Miracle-dz/UniFAR-FTUs huggingface dataset:
Developmental Stability and Change in Self-Regulation From Childhood to Adolescence

The authors examined the developmental course of self-regulation in a cohort of children from the National Longitudinal Survey of Youth. The longitudinal sample included 646 children (48% girls; 52% boys; 36.2% Black, 23.4% Hispanic, 40.4% White) who were 4 to 5 years old in 1986 and who were followed up at ages 8 to 9 and ages 12 to 13. Levels of self-regulation (assessed with 12 maternal-report items that measured regulation of affect, behavior, attention) increased from early childhood (when sample children were 4 or 5 years old) to middle childhood (ages 8 or 9), but not from middle childhood to early adolescence (ages 12 or 13). Girls exhibited significantly higher levels of self-regulation than did boys at all 3 time points. Individual differences in self-regulation were fairly stable across the 8-year span (rs =.47 to .50). Comparisons of 1-, 2-, and 3-factor models suggested that the different aspects of self-regulation are highly interrelated, and support adoption of a single-factor model for both genders. The authors discuss implications of these findings for theory and intervention.
Dynamic Hill Climbing: Overcoming the limitations of optimization techniques

This paper describes a novel search algorithm, called dynamic hill climbing, that borrows ideas from genetic algorithms and hill climbing techniques. Unlike both genetic and hill climbing algorithms, dynamic hill climbing has the ability to dynamically change its coordinate frame during the course of an optimization. Furthermore, the algorithm moves from a coarse-grained search to a ne-grained search of the function space by changing its mutation rate and uses a diversity-based distance metric to ensure that it searches new regions of the space. Dynamic hill climbing is empirically compared to a traditional genetic algorithm using De Jong's well-known ve function test suite 4] and is shown to vastly surpass the performance of the genetic algorithm, often nding better solutions using only 1% as many function evaluations.
Adherence to e-therapy for adults with eating disorders: a systematic review. A retrospective case series investigation of blended internet-based cognitive-behavioural therapy (ICBT) and face-to-face cognitive-behavioural therapy (CBT) in the treatment of adults with eating disorders

s of unpublished research. The search terms were: (online or web* or "e-therap*" or computer* or internet or "e-mental health" or mhealth or CCBT or ICBT or telemedicine or telehealth or mobile) AND (bulimi* or anorexi* or "binge eat*" or purg* or "eating disorder*" or "disordered eating" or EDNOS or OSFED or UFED) AND (Trial). The database search yielded 1,669 papers, with 1,648 remaining after duplicate removal (see Figure 1). During first screening of study titles and abstracts against inclusion criteria, 1,614 papers were removed for meeting one or more exclusion criteria. A further 20 papers were exclude at second screening for not meeting eating disorder diagnosis and/or the e-therapy treatment programme inclusion criteria (see Appendix B for excluded papers). Three protocol authors identified during searching were contacted regarding unpublished results (Castelnuovo et al., 2011; Zwaan et al., 2012, Klein, 2011), with one detailing results were under journal review and not available within this review’s timescales (De Zwaan et al., 2012). Data was extracted using a template developed for this specific review (detailed in Table 2), with information on study characteristics synthesised to explore the nature of intervention/control group within studies (type of e-therapy, duration, therapist support, financial incentives) and sample characteristics (diagnosis, sample size, sex, mean age, mean duration of illness, previous eating disorder treatment). Adherence and dropout information was extracted, and where not explicitly provided, was calculated by the author and additional information deemed useful was extracted. Assessment of quality of included studies CRD guidance indicates a standard quality assessment scale for undertaking systematic reviews is yet to be reached (Centre for Reviews and Dissemination,
Estimation of user's activity from tweets through tri-layer clustering model

We propose a topic model to better estimate activities from tweets. The whole estimation process consists of two phases: one is the cluster generation, and the other is the activity estimation. At the first phase, we obtain the expected trilayer clusters with the components: a topic layer, an activity layer and a word layer. Then, at the second phase, we utilize the activity-specific word distribution derived from the training results to learn the activities of testing tweets. To prove the feasibility of this model, we evaluate the precision of activity estimation using 35 activities to extract 23,988 tweets for training and 350 for testing, respectively. The experimental results demonstrate that the reasonable topic-specific activity distribution contributes to the cluster generation, and the proposed model exhibits the superiority in activity estimation.
Suggesting Hashtags on Twitter

As micro-blogging sites, like Twitter, continue to grow in popularity, we are presented with the problem of how to effectively categorize and search for posts. Looking specifically at Twitter, we see that users may categorize their posts using hashtags, and any word or phrase may be used as the category. Attempting to search for tweets about Facebook, a user would need to try many different hashtags, like #Facebook, #FB, #Facebook.com, or #Zuckerberg. To combat this, we propose, implement and evaluate a tool for suggesting relevant hashtags to a user, given a tweet. Initial analyses suggest our dataset is rich enough to extract informative distributions of words for many hashtags that will facilitate a naive Bayes model for hashtag recommendation given a query post.
A Novel Software Defined Networking Framework for Cloud Environments

