nils-herrmann/clean_scirepeval huggingface dataset:
Marketing strategy in emerging markets: a conceptual framework

Citing difference between emerging and developed markets, scholars highlight need for different approaches to marketing in emerging markets. In this paper, we argue that while there are some unique characteristics of emerging markets, all countries within emerging markets do not have similar levels of product penetration and consumption. As a result, it is wrong to assume that emerging markets are untapped and under served across the product categories. To a list of characteristics identified as unique to emerging markets, we add large population as an important characteristic and discuss its strategic implications. We develop a conceptual framework that factors in combined effect of varying degrees of product penetration consumption levels with large population of emerging market countries. The conceptual framework identifies four strategic alternatives for marketing in emerging markets. Instead of recommending any generic marketing strategy, we propose that marketers need to choose an appropriate mix of strategies aimed at primary and selective demand creation in emerging markets.
Complement component C3a plays a critical role in endothelial activation and leukocyte recruitment into the brain
Venue: Journal of Neuroinflammation

BackgroundThe complement system is becoming increasingly recognized as a key participant in many neurodegenerative diseases of the brain. Complement deficient animals exhibit reduced neuroinflammation.MethodsIn the present study, we administered intracerebroventricularly lipopolysaccharide (LPS) to mimic local infection of the brain and investigated the role of key complement component C3 in brain vasculature endothelial activation and leukocyte recruitment. The degree of neutrophil infiltration was determined by esterase staining. Leukocyte endothelial interactions were measured using intravital microscopy. Cerebral endothelial activation was evaluated using real time PCR and Western blotting.ResultsNeutrophil infiltration into the brain cortex and hippocampus was significantly reduced in C3 mice and C3aR mice but not in C6 mice. We detected markedly attenuated leukocyte endothelial interactions in the brain microvasculature of C3 mice. Accordingly, in response to LPS administration, the brain microvasculature in these mice had decreased expression of P selectin, E selectin, intercellular cell adhesion molecule 1 (ICAM 1) and vascular cell adhesion molecule 1 (VCAM 1) Depletion of C3 from the circulation also caused reduction in VCAM 1 and E selectin expression and leukocyte recruitment, suggesting that C3 in the circulation contributed to brain endothelial activation. Furthermore, C3 mice exhibited decreased leukocyte recruitment into the brain upon tumor necrosis factor a (TNF a) stimulation. C3a activated the phosphorylation of p38 mitogen activated protein kinase (MAPK) and nuclear factor kB (NF kB) and induced the upregulation of VCAM 1 and ICAM 1 expression in murine primary cerebral endothelial cells in vitro.ConclusionsOur study provides the first evidence that C3a plays a critical role in cerebral endothelial activation and leukocyte recruitment during inflammation in the brain.
High Current HTS Cables: Status and Actual Development
Venue: IEEE Transactions on Applied Superconductivity

Second generation high temperature superconductors (HTS) REBCO are promising for high field application due to the excellent Jc(B) performance at low temperatures and for power transmission at liquid nitrogen temperature. For power transmission with HTS, the formation of high current HTS cables from single HTS tapes is desirable for cable currents of several 10 kA up to more than 100 kA. On the other hand, to avoid high inductances, which would cause high voltage problems in case of quench or fast shutdown, high current HTS cables are needed for larger high field magnets, too, typically operated at 4.5 K or lower. In the last years, several HTS cable designs have been proposed, such as twisted stacked cable, CORC cable, and Roebel cable. This talk will give an overview of such proposals and highlight actual developments in HTS cable design and REBCO tape optimization, e.g. for highest field. In addition, an optimization of round TSTC strand will be introduced, which is designed for simple fabrication in long lengths for versatile use either for the production of cables to be used at high fields or for power transmission.
Investigating the Psychometric Properties of the Self Compassion Scale: Using Confirmatory and Exploratory Factor Models

