Miracle-dz/UniFAR-FTUs huggingface dataset:
CHANGES IN BODY COMPOSITION , HORMONAL STATUS , AND PHYSICAL FITNESS IN 11-, 13-, AND 15-YEAR-OLD FINNISH REGIONAL YOUTH SOCCER PLAYERS

Vänttinen, T, Blomqvist, M, Nyman, K, and Häkkinen, K. Changes in body composition, hormonal status, and physical fitness in 11-, 13-, and 15-year-old Finnish regional youth soccer players during a two-year follow-up. J Strength Cond Res 25(12): 3342–3351, 2011—The purpose of this study was to examine the changes in body composition, hormonal status, and physical fitness in 10.8 6 0.3-year-old (n = 13), 12.7 6 0.2-year-old (n = 14), and 14.7 6 0.3-year-old (n = 12) Finnish regional youth soccer players during a 2-year monitoring period and to compare physical fitness characteristics of soccer players with those of age-matched controls (10.7 6 0.3 years, n = 13; 14.7 6 0.3 years, n = 10) not participating in soccer. Body composition was measured in terms of height, weight, muscle mass, percentage of body fat, and lean body weight of trunk, legs, and arms. Hormonal status was monitored by concentrations of serum testosterone and cortisol. Physical fitness was measured in terms of sprinting speed, agility, isometric maximal strength (leg extensors, abdominal, back, grip), explosive strength, and endurance. Age-related development was detected in all other measured variables except in the percentage of body fat. The results showed that the physical fitness of regional soccer players was better than that of the control groups in all age groups, especially in cardiovascular endurance (p , 0.01–0.001) and in agility (p , 0.01–0.001). In conclusion, playing in a regional level soccer team seems to provide training adaptation, which is beyond normal development and which in all likelihood leads to positive health effects over a prolonged period of time.
Hyperbilirubinaemia and bacterial infection in the newborn A prospective study

Bacterial infection and jaundice may be associated without severe constitutional upset and with few abnormal clinical signs or laboratory findings (Rooney, Hill, and Danks, 1971), and in this context the association of neonatal jaundice and urinary tract infection has been particularly emphasized (Seeler and Hahn, 1969; Seeler, 1973). In a retrospective study we found that jaundice was rarely the single, initial sign of infection in an asymptomatic neonate (Escobedo et al., 1974). In this report we present the results of a prospective study of jaundiced infants evaluated for bacterial
Adapting the Complexity Level of a Serious Game to the Proficiency of Players

As games are continuously assessing the player, this assessment can be used to adapt the complexity of a game to the proficiency of the player in real time. We performed an experiment to examine the role of dynamic adaptation. In one condition, participants played a version of our serious game for triage training that automatically adapted the complexity level of the presented cases to how well the participant scored previously. Participants in the control condition played a version of the game with no adaptation. The adapted version was significantly more efficient and resulted in higher learning gains per instructional case, but did not lead to a difference in engagement. Adapting games to the proficiency of the player could make serious games more efficient learning tools.
Firm-Specific Assets and the Link Between Exchange Rates and Foreign Direct Investment

Foreign direct investment (FDI) theory and empirical studies have generated mixed support for a link between exchange rates and FDI. This paper argues that exchange rate movements may affect acquisition FDI because acquisitions involve firm-specific assets which can generate retums in currencies other than that used for purchase. Using data on Japanese acquisitions in the United States across 3-digit SIC industries from 1975-1992, maximum-likelihood estimates from discrete dependent variable models support the hypothesis that real dollar depreciations make Japanese acquisitions more likely in U.S. industries, particularly those which more likely have firm-specific assets. (JEL F21, F23, F31)
Effects of Continuous Kinaesthetic Feedback Based on Tendon Vibration on Motor Imagery BCI Performance

