Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting outcomes for anxious children receiving group cognitive‐behavioural therapy: Does the type of anxiety diagnosis make a difference?

Background Cognitive-behavioural therapy (CBT) is an efficacious treatment for anxiety disorders in children and adolescents, yet not all young people improve. Understanding predictors of treatment response can inform treatment improvements in order to enhance outcomes. Aim The purpose of this study was to compare treatment outcomes following group-based CBT for children with different anxiety disorders (social phobia (SocP), separation anxiety disorder (SAD), generalised anxiety disorder (GAD), specific phobia (SP)) to determine whether differential outcomes from group-based CBT are related to type of diagnosis. Method Participants were 205 clinically anxious children between 4 and 12 years of age. Treatment outcomes were assessed using clinician-rated diagnostic interviews, parent-report, and child-report symptom measures. Ninety-seven children completed a long-term follow-up assessment 6 or 12 months after treatment. Results Children with a principal diagnosis of SocP and GAD had a poorer post-treatment outcome compared to children with a principal diagnosis of SP and SAD. Poorer outcomes persisted in children with a principal diagnosis of SocP by the follow-up assessment compared to children with the other anxiety disorders. Conclusions These findings are consistent with recent studies that have found poorer outcomes from CBT for youth and adults with SocP, and emphasise the need for further research into treatments that target specific factors that could improve outcomes.
“Drinking Cultures” in University Residential Colleges

Young people’s heavy alcohol use has been widely linked to their “drinking cultures. ” Recent scholarly commentary, however, suggests that prevailing conceptualizations of drinking culture, including those in “public health-oriented” research, tend to oversimplify the complexities involved. This article contributes to the conceptual clarification and development of young people’s “drinking cultures. ” We provide a case study of a highly publicized example—that of Australian university residential college students. The case study focuses on the role of residential college policy and management in students’ alcohol use, examining how they represent, understand, and address it. Adopting a qualitative approach, we identify and analyze key themes from college policy documents and minimally structured interviews with college management related to students’ alcohol use. Our analysis is informed by two key existing works on the subject. The first is a sociological framework theorizing young people’s heavy drinking as a “culture of intoxication,” which is embedded in and shaped by broader social forces, especially those linked to a “neoliberal social order. ” The second draws on findings from a previously published study on student drinking in university residential colleges that identified the significant role of institutional “micro-processes” for shaping alcohol use in university residential colleges. In understanding the specific character of students’ drinking in Australian university residential colleges, however, we also draw on sociological—specifically neo-institutionalist—approaches to organizations, proposing that Australian college policy and management related to students’ drinking do not operate simply as regulatory influences. Rather, they are organizational processes integral to residential college students’ drinking cultures and their making. Accordingly, college alcohol policy and management of students’ drinking, as they have prevailed in this Australian context, offer limited opportunities for minimizing harmful drinking.
Program slicing with dynamic points-to sets

Program slicing is a potentially useful analysis for aiding program understanding. However, in reality even slices of small programs are often too large to be useful. Imprecise pointer analyses have been suggested as one cause of this problem. In this paper, we use dynamic points-to data, which represents optimistic pointer information, to obtain a bound on the best case slice size improvement that can be achieved with improved pointer precision. Our experiments show that slice size can be reduced significantly for programs that make frequent use of calls through function pointers because for them the dynamic pointer data results in a considerably smaller call graph, which leads to fewer data dependences. Programs without or with only few calls through function pointers, however, show considerably less improvement. We discovered that C programs appear to have a significant fraction of direct and nonspurious pointer data dependences so that reducing spurious dependences via pointers is only of limited benefit. Consequently, to make slicing useful in general for such programs, improvements beyond better pointer analyses are necessary. On the other hand, since we show that collecting dynamic function pointer information can be performed with little overhead (average slowdown of 10 percent for our benchmarks), dynamic pointer information may be a practical approach to making slicing of programs with frequent function pointer use more successful in practice.
Tuning semantic association for modelling textual data

Text information processing depends critically on the proper representation of documents. Traditional models, like the vector space model, have significant limitations because they do not consider semantic relations amongst terms. Global Association Distance Model (GADM) is an alternative that includes this consideration for document representation, assuming basically that two documents should be closer if the shortest formal distances amongst terms in each document are similar. The association strength function used to model the semantic relations among terms, based on its formal distances is a critical feature of GADM. In this paper the association strength function is analyzed, a family of piecewise association strength functions is proposed and a Simulated Annealing algorithm is used to tune it and to obtain an optimal model of semantic relation. We evaluate this significance for topic classification task.
Belief rule-base inference methodology using the evidential reasoning Approach-RIMER

