Miracle-dz/UniFAR-FTUs huggingface dataset:
De-escalation: A methodology to reduce coercive measures in clinical psychiatry. A project based on Action Research Principles

The study investigates whether coercive measures and violence can be reduced in psychiatric wards when staff uses a deescalating approach, as the patient's behaviour is escalating. The study is based on action research principles and the objective is to identify, characterize and test deescalating methods that can ". redirect a patient towards a calmer personal space . " (National Institute for Clinical Excellence, 2005). Successful de-escalation might prevent violence, and if a patient experiences rapid assistance, the use of coercive measures might be reduced.
Laterality across languages: Results from a global dichotic listening study using a smartphone application

Left-hemispheric language dominance has been suggested by observations in patients with brain damages as early as the 19th century, and has since been confirmed by modern behavioural and brain imaging techniques. Nevertheless, most of these studies have been conducted in small samples with predominantly Anglo-American background, thus limiting generalization and possible differences between cultural and linguistic backgrounds may be obscured. To overcome this limitation, we conducted a global dichotic listening experiment using a smartphone application for remote data collection. The results from over 4,000 participants with more than 60 different language backgrounds showed that left-hemispheric language dominance is indeed a general phenomenon. However, the degree of lateralization appears to be modulated by linguistic background. These results suggest that more emphasis should be placed on cultural/linguistic specificities of psychological phenomena and on the need to collect more diverse samples.
A new dynamical mechanism for major climate shifts

[1] We construct a network of observed climate indices in the period 1900–2000 and investigate their collective behavior. The results indicate that this network synchronized several times in this period. We find that in those cases where the synchronous state was followed by a steady increase in the coupling strength between the indices, the synchronous state was destroyed, after which a new climate state emerged. These shifts are associated with significant changes in global temperature trend and in ENSO variability. The latest such event is known as the great climate shift of the 1970s. We also find the evidence for such type of behavior in two climate simulations using a state-of-the-art model. This is the first time that this mechanism, which appears consistent with the theory of synchronized chaos, is discovered in a physical system of the size and complexity of the climate system. Citation: Tsonis, A. A. , K. Swanson, and S. Kravtsov (2007), A new dynamical mechanism for major climate shifts, Geophys. Res. Lett. , 34, L13705, doi:10.1029/2007GL030288.
Speech Recognition on Vector Architectures Speech Recognition on Vector Architectures Abstract Speech Recognition on Vector Architectures

From cellphones and PDAs to huge automated call centers, speech recognition is becoming more and more ubiquitous. As demand for automatic speech recognition (ASR) applications increases, so too does the need to run ASR algorithms on a variety of unconventional computer architectures. One such architecture uses a vector processor, which has many beneets in terms of performance, power consumption, price, etc. This thesis presents and evaluates ASR algorithms ported to run eeciently on vector architectures. A vector simulation library was developed, and is used to evaluate design trade-oos for both the algorithms and the hardware. Two of the three major components of an ASR system vectorize well. The third component, the decoder, vectorizes well for small vocabularies, especially on long vector length architectures, but is diicult to vectorize as the vocabulary grows.
Knowledge Discovery in Texts: a Definition, and Applications

The first part of this paper will give a general view of Knowledge Discovery in Data (KDD) in order to insist on how much it differs from the fields it stems from, and in some cases, how much it opposes them. The second part will a definition of Knowledge Discovery in Texts (KDT), as opposed to what is known presently under the name of information retrieval, information extraction, or knowledge extraction. I will provide an example of a reallife set of rules obtained by what I want to define as KDT techniques.
FileSender Terabyte Challenge Research Project 1-Report

The purpose of this research project is to identify and solve the bottlenecks in the FileSender application. Besides that it will also look into some more generic problems that can affect more web applications. The main problem in FileSender is that there are gaps between sending chunks. This report will describe this problem and show our implementation for solving this using JavaScript’s multi-threading support called webworkers. It will also discuss SSL performance using different ciphers and give some guidelines for choosing the best performing cipher.
Role of trastuzumab in the management of HER2-positive metastatic breast cancer