Virtual network management is a basic component provided by cloud computing system. In cloud environment, the fact that VMs in the same subnet are located in different hosts, the traffic of VMs attached to different users should be isolated, the VM would be migrated to other hosts makes network management different from that in physical network. Technology like overlay and SDN is usually introduced to establish a reliable and efficient virtual network management scheme. However, there are many drawbacks such as flexibility and hardware costs in most schemes introducing technology above-mentioned. We addressing these problems by designing a scheme on the hyper-visor layer of physical hosts based on overlay and SDN technology, which means the tradition virtual network can be easily transformed to our system without purchasing new devices supported OpenFlow or VXLAN(a kind of technology in overlay) protocol. Besides additional functions like monitor and traffic mirror can be customized by users' needs for the system's flexibility and scalability the SDN technology endowing. We also design a Distributed Virtual Router(DVR) on each host to solve the general problem of traffic between Internet and Intranet concentrating in most schemes. The experimental evaluation shows that our system has achieve the basic intercommunication under the situation of tenant isolation and its performance of communication between Internet and Intranet acts obviously better than that in OpenStack scheme for our DVR design.
Hybrid approach for event detection from video surveillance sequences

In this paper, we propose a strategy of combined SVMs learning system for detection of predefined events in the video. The extraction and synthesis of suitably visual descriptor based on moving object traking are used for this purpose. The results showed that the performance of this combined classifiers is improving vs a single SVM. We then demonstrate the usefulness of the toolbox in the context of feature extraction, events learning and detection in large collection of video surveillance dataset
Repairing syntax errors in LR parsers

This article reports on an error-repair algorithm for LR parsers. It locally inserts, deletes or shifts symbols at the positions where errors are detected, thus modifying the right context in order to resume parsing on a valid piece of input. This method improves on others in that it does not require the user to provide additional information about the repair process, it does not require precalculation of auxiliary tables, and it can be easily integrated into existing LR parser generators. A Yacc-based implementation is presented along with some experimental results and comparisons with other well-known methods.
Encultured Biases: The Role of Products in Pathways to Inequality

Recent sociological work shows that culture is an important causal variable in labor market outcomes. Does the same hold for product markets? To answer this question, we study a product market in which selection decisions occur absent face-to-face interaction between intermediaries and short-term contract workers. We find evidence of “product-based” cultural matching operating as a pathway to inequality. Relying on quantitative and qualitative observational data and semi-structured interviews with intermediaries in trade fiction publishing, we show intermediaries culturally match themselves to manuscripts as a normal feature of doing “good work. ” We propose three organizational conditions under which “encultured biases” come to the fore in product selection, and a fourth resulting in inequalities along demographic lines and other markers of perceived cultural proximity and distance. We close with a discussion of other settings in which product-based cultural matching is likely to occur, call for the investigation of cultural matching beyond previously theorized conditions, and argue for the inclusion of cultural products in the broader movement toward reconsidering culture as a causal factor.
Approche interdisciplinaire-physiologique, psychologique et de traitement du signal-du stress induit au sein d'une interface de résolution de problèmes

Le stress correspond a un processus cognitif au cours duquel un sujet evalue et prend en compte les menaces et les defis de son environnement. Il n'est pas uniquement un stimulus ou une reponse, mais peut etre induit par le contexte d'apprentissage (interferences visuelles et sonores) et l'interface utilisee (pression temporelle et feedbacks). Notre etude vise a analyser les effets psycho-physiologiques d'un stress induit associe a une charge cognitive. Pour ce faire, les sujets sont confrontes a des tâches de resolution de problemes, combinees ou non a differents niveaux de stress. Des tests psychologiques sont utilises afin de quantifier les niveaux d'anxiete et de charge cognitive. Le traitement des signaux cardiaques (intervalles RR) enregistres fournit des parametres issus d'une analyse temporelle, des indicateurs de puissance fondes sur une analyse spectrale et des indices de regularite. Nos resultats montrent qu'une approche interdisciplinaire psychologique, physiologique et statistique permet de differencier le stress d'une tâche cognitive simple.
A pair of heterogeneous agents in a unique vehicle for object motion

We present a multi agent architecture for controlling a mobile robot in an unpredictable environment. This architecture has been developed with the objective of coordinating the various competences of the robot (e.g., perception, navigation, planning). The architecture is made up of two agents: the first one specialized for cognitive tasks, the second one dedicated to control of the robot's physical devices. This two agent architecture guarantees a good robustness of the system, as the navigation modules can run independently of the cognitive ones.
Parallel Real-Time OLAP on Multi-core Processors