Self compassion has quickly gained recognition for its many cognitive, emotional, and psychological benefits (Neff, 2003b) The Self Compassion Scale (SCS; Neff, 2003a) is currently the only instrument measuring self compassion and is commonly used. The current model contains six factors: self kindness, self judgment, common humanity, isolation, mindfulness, and over identification. However, the SCS has recently come under fire due to limited evidence of its psychometric properties (Lopez et al. 2015) Researchers who have attempted to replicate the factor structure proposed by Neff have found mixed results using both exploratory and confirmatory methods. Our primary aim is to establish the factor structure of the SCS with a large, more representative sample. Thirteen samples (total n 2,515) using the SCS were combined to demonstrate a more comprehensive approach to investigating the scales' psychometric properties. A confirmatory factor analysis (CFA) demonstrated good model fit for the six factor solution. However, little is known about how the SCS items naturally load together. A subsequent exploratory factor analysis (EFA) demonstrated lack of good model fit for the six factor model; instead, a simpler, two factor solution emerged. However, the twofactor model is inconsistent with the theoretical conceptualization of self compassion. Future research should use more advanced statistical models to explain the multidimensionality of the
Stackelberg Bayesian Game for Power Allocation in Two Tier Networks
Venue: IEEE Transactions on Vehicular Technology

The downlink power allocation in a two tier cellular network that consists of a macrocell network underlaid by multiple femtocell networks is addressed in this paper. This paper aims to maximize the transmission capacity of the femtocell networks while guaranteeing that the interference experienced at the macro base station does not exceed an interference constraint. We formulate a Bayesian Stackelberg game to model and analyze behaviors of macrocell and femtocell base stations (MBS and FBSs, respectively) In this game, the MBS is the leader, whereas the FBSs are the followers. The channel information between an FBS and its associated femtocell user is private information and is considered the type of the follower. The leader issues the price of interference charged to the followers first to maximize its own profit. Based on the price, the followers decide the strategies to maximize their payoffs defined as the difference between the transmission capacity and the cost of interference (CoI) paid to the leader. Using backward induction, we first analyze the follower game. The existence and uniqueness of the Bayesian Nash equilibrium (BNE) are examined, and the methods to obtain the BNE for a symmetric case are provided. Then, the leader game is analyzed. Finally, the numerical analysis is provided.
An Automated Dynamic Offset for Network Selection in Heterogeneous Networks
Venue: IEEE Transactions on Mobile Computing

Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near optimal solutions for the network. In this paper, we propose a load aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets) In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal) the full channel state information and the non cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n4) (where n is the number of users) It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non cooperative model.
Studying bloat control and maintenance of effective code in linear genetic programming for symbolic regression
Venue: Neurocomputing

Linear Genetic Programming (LGP) is an Evolutionary Computation algorithm, inspired in the Genetic Programming (GP) algorithm. Instead of using the standard tree representation of GP, LGP evolves a linear program, which causes a graph based data flow with code reuse. LGP has been shown to outperform GP in several problems, including Symbolic Regression (SReg) and to produce simpler solutions. In this paper, we propose several LGP variants and compare them with a traditional LGP algorithm on a set of benchmark SReg functions from the literature. The main objectives of the variants were to both control bloat and privilege useful code in the population. Here we evaluate their effects during the evolution process and in the quality of the final solutions. Analysis of the results showed that bloat control and effective code maintenance worked, but they did not guarantee improvement in solution quality. HighlightsWe studied tournament procedures for bloat control in LGP.We proposed seven variations of known tournament procedures.The variations were tested in 35 symbolic regression problems.The proposed procedures show competitive or better solution quality than the original procedure, but with smaller solutions.
Hybrid Single Node Genetic Programming for Symbolic Regression
Venue: Trans. Comput. Collect. Intell.

This paper presents a first step of our research on designing an effective and efficient GP based method for symbolic regression. First, we propose three extensions of the standard Single Node GP, namely 1 a selection strategy for choosing nodes to be mutated based on depth and performance of the nodes, 2 operators for placing a compact version of the best performing graph to the beginning and to the end of the population, respectively, and 3 a local search strategy with multiple mutations applied in each iteration. All the proposed modifications have been experimentally evaluated on five symbolic regression benchmarks and compared with standard GP and SNGP. The achieved results are promising showing the potential of the proposed modifications to improve the performance of the SNGP algorithm. We then propose two variants of hybrid SNGP utilizing a linear regression technique, LASSO, to improve its performance. The proposed algorithms have been compared to the state of the art symbolic regression methods that also make use of the linear regression techniques on four real world benchmarks. The results show the hybrid SNGP algorithms are at least competitive with or better than the compared methods.
Innovation and technology for the elderly: Systematic literature review

