Miracle-dz/UniFAR-FTUs huggingface dataset:
A REVIEW ON THE EFFECTS OF A PROFESSIONAL DEVELOPMENT PROGRAM ON EFL TEACHERS’ BELIEFS AND THEIR CLASSROOM PRACTICES

Bài báo này nhằm mục đích đánh giá các nghiên cứu thực nghiệm trước đây về ảnh hưởng của chương trình bồi dưỡng chuyên môn đối với tín niệm về giảng dạy tiếng Anh và thực hành giảng dạy trên lớp của giáo viên để tìm ra những thiếu sót của nghiên cứu trước đây và đề xuất hướng nghiên cứu tiếp theo tại Việt Nam. Để thu thập số liệu cho nghiên cứu này, phương pháp nghiên cứu lý thuyết hệ thống được sử dụng với nguồn tài liệu lý thuyết được chọn lọc từ 20 bài báo và luận văn khoa học liên quan đến lĩnh vực nghiên cứu. Kết quả cho thấy, có sự thay đổi trong tín niệm về giảng dạy tiếng Anh và thực hành giảng dạy trên lớp của giáo viên sau khi tham gia khóa học bồi dưỡng chuyên môn ở nhiều nghiên cứu trước đây. Tuy nhiên, một số nghiên cứu khác cho rằng có ít hoặc không có sự thay đổi trong tín niệm về giảng dạy tiếng Anh và thực hành giảng dạy trên lớp của giáo viên. Đặc biệt, hầu hết các nghiên cứu đều bộc lộ một số hạn chế nhất định như phương pháp nghiên cứu, mẫu đại diện tham gia nghiên cứu, sự phân chia tách biệt giữa tín niệm và thực hành, và có rất ít nghiên cứu trong lĩnh vực này đặc biệt là tại các trường phổ thông ở Việt Nam.
Developing New Software to Analyze the Emo-‎Sensory Load of Language

Technology plays a crucial role in fully understanding all aspects ‎of language and uncovering the hidden patterns, such as sense and emotion ‎density in texts. Yet, it seems that remarkable attention has not been paid to ‎the sensory and emotional loads of learning texts as the primary source of ‎learning. This study attempts to present an objective way of analyzing ‎English learning texts from both emotional and sensory perspectives to ‎provide material developers to measure the emotional and sensory loads of ‎the texts. For this purpose, a new kind of software was developed using ‎two datasets; Sensicon and EmoLex. Then as an example, an English ‎course book series, Interchange (5th ed.), was analyzed by this software to ‎determine any probable pattern(s) concerning sensory and emotional loads. ‎The results showed that the dominant sense in these books is hearing at all ‎levels of language proficiency. In the emotion analysis part, the eight basic ‎emotions were categorized as positive and negative emotions, and the ‎results showed a higher frequency of positive emotions. It was also found ‎that the frequency of negative emotions increases at higher levels, resulting ‎in more authenticity. ‎
Heat-shock Protein 70: Sequence and Expression Analysis in African Catfish Clarias gariepinus after Bacterial Infection and Stress Exposures

Heat-shock protein 70 (HSP70) is a member of the Heat-shock protein family that plays an important role in cellular homeostasis against various stressors in fish. This research aimed to identify the full length of cDNA sequence HSP70 in African catfish C. gariepinus and assessed its mRNA expression under various tissues and stress conditions. The cDNA was cloned and amplified using the polymerase chain reaction (PCR) followed by bi-directional sequencing. The mRNA expression was quantified using the real-time PCR (qPCR) method. A full-length ORF of C. gariepinus HSP70 cDNA was 1932 bp long, encoded 643 amino acids. Three signature sequences of the HSP70 family were detected in the predicted amino acid sequence. The C. gariepinus HSP70 showed the highest similarity in nucleotide and amino acid sequence (>90%) to HSP70 from other Siluriformes catfish species. The HSP70 mRNA was expressed in all tested tissues, with the highest expression found in the liver and spleen, followed by the intestine, heart, head-kidney, and gill. The C. gariepinus HSP70 expression was significantly induced generally after 6 hours of bacterial infection, transportation, heat shock, and high nitrite exposure. The results indicated that the HSP70 gene could serve as an early stress biomarker in C. gariepinus
Microstructures and properties of TIG welded 5A06-Al: responses to variable Ar-He alternating supplying conditions