In this paper, a generic rule-base inference methodology using the evidential reasoning (RIMER) approach is proposed. Existing knowledge-base structures are first examined, and knowledge representation schemes under uncertainty are then briefly analyzed. Based on this analysis, a new knowledge representation scheme in a rule base is proposed using a belief structure. In this scheme, a rule base is designed with belief degrees embedded in all possible consequents of a rule. Such a rule base is capable of capturing vagueness, incompleteness, and nonlinear causal relationships, while traditional if-then rules can be represented as a special case. Other knowledge representation parameters such as the weights of both attributes and rules are also investigated in the scheme. In an established rule base, an input to an antecedent attribute is transformed into a belief distribution. Subsequently, inference in such a rule base is implemented using the evidential reasoning (ER) approach. The scheme is further extended to inference in hierarchical rule bases. A numerical study is provided to illustrate the potential applications of the proposed methodology.
Open-Ended Interaction in Coorperative Prototyping: A Video-Based Analysis

Cooperative Prototyping can be characterized as the use and development of prototypes as catalysts during discussions between designers and potential users ‐ the overall intention being one of mutual learning. On the one hand, the designers learn more about the work practices of the users in ways that are tied concretely to some current version of the prototype. On the other hand, the users learn more about the potential for change in their work practice, whether computer-based or otherwise. This paper presents the results of a field study of the cooperative prototyping process. The study is based on a fine-grained video-based analysis of a single prototyping session, and focuses on the effects of an open-ended style of interaction between users and designers around a prototype. An analysis of focus shifts, initiative and storytelling during the session is brought to bear on the question of whether and how cooperative prototyping can be successful with users who are reluctant to “play in the future. ” The paper also discusses issues in applying video analysis to system design.
Boosting Classification Based Speech Separation Using Temporal Dynamics

Significant advances in speech separation have been made by formulating it as a classification problem, where the desired output is the ideal binary mask (IBM). Previous work does not explicitly model the correlation between neighboring time-frequency units and standard binary classifiers are used. As one of the most important characteristics of speech signal is its temporal dynamics, the IBM contains highly structured, instead of, random patterns. In this study, we incorporate temporal dynamics into classification by employing structured output learning. In particular, we use linear-chain structured perceptrons to account for the interactions of neighboring labels in time. However, the performance of structured perceptrons largely depends on the linear separability of features. To address this problem, we employ pretrained deep neural networks to automatically learn effective feature functions for structured perceptrons. The experiments show that the proposed system significantly outperforms previous IBM estimation systems.
Speciation in NEAT

This paper investigates speciation in NEAT and its effect on NEAT’s performance. Speciation is the set of processes by which NEAT creates, maintains and uses several disjoint groups of similar genomes for guiding reproduction. This paper also examines the issue of adoption, where mating within a species produces an individual in a different species. It then examines the relationship between NEAT’s performance, the adoption rate and the number of species. The paper demonstrates that while species and adoptions are necessary, too many species and adoptions harm the algorithm’s performance.
, implications for tubular Na reabsorption renal cells by affecting constitutive endocytosis :-Adducin mutations increase Na / K pump activity in

295:F478-F487, 2008. First published 4 June 2008; Am J Physiol Renal Physiol Giuseppe Bianchi and Chiara Zurzolo Paolo Tarsini, Ornella Russo, Daniela Sarnataro, Pasquale Strazzullo, Patrizia Ferrari, Lucia Torielli, Simona Tivodar, Rosa Chiara Montella, Roberto Iacone, Gloria Padoani, implications for tubular Na reabsorption renal cells by affecting constitutive endocytosis: -Adducin mutations increase Na/K pump activity in α
It's all in the game: Towards an affect sensitive and context aware game companion

Robot companions must be able to display social, affective behaviour. As a prerequisite for companionship, the ability to sustain long-term interactions with users requires companions to be endowed with affect recognition abilities. This paper explores application-dependent user states in a naturalistic scenario where an iCat robot plays chess with children. In this scenario, the role of context is investigated for the modelling of user states related both to the task and the social interaction with the robot. Results show that contextual features related to the game and the iCat's behaviour are successful in helping to discriminate among the identified states. In particular, state and evolution of the game and display of facial expressions by the iCat proved to be the most significant: when the user is winning and improving in the game her feeling is more likely to be positive and when the iCat displays a facial expression during the game the user's level of engagement with the iCat is higher. These findings will provide the foundation for a rigorous design of an affect recognition system for a game companion.
Bioconversion of Artemisinin to its Nonperoxidic Derivative Deoxyartemisinin through Suspension Cultures of Withania somnifera Dunal

