Miracle-dz/UniFAR-FTUs huggingface dataset:
Differential Associations of Sports Participation With Self-Rated Health and Depressive Symptoms Among Japanese Adolescents

Introduction: We aimed to evaluate the associations of sports participation with self-rated health and depressive symptoms in a nationally representative sample of Japanese adolescents. Methods: A questionnaire survey was conducted with 1,658 adolescents aged between 12 and 21 years. Sports participation levels were divided into high-frequency, moderate-frequency, low-frequency, and no-participation groups. Self-rated health was evaluated using a four-grade scale. Depressive symptoms were assessed using the Japanese version of the Patient Health Questionnaire-8. Other lifestyle behaviors were also surveyed. The associations of sports participation with self-rated health and depressive symptoms were examined using multiple logistic regression analysis. Results: The participants in the high- (odds ratio (OR), 0.45) and moderate-frequency (OR, 0.46) groups were less likely to self-report poor health than those in the non-participation group. By contrast, a U-shaped association was found between sports participation and depression, in which the participants in the moderate-frequency group (OR, 0.52) were less likely to have depressive symptoms. The OR for the high- (0.89) and low-frequency (0.91) groups were not significant. Furthermore, eating regular breakfasts, six or more days/week, and having shorter screen times of less than two hours/day were negatively associated with poor self-reported health and depressive symptoms. Conclusion: Moderate- to high-frequency sports activities are associated with a reduced risk of poor self-rated health among Japanese adolescents. However, only moderate-frequency activities were associated with a reduced risk of depression. Participation in optimal sports activities may effectively lower the risk of poor health in adolescents.
Artificial Intelligence in Detecting Peri Apical Lesion: A systematic review

Objective: Artificial intelligence plays a very important role in diagnosis and treatment planning in dentistry. The aim of this systematic review is to analyze the accuracy of artificial intelligence in detecting periapical lesions in endodontics. Material and Methods: Using the MeSH keywords: Artificial intelligence (AI), AI in endodontics, neural networks and endodontics, machine learning, deep neural network and periapical lesion, AI dental imaging, and AI treatment diagnosis and endodontics electronic search was performed in four databases - PubMed/Medline (National Library of Medicine), Scopus (Elsevier), ScienceDirect databases (Elsevier), Web of Science (Clarivate Analytics). The English language articles reporting on AI in different dental specialities were screened for eligibility and chosen for analysis based on set inclusion criteria. Results: A total of seven full-text articles were selected and systematically analysed. Artificial intelligence technology was found to have greater accuracy in detecting periapical lesions when compared to clinicians. Conclusion: Artificial intelligence is a reliable tool in the diagnosis of periapical lesions in endodontics, with the use of which accuracy and precision of diagnosis can be enhanced.
A NEW TRANSDUCTIVE FRAMEWORK FOR FEW-SHOT BIOACOUSTIC EVENT DETECTION TASK Technical Report

Few-shot learning is introduced to reduce the requirements of data availability in machine learning, especially when the labelling is labour expensive. Few-shot learning algorithms usually suffer from the extraordinary feature distribution of the query class, especially in few-shot bioacoustic event detection task. In this work, Knowledge transfer technique is introduced into the transductive inference process to restrict the feature distribution of newly appeared class to a dedicated sub-space, while adapts the feature distribution for existing classes. The proposed system outperforms the traditional few-shot learning system according to the development dataset provided by bioacoustics event detection (Task 5) in DCASE data challenge 2022. The f-measure score of the validation in development dataset successfully reaches 57.40
Matchmaker: signaling for dynamic publish/subscribe applications

The publish/subscribe (pub/sub) paradigm provides content-oriented data dissemination in which communication channels are established between content publishers and content subscribers based on a matching of subscribers interest in the published content provided - a process we refer to as "matchmaking". Once an interest match has been made, content forwarding state can be installed at intermediate nodes (e.g., active routers, application-level relay nodes) on the path between a content provider and an interested subscriber. In dynamic pub/sub applications, where published content and subscriber interest change frequently the signaling overhead needed to perform matchmaking can be a significant overhead. We first formalize the matchmaking process as an optimization problem, with the goal of minimizing the amount of matchmaking signaling messages. We consider this problem for both shared and per-source multicast data (content) distribution topologies. We characterize the fundamental complexity of the problem, and then describe several efficient solution approaches. The insights gained through our analysis are then embodied in a novel active matchmaker signaling protocol (AMSP). AMSP dynamically adapts to applications' changing publication and subscription requests through a link-marking approach. We simulate AMSP and two existing broadcast-based approaches for conducting matchmaking, and find that AMSP significantly reduces signaling overhead.
Moving toward sustainable development: the influence of digital transformation on corporate ESG performance