As life expectancy increases, so does the number of elders. This increase poses a challenge regarding the ability of maintaining the costs for providing services to this group. In search of solution, practitioners have found technology to improve the life style of the elderly and reducing the costs in long term. This demographic change leads to opportunities for disruptive innovation as well. Elders' acceptance of innovative technology in their everyday life is a success key factor for the governments, technology providers, healthcare providers, and other major players in elders' life. This study systematically reviews the existing literature and identifies the actors in elders' life. In addition, the study provides a comprehensive review of elder's innovative technology adoption, including the impacts and costs. The study also offers suggestions and guidelines for future research.
Sport, Innovation and Strategic Management: A Systematic Literature Review

Sport organizations adapt, renew and develop through creative and novel ideas. The various strategies for innovation applied by sport organizations hold the potential to radically change how we play, view and organize sport. In other words, through strategy, strategic management and innovation modern sport is shaped and improved. To date, limited scholarly attention has been given to strategy, strategic management and innovation in sport. However as the present review will demonstrate, sport innovation and strategic management of sports innovations are crucial for improvement of athletic performance. Furthermore, current research indicates that sport innovation can be a valuable tool to combat demanding challenges in modern sport, such as social exclusion. Therefore, innovation and strategic management needs specific attention within the sport sciences. The present paper attempts to provide more insight in the current body of research on sport innovation and strategic management. Finally, some recommendations for further research in this field is formulated.
Dichromatic State Sum Models for Four Manifolds from Pivotal Functors

A family of invariants of smooth, oriented four dimensional manifolds is defined via handle decompositions and the Kirby calculus of framed link diagrams. The invariants are parametrised by a pivotal functor from a spherical fusion category into a ribbon fusion category. A state sum formula for the invariant is constructed via the chain mail procedure, so a large class of topological state sum models can be expressed as link invariants. Most prominently, the Crane Yetter state sum over an arbitrary ribbon fusion category is recovered, including the nonmodular case. It is shown that the Crane Yetter invariant for nonmodular categories is stronger than signature and Euler invariant. A special case is the four dimensional untwisted Dijkgraaf Witten model. Derivations of state space dimensions of TQFTs arising from the state sum model agree with recent calculations of ground state degeneracies in Walker Wang models. Relations to different approaches to quantum gravity such as Cartan geometry and teleparallel gravity are also discussed.
"It Don't Mean a Thing if It Ain't Got that Swing" an Alternative Concept for Understanding the Evolution of Dance and Music in Human Beings
Venue: Front. Hum. Neurosci.

The functions of dance and music in human evolution are a mystery. Current research on the evolution of music has mainly focused on its melodic attribute which would have evolved alongside (proto )language. Instead, we propose an alternative conceptual framework which focuses on the co evolution of rhythm and dance (R&D) as intertwined aspects of a multimodal phenomenon characterized by the unity of action and perception. Reviewing the current literature from this viewpoint we propose the hypothesis that R&D have co evolved long before other musical attributes and (proto )language. Our view is supported by increasing experimental evidence particularly in infants and children: beat is perceived and anticipated already by newborns and rhythm perception depends on body movement. Infants and toddlers spontaneously move to a rhythm irrespective of their cultural background. The impulse to dance may have been prepared by the susceptibility of infants to be soothed by rocking. Conceivable evolutionary functions of R&D include sexual attraction and transmission of mating signals. Social functions include bonding, synchronization of many individuals, appeasement of hostile individuals, and pre and extra verbal communication enabling embodied individual and collective memorizing. In many cultures R&D are used for entering trance, a base for shamanism and early religions. Individual benefits of R&D include improvement of body coordination, as well as painkilling, anti depressive, and anti boredom effects. Rhythm most likely paved the way for human speech as supported by studies confirming the overlaps between cognitive and neural resources recruited for language and rhythm. In addition, dance encompasses visual and gestural communication. In future studies attention should be paid to which attribute of music is focused on and that the close mutual relation between R&D is taken into account. The possible evolutionary functions of dance deserve more attention.
The dysconnection hypothesis (2016)
Venue: Schizophrenia Research