Background and objectives: Feedback plays a crucial role for using brain computer interface systems. This paper proposes the use of vibration-evoked kinaesthetic illusions as part of a novel multisensory feedback for a motor imagery (MI)-based BCI and investigates its contributions in terms of BCI performance and electroencephalographic (EEG) correlates. Methods: sixteen subjects performed two different right arm MI-BCI sessions: with the visual feedback only and with both visual and vibration-evoked kinaesthetic feedback, conveyed by the stimulation of the biceps brachi tendon. In both conditions, the sensory feedback was driven by the MI-BCI. The rich and more natural multisensory feedback was expected to facilitate the execution of MI, and thus to improve the performance of the BCI. The EEG correlates of the proposed feedback were also investigated with and without the performing of MI. Results and Conclusions: the contribution of vibration-evoked kinaesthetic feedback led to statistically higher BCI performance (Anova, F(1,14) = 18.1, p < . 01) and more stable EEG event-related-desynchronization. Obtained results suggest promising application of the proposed method in neuro-rehabilitation scenarios: the advantage of an improved usability could make the MI-BCIs more applicable for those patients having difficulties in performing kinaesthetic imagery.
On Maximizing the Lifetime of Wireless Sensor Networks by Optimally Assigning Energy Supplies

The extension of the network lifetime of Wireless Sensor Networks (WSN) is an important issue that has not been appropriately solved yet. This paper addresses this concern and proposes some techniques to plan an arbitrary WSN. To this end, we suggest a hierarchical network architecture, similar to realistic scenarios, where nodes with renewable energy sources (denoted as primary nodes) carry out most message delivery tasks, and nodes equipped with conventional chemical batteries (denoted as secondary nodes) are those with less communication demands. The key design issue of this network architecture is the development of a new optimization framework to calculate the optimal assignment of renewable energy supplies (primary node assignment) to maximize network lifetime, obtaining the minimum number of energy supplies and their node assignment. We also conduct a second optimization step to additionally minimize the number of packet hops between the source and the sink. In this work, we present an algorithm that approaches the results of the optimization framework, but with much faster execution speed, which is a good alternative for large-scale WSN networks. Finally, the network model, the optimization process and the designed algorithm are further evaluated and validated by means of computer simulation under realistic conditions. The results obtained are discussed comparatively.
Nitrogen loss from watersheds of interior Alaska underlain with discontinuous permafrost

We constructed annual nitrogen budgets for four years for three watersheds underlain with discontinuous permafrost in interior Alaska. During all years, nitrogen export in stream flow exceeded input from deposition, with loss rate greatest from the two watersheds with the lowest spatial extents of permafrost. Elevated nitrogen export appears to be common in regions with discontinuous permafrost, based on nitrogen concentration in streams spanning a latitudinal gradient in permafrost coverage. This pattern of nitrogen loss is counter to temperate regions, where watersheds retain nitrogen even with elevated atmospheric deposition, and unexpected, given that terrestrial primary production appears to be nitrogen limited.
Unsupervised Feature Construction and Knowledge Extraction from Genome-Wide Assays of Breast Cancer with Denoising Autoencoders

Big data bring new opportunities for methods that efficiently summarize and automatically extract knowledge from such compendia. While both supervised learning algorithms and unsupervised clustering algorithms have been successfully applied to biological data, they are either dependent on known biology or limited to discerning the most significant signals in the data. Here we present denoising autoencoders (DAs), which employ a data-defined learning objective independent of known biology, as a method to identify and extract complex patterns from genomic data. We evaluate the performance of DAs by applying them to a large collection of breast cancer gene expression data. Results show that DAs successfully construct features that contain both clinical and molecular information. There are features that represent tumor or normal samples, estrogen receptor (ER) status, and molecular subtypes. Features constructed by the autoencoder generalize to an independent dataset collected using a distinct experimental platform. By integrating data from ENCODE for feature interpretation, we discover a feature representing ER status through association with key transcription factors in breast cancer. We also identify a feature highly predictive of patient survival and it is enriched by FOXM1 signaling pathway. The features constructed by DAs are often bimodally distributed with one peak near zero and another near one, which facilitates discretization. In summary, we demonstrate that DAs effectively extract key biological principles from gene expression data and summarize them into constructed features with convenient properties.
Effect of Latinos in Action Peer Tutoring on Elementary Student Oral Reading Fluency Scores

