German Phoneme Recognition with Text-to-Phoneme Data Augmentation

In this study, we experimented to examine the effect of adding the most frequent n phoneme bigrams to the basic vocabulary on the German phoneme recognition model using the text-to-phoneme data augmentation strategy. As a result, compared to the baseline model, the vowel30 model and the const20 model showed an increased BLEU score of more than 1 point, and the total30 model showed a significant decrease in the BLEU score of more than 20 points, showing that the phoneme bigrams could have a positive or negative effect on the model performance. In addition, we identified the types of errors that the models repeatedly showed through error analysis

The Effect of Competitive Advantage and Human Advantage on Industrial Competitive Strategy (Case Study: Smis in Gorontalo Province)

Small and Medium Industries (SMIs) have a strategic role in the Indonesian economy, as they earn 61.9 percent of the foreign exchange which goes to make up the nation\u27s Gross Domestic Product, and nationally they are able to absorb 97 percent of the workforce. The Global Competitiveness Report also notes that SMIs serve as the business units that affect every nation\u27s competitiveness. Considering this strategic role, the selection of a competitive strategy for these SMIs is absolutely necessary. Through an in-depth literature review, this study aims to explore what variables influence the competitive strategy of industries, particularly the SMIs. By using a Systematic Literature Review (SLR) with a total of 31 main literature (articles, papers and books), this study has found two dominant factors that influence industrial competitive strategy: Competitive advantage and human advantage, which are subsequently developed into six independent variables (construct variables), i.e. cost, delivery, product quality, product variety, know-how and innovativeness, with a total of 44 indicators. The results of measurements of the sample of SMIs in Gorontalo Province, using Structural Equation Modeling, found that both competitive advantage and human advantage jointly influence 40.2 percent of the industrial competitive strategies. These results indicate that competitive strategies, such as creating products with unique features, on-time delivery, flexibility in production, and employee involvement in the innovations, are indispensable to SMIs in order for them to produce quality products and be able to maintain their advantage

Properties, Dimensions, and Heritability of Obsessive-Compulsive Symptoms in a Community Sample of Children and Adolescents

Obsessive-compulsive disorder (OCD) is a debilitating neuropsychiatric disorder commonly seen in children and adolescents. The etiology of OCD remains elusive mostly due to its complex, heterogeneous phenotype and genotype. Increasing evidence support a multidimensional model of OCD and a continuous nature of obsessive-compulsive (OC) symptoms in the general population. However, there is limited understanding of OC symptoms in pediatric populations. Using a novel questionnaire, the Toronto Obsessive Compulsive Scale, we investigated properties, dimensions, and heritability of OC symptoms in a community sample of 16,380 children and adolescents, and a sub-sample of 220 twin pairs, respectively. We identified six distinct OC symptom dimensions in our study that parallel those identified in previous studies: (1) Superstition, (2) Cleaning/Contamination, (3) Hoarding, (4) Symmetry/Ordering, (5) Checking/Counting, (6) Rumination. Phenotypic and heritability characteristics of overall and dimensions of OC symptoms are reviewed in detail. Research and clinical implications of the current study are also discussed.MAS

Risk and culture: variations in dioxin risk perceptions, behavioral preferences among social groups in South Korea

Objectives This study examined variations in the perceptions of dioxin risk among social groups defined by geographical living location, environmental education, and occupation. Dioxin risk perceptions were analyzed according to values, risk awareness, knowledge, and behavioral preferences. Methods A quasi-experimental survey was designed and conducted on individuals from seven experimental groups in Jeonju city, South Korea, including: people living near incineration facilities; people living far from incineration facilities; governmental experts; nongovernmental organization members; office workers in developmental institutes or banks; students who were enrolled in environmental-related classes; and students who were enrolled in business-related classes. Results The results show variations among groups in values, awareness and behavioral preferences. Particular attention should be given to the result that groups with higher connectedness- to-nature values show higher willingness-to-act (WTA) for risk reduction. Result s can be summarized as follows. First, awareness is associated with one’s geographical setting. Second, values and WTA behaviors are related to one’s environmental-related education and occupation. Third, values are significantly related to WTA behaviors. Conclusions Different cultures, in terms of values or worldview, among groups influence their perceptions of dioxin risk and choices of risk reduction behaviors. It is important to consider values in communicating complicated long-term risk management involving public participation. Further research should be continuously conducted on the effects of multiple dimensions of values on one’s WTA for risk reduction behaviors