During the TIG welding process, the interactions between arc plasma and molten pool could be periodically influenced by supplying Ar–He shield gas alternatively, which would affect the solidification and forming of the weld metal. In this work, the responses of microstructures and mechanical properties of the TIG welded 5A06 joint to the variable Ar–He alternating supplying conditions were investigated systematically. The variable shielding gas supply had a grain refining effect on the weld seam due to more violent and impacting effect on the molten pool. Moreover, the number of strengthening phases increased and became more dispersed, which increased the tensile strength further. The electrochemical experiment showed that the weld seam under continuous gas supply had better corrosion resistance.
Systèmes de lois de conservation et stabilité BV

© Mémoires de la S. M. F. , 1998, tous droits réservés. L’accès aux archives de la revue « Mémoires de la S. M. F. » (http:// smf.emath.fr/Publications/Memoires/Presentation.html) implique l’accord avec les conditions générales d’utilisation (http://www.numdam.org/legal.php). Toute utilisation commerciale ou impression systématique est constitutive d’une infraction pénale. Toute copie ou impression de ce fichier doit contenir la présente mention de copyright.
Structural Heart Alterations in Brugada Syndrome: Is it Really a Channelopathy? A Systematic Review

Brugada syndrome (BrS) is classified as an inherited cardiac channelopathy attributed to dysfunctional ion channels and/or associated proteins in cardiomyocytes rather than to structural heart alterations. However, hearts of some BrS patients exhibit slight histologic abnormalities, suggesting that BrS could be a phenotypic variant of arrhythmogenic cardiomyopathy. We performed a systematic review of the literature following Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statement (PRISMA) criteria. Our comprehensive analysis of structural findings did not reveal enough definitive evidence for reclassification of BrS as a cardiomyopathy. The collection and comprehensive analysis of new cases with a definitive BrS diagnosis are needed to clarify whether some of these structural features may have key roles in the pathophysiological pathways associated with malignant arrhythmogenic episodes.
Wide Field Spectroscopy and the Distant Universe: The 35th Herstmonceux Conference Cambridge, United Kingdom July 4-8, 1994

The Sloan digital sky survey, J. Gunn the AAO's 2df facility - progress and predicted performance, K. Taylor WYFFOS? why not? (progress with the WHT's prime-focus multi-object spectroscopy system), F. Watson ROSAT surveys and follow-up spectroscopy, G. Hasinger the IRAS PSC Redshift survey, W. Saunders the Las Campanas fibre optic redshift survey, S. Shectman spectroscopy of K-selected galaxy samples, L. Cowie following normal galaxies to high redshift using QSO absorption line selection, C. Steidel constraints on cosmological models from once and future surveys, M. Vogeley extracting science from large galaxy redshift surveys, D. Weinberg evolution of structure, N. Kaiser galaxy clustering at high redshift, G. Efstathiou evolution in optical galaxy samples, M. Colless evolution of stellar populations at high z, B. Guiderdoni. (Part Contents).
HGA: Hierarchical Feature Extraction With Graph and Attention Mechanism for Linguistic Steganalysis