: Breast cancer is a major health issue in developed countries. Overexpression of HER2, a member of epidermal growth factor receptor family, occurs in 20%–30% of breast cancers. HER2 drives the cancer cells to develop a more aggressive phenotype, to metastasize to viscera and central nervous system, and to be less sensitive to chemotherapeutic agents. Trastuzumab (Herceptin  ) is a monoclonal antibody directed against the extracellular domain of HER2. As single agent or with chemotherapy, trastuzumab improves survival of HER2-positive breast cancers. In the past years, trastuzumab has completely revolutionized the scenario of the treatment of HER2-positive breast cancer, representing one of the most remarkable examples of targeted therapy in oncology. However, issues such as the best chemotherapeutic companion to associate with trastuzumab, cardiac toxicities, and clinical resistance still require tremendous efforts by researchers. Here, we review pharmacology, efficacy studies, and toxicities of trastuzumab in metastatic breast cancer. Moreover, we provide some insights on resistance to therapy. Finally, we briefly discuss trastuzumab’s place in the clinical
Gender Differences in Cyberlearning

Even women in technical professional programs in a Taiwan university in 2003 continue to be less receptive than men to uses of instructional computing. The pace of adoption of cyberlearning is influenced by gender factors. Although Taiwan is a semi-conductor world leader, university women in technical universities have not been as receptive as men toward Web-based distance learning. This study used cluster sampling, independent-sample t tests, and stepwise regression analysis to determine differences between males and females in a survey adapted from Davis's technology acceptance model (TAM). Research results in 2003 showed that Taiwanese women in technical programs in the Tajen Institute of Technology were more resistant to computing and Web online distance courses than men.
The Interface between Social Anxiety and Sexual Victimization: A Study of College Women's Experiences

MENATTI, ALISON R. , Ph.D., August 2016, Clinical Psychology The Interface between Social Anxiety and Sexual Victimization: A Study of College Women’s Experiences Director of Dissertation: Christine A. Gidycz Research has yet to examine thoroughly how the socio-evaluative fears that typify social anxiety affect the characteristics of sexual assault and post-assault recovery. Accordingly, the present study sought to examine how social anxiety influences sexual assault correlates (e.g., alcohol consumption, tactics used by a perpetrator to compel unwanted sexual activity, and victim resistance to assault) and sequelae (e.g., helpseeking behavior, and interpersonal and sexual functioning difficulties). College women (N = 203) completed a battery of online questionnaires for partial course credit. Results supported that social anxiety significantly predicted the frequency of coercion, attempted rape, and rape. Potential mediators of these relationships were examined. Difficulties with interpersonal functioning and sexual aversion (but not sexual dysfunction) were particularly pronounced for women high in social anxiety with past-year assault histories. In addition, although social anxiety exacerbated some psychological barriers to resistance, social anxiety also significantly predicted assertive, but not non-assertive, behavioral resistance to sexual assault. Further, social anxiety and victimization history independently predicted drinking-related consequences. Lastly, post-assault help-seeking was found to be particularly challenging for socially anxious individuals, although social anxiety may not act as a barrier to disclosure of sexual assault to others. In all, current
Self-action of Light in Photonic Crystals

We pre sent the results of z-scan studies carried out on photonic crystals and microcavities made of Bi:YIG, showing the enhancement of light self-action in the vicinity of the microcavity mode and the wavelength-dependent intensity localization in certain type layers at the longwavelength edge of the photonic bandgap.
h{ADAPTIVE MESH REFINEMENT IN NONLINEAR FINITE ELEMENT ANALYSES OF SHELL STRUCTURES

SUMMARY This paper discusses procedures for improving the reliability and computational ee-ciency of nite element solutions to geometrically nonlinear shell{type problems. This is addressed using a posteriori error estimation and adaptive mesh reenement. The paper brieey reviews the Zienkiewicz{Zhu error estimator as it applies to nite element analysis with shell problems, and discusses the problem of transfering solution variables between the old and the new mesh. A geometrically nonlinear shell problem involving large deformations is presented to illustrate the cost{eeectiveness of the procedures described.
Performance analysis of p-type silicon nanowire FETs with silicon-germanium cladding

The performance of p-type silicon nanowire FETs with three different silicon-germanium cladding options is bench-marked against the silicon reference device. Low-field mobilities and full device characteristics are obtained from the solution of the subband Boltzmann transport equation, including phonon and surface roughness scattering. The subband dispersion is calculated using 6kp band structure model, including the strain induced by the cladding layer. We show that silicon nanowires can be outperformed due to the superior hole mobility of strained silicon-germanium, but the off-state behavior degrades with increasing cladding thickness.
Community Conversations on Integrated Employment: Examining Individualization, Influential Factors, and Impact

