Miracle-dz/UniFAR-FTUs huggingface dataset:
Aggression in Amateur and Professional Hockey

Aggressive behaviour (as measured by "minutes in aggressive penalties") and players* perceived attitudes were investigated at four levels of hockey pee wee and midget (major All Star), Junior A (Jr. A) and the National Hockey League (NHL). No support was found for hypotheses suggesting that minutes in aggressive penalties occur as a function of differences in weight (light or heavy), position (forward or defense), skill ("less-skilled" or "more-skilled"), or years in league (rookie or veteran). The midget sample incurred significantly more minutes in aggressive penalties per player per 60 minutes of game time than did the other three samples. Analyses of players* responses to questionnaire items indicated that the Jr. A sample revealed the most aggressive attitudes, the pee wee sample the least aggressive, while the midget and NHL samples fell between the two. The midget and NHL samples demonstrated a very similar pattern of responses. It is suggested that these results cannot be explained by a simple modeling paradigm. Rather, they are discussed in terms of a process wherein players, as they progress towards professional status, overemphasize qualities which they believe to be typical of a professional player,
Optical, near-infrared and hard X-ray observations of SAX J1353.9+1820: a red quasar

We present the results of a follow-up ASCA observation and multicolour optical and near-infrared photometry carried out at the 3.5-m Italian National Telescope Galileo of SAXJ1353.9+1820. This object, serendipitously discovered by BeppoSAX in the 5-10 keV band, has been spectroscopically identified as a red quasar at z=0.217. The combined X-ray and optical-infrared data reveal the presence of a moderately luminous X-ray source (~ 10^{44} erg s^{-1}) obscured by a column density of the order of 10^{22} cm^{-2} in a otherwise optically passive early-type galaxy. The implications for the nature of red quasars and their possible contribution to the hard X-ray background are briefly outlined.
Profiling Synaptic Proteins Identifies Regulators of Insulin Secretion and Lifespan

Cells are organized into distinct compartments to perform specific tasks with spatial precision. In neurons, presynaptic specializations are biochemically complex subcellular structures dedicated to neurotransmitter secretion. Activity-dependent changes in the abundance of presynaptic proteins are thought to endow synapses with different functional states; however, relatively little is known about the rules that govern changes in the composition of presynaptic terminals. We describe a genetic strategy to systematically analyze protein localization at Caenorhabditis elegans presynaptic specializations. Nine presynaptic proteins were GFP-tagged, allowing visualization of multiple presynaptic structures. Changes in the distribution and abundance of these proteins were quantified in 25 mutants that alter different aspects of neurotransmission. Global analysis of these data identified novel relationships between particular presynaptic components and provides a new method to compare gene functions by identifying shared protein localization phenotypes. Using this strategy, we identified several genes that regulate secretion of insulin-like growth factors (IGFs) and influence lifespan in a manner dependent on insulin/IGF signaling.
GRASP: analysis of genotype-phenotype results from 1390 genome-wide association studies and corresponding open access database

SUMMARY We created a deeply extracted and annotated database of genome-wide association studies (GWAS) results. GRASP v1.0 contains >6.2 million SNP-phenotype association from among 1390 GWAS studies. We re-annotated GWAS results with 16 annotation sources including some rarely compared to GWAS results (e.g. RNAediting sites, lincRNAs, PTMs). MOTIVATION To create a high-quality resource to facilitate further use and interpretation of human GWAS results in order to address important scientific questions. RESULTS GWAS have grown exponentially, with increases in sample sizes and markers tested, and continuing bias toward European ancestry samples. GRASP contains >100 000 phenotypes, roughly: eQTLs (71.5%), metabolite QTLs (21.2%), methylation QTLs (4.4%) and diseases, biomarkers and other traits (2.8%). cis-eQTLs, meQTLs, mQTLs and MHC region SNPs are highly enriched among significant results. After removing these categories, GRASP still contains a greater proportion of studies and results than comparable GWAS catalogs. Cardiovascular disease and related risk factors pre-dominate remaining GWAS results, followed by immunological, neurological and cancer traits. Significant results in GWAS display a highly gene-centric tendency. Sex chromosome X (OR = 0.18[0.16-0.20]) and Y (OR = 0.003[0.001-0.01]) genes are depleted for GWAS results. Gene length is correlated with GWAS results at nominal significance (P ≤ 0.05) levels. We show this gene-length correlation decays at increasingly more stringent P-value thresholds. Potential pleotropic genes and SNPs enriched for multi-phenotype association in GWAS are identified. However, we note possible population stratification at some of these loci. Finally, via re-annotation we identify compelling functional hypotheses at GWAS loci, in some cases unrealized in studies to date. CONCLUSION Pooling summary-level GWAS results and re-annotating with bioinformatics predictions and molecular features provides a good platform for new insights. AVAILABILITY The GRASP database is available at http://apps.nhlbi. nih.gov/grasp.
An integrated Bayesian approach to layer extraction from image sequences