PurposeAmidst the rapid development of the global digital economy, digital transformation has become a strategic choice that firms must use to respond to the changing times. This study analyzes the impact of digital transformation on corporate environmental, social and governance (ESG) performance.Design/methodology/approachThis study analyzes the impact of digital transformation on corporate ESG performance.FindingsUsing panel data from Chinese A-share-listed companies from 2010 to 2019, the authors found that digital transformation has a positive impact on corporate ESG performance, especially for high-tech firms and state-owned firms. In particular, the authors find that the digital production and digital marketing exert a positive effect on corporate ESG performance. Mechanism tests showed that digital transformation helps promote corporate green innovation, improve information transparency and improve corporate governance, thus enhancing ESG performance. A moderating effect analysis revealed that the positive impact of digital transformation on ESG performance is more significant in firms with government subsidies and chief executive officers (CEOs) with rich career experience.Originality/valueMost existing research has confirmed the positive effect of digital transformation on firms' financial performance, whereas fewer studies have focused on the impact of digital transformation on the non-financial performance of firms.
Interprofessional collaboration between residential child care and mental care practitioners: a cross-country study in six European countries

ABSTRACT The severe mental health problems of many of the young people living in residential settings pose a great challenge and demand on child protection and mental care (MC) services. Drawing on comparative research and debates from six European countries, this study examines demands for integrated care and interprofessional collaboration practices between residential child care (RCC) and MC. In this article, research data will be brought together from Denmark, Finland, Germany, Lithuania, the UK (Scotland) and Spain. In total, 61 practitioners from RCC and MC were interviewed. Given the complexity of the residential care service context and service system differences across national contexts, the original hypothesis was that this would differentiate the collaboration practices. However, the similarity between the countries is greater than anticipated. The concluding findings are organised by matrix technique into a content-analytic summary table. The main finding was that in spite of encouragement for integrated RCC, obstacles for collaboration and lack of coordination between systems remain, often related to understanding the professional role and tasks, lack of shared knowledge, attitudes and ways of communication. One significant finding in the cross-country comparison was the evident and unrealistic expectations for the ‘other’ provider to help and care.
Effect of Biosynthesized Zinc oxide Nanoparticles on Phenotypic and Genotypic Biofilm Formation of Proteus mirabilis

Proteus mirabilis is considered as a third common cause of catheter-associated urinary tract infection, with urease production, the potency of catheter blockage due to the formation of biofilm formation is significantly enhanced. Biofilms are major virulence factors expressed by pathogenic bacteria to resist antibiotics; in this concern the need for providing new alternatives for antibiotics is getting urgent need, This study aimed to explore whether green synthesized zinc oxide nanoparticles (ZnO NPs) can function as an anti-biofilm agent produced by P.mirabilis. Bacterial cells were capable of catalyzing the biosynthesis process by producing reductive enzymes. The nanoparticles were synthesized from cell free extract of P.mirabilis. Characterization of biosynthesized zinc nanoparticles was carried out to determine the chemical and physical properties of the product using AFM, TEM, FESEM, XRD and UV visible spectrometry. The hexagonal structure was confirmed by XRD, Particle size was marked at 84.45 nm by TEM, FESEM was used to confirm the surface morphology. AFM analysis was used to reveal the roughness and distribution of nanoparticles. UV–visible spectra of the synthesized nanoparticles recorded maximum peak at 287 nm. Zinc nanoparticles showed remarkable biofilm inhibitory effect on clinical isolates of multidrug resistant Proteus mirabilis. Strong biofilm producer strains show weak biofilm production After incubation for 24 and 48 hours at 37Co with 32 μg/ml sub -MIC concentration of ZnO nanoparticles. Down regulation changes in LuxS expression using Real time PCR technology were detected after treatment with zink nanoparticles of these isolates compared to untreated isolates. From all findings conducted by this study, zinc oxide nanoparticles can function as anti-bacterial agent in concentration dependent manner.
Reputable Audit Quality Attributes and Related Party Transactions Disclosure

We examine the relationship between reputable audit quality attributes (international-based brand name and industry expertise) and related party transactions (RPT) disclosure among listed companies in Malaysia. A decrease magnitude of RPT disclosure in recent years may indicate that companies tend not to report RPT appropriately, especially transactions with entities involving the interest of individual-related parties (RPT-conflict). We argue that the auditors with reputable international brand names and industry specialist, are more inspired to ensure companies disclose RPTs appropriately. We test listed companies from 2013 to 2016 with 1,249 total observations and find that a reputable international brand name audit firm increases RPT-conflict disclosure. However, the relationship is attributable to international non-Big 4 rather than international Big 4 auditors. The reputable industry specialist auditor also increases RPT-conflict disclosure. This study contributes a greater understanding of the association between an auditor’s reputable status towards RPT disclosure from the reputation theory perspective. The evidence suggests that the reputable audit quality status inspires the auditor to provide better audit efforts to discipline RPT from being abused by the related parties. The policymakers and regulators can ensure transparency of RPT disclosure by considering the reputable audit quality attributes to regulate companies that engage in RPTs.
UPAYA PENINGKATAN PEMAHAMAN KONSEP SISWA PADA PEMBELAJARAN PERKAKAS TANGAN MELALUI MODEL PEMBELAJARAN PROBLEM BASED LEARNING DI SMKN 1 CILEUNGSI