Although “community conversations” are a promising approach to address employment outcomes for young people with intellectual and developmental disabilities (IDDs), little research has addressed how these events are tailored to address the unique needs, assets, and resources of communities. Through in-depth interviews, organizers from seven diverse communities addressed their motivations for involvement, their pathways of personalization, and the factors contributing to the success of the events. Collectively, attendees generated more than 2,000 strategies to expand integrated employment locally, falling across six primary areas. Attendees considered these events to be a good investment of their time; however, they reported that additional action, education, and partnerships were needed in their communities. Following the events, attendees reported taking a variety of follow-up actions including sharing information, developing new relationships, talking with neighbors, and educating employers. We offer implications for policy, practice, and research aimed at expanding integrated employment for young people with disabilities.
Kinetic Analysis of [11C]Vorozole Binding in the Human Brain with Positron Emission Tomography

Using positron emission tomography, we investigated the kinetics of [11C]vorozole ([11C]VOR), a radiotracer for the enzyme aromatase that catalyzes the last step in estrogen biosynthesis. Six subjects were scanned under baseline conditions followed by retest 2 weeks later. The retest was followed by a blocking study with 2.5 mg of the aromatase inhibitor letrozole. The binding potential (BPAd) was estimated from a Lassen plot using the total tissue distribution volume (VT) for baseline and blocked. BPAND for the thalamus was found to be 15 times higher than that for the cerebellum. From the letrozole studies, we found that [11C]VOR exhibits a slow binding compartment (small k4) that has a nonspecific and a blockable component. Because of the sensitivity of VT to variations in k4, a common value was used for the four highest binding regions. We also considered the tissue uptake to plasma ratio for 60 to 90 minutes as an outcome measure. Using the ratio method, the difference between the highest and lowest was 2.4 compared to 3.5 for the VT. The ratio method underestimates the high regions but is less variable and may be more suitable for patient studies. Because of its kinetics and distribution, this tracer is not a candidate for a bolus infusion or reference tissue methods.
The quantum nonlinear Schrödinger model with point-like defect

We establish a family of point-like impurities which preserve the quantum integrability of the nonlinear Schrodinger model in 1+1 spacetime dimensions. We briefly describe the construction of the exact second quantized solution of this model in terms of an appropriate reflection–transmission algebra. The basic physical properties of the solution, including the spacetime symmetry of the bulk scattering matrix, are also discussed.
Toward an OSGi-based infrastructure for context-aware applications

Applications and services must adapt to changing contexts in dynamic environments. However, building context-aware applications is still complex and time-consuming due to inadequate infrastructure support. We propose a context-aware infrastructure for building and rapidly prototyping such applications in a smart-home environment. This OSGi-based infrastructure manages context-aware services reliably and securely and efficiently supports context acquisition, discovery, and reasoning. A formal, ontology-based context model enables semantic context representation, reasoning, and knowledge sharing. We propose an ontology-based context model that leverages Semantic Web technology and OWL (Web Ontology Language). OWL is an ontology markup language that enables context sharing and context reasoning. Based on our context model, we also propose a service-oriented context-aware middleware (SOCAM) architecture, including a set of independent services that perform context discovery, acquisition, and interpretation.
A Genetic Prototype Learner

Supervised classification problems have received considerable attention from the machine learning community. We propose a novel genetic algorithm based prototype learning system, PLEASE, for this class of problems. Given a set of prototypes for each of the possible classes, the class of an input instance is determined by the prototype nearest to this instance. We assume ordinal attributes and prototypes are represented as sets of feature-value pairs. A genetic algorithm is used to evolve the number of prototypes per class and their positions on the input space as determined by corresponding feature-value pairs. Comparisons with C4.5 on a set of artificial problems of controlled complexity demonstrate the effectiveness of the proposed system.
Modeling Selectivity in Households' Purchase Quantity Outcomes: A Count Data Approach

We present an econometric technique for modeling endogenous selectivity in households quantity outcomes as observed in scanner panel data. Simultaneous models of incidence, brand choice and quantity, that treat quantity outcomes as count data, ignore such self-selectivity considerations in quantity outcomes. Previously proposed approaches to modeling selectivity in continuous quantity outcomes do not apply to count data. Therefore, we adopt a recently proposed econometric technique to deal with selectivity in count data, and then appropriately extend it to handle correlations of quantity outcomes not only with incidence outcomes but also with brand choice outcomes. Our proposed methodology will be useful to researchers who want to estimate simultaneous models of whether, what and how much to buy decisions of households, treating quantity data as counts.
CountMeIn: evaluating social presence in a collaborative pervasive mobile game using NFC and touchscreen interaction