Effect of Latinos in Action Peer Tutoring on Elementary Student Oral Reading Fluency Scores Darren M. Hansen Department of Counseling Psychology and Special Education, BYU Educational Specialist The Latino population is the largest minority group in the United States, making up 16.3% of the total population. As the Latino population of the US grows, the Latino student population within schools across the nation is also growing, accounting for 10.5% of the student population. While the Latino student population continues to grow, there is evidence that this group is not achieving academically at the same rate as other groups. Latino statistics in Utah showed a similar situation within public schools. Fifty-one percent of Latino fourth graders were reading below the expected levels, compared to 22% for Caucasian students. Latino student dropout rates were higher than other groups at 28%, compared to 13% for African American students and 7% for Caucasian students. Students who fail to learn to read are more likely to fail in school. One reason why Latinos graduate at a lower rate is that Latino literacy rates in the U.S. and Utah are lower than other groups. An effective literacy program was needed to assist Latino elementary school students in literacy. Latinos in Action (LIA), a secondary school tutoring program, trained Latino secondary students as tutors for Latino elementary school students. Students’ progress was tracked using the Dynamic Indicators of Basic Early Literacy Skills (DIBELS) Oral Reading Fluency (ORF) measure. LIA tutored ELL students’ ORF progress was compared to the ORF scores of ELL students who did not receive LIA tutoring, ELL students in Spanish dual-immersion instruction who did not receive LIA tutoring, and native English speakers who did not receive LIA tutoring or dual-immersion instruction. Results showed that LIA tutoring was not statistically more or less effective that general instruction on dual-immersion instruction for improving ORF scores for ELL students. Larger sample sizes are needed to increase the validity of this study.
Multi-Level Cause-Effect Systems

We present a domain-general account of causation that applies to settings in which macro-level causal relations between two systems are of interest, but the relevant causal features are poorly understood and have to be aggregated from vast arrays of micro-measurements. Our approach generalizes that of Chalupka et al. (2015) to the setting in which the macro-level effect is not specified. We formalize the connection between micro- and macro-variables in such situations and provide a coherent framework describing causal relations at multiple levels of analysis. We present an algorithm that discovers macro-variable causes and effects from micro-level measurements obtained from an experiment. We further show how to design experiments to discover macro-variables from observational micro-variable data. Finally, we show that under specific conditions, one can identify multiple levels of causal structure. Throughout the article, we use a simulated neuroscience multi-unit recording experiment to illustrate the ideas and the algorithms.
Monitoring Affect States During Effortful Problem Solving Activities

We explored the affective states that students experienced during effortful problem solving activities. We conducted a study where 41 students solved difficult analytical reasoning problems from the Law School Admission Test. Students viewed videos of their faces and screen captures and judged their emotions from a set of 14 states (basic emotions, learning-centered emotions, and neutral) at relevant points in the problem solving process (after new problem is displayed, in the midst of problem solving, after feedback is received). The results indicated that curiosity, frustration, boredom, confusion, happiness, and anxiety were the major emotions that students experienced, while contempt, anger, sadness, fear, disgust, eureka, and surprise were rare. Follow-up analyses on the temporal dynamics of the emotions, their contextual underpinnings, and relationships to problem solving outcomes supported a general characterization of the affective dimension of problem solving. Affective states differ in: (a) their probability of occurrence as regular, routine, or sporadic emotions, (b) their temporal dynamics as persistent or random emotions, (c) their characterizations as product or process related emotions, and (d) whether they were positively or negatively related to problem solving outcomes. A synthesis of our major findings, limitations, resolutions, and implications for affect-sensitive artificial learning environments are discussed.
Spanish adaptation of the Antifat Attitudes Scale / Adaptación al castellano de la Escala de Actitud Antiobesos

Abstract Antifat attitudes may be defined as the negative assessment of people with weight problems. To evaluate them, the Antifat Attitudes Scale (AFA) has been used in most studies. The aim of this study is to adapt the AFA questionnaire to the Spanish population. The sample was made up of 1,457 university students from all over Spain. Exploratory and confirmatory factor analyses showed that the items on the questionnaire fit a three-factor model corresponding to the three dimensions proposed by the original author (dislike, fear of fat and willpower) and that they are interrelated. In light of these results, we conclude that the questionnaire is methodologically valid and can be used by the scientific community to measure antifat attitudes.
LSTM Shift-Reduce CCG Parsing

We describe a neural shift-reduce parsing model for CCG , factored into four unidirectional LSTMs and one bidirectional LSTM. This factorization allows the linearization of the complete parsing history, and results in a highly accurate greedy parser that outperforms all previous beam-search shift-reduce parsers for CCG . By further deriving a globally optimized model using a task-based loss, we improve over the state of the art by up to 2 . 67% labeled F1.
The most common factors influencing on quality of life of thyroid cancer patients after thyroid hormone withdrawal.