One of the most powerful and prominent technologies for knowledge discovery in Decision Support systems is On-line Analytical Processing (OLAP). Most of the traditional OLAP research, and most of the commercial systems, follow the static data cube approach proposed by Gray etal. and materialize all or a subset of the cuboids of the data cube in order to ensure adequate query performance. Practitioners have called for some time for a real-time OLAP approach where the OLAP system gets updated instantaneously as new data arrives and always provides an up-to-date data warehouse for the decision support process. However, a major problem for real-time OLAP are significant performance issues with large scale data warehouses. The aim of our research is to address these problems through the use of efficient parallel computing methods. In this paper, we present a parallel real-time OLAP system for multi-core processors. To our knowledge, this is the first real-time OLAP system that has been parallelized and optimized for contemporary multi-core processors, providing the opportunity for real-time OLAP on large scale data warehouses. Our system allows for multiple insert and multiple query operations (transactions) to be executed in parallel and in real-time. We evaluated our method for a multitude of scenarios (different ratios of insert and query transactions, query transactions with different sizes of results, different system loads, etc.), using the TPC-DS "Decision Support'" benchmark data set. The tests demonstrate that our parallel system achieves a significant speedup in transaction response time and a significant increase in transaction throughput. Since hardware performance improvements are currently achieved not by faster processors but by increasing the number of processor cores, our new parallel real-time OLAP method has the potential to enable OLAP systems that are real-time and efficient/feasible for large databases.
Scalable Content-based Publish / Subscribe

Despite suffering from inefficiency and flexibility limitations, the filter-based routing (FBR) algorithm is widely used in content-based publish/subscribe (pub/sub) systems. To address these limitations, we propose a dynamic destination-based routing algorithm called D-DBR, which decomposes pub/sub into two independent parts: Content-based matching and destinationbased multicasting. D-DBR exhibits low event matching cost and high efficiency, flexibility, and robustness for event routing for overlays with up to hundreds of brokers. We further extend DDBR to a novel routing algorithm called MERC for overlays with larger number of brokers. MERC divides the overlay into interconnected clusters and applies FBR and D-DBR to route events interand intra-cluster, respectively. We implemented all algorithms in the PADRES pub/sub system. Experimental results show that our algorithms outperform FBR in terms of improving event dissemination throughput by up to 700% and reducing the end-to-end latency by up to 55%.
Using Lie group symmetries for fast corrective motion planning

In this paper we develop an algorithmic framework allowing for fast and elegant path correction exploiting Lie group symmetries and operating without the need for explicit control strategies such as cross-track regulation. These systems occur across the gamut of robotics, notably in locomotion, be it ground, underwater, airborne, or surgical domains. Instead of reintegrating an entire trajectory, the method selectively alters small key segments of an initial trajectory in a consistent way so as to transform it via symmetry operations. The algorithm is formulated for arbitrary Lie groups and applied in the context of the special Euclidean group and subgroups thereof. A sampling-based motion planner is developed that uses this method to create paths for underactuated systems with differential constraints. It is also shown how the path correction method acts as a controller within a feedback control loop for real-time path correction. These approaches are demonstrated for ground vehicles in the plane and for flexible bevel tip needle steering in space. The results show that using symmetry-based path correction for motion planning provides a prudent and simple, yet computationally tractable, integrated planning and control strategy.
Information Management Tools for the Development of Self-Regulated Learning Skills in Pre-service Teacher Education

This article presents a didactic strategy aimed at developing student teachers’ personal learning environments (PLEs) with a self-regulated learning (SRL) approach. The strategy is framed in the Dabbagh and Kitsantas (2012) model, which relates Zimmerman’ SRL cycle (forethought, performance, self-reflection) to the three levels of social media usage (personal information management, social interaction and collaboration, and information aggregation and management). A learning scenario was implemented to facilitate SRL skills through information management. The participants were 241 students of Education at the University of Balearic Islands (Spain) and data was collected through a questionnaire designed to explore tool usage and their perceptions of the effectiveness of those tools for information management tasks. Data analysis allows the observation of some patterns in the usage of information management tools in the diverse learning scenarios. In the conclusions challenges such as resistance and traditional assessment focus are identified; affordances for transferability of the acquired skills to other contexts are highlighted and further educational implementation and research are suggested. With this work, a model applicable to other contexts is provided, and a didactic strategy for the management of information based on the PLE and the SRL is presented.
An Efficient Semantic Similarity Search on XML Documents

In this paper, we study the use of XML path query to search an XML fragment in a collection of XML documents. We present efficient techniques that are able to employ bit-slice bloom-filtered signature file as filter and investigate an approach that are able to measure semantic similarity between the query and the XML document in the collection by considering their structures and contents. A ranked list of XML fragments is generated as the search results. By using a set of path queries on a variety of XML documents, the experiments show that the precision and efficiency of the results perform better than ever.
Do the physical characteristics of a virtual reality device contraindicate its use for balance assessment?