This paper describes a Bayesian approach for modeling 3D scenes as a collection of approximately planar layers that are arbitrarily positioned and oriented in the scene. In contrast to much of the previous work on layer based motion modeling, which compute layered descriptions of 2D image motion, our work leads to a 3D description of the scene. We focus on the key problem of automatically segmenting the scene into layers as a precursor to recovery of stereo disparity data. The prior assumptions about the scene are formulated within a Bayesian decision making framework, and are then used to automatically determine the number of layers and the assignment of individual pixels to layers. Although using a collection of 3D layers has been previously proposed as an efficient and effective representation for multimedia applications, results to date have relied on hand segmentation. In contrast, the work described aims at fully automatic segmentation.
Groupwork with female adult survivors of childhood abuse

A programme of time-limited therapeutic groupwork with female adult survivors of childhood abuse within the United Kingdom is described and a statistical evaluation of its outcomes reported. The programme involved two separate groups, with a total of eight group members completing the test materials on the first and final group sessions and subsequently at a two-month post-treatment follow-up. Although a relatively small sample, the test results show a significant reduction in clinical symptoms and demonstrate the utility of this approach.
Effects of Obsessive-Compulsive Disorder Symptom Intensity on Brain Electro-Cortical Activity Associated with Emotional Memory

Obsessive-Compulsive Disorder (OCD) consists of recurrent and persistent thoughts (obsessions), accompanied by the development of ritual and/or repetitive behaviors (com‐ pulsions). It has been widely suggested that these symptoms might be linked to different types of cognitive and cerebral impairments. More precisely, it has been shown that OCD patients present specific memory difficulties that could be related to a Cortico-Striato-Thalamo-Cortical (CSTC) loop dysfunction. Some research has further explained these memory problems as a result of poor confidence, along with affected emotional evaluation.
Missing data treatment method on cluster analysis

The missing data in household health survey was challenged for the researcher because of incomplete analysis. The statistical tool cluster analysis methodology implemented in the collected data of Sudan's household health survey in 2006. Current research specifically focuses on the data analysis as the objective is to deal with the missing values in cluster analysis. Two-Step Cluster Analysis is applied in which each participant is classified into one of the identified pattern and the optimal number of classes is determined using SPSS Statistics/IBM. However, the risk of over-fitting of the data must be considered because cluster analysis is a multivariable statistical technique. Any observation with missing data is excluded in the Cluster Analysis because like multi-variable statistical techniques. Therefore, before performing the cluster analysis, missing values will be imputed using multiple imputations (SPSS Statistics/IBM). The clustering results will be displayed in tables. The descriptive statistics and cluster frequencies will be produced for the final cluster model, while the information criterion table will display results for a range of cluster solutions.
How efficient is our radix join implementation ?