Biotransformation of artemisinin was investigated with two different cell lines of suspension cultures of Withania somnifera. Both cell lines exhibited potential to transform artemisinin into its nonperoxidic analogue, deoxyartemisinin, by eliminating the peroxo bridge of artemisinin. The enzyme involved in the reaction is assumed to be artemisinin peroxidase, and its activity in extracts of W. somnifera leaves was detected. Thus, the non-native cell-free extract of W. somnifera and suspension culture-mediated bioconversion can be a promising tool for further manipulation of pharmaceutical compounds.
Stickelberger elements and Kolyvagin systems

A BSTRACT . In this paper, we construct (many) Kolyvagin systems out of Stickelberger elements utilizing ideas borrowed from our previous work on Kolyvagin systems of Rubin-Stark elements. The applications of our approach are two-fold: First, assuming Brumer’s conjecture , we prove results on the odd parts of the ideal class groups of CM ﬁelds which are abelian over a totally real ﬁeld, and deduce Iwasawa’s main conjecture for totally real ﬁelds (for totally odd characters). Although this portion of our results have already been established by Wiles un-conditionally (and reﬁned by Kurihara using an Euler system argument, when Wiles’ work is assumed), the approach here ﬁts well in the general framework the author has developed else-where to understand Euler / Kolyvagin system machinery when the core Selmer rank is r > 1 (in the sense of Mazur and Rubin). As our second application, we establish a rather curious link between the Stickelberger elements and Rubin-Stark elements by using the main constructions of this article hand in hand with the ‘rigidity’ of the collection of Kolyvagin systems proved by Mazur, Rubin and the author.
A new gap-based collision avoidance method for mobile robots

This paper presents a new concept, the “Directly Navigable Gap”, for reactive obstacle avoidance. A directly navigable gap DNG is defined as the gap that a robot can safely navigate through by executing only a single motion command. With this concept, it has been possible to achieve navigation in unknown cluttered environments, similar to the gap-based obstacle avoidance methods (e.g the Nearness-Diagram Navigation). Compared to these methods, however, our approach avoids the limitation of being prone to oscillatory and unstable motion, improving their navigation performance, especially in narrow spaces. Experimental results are presented to verify the outstanding performance of the proposed DNG approach. Moreover, a discussion and comparison with existing gap-based methods is reported where the DNG approach generates less-oscillatory, safer, and faster trajectories than its counterparts.
Dissociative Experiences and Trauma Exposure Among Newly Arrived and Settled Young War Refugees

ABSTRACT War-traumatized refugee adolescents are a vulnerable and understudied group. This study of two different groups of war-traumatized youth (N = 77) resettled in Sweden (newly arrived refugee adolescents, n = 42, 13–19 years, and settled students with childhood war experiences, n = 35, 11–18 years) evaluated their war experiences, refugee journey, general trauma exposure, posttraumatic stress symptoms, and dissociative experiences. Both groups had experienced many traumas and a substantial proportion reported levels consistent with posttraumatic stress (71% in the newly arrived group and 34% among the settled students) and dissociation (36% and 23%, respectively). The study also provides information about the type of adverse events experienced by war-refugee adolescents, including their own subjective appraisals of the worst events. The results show that the extent of trauma exposure and posttraumatic and dissociative symptomatology among refugee adolescents are considerable even after a period of resettlement, a finding that has educational, clinical, and social implications.
Pathogen espionage: multiple bacterial adrenergic sensors eavesdrop on host communication systems

The interactions between bacterial pathogens and their eukaryotic hosts are vital in determining the outcome of infections. Bacterial pathogens employ molecular sensors to detect and facilitate adaptation to changes in their niche. The sensing of these extracellular signals enables the pathogen to navigate within mammalian hosts. Intercellular bacterial communication is facilitated by the production and sensing of autoinducer (AI) molecules via quorum sensing. More recently, AI‐3 and the host neuroendocrine (NE) hormones adrenaline and noradrenaline were reported to display cross‐talk for the activation of the same signalling pathways. Remarkably, there is increasing evidence to suggest that enteric bacteria sense and respond to the host NE stress hormones adrenaline and noradrenaline to modulate virulence. These responses can be inhibited by α and β‐adrenergic receptor antagonists implying a bacterial receptor‐based sensing and signalling cascade. In Escherichia coli O157:H7 and Salmonella, QseC has been proposed as the adrenergic receptor. Strikingly, there is an increasing body of evidence that not all the bacterial adrenergic responses require signalling through QseC. Here we provide additional hypotheses to reconcile these observations implicating the existence of alternative adrenergic receptors including BasS, QseE and CpxA and their associated signalling cascades with major roles in interkingdom communication.
Effect of Whole-Body Exposure to High-Frequency Electromagnetic Field on the Brain Cortical and Hippocampal Activity in Mouse Experimental Model

