nils-herrmann/clean_scirepeval huggingface dataset:
Anodal transcranial direct current stimulation of the motor cortex increases cortical voluntary activation and neural plasticity
Venue: Muscle nerve

We examined the cumulative effect of 4 consecutive bouts of noninvasive brain stimulation on corticospinal plasticity and motor performance, and whether these responses were influenced by the brain derived neurotrophic factor (BDNF) polymorphism.  In a randomized double blinded cross over design, changes in strength and indices of corticospinal plasticity were analyzed in 14 adults who were exposed to 4 consecutive sessions of anodal and sham transcranial direct current stimulation (tDCS) Participants also undertook a blood sample for BDNF genotyping (N 13)  We observed a significant increase in isometric wrist flexor strength with transcranial magnetic stimulation revealing increased corticospinal excitability, decreased silent period duration, and increased cortical voluntary activation compared with sham tDCS.  The results show that 4 consecutive sessions of anodal tDCS increased cortical voluntary activation manifested as an improvement in strength. Induction of corticospinal plasticity appears to be influenced by the BDNF polymorphism. Muscle Nerve 54: 903 913, 2016
Response: "Commentary: Duration dependent effects of the BDNF Val66Met polymorphism on anodal tDCS induced motor cortex plasticity in older adults: a group and individual perspective"
Venue: Front. Aging Neurosci.

Puri R and Hinder MR (2016) Response: "  Duration dependent effects of the BDNF Val66Met polymorphism on anodal tDCS induced motor cortex plasticity in older adults: a group and individual perspective " In a commentary on our recent paper (Puri et al. 2015) Shpektor et al. (2015) provide alternative interpretations on the effects of the BDNF Val66Met polymorphism on transcranial direct current stimulation (tDCS) induced plasticity in older adults. Here we respond to several key issues raised in regard to our findings, and discuss broader implications for the field of non invasive brain stimulation (NBS) Shpektor et al. (2015) suggest that our findings, whereby older Met carriers (homozygous or heterozygous for the Met allele) exhibit a greater plastic response to 20 min of anodal tDCS compared to Val/Val homozygotes, may be seen as " controversial " as we reported an influence of the BDNF Val66Met polymorphism on plasticity at rest (i.e. not during task performance) However, a broader search of the extant literature suggests that the effects of the BDNF Val66Met polymorphism on tDCS induced plasticity are varied, even before one considers the interaction of tDCS effects with neural activation resulting from performing a concurrent motor task (e.g. Fritsch et al. 2010) Specifically, Antal et al. (2010) reported a significant Genotype x Time interaction where greater motor evoked potential (MEP) amplitude was observed in Met allele carriers compared to Val/Val homozygotes at 25 and 60 min following anodal tDCS. Furthermore, Teo et al. (2014) reported a significant facilitation in MEPs post anodal stimulation only for Met carriers and not Val/Val homozygotes. Recently, Strube et al. (2015) reported a greater increase in MEPs for healthy Met carriers than Val/Val homozygotes after anodal tDCS (although this did not quite reach the a priori level of statistical significance, p 0.072, it was associated with a large effect size, d 0.799) On the other hand, some studies do not report statistically significant differences between Met carriers and Val/Val homozygotes (Cheeran et al. 2008; Di Lazzaro et al. 2012; Fujiyama et al. 2014) However, as we alluded to in our paper, an absence of statistically significant effects should be interpreted with caution, especially when sample Puri and Hinder BDNF, Cortical Plasticity, and Aging sizes are small and studies are not primarily designed to investigate BDNF polymorphism effects (e.g. Fujiyama et al. 2014) In addition, there appears to be some preliminary evidence to suggest that the specific
SOLVING LINEAR AND NONLINEAR KLEIN GORDON EQUATIONS BY NEW PERTURBATION ITERATION TRANSFORM METHOD