Linguistic steganalysis is an important topic in the field of information security and signal processing. In recent years, linguistic steganalysis have mainly utilized deep learning techniques and make great success. But suffer from the following major disadvantages. From the perspective of model structure, current methods only extract coarse features of the text, without focusing on the fine-grained representations. In terms of application, most of the studies only focus on single hidden scene and ignore the more realistic mixed hidden scenes which are more complex and realistic. These weaknesses limit the performance and the application of linguistic steganalysis in reality. In this letter, we propose a novel linguistic steganalysis method to overcome these weaknesses. This proposed method can extract distinguished text representation which fuses hierarchical features and perform excellently in sophisticated conditions. Firstly, we adapt gated graph neural networks as the coarse graph updater to update node representations on the graph level. Then we design a fine graph updater composed of the graph attention mechanism to focus on the highlighted nodes on the node-level. Moreover, we extract the most notable feature on the dimension-level of node by the graph channel attention module. Finally, the readout function is designed to fuse the hierarchical features and make the classification. The experimental results show that our method achieves the best results compared with the previous methods in both single hidden scene and mixed hidden scenes, which prove the effectiveness of the proposed method.
Oxygenated volatile organic compounds (VOCs) as significant but varied contributors to VOC emissions from vehicles

Abstract. Vehicular emissions are an important source for volatile organic compounds (VOCs) in urban and downwind regions. In this study, we conducted a chassis dynamometer study to investigate VOC emissions from vehicles using gasoline, diesel, and liquefied petroleum gas (LPG) as fuel. Time-resolved VOC emissions from vehicles are chemically characterized by a proton-transfer-reaction time-of-flight mass spectrometer (PTR-ToF-MS) with high frequency. Our results show that emission factors of VOCs generally decrease with the improvement of emission standards for gasoline vehicles, whereas variations in emission factors for diesel vehicles with emission standards are more diverse. Mass spectrum analysis of the PTR-ToF-MS suggests that cold starts significantly influence VOC emissions of gasoline vehicles, while the influences are less important for diesel vehicles. Large differences in VOC emissions between gasoline and diesel vehicles are observed with emission factors of most VOC species from diesel vehicles being higher than gasoline vehicles, especially for most oxygenated volatile organic compounds (OVOCs) and heavier aromatics. These results indicate quantification of heavier species by the PTR-ToF-MS may be important in the characterization of vehicular exhausts. Our results suggest that VOC pairs (e.g., C14 aromatics / toluene ratio) could potentially provide good indicators for distinguishing emissions from gasoline and diesel vehicles. The fractions of OVOCs in total VOC emissions are determined by combining measurements of hydrocarbons from canisters and online observations of the PTR-ToF-MS. We show that OVOCs contribute 9.4 % ± 5.6 % of total VOC emissions for gasoline vehicles, while the fractions are significantly higher for diesel vehicles (52 %–71 %), highlighting the importance of detecting these OVOC species in diesel emissions. Our study demonstrated that the large number of OVOC species measured by the PTR-ToF-MS are important in the characterization of VOC emissions from vehicles.
Evaluation of the Therapeutic Potential of Mesenchymal Stem Cells (MSCs) in Preclinical Models of Autoimmune Diseases

Autoimmune diseases, chronic in nature, are generally hard to alleviate. Present long-term treatments with available drugs such as steroids, immune-suppressive drugs, or antibodies have several debilitating side effects. Therefore, new treatment options are urgently needed. Stem cells, in general, have the potential to reduce immune-mediated damage through immunomodulation and T cell regulation (T regs) by inhibiting the proliferation of dendritic cells and T and B cells and reducing inflammation through the generation of immunosuppressive biomolecules like interleukin 10 (IL-10), transforming growth factor-β (TGF-β), nitric oxide (NO), indoleamine 2,3-dioxygenase (IDO), and prostaglandin E2 (PGE2). Many stem cell-based therapeutics have been evaluated in the clinic, but the overall clinical outcomes in terms of efficacy and the longevity of therapeutic benefits seem to be variable and inconsistent with the postulated benefits. This emphasizes a greater need for building robust preclinical models and models that can better predict the clinical translation of stem cell-based therapeutics. Stem cell therapy based on MSCs having the definitive potential to regulate the immune system and control inflammation is emerging as a promising tool for the treatment of autoimmune disorders while promoting tissue regeneration. MSCs, derived from bone marrow, umbilical cord, and adipose tissue, have been shown to be highly immunomodulatory and anti-inflammatory and shown to enhance tissue repair and regeneration in preclinical models as well as in clinical settings. In this article, a review on the status of MSC-based preclinical disease models with emphasis on understanding disease mechanisms in chronic inflammatory disorders caused by exaggerated host immune response in rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) was carried out. We also emphasized various factors that better predict the translation of stem cell therapeutic outcomes from preclinical disease models to human patients.
Can Green Finance Policies Stimulate Technological Innovation and Financial Performance? Evidence from Chinese Listed Green Enterprises