Mental Health Implications of Traumatic Brain Injury (TBI) in Children and Youth

Objective: Traumatic brain injury (TBI) is the most common cause of death and disability in children and adolescents. Psychopathology is an established risk factor for, and a frequent consequence of, TBI. This paper reviews the literature relating psychopathology and TBI. Method: Selective literature review. Results: The risk of sustaining a TBI is increased by pre-existing psychopathology (particularly ADHD and aggression) and psychosocial adversity. Even among individuals with no psychopathology prior to the injury, TBI is frequently followed by mental illness especially ADHD, personality change, conduct disorder and, less frequently, by post-traumatic stress and anxiety disorders. The outcome of TBI can be partially predicted by pre-injury adjustment and injury severity, but less well by age at injury. Few individuals receive treatment for mental illness following TBI. Conclusion: TBI has substantial relevance to mental health professionals and their clinical practice. Available evidence, while limited, indicates that the risk for TBI in children and adolescents is increased in the presence of several, potentially treatable mental health conditions and that the outcome of TBI involves a range of mental health problems, many of which are treatable. Prevention and management efforts targeting psychiatric risks and outcomes are an urgent priority. Child and adolescent mental health professionals can play a critical role in the prevention and treatment of TBI through advocacy, education, policy development and clinical practice

Validation of the influence of biosignals on performance of machine learning algorithms for sleep stage classification

Background Sleep stage identification is critical in multiple areas (e.g. medicine or psychology) to diagnose sleep-related disorders. Previous studies have reported that the performance of machine learning algorithms can be changed depending on the biosignals and feature-extraction processes in sleep stage classification. Methods To compare as many conditions as possible, 414 experimental conditions were applied, considering the combination of different biosignals, biosignal length, and window length. Five biosignals in polysomnography (i.e. electrocardiogram (ECG), electroencephalogram (EEG), electromyogram (EMG), electrooculogram left, and electrooculogram right) were used to identify optimal signal combinations for classification. In addition, three different signal-length conditions and six different window-length conditions were applied. The validity of each condition was examined via classification performance from the XGBoost classifiers trained using 10-fold cross-validation. Furthermore, results considering feature importance were examined to validate the experimental results in terms of model explanation. Results The combination of EEG + EMG + ECG with a 40 s window and 120 s signal length resulted in the best classification performance (precision: 0.853, recall: 0.855, F1-score: 0.853, and accuracy: 0.853). Compared to other conditions and feature importance results, EEG signals showed a relatively higher importance for classification in the present study. Conclusion We determined the optimal biosignal and window conditions for the feature-extraction process in machine learning algorithm-based sleep stage classification. Our experimental results inform researchers in the future conduct of related studies. To generalize our results, more diverse methodologies and conditions should be applied in future studies

The Positive Effects of Poria cocos Extract on Quality of Sleep in Insomnia Rat Models

Sleep disorders may have various causes and can incur mental and/or physical symptoms, and affect an individual’s quality of life. In this study, we confirm that the Poria cocos extract (PCET) can improve sleep quality and structure by promoting inhibitory neurotransmission via the γ-aminobutyric acid (GABA) type A (GABAA) receptors based on the mechanisms revealed in the experiment with superior cervical ganglion neurons. Pentobarbital-induced sleep tests were conducted in order to determine whether the PCET extract improves the sleep quality and structure in normal ICR mice. Sleep latency and duration were checked with the righting reflex. To simulate the state of awakening as well as a normal sleep state, caffeine was administered orally before the PCET diet. After oral gavage of PCET, sleep latency was decreased, and total sleep duration was increased in normal and caffeine-induced sleep disturbance state. In the ACTH-induced sleep disturbed models, administration of PCET significantly reduced the sleep latency and increased the non-REM sleep duration, which was analyzed in real-time EEG by implanting wireless electrodes in SD rats. PCET was found to improve the sleep quality under a normal sleep state through the GABAA receptor; it also promoted and improved the sleep quality and sleep structure in both the arousal activation state and stress-based sleep disturbance