CONTEXT Virtual reality environments may allow researchers to investigate functional balance performance without risks associated with testing in the real world. OBJECTIVE To investigate the effects of the mass of a head-mounted display (HMD) on balance performance. DESIGN Counterbalanced pretest-posttest. SETTING Virtual reality laboratory. PARTICIPANTS 20 healthy college students. INTERVENTION(S) Balance Error Scoring System (BESS) with a tracker-only headband and again with tracker plus HMD was performed. MAIN OUTCOME MEASURES BESS error scores, elliptical sway area, and center of pressure travel distance were recorded. RESULTS No effect of the HMD mass on balance performance was observed. A significant stance by surface interaction was present but was negated when the HMD conditions were included in the model. CONCLUSIONS The mass of a HMD has not been proven to adversely affect balance performance. These data suggest the HMD mass is not a contraindication to the use of immersive virtual environments in future concussion research involving balance.
Academic Underperformance in Children with ADHD: Is Medication the Solution?

Background Academic improvement is amongst the most common treatment targets when prescribing stimulants to children with ADHD. Previous reviews on stimulant-related academic improvements are inconclusive and focus on task-engagement. Recent literature suggests outcome-domain specific medication effects that are larger for productivity than for accuracy. Aims Quantifying methylphenidate effects on academic productivity and accuracy for math, reading, spelling; exploring the mediating or moderating effects of symptomimprovements; demographic-, designand disorder-related variables. Method PubMed, EMBASE, ERIC and PsycINFO were searched for articles reporting methylphenidate effects on academic productivity and accuracy. Results Thirty-four studies met entry criteria. Methylphenidate improved math productivity (7.8% increase, p<.001); math accuracy (3.0% increase, p=.001); increased reading speed (SMD .47, p<.001) but not reading accuracy. None of the mediators or moderators tested affected methylphenidate efficacy. Conclusions Academic improvements were small compared to symptom-improvements; qualitative changes limited to math. Clinicians should take this discrepancy into account when prescribing medication for ADHD.
Designing Climate Mitigation Policy

This paper provides an exhaustive review of critical issues in the design of climate mitigation policy by pulling together key findings and controversies from diverse literatures on mitigation costs, damage valuation, policy instrument choice, technological innovation, and international climate policy. We begin with the broadest issue of how high assessments suggest the near and medium term price on greenhouse gases would need to be, both under cost-effective stabilization of global climate and under net benefit maximization or Pigouvian emissions pricing. The remainder of the paper focuses on the appropriate scope of regulation, issues in policy instrument choice, complementary technology policy, and international policy architectures.
Electoral Sociology : Who Votes for the Extreme Right and why – and when ?

This chapter profiles the social base of electoral support for the parties of the Extreme Right in Western Europe, i.e. the question of whether some groups in society are more susceptible to the appeal of these parties than others. This issue is relevant for a number of reasons: First, by looking at the social composition of European societies we might be able to better understand why parties of the Extreme Right are more successful in some countries than in others. Second, a careful analysis of the link between the social and the political might help us to gauge the potential for future right-wing mobilisation in countries which currently have no electorally successful parties of the Extreme Right. Third, knowing who votes for a party might help us to get a clearer understanding of the underlying motives to cast a vote for the Extreme Right. Over the last 15 years or so, analyses of the Extreme Right’s electorate(s) have become a minor industry within the larger context of (comparative) Political Sociology. By necessity, this chapter aims at summarising the main findings from this research program, but cannot strive for a comprehensive presentation of all that has been achieved during these years. More specifically, findings from national and small-n studies are (almost) completely ignored. Much by the same token, I will not delve into the fascinating literature on the social bases of the Interwar Extreme Right in Germany and in other countries (Childers, 1983; Falter, 1991; King, Tanner and Wagner, 2008; Küchler, 1992; O’Loughlin, 2002). Recent events in Central and Eastern Europe (Mudde, 2005) provide a fascinating complement to this Western perspective. However, much like Central and Eastern European parties and electorates themselves, our (comparative) knowledge of the social base of the Extreme Right in CEE in still very much in flux. Therefore, the chapter aims to provide a comparative perspective on developments in West European electoral politics since the 1980s.
The deconfining phase transition for SU(N) theories in 2+1 dimensions

The critical temperatures for the 2+1 dimensional $SU(N_c)$ gauge theories are calculated, for $N_c = 4,5,6$. The transition is shown to be first order for $N_c \geq 5$. The critical temperature and latent heat are extrapolated to $N_c = \infty$.