The impact of China’s green finance policies on renewable energy, clean energy, and other green companies is a hot topic of concern. This study uses the difference-in-differences (DID) model to examine the incentive effect of the Green Credit Guidelines (GCG) on the technological innovation and financial performance of Chinese listed green enterprises. The heterogeneity analysis is carried out from the level of digital finance, green development, and marketization. This study finds that: (1) Green finance is conducive to stimulating the technological innovation and financial performance of green enterprises. (2) Green enterprises in areas with high digital finance levels have a more significant incentive effect on green finance policies, compared to areas with less-developed digital finance. (3) Green enterprises in areas with high levels of green development are more significantly positively affected by green finance policies, compared to areas with less-developed digital finance. (4) The incentive effect of green credit policies on green enterprises in areas with a high degree of marketization is more significant, compared with regions with a lower level of green development. Finally, some policy implications are proposed to provide a reference for China to improve the green financial system to facilitate the financing of green enterprises.
Optimal Design for Modulated Binary Sensors

A paramount factor limiting the applications of binary sensors is these senors’ on-off property outputting binary digits of “0” or “1”. To overcome this limitation, modulators or obscurants are added to enhance the sensing ability of binary sensors and render them usable in applications such as multi-target tracking and human activity recognition. Obscurants segment the field of interest into subregions and distinguish each subregion by a list of sensor states called signatures. This paper studies two placement scenarios in a two-dimensional planar graph. In the first scenario, we prove upper and lower bounds on the maximum number of achievable signatures. In the second scenario, starting from the placement of sensors and obscurants in which the maximum number of signatures is achievable, we propose a novel mathematical model based on four main metrics: the object space size, the sensor space size, the obscurant space size, and the sizes of individual obscurants. We find the minimum and maximum radiuses that bound the object detection area given the number and sizes of sensors and obscurants. We derive the obscurant space size as a function of the object space size and the size of individual obscurants. We also provide a linear relationship formula between the obscurant space radius, the sensor space radius, and the obscurants’ radiuses and conduct modeling experiments to study the relationship between these metrics. Finally, we deduct an explicit formula for the maximum obscurant space size for the sensor space and the individual obscurant sizes.
The Effects of Internet-Based Acceptance and Commitment Therapy on Process Measures: Systematic Review and Meta-analysis

Background Acceptance and commitment therapy (ACT) is based on a psychological flexibility model that encompasses 6 processes: acceptance, cognitive defusion, self-as-context, being present, values, and committed action. Objective This systematic review and meta-analysis of randomized controlled trials (RCTs) aimed to examine the effects of internet-based ACT (iACT) on process measures. Methods A comprehensive search was conducted using 4 databases. The quality of the included RCTs was assessed using the Cochrane Collaboration Risk of Bias Tool. A random-effects or fixed-effects model was used. Subgroup analyses for each outcome were conducted according to the type of control group, use of therapist guidance, delivery modes, and use of targeted participants, when applicable. Results A total of 34 RCTs met the inclusion criteria. This meta-analysis found that iACT had a medium effect on psychological flexibility and small effects on mindfulness, valued living, and cognitive defusion at the immediate posttest. In addition, iACT had a small effect on psychological flexibility at follow-up. The overall risk of bias across studies was unclear. Conclusions Relatively few studies have compared the effects of iACT with active control groups and measured the effects on mindfulness, valued living, and cognitive defusion. These findings support the processes of change in iACT, which mental health practitioners can use to support the use of iACT.
Ivermectin Inhibits the Replication of Usutu Virus In Vitro