We present an effective algorithm to solve the Linear and Nonlinear KleinGordon equation, which is based on the Perturbation Iteration Transform Method (PITM) The Klein Gordon equation is the name given to the equation of motion of a quantum scalar or pseudo scalar field, a field whose quanta are spin less particles. It describes the quantum amplitude for finding a point particle in various places, the relativistic wave function, but the particle propagates both forwards and backwards in time. The Perturbation Iteration Transform Method (PITM) is a combined form of the Laplace Transform Method and Perturbation Iteration Algorithm. The method provides the solution in the form of a rapidly convergent series. Some numerical examples are used to illustrate the preciseness and effectiveness of the proposed method. The results show that the PITM is very efficient, simple and can be applied to other nonlinear problems.
A software tool for the decentralized control of AGV systems
Venue: 2016 International Conference on Control, Decision and Information Technologies (CoDIT)

This paper presents a software tool for the simulation of a decentralized control strategy to assign tasks to Autonomous Guided Vehicles (AGV) and coordinate their paths to avoid deadlock and collisions. We consider a zone controlled guidepath network where a set of intelligent vehicles (agents) has to autonomously reach a consensus about the distribution of a set of tasks, i.e. a set of zones to be reached. To this aim, first the agents apply a discrete consensus algorithm in order to locally minimize the global cost for reaching the destination zone, then they move according to a decentralized coordination protocol that is based on a zone controlled approach with the aim of avoiding deadlock and collisions. The software tool allows the user to define the guidepath network, then randomly generates the positions of AGVs and destinations and runs the two algorithms visually showing their behavior.
Three dimensional segmentation of retroperitoneal masses using continuous convex relaxation and accumulated gradient distance for radiotherapy planning
Venue: Medical Biological Engineering Computing

An innovative algorithm has been developed for the segmentation of retroperitoneal tumors in 3D radiological images. This algorithm makes it possible for radiation oncologists and surgeons semiautomatically to select tumors for possible future radiation treatment and surgery. It is based on continuous convex relaxation methodology, the main novelty being the introduction of accumulated gradient distance, with intensity and gradient information being incorporated into the segmentation process. The algorithm was used to segment 26 CT image volumes. The results were compared with manual contouring of the same tumors. The proposed algorithm achieved 90 sensitivity, 100 specificity and 84 positive predictive value, obtaining a mean distance to the closest point of 3.20 pixels. The algorithm's dependence on the initial manual contour was also analyzed, with results showing that the algorithm substantially reduced the variability of the manual segmentation carried out by different specialists. The algorithm was also compared with four benchmark algorithms (thresholding, edge based level set, region based level set and continuous max flow with two labels) To the best of our knowledge, this is the first time the segmentation of retroperitoneal tumors for radiotherapy planning has been addressed.
Adaptive scholarship and situated knowledges? Hybrid methodologies and plural epistemologies in climate change adaptation research

Climate change, along with other so called global challenges, demands that scholars work across disciplines. Drawing on Donna Haraway's idea of situated knowledges, this paper develops an approach to mixing disciplines by engaging in epistemological pluralism, or approaching a research problem through more than one way of conceptualising it. The example of climate change adaptation planning in Nepal is used to show how a hybrid methodology research design requires thinking through what can be known and also what cannot be known by using a particular method. The main argument is that it is not possible to prove methodologically which conceptualisation or analytical entry point is better than another. Rather, new insights are gained both by triangulating data from different methods, and by probing the ways that they present contradictory results. An interdisciplinary research design is therefore used as a kind of kaleidoscope wherein plural epistemologies help to reveal new, albeit partial and situated, patterns.
Compact Bilinear Pooling
Venue: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Bilinear models has been shown to achieve impressive performance on a wide range of visual tasks, such as semantic segmentation, fine grained recognition and face recognition. However, bilinear features are high dimensional, typically on the order of hundreds of thousands to a few million, which makes them impractical for subsequent analysis. We propose two compact bilinear representations with the same discriminative power as the full bilinear representation but with only a few thousand dimensions. Our compact representations allow back propagation of classification errors enabling an end to end optimization of the visual recognition system. The compact bilinear representations are derived through a novel kernelized analysis of bilinear pooling which provide insights into the discriminative power of bilinear pooling, and a platform for further research in compact pooling methods. Experimentation illustrate the utility of the proposed representations for image classification and few shot learning across several datasets.
Purchase prediction using Tmall specific features
Venue: Concurr. Comput. Pract. Exp.