We recently published a paper [2] that examines the design choices available to create a high-performance main-memory hash join algorithm. We experimentally evaluated four hash join variants on two different architectures, and we showed that an algorithm that does not do any partitioning on the input tables often outperforms the other more complex partitioning-based join alternatives. Our claim is that in an environment with a single processor and multiple cores, the non-partitioning method has many advantages over the more complex methods that have been proposed before. If the memory access latency between different processors is non-uniform, partitioning will be more beneficial; the non-partitioning method could then be used as a building block for an efficient hash join algorithm for data that has been partitioned to each processor (NUMA node). A full exploration of hash join methods for NUMA environments is part of our future work. In our paper [2], one of the algorithms that we evaluated this simple hash join algorithm against was the radix-partitioned hash join [3]. We implemented the parallel radix-partitioned hash join algorithm that is described in [4]. During the conference, there were some questions regarding how efficient our radix join implementation is. Unfortunately, because of three differences in the experimental setup, a direct comparison between [2] and [4] is impossible. First, the tuples in [2] are 16 bytes wide, but only 8 bytes in [4]. Second, most of the experiments in [2] show results where the size ratio between two the join inputs is 1 16 , to mimic a primary key–foreign key join in a decision support environment where there is a small dimension table and larger fact table. In [4], the two inputs have equal size. Finally, although both papers use CPUs based on the Intel Nehalem microarchitecture, the hardware is not the same. Among other differences, the available memory bandwidth per core is the most striking: In the Xeon X5650 CPU used in [2], twelve hardware threads share the 6.4GT/s memory bus. In the i7-965 that is used in [4], only eight hardware threads share the memory bus of the same bandwidth. Although the exact effect of reduced memory bandwidth per core on parallel radix hash join performance is unknown, Intel reports that the i7-965 has 1.2X the effective bandwidth per core than the Xeon X5650 [1]. Although the implementation used in [4] was unavailable, the co-authors of the Kim et al. [4] …
Elevated expectancies among persons diagnosed with bipolar disorder.

OBJECTIVE Students at risk for bipolar disorder endorse highly ambitious goals. This study examined expectations for the future among people with actual bipolar disorder, versus people with no history of mood disorder and persons with history of unipolar depression. METHODS One hundred and three students were assessed for Axis I disorders and completed a measure of expected life outcomes. RESULTS History of mania, but not history of depression, related to higher expectations of achieving popular fame and wealth. CONCLUSIONS People with history of mania anticipate great success in domains involving public recognition.
Process-of-Care Measures as Predictors of Client Outcome Among a Methamphetamine-Dependent Sample at 12- and 36-Month Follow-ups

Abstract This study examines the utility of several process-of-care performance measures (initiation, engagement, retention, and monitoring of drug use during treatment) as predictors of methamphetamine (MA) use outcomes at 12- and 36-month follow-ups. MA-dependent individuals (n = 871) participated in a randomized, controlled trial of outpatient psychosocial treatment from 1999–2002 and completed 12- and 36-month follow-up interviews. This sample included a treatment-as-usual group (n = 436) and a 16-week Matrix treatment (n = 435) group. Significant associations were observed between select process-of-care measures and MA use outcomes at both follow-ups. While correlational analyses showed an association between MA abstinence at follow-up and enhanced treatment engagement and retention, mixed logistic regression analyses indicated that sustained abstinence from MA during outpatient treatment was the strongest predictor of testing negative for MA use at both follow-ups. Results suggest that monitoring client drug use during treatment may be a useful process-of-care measure with MA-dependent users.
Two-Term Asymptotic Approximation of a Cardiac Restitution Curve

If spatial extent is neglected, ionic models of cardiac cells consist of systems of ordinary differential equations (ODEs) which have the property of excitability, i.e., a brief stimulus produces a prolonged evolution (called an action potential in the cardiac context) before the eventual return to equilibrium. Under repeated stimulation, or pacing, cardiac tissue exhibits electrical restitution: the steady-state action potential duration (APD) at a given pacing period B shortens as B is decreased. Independent of ionic models, restitution is often modeled phenomenologically by a one-dimensional mapping of the form APD(next) = f(B - APD(previous)). Under some circumstances, a restitution function f can be derived as an asymptotic approximation to the behavior of an ionic model.In this paper, extending previous work, we derive the next term in such an asymptotic approximation for a particular ionic model consisting of two ODEs. The two-term approximation exhibits excellent quantitative agreement with the actual restitution curve, whereas the leading-order approximation significantly underestimates actual APD values.
Feminist Postcolonial Theory : A Reader