This paper presents the motivation, design and evaluation of CountMeIn, a mobile collaborative pervasive memory game to revive social interactions in public places (e.g. a train station or bus stop). Two versions of CountMeIn were tested; an NFC-based and a touchscreen version. In a 2×1 within-subject (NFC vs. Touch) experiment (N = 20), postexperiment group interviews and findings indicate the NFC version led to increased perception of social presence while participants were more aware of others' actions and intentions (mode of co-presence). However, we did not find quantitative evidence that attributes of social presence were higher from the Social Presence Game Questionnaire. Together, our findings suggest that placement of a physical NFC interface does not necessarily increase perceived social presence when users play collaboratively. However, social expansion in mobile collaborative pervasive games can greatly benefit from people's mutual awareness from such an interface. This mutual awareness has the potential to both attract users and spectators, and reduce anxiety of users to invite spectators, or accept an invite from users.
Recursive Aggregation of Estimators by Mirror Descent Algorithm with Averaging

We consider a recursive algorithm to construct an aggregated estimator from a finite number of base decision rules in the classification problem. The estimator approximately minimizes a convex risk functional under the l1-constraint. It is defined by a stochastic version of the mirror descent algorithm (i.e., of the method which performs gradient descent in the dual space) with an additional averaging. The main result of the paper is an upper bound for the expected accuracy of the proposed estimator. This bound is of the order $\sqrt{(\log M)/t}$ with an explicit and small constant factor, where $M$ is the dimension of the problem and $t$ stands for the sample size. A similar bound is proved for a more general setting that covers, in particular, the regression model with squared loss.
Integrated comprehensive methodology based on DEA and PCA

Data Envelopment Analysis (DEA) is a kind of comprehensive evaluation method to rank and calculate the corresponding efficiency for each Decision Making Unit (DMU) by constructing a production frontier in multiple inputs and outputs system. For each DMU, we can use multiple variables to describe the characters of DMU, which can be classified as input variables and output variables separately. In traditional DEA models, we needn't do any transformation for input and output variables when we apply DEA into evaluation procedure because the linear programming can allocate optimal weights for different variables based on the principle of the lower inputs and higher outputs the better. However, traditional DEA models can obtain weak evaluation results that most of DMUs are efficient when each DMU has large amount input variables and output variables. To overcome the shortcoming of DEA models, we proposed an integrated DEA model, denoted as PCA-DEA, in this paper. By using CPA arithmetic, the original data for each DMU can be transferred into uncorrelated data. Then, CPA-DEA models have stronger evaluation capability than traditional DEA models.
Web service allocations based on combinatorial auctions and market-based mechanisms

The main idea in this paper is using combinatorial Web service market based mechanism (CWSMBM) to allow service demanders bid for more than one service at the same time. It takes quality of service into consideration in the design of market allocation mechanisms. We define the cost-benefit threshold for service providers to decide whether to accept or reject service tasks. We found that the cost-benefit threshold improves the global benefit value effectively but would sometimes cause a starvation problem. But the starvation can be a trade-off in sacrificing some service demanders to enhance the global benefit.
Managing diversity: Domestication and gene flow in Stenocereus stellatus Riccob. (Cactaceae) in Mexico

Microsatellite markers (N = 5) were developed for analysis of genetic variation in 15 populations of the columnar cactus Stenocereus stellatus, managed under traditional agriculture practices in central Mexico. Microsatellite diversity was analyzed within and among populations, between geographic regions, and among population management types to provide detailed insight into historical gene flow rates and population dynamics associated with domestication. Our results corroborate a greater diversity in populations managed by farmers compared with wild ones (HE = 0.64 vs. 0.55), but with regional variation between populations among regions. Although farmers propagated S. stellatus vegetatively in home gardens to diversify their stock, asexual recruitment also occurred naturally in populations where more marginal conditions have limited sexual recruitment, resulting in lower genetic diversity. Therefore, a clear-cut relationship between the occurrence of asexual recruitment and genetic diversity was not evident. Two managed populations adjacent to towns were identified as major sources of gene movement in each sampled region, with significant migration to distant as well as nearby populations. Coupled with the absence of significant bottlenecks, this suggests a mechanism for promoting genetic diversity in managed populations through long distance gene exchange. Cultivation of S. stellatus in close proximity to wild populations has led to complex patterns of genetic variation across the landscape that reflects the interaction of natural and cultural processes. As molecular markers become available for nontraditional crops and novel analysis techniques allow us to detect and evaluate patterns of genetic diversity, genetic studies provide valuable insights into managing crop genetic resources into the future against a backdrop of global change. Traditional agriculture systems play an important role in maintaining genetic diversity for plant species.