Historical user activity, such as online shopping recommendations, content personalization, and advertising clicking rates, is a critical component of building user profiles to predict purchases and preferences. Alongside the rapid development of e commerce, purchase prediction has become an increasingly important consideration for a wide variety of retail platforms. This paper proposes a framework which combines machine learning methods with a threshold moving approach to predict sets of pairs (user id and brand id, in terms of whether a certain brand is purchased by a specified user according to his or her historical activity records. Three specific feature groups are extracted: click features, purchase features, and collect and cart features using a dataset from Tmall, a Chinese business to consumer online retail platform. Next, seven user purchase prediction experiments with different combinations of the three feature groups are conducted, and the purchase prediction performance is observed. Results showed that a combination of all three feature groups, with 27 features in total, provided valuable purchase prediction contributions and performed favorably. Also, three feature groups are proved to be relative independent, and our prediction model identified the most important feature, from the collect and cart feature group. Detailed result analysis validated the effectiveness of both the extracted features and proposed machine learning methods.
Circular sequence comparison: algorithms and applications
Venue: Algorithms for Molecular Biology

BackgroundSequence comparison is a fundamental step in many important tasks in bioinformatics; from phylogenetic reconstruction to the reconstruction of genomes. Traditional algorithms for measuring approximation in sequence comparison are based on the notions of distance or similarity, and are generally computed through sequence alignment techniques. As circular molecular structure is a common phenomenon in nature, a caveat of the adaptation of alignment techniques for circular sequence comparison is that they are computationally expensive, requiring from super quadratic to cubic time in the length of the sequences.ResultsIn this paper, we introduce a new distance measure based on q grams, and show how it can be applied effectively and computed efficiently for circular sequence comparison. Experimental results, using real DNA, RNA, and protein sequences as well as synthetic data, demonstrate orders of magnitude superiority of our approach in terms of efficiency, while maintaining an accuracy very competitive to the state of the art.
A topological navigation system for indoor environments based on perception events

The aim of the work presented in this article is to develop a navigation system that allows a mobile robot to move autonomously in an indoor environment using perceptions of multiple events. A topological navigation system based on events that imitates human navigation using sensorimotor abilities and sensorial events is presented. The increasing interest in building autonomous mobile systems makes the detection and recognition of perceptions a crucial task. The system proposed can be considered a perceptive navigation system as the navigation process is based on perception and recognition of natural and artificial landmarks, among others. The innovation of this work resides in the use of an integration interface to handle multiple events concurrently, leading to a more complete and advanced navigation system. The developed architecture enhances the integration of new elements due to its modularity and the decoupling between modules. Finally, experiments have been carried out in several mobile robots, and their results show the feasibility of the navigation system proposed and the effectiveness of the sensorial data integration managed as events.
Tourism and the creative industries theories, policies and practice