BACKGROUND The aim of study was to evaluate which factors impact mostly on life-quality of patients with differentiated thyroid carcinoma after thyroid hormone withdrawal. SUBJECTS AND METHODS 150 patients were enrolled in the study by using Quality of life- Thyroid version questionnaire in which they expressed their physical, psychological, social and spiritual well-being. The answers have been interpreted on a scale from 0 to 10. All patients underwent four weeks levothyroxine withdrawal in preparation for I-131 procedures and thyroglobulin testing. RESULTS Individual statements on the physical subscale showed that patients had most difficulties with fatigue, intolerance to cold and heat, sleep changes and weight gain, but with higher average values than expected. Fatigue was one of the most common physical difficulties. Female patients had significantly more difficulties than male respondents. Five most expressed psychological difficulties have been stress caused by initial diagnosis, followed by stress caused by surgical treatment, fear of metastases, stress caused by initial radioiodine ablation treatment and fear of cancer recurrence. Generally, results revealed troubles mostly in physical symptoms relating to thyroid hormone withdrawal, as well as psychological distress caused by initial diagnosis. Respondents with higher educational level achieved a significantly higher score than less educated patients (p=0.026, Mann-Whitney U test). Illness was very distressing for their families (median value 1, range: 0 to 10) and they reported insufficient support from others (1, range: 0 to 10), but they did not feel isolated. Family and work consequences were less apparent. CONCLUSION The results of QOL-Thyroid questionnaire help to identify high-risk areas in patients' lives that are negatively affected by hormone withdrawal. Regarding the wide definition of quality of life, a positive impact on patients' recovery could be achieved by directing attention to most expressed difficulties noted in this questionnaire.
Additive Enhanced Crystallization of Solution‐Processed Perovskite for Highly Efficient Planar‐Heterojunction Solar Cells

P.-W. Liang, C. -Y. Liao, Dr. C. -C. Chueh, Dr. F. Zuo, S. T. Williams, Dr. X. -K. Xin, Prof. A. K. -Y. Jen Department of Materials Science and Engineering University of Washington Seattle , WA 98195 , USA E-mail: ajen@u.washington. edu Prof. A. K. -Y. Jen Department of Chemistry University of Washington Seattle , WA 98195 , USA C. -Y. Liao, Prof. J. J. Lin Institute of Polymer Science and Engineering National Taiwan University Taipei 106 , Taiwan
Retinoic acid receptor beta expression and growth inhibition of gynecologic cancer cells by the synthetic retinoid N-(4-hydroxyphenyl) retinamide.

BACKGROUND The synthetic retinoid N-(4-hydroxyphenyl) retinamide (4HPR) can inhibit the growth of tumor cells. Preliminary results from a clinical trial suggest that 4HPR may reduce ovarian cancer incidence. We examined the growth-inhibitory effects of 4HPR on gynecologic cancer cell lines in vitro and the role of retinoid receptors in modulating this effect. METHODS Twelve human gynecologic cancer cell lines (the ovarian cell lines--A224, AD10, UCI 101, UCI 107, SKOV3, 222, CP70, ML3B, and ML5; the cervical cell lines--HT3 and ME180; and the endometrial cell line--Hec 1A were tested for sensitivity to 4HPR (by assaying cell proliferation rates). Gel electrophoretic analysis of DNA fragmentation was used to measure programmed cell death (apoptosis). Specific retinoid receptor (retinoic acid receptor [RAR] and retinoid X receptor) messenger RNA (mRNA) levels were measured by northern blot hybridization. AD10 cells were stably transfected with human RARbeta complementary DNA, and the effect of 4HPR on cell proliferation was examined. RESULTS 4HPR inhibited the growth of all 12 cell lines, but to varying degrees; IC50 values (i.e., concentrations that inhibit proliferation by 50%) ranged from 0.3 to 9 microM. Following 4HPR treatment, ovarian cancer cells that were sensitive to 4HPR (222, CP70, and UCI 101; IC50 <3 microM) contained higher levels of RARbeta transcripts than more resistant cells (AD10, ME180, Hec 1A, and A224; IC50 > or =3 microM) (2.8-fold; two-sided P = .006). Anchorage-independent growth of transfected AD10 cells expressing high levels of RARbeta was totally abolished, even in the absence of 4HPR; transfectants expressing low levels of RARbeta exhibited lower levels of anchorage-independent growth and grew more slowly in the presence of 4HPR than control untransfected AD10 cells. CONCLUSION 4HPR inhibited the proliferation of ovarian cancer cells in vitro; RARbeta expression appeared to be associated with this effect.
Transcription of Virulence Factors in Staphylococcus aureus Small-Colony Variants Isolated from Cystic Fibrosis Patients Is Influenced by SigB