Twenty years have passed since the dysconnection hypothesis was first proposed (Friston and Frith, 1995; Weinberger, 1993) In that time, neuroscience has witnessed tremendous advances: we now live in a world of non invasive neuroanatomy, computational neuroimaging and the Bayesian brain. The genomics era has come and gone. Connectomics and large scale neuroinformatics initiatives are emerging everywhere. So where is the dysconnection hypothesis now? This article considers how the notion of schizophrenia as a dysconnection syndrome has developed and how it has been enriched by recent advances in clinical neuroscience. In particular, we examine the dysconnection hypothesis in the context of (i) theoretical neurobiology and computational psychiatry; (ii) the empirical insights afforded by neuroimaging and associated connectomics and (iii) how bottom up (molecular biology and genetics) and top down (systems biology) perspectives are converging on the mechanisms and nature of dysconnections in schizophrenia.
Implementation of multi level bridgeless PFC rectifiers for mid power single phase applications
Venue: 2016 IEEE Applied Power Electronics Conference and Exposition (APEC)

Multi level approaches to AC/DC power conversion have been successfully deployed in high voltage high power industrial applications, and are recently considered for mid power ranges due to their capability of reducing component sizes and improving efficiency. The main challenge for mid power deployment is the complexity of sensing circuits and control algorithms used to maintain the capacitor voltage balance, which typically results in expensive and impractical designs. Although several studies have been carried out to address the issue, they have not simplified the system complexity and fully exploited the advantages of multi level converters. This paper presents a new four level topology for PFC rectifiers, and demonstrates its performance and practicality through a 200W prototype. The theoretical works and experimental results are also provided to confirm the feasibility of the solution.
Reduction of Rough Set Based on Generalized Neighborhood System Operator

The theory of generalized neighborhood system based pproximation operators plays an important role in the theory of generalize d rough sets since it includes both the neighborhood based approximation operators and the covering based approximation operators as its special circumstances. The theory of reduction is one of the most significant directions in rough sets. In this work, the reduction of rough set based on generalized neighborhood system operator is defined and discussed. In particular, the conditions for two generalized neighborhood system operator to generate the same lower or upper approximation are provided.
Robust Point Set Matching for Partial Face Recognition
Venue: IEEE Transactions on Image Processing

Over the past three decades, a number of face recognition methods have been proposed in computer vision, and most of them use holistic face images for person identification. In many real world scenarios especially some unconstrained environments, human faces might be occluded by other objects, and it is difficult to obtain fully holistic face images for recognition. To address this, we propose a new partial face recognition approach to recognize persons of interest from their partial faces. Given a pair of gallery image and probe face patch, we first detect keypoints and extract their local textural features. Then, we propose a robust point set matching method to discriminatively match these two extracted local feature sets, where both the textural information and geometrical information of local features are explicitly used for matching simultaneously. Finally, the similarity of two faces is converted as the distance between these two aligned feature sets. Experimental results on four public face data sets show the effectiveness of the proposed approach.
NEW OPERATIONS OVER GENERALIZED INTERVAL VALUED INTUITIONISTIC FUZZY SETS

The concept of intuitionistic fuzzy sets and its generalizations play a vital role in modeling uncertainty and vagueness involved in deferent field of science. Recently, generalized interval valued intuitionistic fuzzy sets were presented by Baloui Jamkhaneh (2015) and defined some operations over it. In this paper, defined arithmetic mean operation and geometric mean operation over are proposed and few theorems were proved. In addition, some of the basic properties of the new operations are discussed. By using these new operations, a prioritization method for generalized interval valued intuitionistic fuzzy judgment matrix is proposed.
The Effect of Educational Intervention in Promoting Safe Behaviors in a Sample of Iranian Primary School Students: An Application of the Health Belief Model.
Venue: Global journal of health science

Road traffic accidents account for the biggest mortality rate in Iran and children are among the main victims of these accidents. The present study was conducted to assess the effect of an educational intervention based on the Health Belief Model on behaviors associated with obeying traffic regulations in primary school students during the academic year 2014 15 in Khorramabad, Iran.  The present quasi experimental has a pre post intervention design and was conducted on 106 sixth grade primary school students selected through multi stage sampling and divided into an intervention and a control group. The students were assessed before, a week after and two months after the intervention. Data were collected using a two part questionnaire containing a demographic section and a section with items on the constructs of the Health Belief Model. The data obtained were then analyzed in SPSS 20.  The mean scores of perceived susceptibility, perceived severity, perceived benefits, perceived barriers, self efficacy and cues to action significantly improved in the intervention group compared to the control group (P<0. 01) CONCLUSION An educational intervention based the Health Belief Model managed to effectively improve behaviors associated with obeying traffic regulations.