1. Introduction (Philip E. Long and Nigel D Morpeth) 2. Film, Mobility and Urban Space (Les Roberts) 3. Creativity, the visual arts and tourism (Nigel D Morpeth and Philip E. Long) 4. Tourism and Advertising as Creative Industry Sector (Mark Passera) 5. Tourism and the Creative Industries: Design and Designer Fashion (Corinna Budnarowska and Ruth Marciniak) 6. Urban Planning, Architecture And The Making of Creative Spaces (Ian Strange) 7. Challenges and opportunities for South Korean Tourism and Creative Industries (Sangkyun Kim Chanwoo Nam) 8.  The creative renaissance of Nantes and Saint Etienne (Charles Ambrosino, Vincent Guillon, Dominique Sagot Duvauroux) 9. Creating a Cosmopolitan Tourism Destination: The visual arts and music in the Ouseburn Valley, Newcastle upon Tyne, UK (James Whiting and Kevin Hannam) 10. The virtual tourist: the simulated environments and impossible geographies of videogames. (Michael Salmond and Jacqueline Salmond) 11. Travel and Transformation in the Fantasy Genre (Warwick Frost and Jennifer Laing) 12.  (Philip E. Long and Nigel D. Morpeth)
On videogames representing narrative in an interactive medium

This thesis investigates the function of narrative in videogames, challenging views that games do not and should not have anything to do with narrative. It tests videogames against literary narrative theories and examines ways in which videogames have evolved beyond other narratives and narrative theories. The narrative vs. ludology debate among videogame scholars has, at its core, the question of whether narrative is possible in videogames. Ludologists, who prioritize videogames as games, argue that narrative is incompatible with play, both interrupting and interfering with it. My research suggests that videogames often render narrative and play symbiotic, even inseparable, as the act of playing reveals and produces videogame narrative. Other objections to videogame narrative include the argument that videogame narrative is less sophisticated than narrative forms in other media. My thesis demonstrates that some videogames contain narrative every bit as complex as those in literature and film, holding up to rigorous testing by complex narratological theories. It further shows that changes in videogame technology and design have brought about evolutions in narrative that are the result of playing rather than being at odds with it. As narrative has evolved in videogames beyond its manifestations in older media, narrative theories developed to account for older media prove to be inadequate to explicate videogame narratives. The introduction and first chapter of the thesis delineate these issues, theories, and debates. The remaining chapters probe how videogame narrative unfolds in specific areas, such as identity and identification, the navigation of narrative space, narrative agency and authority, consumer ethics, and concepts of death and genre. Finally, the thesis considers the endings of videogames and how death is presented and represented in this medium. My conclusion summarises my own work and suggests possibilities for future studies of videogame narratives.
Counterfactual Thinking in Children With Autism Spectrum Disorders

Baron Cohen, S. Tager Flusberg, H. Cohen, D. J. (Eds. (2007) Understanding other minds: Perspectives from developmental cognitive neuroscience (2nd ed. Oxford, UK:  (2011) Almost thinking counterfactually: Children's understanding of close counterfactuals. Child Development 82: 1189 1198. Beck, S. R. Riggs, K. J. Gorniak, S. L. (2009) Relating developments in children's counterfactual thinking and executive functions. Thinking Reasoning, 15, 337 354. Epstude, K. Roese, N. J. (2008) The functional theory of counterfactual thinking. Personality and Social Psychology Review, 12, 168 192. Ferrell, J. M. Guttentag, R. E. Gredlein, J. M. (2009) Children's understanding of counterfactual emotions: Age differences, individual differences, and the effects of counterfactual information salience. The British Journal of Developmental Psychology, 27, 569 585. German, T. P. (1999) Children's causal reasoning: Counterfactual thinking occurs for "negative" outcomes only. Developmental Science, 2, 442 447. Gilbert, D. T. Morewedge, C. K. Risen, J. L. Wilson, T. D. (2004) Looking forward to looking backward The misprediction of regret.  (2004) Reality compared with its alternatives: Age differences in judgments of regret and relief. Developmental Psychology, 40, 764 775. Guttentag, R. Ferrell, J. (2008) Children's understanding of anticipatory regret and disappointment. Cognition and Emotion, 22, 815 832. Robinson, E. J. Beck, S. R. (2000) What is difficult about counterfactual reasoning? In P. Mitchell K. J. Riggs (Eds. Children's reasoning and the mind. Hove, UK: Psychology Press. Roese, N. J. (1997) Counterfactual thinking.  Bulletin, 121, 133 148. Perner, J. Sprung, M. Steinkogler, B. (2004) Counterfactual conditionals and false belief: A developmental dissociation. Cognitive Development, 19, 179 201. Sanna, L. J. Turley, K. J. (1996) Antecedents to spontaneous counterfactual thinking: Effects of expectancy violation and outcome valence. Personality and Social Psychology Bulletin, 22, 906 919. Weisberg, D. P. Beck, S. R. (2010) Children's thinking about their own and others' regret and relief. Journal of Experimental Child Psychology, 106, 184 191. White, K. Lehman, D. R. (2005) Looking on the bright side: Downward counterfactual thinking in response to negative life events. Personality and Social Psychology Bulletin,  Zeelenberg, M. Van Dijk, W. W. Manstead, A. S. R. van der Pligt, J. (1998) The experience of regret and disappointment. Cognition and Emotion, 12, 221 230.
Network intrusion detection system model based on data mining
Venue: 2016 17th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)