Usutu virus (USUV) is an emerging mosquito-borne arbovirus within the genus Flavivirus, family Flaviviridae. Similar to the closely related West Nile virus (WNV), USUV infections are capable of causing mass mortality in wild and captive birds, especially blackbirds. In the last few years, a massive spread of USUV was present in the avian population of Germany and other European countries. To date, no specific antiviral therapies are available. Nine different approved drugs were tested for their antiviral effects on the replication of USUV in vitro in a screening assay. Ivermectin was identified as a potent inhibitor of USUV replication in three cell types from different species, such as simian Vero CCL-81, human A549 and avian TME R. A 2- to 7-log10 reduction of the viral titer in the supernatant was detected at a non-cytotoxic concentration of 5 µM ivermectin dependent on the applied cell line. IC50 values of ivermectin against USUV lineage Africa 3 was found to be 0.55 µM in Vero CCL-81, 1.94 µM in A549 and 1.38 µM in TME-R cells. The antiviral efficacy was comparable between the USUV lineages Africa 2, Africa 3 and Europe 3. These findings show that ivermectin may be a candidate for further experimental and clinical studies addressing the treatment of USUV disease, especially in captive birds.
Exploring the effects of problem- and solution-related knowledge sharing in internal crowdsourcing

Purpose Firms increasingly rely on both external and internal crowdsourcing to capture ideas more broadly and enhance innovative problem-solving. Especially in internal crowdsourcing, knowledge sharing that contributes to develop or further the understanding of the problem the idea is focused on solving can take place between critical employees, and in that way improve ideas generated by others. This far, most crowdsourcing practices have focused on identifying solutions to proposed problems, whereas much less is known about how crowds can be used to share problem-related knowledge. There is thus an untapped potential in leveraging crowds not just to generate solution-oriented ideas but also to share knowledge to improve ideas and even to reframe problems. This paper aims to explore the effect of problem- and solution-related knowledge sharing in internal crowdsourcing for idea development. Design/methodology/approach Data on ideas and comments were collected from an idea management system in a Swedish multinational company. The investigation captures the influences of the problem- and solution-related knowledge sharing on ideas based on content analysis and logistic regression analysis. Findings The results from this study show that sharing knowledge related to solutions in idea development impacts idea acceptance positively, whereas sharing knowledge related to problems in idea development has a negative effect on the likelihood of idea acceptance and these effects of knowledge sharing are moderated by the active author responses. Practical implications This research provides managerial implications for firms to deliberately manage knowledge sharing in peer communities in internal crowdsourcing, especially by providing suggestions on problem reframing and solution refining for ideas. Originality/value The results contribute to existing theory in terms of extending the view of crowdsourcing in ideation to include how crowds contribute to the development of the problem and the solution during the development of ideas and providing new insights on knowledge sharing in internal crowdsourcing based on problem-solving theory.
Wastewater-Based Epidemiology for COVID-19: Handling qPCR Nondetects and Comparing Spatially Granular Wastewater and Clinical Data Trends

Wastewater-based epidemiology (WBE) is a useful complement to clinical testing for managing COVID-19. While community-scale wastewater and clinical data frequently correlate, less is known about subcommunity relationships between the two data types. Moreover, nondetects in qPCR wastewater data are typically handled through methods known to bias results, overlooking perhaps better alternatives. We address these knowledge gaps using data collected from September 2020–June 2021 in Davis, California (USA). We hypothesize that coupling the expectation maximization (EM) algorithm with the Markov Chain Monte Carlo (MCMC) method could improve estimation of “missing” values in wastewater qPCR data. We test this hypothesis by applying EM-MCMC to city wastewater treatment plant data and comparing output to more conventional nondetect handling methods. Dissimilarities in results (i) underscore the importance of specifying nondetect handling method in reporting and (ii) suggest that using EM-MCMC may yield better agreement between community-scale clinical and wastewater data. We also present a novel framework for spatially aligning clinical data with wastewater data collected upstream of a treatment plant (i.e., distributed across a sewershed). Applying the framework to data from Davis reveals reasonable agreement between wastewater and clinical data at highly granular spatial scales—further underscoring the public-health value of WBE.