the relations of "synonymy of, "kind of and "part of between concepts. At the end we conclude that ontology is a good tool to integrate information among various heterogeneous urban management systems on semantic level.
Residual Gated Graph ConvNets

Graph-structured data such as functional brain networks, social networks, gene regulatory networks, communications networks have brought the interest in generalizing neural networks to graph domains. In this paper, we are interested to design efficient neural network architectures for graphs with variable length. Several existing works such as Scarselli et al. (2009); Li et al. (2016) have focused on recurrent neural networks (RNNs) to solve this task. A recent different approach was proposed in Sukhbaatar et al. (2016), where a vanilla graph convolutional neural network (ConvNets) was introduced. We believe the latter approach to be a better paradigm to solve graph learning problems because ConvNets are more pruned to deep networks than RNNs. For this reason, we propose the most generic class of residual multi-layer graph ConvNets that make use of an edge gating mechanism, as proposed in Marcheggiani & Titov (2017). Gated edges appear to be a natural property in the context of graph learning tasks, as the system has the ability to learn which edges are important or not for the task to solve. We apply several graph neural models to two basic network science tasks; subgraph matching and semi-supervised clustering for graphs with variable length. Numerical results show the performances of the new model.
Homomorphic encryption method applied to Cloud Computing

When the data transferred to the Cloud we use standard encryption methods to secure this data, but when we want to do the calculations on data located on a remote server, it is necessary that the Cloud provider has access to the raw data, and then it will decrypt them. In this paper we propose the application of a method to perform the operation on encrypted data without decrypted and provide the same result as well that the calculations were carried out on raw data.
Antimicrobial Activity – The Most Important Property of Probiotic and Starter Lactic Acid Bacteria

The antimicrobial activity of industrially important lactic acid bacteria as starter cultures and probiotic bacteria is the main subject of this review. This activity has been attributed to the production of metabolites such as organic acids (lactic and acetic acid), hydrogen peroxide, ethanol, diacetyl, acetaldehyde, acetoine, carbon dioxide, reuterin, reutericyclin and bacteriocins. The potential of using bacteriocins of lactic acid bacteria, primarily used as biopreservatives, represents a perspective, alternative antimicrobial strategy for continuously increasing problem with antibiotic resistance. Another strategy in resolving this problem is an application of probiotics for different gastrointestinal and urogenital infection therapies.
Box Pleating is Hard

In their seminal 1996 paper, Bern and Hayes initiated investigation into the computational complexity of origami . They proved that it is NP-hard to determine whether a given general crease pattern can be folded flat, when the creases have or have not been assigned crease directions (mountain fold or valley fold). Since that time, there has been considerable work in analyzing the computational complexity of other origami related problems. For example, Arkin et al.  proved that deciding foldability is hard even for simple folds, while Demaine et al.  proved that optimal circle packing for origami design is also hard. At the end of their paper, Bern and Hayes pose some interesting open questions to further their work. While most of them have been investigated since, two in particular (problems 2 and 3) have remained untouched until now. First, while the gadgets used in their hardness proof for unassigned crease patterns are relatively straightforward, their gadgets for assigned crease patterns are considerably more convoluted, and quite difficult to check. In particular, we found an error in their crossover gadget where signals are not guaranteed to transmit dependably for wires that do not cross orthogonally, which is required in their construction. Is there a simpler way to achieve a correct result (i.e. “without tabs”)? Second, their reductions construct creases at a variety of unconstrained angles. Is deciding flat foldability easy under more restrictive inputs? For example box pleating, folding only along creases aligned at multiples of 45◦ to each other, is a subset of particular interest in transformational robotics and selfassembly, with a universality result constructing arbitrary polycubes using box pleating . In this paper we prove deciding flat foldability of box pleated crease patterns to be NP-hard in both the unassigned and assigned cases, using relatively simple gadgets containing no more than 20 layers at any point. A crease pattern is a straight-line graph of creases on a square paper which all must be folded by ±180◦ resulting in a flat folding, a piecewise isometry in the plane such that the paper does not intersect itself. We call a crease a valley fold if it folds
Genetic Programming + Unfolding Embryology in Automated Layout Planning

Automated layout planning aims to the implementation of computational methods for the generation and the optimization of floor plans, considering the spatial configuration and the assignment of activities. Sophisticated strategies such as Genetic Algorithms have been implemented as heuristics of good solutions. However, the generative forces that derive from the social structures have been often neglected. This research aims to illustrate that the data that encode the layout’s social and cultural generative forces, can be implemented within an evolutionary system for the design of residential layouts. For that purpose a co-operative system was created, which is composed of a Genetic Programming algorithm and an agent-based unfolding embryology procedure that assigns activities to the spaces generated by the GP algorithm. The assignment of activities is a recursive process which follows instructions encoded as permeability graphs. Furthermore, the Ranking Sum Fitness evaluation method is proposed and applied for the achievement of multiobjective optimization. Its efficiency is tested against the Weighted-Sum Fitness function. The system’s results, both numerical and spatial, are compared to the results of a conventional evolutionary approach. This comparison showed that, in general, the proposed system can yield better solutions.
A $3 gesture recognizer: simple gesture recognition for devices equipped with 3D acceleration sensors

We present the $3 Gesture Recognizer, a simple but robust gesture recognition system for input devices featuring 3D acceleration sensors. The algorithm is designed to be implemented quickly in prototyping environments, is intended to be device-independent and does not require any special toolkits or frameworks. It relies solely on simple trigonometric and geometric calculations. A user evaluation of our system resulted in a correct gesture recognition rate of 80%, when using a set of 10 unique gestures for classification. Our method requires significantly less training data than other gesture recognizers and is thus suited to be deployed and to deliver results rapidly.