Feminism and postcolonialism are allies, and the impressive selection of writings brought together in this volume demonstrate how fruitful that alliance can be. Reina Lewis and Sara Mills have assembled a brilliant selection of thinkers, organizing them into six categories: "Gendering Colonialism and Postcolonialism/Radicalizing Feminism," "Rethinking Whiteness," "Redefining the 'Third World' Subject," "Sexuality and Sexual Rights," "Harem and the Veil," and "Gender and Post/colonial Relations. " A bibliography complements the wide-ranging essays. This is the ideal volume for any reader interested in the development of postcoloniality and feminist thought.
A MACHINE LEARNING APPROACH FOR AUTOMATED GEOMORPHIC MAP GENERATION

Intelligent, automated analysis of data is a critical task in modern data-intensive sciences. The work presented in this thesis is a contribution to this body of research, focusing on automatic geomorphic characterization of planetary surfaces (particularly Mars). We present a framework for automated generation of geomorphic maps from topographic data. Our approach first segments the topographic data into objects and then applies supervised learning for classifying the objects into corresponding geomorphic classes. Choice of optimal segmentation strategy (divisive vs agglomerative) and optimal segmentation resolution are investigated. A custom clustering based agglomerative segmentation algorithm has been developed and implemented, for comparison with an H-Transform based watershed segmentation strategy. Three supervised learning algorithms Naive Bayes, Bagging with decision trees and Support Vector Machines are compared and their map producing abilities evaluated. Finally, a rule-based post processing algorithm has been developed for refining the produced maps. Our algorithm has been tested on five Martian sites and produces encouraging results. The agglomerative segmentation strategy outperforms the conventional watershed based strategy. Furthermore, over-segmented images were found to be more suitable for map generation. Finally, SVM with a quadratic kernel and Bagging with C4.5, both produce accurate maps. Maps produced by SVMs are more robust and visually appealing.
Obg-like ATPase 1 regulates global protein serine/threonine phosphorylation in cancer cells by suppressing the GSK3β-inhibitor 2-PP1 positive feedback loop

OLA1 is an Obg family P-loop NTPase that possesses both GTP- and ATP-hydrolyzing activities. Here we report that OLA1 is a GSK3β interacting protein, and through its ATPase activity, inhibits the GSK3β-mediated activation of protein serine/threonine phosphatase 1 (PP1). It is hypothesized that GSK3β phosphorylates inhibitor 2 (I-2) of PP1 at Thr-72 and activates the PP1 · I-2 complex, which in turn dephosphorylates and stimulates GSK3β, thus forming a positive feedback loop. We revealed that the positive feedback loop is normally suppressed by OLA1, and becomes over-activated under OLA1 deficiency, resulting in increased cellular PP1 activity and dephosphorylation of multiple Ser/Thr phosphoproteins, and more strikingly, decreased global protein threonine phosphorylation. Furthermore, using xenograft models of colon cancer (H116) and ovarian cancer (SKOV3), we established a correlation among downregulation of OLA1, over-activation of the positive feedback loop as indicated by under-phosphorylation of I-2, and more aggressive tumor growth. This study provides the first evidence for the existence of a GSK3β-I-2-PP1 positive feedback loop in human cancer cells, and identifies OLA1 as an endogenous suppressor of this signaling motif.
Sorting hierarchical data in external memory for archiving

