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This study was the first of its kind to explore the impact of GDP and LPI on international trade of nations across worldwide.In real-time strategy games, players collect resources, control various units, and create strategies to win. The creation of winning strategies requires accurately analyzing previous games; therefore, it is important to be able to identify the key situations that determined the outcomes of those games. However, previous studies have mainly focused on predicting game results. In this study, we propose a methodology to predict outcomes and to identify information about the turning points that determine outcomes in StarCraft Ⅱ, one of the most popular real-time strategy games. We used replay data from StarCraft Ⅱ that is similar to video data providing continuous multiple images. First, we trained a result prediction model using 3D-residual networks (3D-ResNet) and replay data to improve prediction performance by utilizing in-game spatiotemporal information. Second, we used gradient-weighted class activation mapping to extract information defining the key situations that significantly influenced the outcomes of the game. We then proved that the proposed method outperforms by comparing 2D-residual networks (2D-ResNet) using only one time-point information and 3D-ResNet with multiple time-point information. We verified the usefulness of our methodology on a 3D-ResNet with a gradient class activation map linked to a StarCraft Ⅱ replay dataset.This research aimed to qualitatively explore whether the determinants of handwashing behaviour change according to the duration of displacement or the type of setting that people are displaced to. We conducted an exploratory qualitative study in three different post-conflict settings in Northern Iraq-a long-term displacement camp, a short-term displacement camp, and villages where people were returning to post the conflict. We identified 33 determinants of handwashing in these settings and, of these, 21 appeared to be altered by the conflict and displacement. Determinants of handwashing behaviour in the post-conflict period were predominantly explained by disruptions to the physical, psychological, social and economic circumstances of displaced populations. Future hygiene programmes in post-conflict displacement settings should adopt a holistic way of assessing determinants and design programmes which promote agency, build on adaptive norms, create an enabling environment and which are integrated with other aspects of humanitarian response.Measurement of oxygen consumption of cultured cells is widely used for diagnosis of mitochondrial diseases, drug testing, biotechnology, and toxicology. Fibroblasts are cultured in monolayers, but physiological measurements are carried out in suspended or attached cells. We address the question whether respiration differs in attached versus suspended cells using multiwell respirometry (Agilent Seahorse XF24) and high-resolution respirometry (Oroboros O2k), respectively. Respiration of human dermal fibroblasts measured in culture medium was baseline-corrected for residual oxygen consumption and expressed as oxygen flow per cell. No differences were observed between attached and suspended cells in ROUTINE respiration of living cells and LEAK respiration obtained after inhibition of ATP synthase by oligomycin. The electron transfer capacity was higher in the O2k than in the XF24. This could be explained by a limitation to two uncoupler titrations in the XF24 which led to an underestimation compared to multiple titration steps in the O2k. A quantitative evaluation of respiration measured via different platforms revealed that short-term suspension of fibroblasts did not affect respiratory activity and coupling control. Evaluation of results obtained by different platforms provides a test for reproducibility beyond repeatability. Repeatability and reproducibility are required for building a validated respirometric database.Topic models extract latent concepts from texts in the form of topics. Lifelong topic models extend topic models by learning topics continuously based on accumulated knowledge from the past which is updated continuously as new information becomes available. Hierarchical topic modeling extends topic modeling by extracting topics and organizing them into a hierarchical structure. In this study, we combine the two and introduce hierarchical lifelong topic models. Hierarchical lifelong topic models not only allow to examine the topics at different levels of granularity but also allows to continuously adjust the granularity of the topics as more information becomes available. A fundamental issue in hierarchical lifelong topic modeling is the extraction of rules that are used to preserve the hierarchical structural information among the rules and will continuously update based on new information. To address this issue, we introduce a network communities based rule mining approach for hierarchical lifelong topic models (NHLTM). The proposed approach extracts hierarchical structural information among the rules by representing textual documents as graphs and analyzing the underlying communities in the graph. Experimental results indicate improvement of the hierarchical topic structures in terms of topic coherence that increases from general to specific topics.Moore's Law is approaching its end as transistors are scaled down to tens or few atoms per device, researchers are actively seeking for alternative approaches to leverage more-than-Moore nanoelectronics. Substituting the channel material of a field-effect transistors (FET) with silicene is foreseen as a viable approach for future transistor applications. In this study, we proposed a SPICE-compatible model for p-type (Aluminium) uniformly doped silicene FET for digital switching applications. The performance of the proposed device is benchmarked with various low-dimensional FETs in terms of their on-to-off current ratio, subthreshold swing and drain-induced barrier lowering. The results show that the proposed p-type silicene FET is comparable to most of the selected low-dimensional FET models. With its decent performance, the proposed SPICE-compatible model should be extended to the circuit-level simulation and beyond in future work.This paper reports the results of a qualitative study regarding the main attitudes and concerns of Swiss psychiatrists related to the utility, usability and acceptability of EHR and how they address the pitfalls of sharing sensitive information with other parties. A total of 20 semi-structured interviews were carried out. Applied thematic analysis was used to identify themes with regard to participation. Three main themes were identified 1) strengths of the use of EHR in the clinical context; 2) limitations of EHR; and 3) recommendations on preserving confidentiality in health records. The study shows variable practices of EHR use in psychiatric hospitals in Switzerland and a lack of standards on how to document sensitive information in EHR.