The paper's object is to develop a network intrusion detection model based on data mining technology, which can detect known intrusion effectively and has a good capacity to recognize unknown data schema which can't be detected effectively in traditional IDS. The paper mainly does the following work: by analyzing the intrusion deeply, extract the properties which can reflect intrusion characteristics effectively; combine misuse detection, anomaly detection and human intervention, establish rule library based on C.45 decision tree algorithm and use the optimal pattern matching so as to improve detection rate; the hosts are clustered to be IP group based on visit number by k means clustering algorithm, the audit data are divided into parts under the IP group's direction, and the classifiers are built up by divided audit data respectively, then the detected Data apply different rules according to their own IP group, thereby reduce false positives. The experiments proved that the method is effective to detect intrusion such as scanning and Deny of Service.
Combined Data and Execution Flow Host Intrusion Detection Using Machine Learning

We present in this chapter a novel method for detecting intrusion into host systems that combines both data and execution flow of programs. To do this, we use sequences of system call traces produced by the host's kernel, together with their arguments. The latter are further augmented with contextual information and domain level knowledge in the form of signatures, and used to generate clusters for each individual system call, and for each application type. The argument driven cluster models are then used to rewrite process sequences of system calls, and the rewritten sequences are fed to a naive Bayes classifier that builds class conditional probabilities from Markov modeling of system call sequences, thus capturing execution flow. The domain level knowledge augments our machine learning based detection technique with capabilities of deep packet inspection capabilities usually found, until now, in network intrusion detection systems. We provide the results for the clustering phase, together with their validation using the Silhouette width, the cross validation technique, and a manual analysis of the produced clusters on the 1999 DARPA data set from the MIT Lincoln Lab.
Environmental conditions shape soil bacterial community structure in a fragmented landscape

Several biogeographical hypotheses have been proposed to explain microbial distribution, but there is ongoing debate about the magnitude of the contribution of niche based processes and historical contingencies in determining patterns of microbial structure. In this context, currently fragmented relict forests of olivillo Aextoxicon punctatum Ruiz et. Pav. which belonged to a continuous community along the coast of Chile during the Pleistocene, and their surrounding scrublands are ideally suited for testing these hypotheses, since they remain as patches located at the northern tip of the distribution of the relicts. In each study site, edaphic and geographic variables were determined, and the bacterial structures were evaluated at the genetic and metabolic levels through fingerprint approaches along with multivariate analytical methods including redundancy (RDA) and variance partitioning (VPA) analyses. Forests possessed lower pH, and higher contents of moisture and organic matter. In addition, bacterial communities from both habitats differed, whereas the bacterial communities of the forests in different regions were very similar to each other. Our conclusion is that current abiotic soil factors, but not past events due to the historical connection of the forests, account for the variance in the structure of these soil bacterial communities.