Sorting hierarchical data in external memory is necessary for a wide variety of applications including archiving scientific data and dealing with large XML datasets. The topic of sorting hierarchical data, however, has received little attention from the research community so far. In this paper we focus on sorting arbitrary hierarchical data that far exceed the size of physical memory. We propose HErMeS, an algorithm that generalizes the most widely-used techniques for sorting flat data in external memory. HErMeS efficiently exploits the hierarchical structure to minimize the number of disk accesses and optimize the use of available memory. We extract the theoretical bounds of the algorithm with respect to the structure of the hierarchical dataset. We then show how the algorithm can be used to support efficient archiving. We have conducted an experimental study using several workloads and comparing HErMeS to the state-of-the-art approaches. Our results show that our algorithm (a) meets its theoretical expectations, (b) allows for scalable database archiving, and (c) outperforms the competition by a significant factor. These results, we believe, prove our technique to be a viable and scalable solution to the problem of sorting hierarchical data in external memory.
Beck Depression Inventory‐II

The Beck Depression Inventory-II (BDI-II) is a 21-item self-administered inventory designed to measure the intensity of depressive symptoms in adults and adolescents (Beck, Steer, & Brown, 1996). Respondents are instructed to indicate which statement best describes how they felt during the past two weeks including today. Items are rated on a 4-point (0 to 3) scale, with total scores obtained by summing the ratings for all items. Scores ranging between 0 and 13 are indicative of minimal depression; scores that fall between 14 and 19 are considered to reflect a mild level of depression; scores of 20 to 28 are considered moderate; and a score ranging from 29 to 63 is labeled severe. The BDI-II requires approximately 5–10 minutes to complete and is appropriate for individuals 13 to 80 years of age. Keywords: depression; assessment; Beck depression inventory
Eating behaviour, affect and cognitive function.

The aim of this thesis was to examine the affective and cognitive disturbance associated with weight-loss dieting. We were particularly interested in how mood might interact with dietary restraint to produce cognitive deficit. Initially dieting was investigated in a community sample of overweight dieters. Affect was assessed by self-reported feelings of positive and negative mood (PANAS) and general psychological well-being (Ryff s PWB). Cognitive performance was assessed using a battery of computer administered tasks that measured speed to respond to a target stimulus; immediate memory recall; working memory capacity; vigilance (Bakan task); attentional distraction for food related stimuli (Stroop task); and, preference for food and body-shape related stimuli (Implicit Association Test). In replication of previous studies (e. g. Green, Rogers, Elliman, & Gatenby, 1994), dieting was found to be related to cognitive deficit. The same dieters were also found to be more neurotic and to have greater levels of affective disturbance compared to non-dieters. Contrary to expectation, restraint per se could not account for the dieter-non-dieter differences found. Further, differences in cognitive performance could not be explained as directly due to dieter-non-dieter differences in BMI, hunger, preoccupation, attentional bias or mood. Rather, it was the tendency to eat when emotional which best identified those dieters most vulnerable to cognitive and affective disturbance. Further investigation revealed that under conditions of high negative mood, tendency towards emotional eating was associated with an increase in preference for food related stimuli, and a decrease in attentional capacity. Accordingly, it was proposed that under dieting conditions, where opportunity for affective disturbance is increased, cognitive deficit is most likely to occur in the high emotional eater because they are highly sensitive to affective disturbance, and for them such disturbance results in preferential allocation of attentional resources to food and eating related cognitions. Further research is needed to fully examine the psychological profile of the individual with high tendency towards emotional eating. This issue is of particular importance given the additional finding that the tendency to consume when emotional is not context-bound but can also be observed in other behavioural domains, such as "emotional spending" on other consumer goods.
Clustering with Local and Global Consistency

Clustering aims at (cid:2)nding hidden structure in data. In this paper we present a new clustering algorithm that builds upon the local and global consistency method (Zhou, et. al. , 2003), a semi-supervised learning technique with the property of learning very smooth functions with respect to the intrinsic structure revealed by the data. Starting from this algorithm, we derive an optimization framework that discovers structure in data without requiring labeled data. This framework is capable of simultaneously optimizing all learning parameters, as well as picking the optimal number of clusters. It also allows easy detection of both global outliers and outliers within clusters. Finally, we show that the learned cluster models can be used to add previously unseen points to the clusters, without re-learning the original cluster model. Encouraging experimental results are obtained on a number of toy and real world problems.