High yield HIV testing strategies are critical to reach epidemic control in high prevalence and low-resource settings such as East and Southern Africa. In this study, we aimed to predict the HIV status of individuals living in Angola, Burundi, Ethiopia, Lesotho, Malawi, Mozambique, Namibia, Rwanda, Zambia and Zimbabwe with the highest precision and sensitivity for different policy targets and constraints based on a minimal set of socio-behavioural characteristics.

We analysed the most recent Demographic and Health Survey from these 10 countries to predict individual's HIV status using four different algorithms (a penalized logistic regression, a generalized additive model, a support vector machine, and a gradient boosting trees). The algorithms were trained and validated on 80% of the data, and tested on the remaining 20%. We compared the predictions based on the F1 score, the harmonic mean of sensitivity and positive predictive value (PPV), and we assessed the generalization of our models by testing themngs constraints.

We trained a gradient boosting trees algorithm to find 95% of PLHIV with a precision twice higher than with general population testing by using only a limited number of socio-behavioural characteristics. We also successfully identified people at high risk of infection who may be offered pre-exposure prophylaxis or voluntary medical male circumcision. These findings can inform the implementation of new high-yield HIV tests and help develop very precise strategies based on low-resource settings constraints.Studying the linkage between manufacturing industry and logistics industry is conducive to explore and improve the efficiency of the common development of them. In order to study the interaction of logistics industry on the development of manufacturing industry and the development of two-industry-linkage, it first calculates the high-quality development level of logistics industry and manufacturing industry, then uses the coupling coordination model to theoretically analyze and empirically test the coupling and coordinated development level of high-quality development of logistics industry and manufacturing industry from three aspects coupling degree, coordination degree and coupling coordination degree, and based on the perspective of integration field theory, it takes the three basic synthetic fields of logistics integrator, logistics base-nuclear and logistics connection-key as the analysis dimension, PVAR model was introduced for in-depth analysis the impact of logistics industry on manufacturing industryevel of the two-industry-linkage is not necessarily beneficial, blindly exceeding the demand for logistics investment will cause a waste of resources, which is not conducive to the high-quality development of the logistics industry and the coupling and coordinated development of the two industries. In the long run, the change of the logistics basic-nuclear capacity, the logistics integrator scale and logistics connection-key level will have a positive impact on the change of green total factor productivity in manufacturing industry.Parsers are used in different software development scenarios such as compiler construction, data format processing, machine-level translation, and natural language processing. Due to the widespread usage of parsers, there exist different tools aimed at automizing their generation. find more Two of the most common parser generation tools are the classic Lex/Yacc and ANTLR. Even though ANTLR provides more advanced features, Lex/Yacc is still the preferred choice in many university courses. There exist different qualitative comparisons of the features provided by both approaches, but no study evaluates empirical features such as language implementor productivity and tool simplicity, intuitiveness, and maintainability. In this article, we present such an empirical study by conducting an experiment with undergraduate students of a Software Engineering degree. Two random groups of students implement the same language using a different parser generator, and we statistically compare their performance with different measures. Under the context of the academic study conducted, ANTLR has shown significant differences for most of the empirical features measured.