Evaluation of the direct registration of brain cortical and hippocampal activity during a high-frequency electromagnetic field (HF-EMF) exposure was performed. Experimental procedures were done under general anesthesia (urethane, 20%, 2g/kg i.p.) in Lurcher mutant mice, wild type (healthy littermates) were used as controls. Animals were exposed to the HF-EMF with frequency corresponding to cellular phones (900 MHz). We used of gel electrodes (silicon tubes or glass microcapillary filled with agar) where the connection with classical electrodes was located out of HF-EMF space. ECoG evaluation showed a distinct shift to lower frequency components but clear effect has been observed only in wild type (healthy) mice whereas in Lurcher mutant mice only gentle differences between frequency spectra were found. Measurement of hippocampal rhythmicity showed gentle changes with increase of higher frequencies (i.e. opposite effect than in cortex) and changes in theta oscillations registered from a dentate gyrus and CA1 area in both types of animals (healthy and mutant). These findings support an idea about possible influencing the central nervous system by HF-EMF exposure and support also some recent results about possible health risks resulting from cellular phones use.
Parallel Tagged Next-Generation Sequencing on Pooled Samples – A New Approach for Population Genetics in Ecology and Conservation

Next-generation sequencing (NGS) on pooled samples has already been broadly applied in human medical diagnostics and plant and animal breeding. However, thus far it has been only sparingly employed in ecology and conservation, where it may serve as a useful diagnostic tool for rapid assessment of species genetic diversity and structure at the population level. Here we undertake a comprehensive evaluation of the accuracy, practicality and limitations of parallel tagged amplicon NGS on pooled population samples for estimating species population diversity and structure. We obtained 16S and Cyt b data from 20 populations of Leiopelma hochstetteri, a frog species of conservation concern in New Zealand, using two approaches – parallel tagged NGS on pooled population samples and individual Sanger sequenced samples. Data from each approach were then used to estimate two standard population genetic parameters, nucleotide diversity (π) and population differentiation (FST), that enable population genetic inference in a species conservation context. We found a positive correlation between our two approaches for population genetic estimates, showing that the pooled population NGS approach is a reliable, rapid and appropriate method for population genetic inference in an ecological and conservation context. Our experimental design also allowed us to identify both the strengths and weaknesses of the pooled population NGS approach and outline some guidelines and suggestions that might be considered when planning future projects.
ARI

Decreasing the traffic from the CPU LLC to main memory is a very important issue in modern systems. Recent work focuses on cache misses, overlooking the impact of writebacks on the total memory traffic, energy consumption, IPC, and so forth. Policies that foster a balanced approach, between reducing write traffic to memory and improving miss rates, can increase overall performance and improve energy efficiency and memory system lifetime for NVM memory technology, such as phase-change memory (PCM). We propose Adaptive Replacement and Insertion (ARI), an adaptive approach to last-level CPU cache management, optimizing the two parameters (miss rate and writeback rate) simultaneously. Our specific focus is to reduce writebacks as much as possible while maintaining or improving the miss rate relative to conventional LRU replacement policy. ARI reduces LLC writebacks by 33%, on average, while also decreasing misses by 4.7%, on average. In a typical system, this boosts IPC by 4.9%, on average, while decreasing energy consumption by 8.9%. These results are achieved with minimal hardware overheads.
Hybrid emergency voltage control in power systems

This paper presents a novel emergency control scheme capable of predicting and preventing a voltage collapse in a power system, that is modelled as a hybrid system incorporating nonlinear dynamics, discrete events and discrete manipulated variables. Model Predictive Control in connection with the Mixed Logical Dynamical framework is used to successfully stabilize the voltage of a four bus example system.
User browsing behavior-driven web crawling

To optimize the performance of web crawlers, various page importance measures have been studied to select and order URLs in crawling. Most sophisticated measures (e.g. breadth-first and PageRank) are based on link structure. In this paper, we treat the problem from another perspective and propose to measure page importance through mining user interest and behaviors from web browse logs. Unlike most existing approaches which work on single URL, in this paper, both the log mining and the crawl ordering are performed at the granularity of URL pattern. The proposed URL pattern-based crawl orderings are capable to properly predict the importance of newly created (unseen) URLs. Promising experimental results proved the feasibility of our approach.
Methods for precise named entity matching in digital collections

We describe an interactive system, built within the context of CLiMB project, which permits a user to locate the occurrences of named entities within a given text. The named entity tool was developed to identify references to a single art object (e.g. a particular building) with high precision in text related to images of that object in a digital collection. We start with an authoritative list of art objects, and seek to match variants of these named entities in related text. Our approach is to "decay" entities into progressively more general variants while retaining high precision. As variants become more general, and thus more ambiguous, we propose methods to disambiguate intermediate results. Our results are used to select records into which automatically generated metadata are loaded.