ABSTRACT Staphylococcus aureus small-colony variants (SCVs) are believed to account in part for the persistence of S. aureus during chronic infections. Little is understood about the gene expression profile that may explain the phenotype and distinguish SCVs from prototype S. aureus strains. In this study, DNA array transcriptional profiles of clinical SCVs isolated from the airways of cystic fibrosis patients were obtained and compared to those obtained from a laboratory-derived SCV strain (i.e., a respiratory-deficient hemB mutant) and prototype S. aureus strains. The genes commonly up-regulated in both hemB and clinical SCVs were found to be implicated in fermentation and glycolysis pathways. The well-known virulence regulator agr was not activated in SCVs, and such strains had low levels of alpha-toxin (hla) gene expression. Clinical SCVs also had a transcriptional signature of their own. Of striking interest is that many genes, most of them under the positive control of the alternate sigma factor SigB, were specifically up-regulated and differed in that way from that seen in prototype S. aureus and the hemB mutant. Since SigB influences up-regulation of adhesin type genes while indirectly down-regulating exoproteins and toxins, we evaluated the internalization and persistence of SCVs in mammalian cells. Results showed that clinical SCVs persisted much more efficiently in cells than the hemB and prototype strains and that a sigB mutant was a poor persister. Thus, it appears that the agr locus plays a minor role in the regulation of the virulon of SCVs, unlike SigB, which may have a key role in intracellular persistence.
Efficacy and safety of tadalafil in men with erectile dysfunction following spinal cord injury.

OBJECTIVE To determine the efficacy and safety of tadalafil when taken on demand by men with erectile dysfunction (ED) secondary to traumatic spinal cord injury (SCI). DESIGN AND SETTING Multicenter, randomized, double-blind, placebo-controlled, flexible dose-titration, parallel-group study in clinical practices in Europe. Patients Enrolled patients had ED secondary to SCI (all spinal levels) and sustained 6 months or longer before visit 1. INTERVENTIONS After a 4-week run-in period, patients were randomly assigned to tadalafil, 10 mg, (n = 142) or placebo (n = 44) for a 12-week, on-demand treatment period with assessments at 4-week intervals. The dose of tadalafil was maintained or titrated (10 or 20 mg) at 4 and 8 weeks. MAIN OUTCOME MEASURES Efficacy was measured using the International Index of Erectile Function (IIEF), Sexual Encounter Profile (SEP), and Global Assessment Question (GAQ). Treatment-emergent adverse events and vital signs were collected at each visit. RESULTS Mean age was 38 years. Mean baseline IIEF erectile function domain score was 13.4, and following 12 weeks of treatment, 22.6 for tadalafil and 13.6 for placebo (P < .001). After treatment, the tadalafil group compared with the placebo group was significantly greater (P < .001) in mean per-patient percentage of successful penetration attempts (SEP question 2; 75.4% vs 41.1%) and intercourse attempts (SEP question 3; 47.6% vs 16.8%); percentage of improved erections (GAQ question 1; 84.6% vs 19.5%); and ejaculatory frequency (IIEF question 9; P = .03). The 2 most common treatment-emergent adverse events in the tadalafil group compared with placebo were headache (8.5% vs 4.5%) and urinary tract infection (7.7% vs 6.8%). CONCLUSIONS Tadalafil (10 mg and 20 mg) improved erectile function and was well tolerated by men with ED secondary to traumatic SCI.