The purpose of this study was to increase students' understanding of the concepts of class X TPGM at SMKN 1 Cileungsi through the problem-based learning model. The method used is Classroom Action Research (CAR) using the spiral/cycle model from Kemmis and McTaggart which consists of 2 cycles with four stages in each cycle namely, planning, action, observation and reflection. The subjects of this study were 36 students. Data collection techniques used include observation, learning achievement tests, and documentation. Data on student activity was obtained through class observation and analyzed to compare student activity levels in each cycle. Data about students' understanding of concepts can be seen from the learning outcomes obtained through written tests and practical tests then analyzed to compare the results of the exams in each cycle. The results showed an increase in activity and student learning outcomes in the subject of hand tools using the PBL method. This is evidenced by the increase in student activity as seen from the percentage of student activity in cycle I of 55.56% (enough) increased by 22.22% in cycle II to 77.78% (good). Of the 9 aspects observed in cycle I, 4 aspects are still below the KKM, namely in the aspect of the ability to work on student worksheets, the courage of students in presenting their findings, the ability of students to relate material to real life, and the ability to solve problems while in cycle II all aspects have reached KKM. An increase in students' understanding of concepts can be seen from the average increase in practical test scores and written test scores. The average practice test score in cycle I was 68.24 (55.56%) increasing to 81.59 (86.11%) in cycle II. While the average written test score in cycle I was 59.08 (41.67%) increased to 62.04 (77.78%) in cycle II of the 36 students who still had not reached the KKM on the practical test as many as 5 students (13 .89%) while in the written test there were 8 students (22.22%) at the end of the cycle.
Effectiveness of Marketing Strategies of LPU Batangas among CITHM Freshmen in the case of New Normal

– Amidst the COVID-19 pandemic, LPU-Batangas shall still pursue the academic year and has nothing to adapt the new normal and continue marketing the school to attract students to enroll. The effectivity of marketing strategies is a must right now to encourage students to still continue their studies regardless of pandemic. With this, the researchers aimed to evaluate the effectiveness of marketing strategies of LPU-Batangas among CITHM freshmen in the case of new normal. The study utilized an adopted survey questionnaire among the 317 freshman students. All data were treated using a statistical software known as SPSS version 26. It was revealed that the most effective strategies employed were webinars, online advertisement and boosting Facebook page. It is the quality of education offered and being accredited to be center for excellence that encourages the respondents to enroll. It was found out that there was no significant difference observed since the computed p-values were all greater than 0.05 alpha level, which means that the responses did not differ significantly. However, it was revealed that there was a poor planning in advertising. With this, the researchers proposed an action plan for continuous improvement of the university’s marketing strategies.
Hybrid improper ferroelectricity and possible ferroelectric switching paths in Sr3Hf2O7

Hybrid improper ferroelectricity, which is induced by the coupling of oxygen octahedral rotation and tilt in oxide materials, has great potential to create single-phase multiferroic materials with intrinsic electric field-controlled magnetism. Based on previous experiments with bi-layered Ruddlesden-Popper Sr-based materials, hybrid improper ferroelectricity in Sr3Hf2O7 was investigated by first-principle calculations in the present work. The results show that the ferroelectric A21am phase has the lowest energy among all possible phases, indicating that it is the ground state. The spontaneous polarization calculated by the Berry phase approach and Born effective charge model is approximately 4.6 μC/cm2, in agreement with those reported for other Sr-based compounds. Compared to Ca3Ti2O7, the smaller polarization of Sr3Hf2O7 is attributed to the negative contribution of the HfO2 layer to global polarization. The possible ferroelectric switching path was determined using the nudged elastic band method. The energy barriers of the two four-step paths across the non-polar Pbnm and Pnab phases are almost the same, and they are the lowest energies among all possible paths. Competition between these paths can help us understand complex phase transitions in analogous compounds. In summary, hybrid improper ferroelectricity was predicted in Sr3Hf2O7 for the first time, and the possible ferroelectric switching paths were determined.Hybrid improper ferroelectricity, which is induced by the coupling of oxygen octahedral rotation and tilt in oxide materials, has great potential to create single-phase multiferroic materials with intrinsic electric field-controlled magnetism. Based on previous experiments with bi-layered Ruddlesden-Popper Sr-based materials, hybrid improper ferroelectricity in Sr3Hf2O7 was investigated by first-principle calculations in the present work. The results show that the ferroelectric A21am phase has the lowest energy among all possible phases, indicating that it is the ground state. The spontaneous polarization calculated by the Berry phase approach and Born effective charge model is approximately 4.6 μC/cm2, in agreement with those reported for other Sr-based compounds. Compared to Ca3Ti2O7, the smaller polarization of Sr3Hf2O7 is attributed to the negative contribution of the HfO2 layer to global polarization. The possible ferroelectric switching path was determined using the nudged elastic band method. The e.
Detection Of

Audio deep is the next frontier for company compromise scams, and it's becoming more usual for crooks to get access to corporate funds through deception. With the popularity and capability of audio deep fakes growing, it's more critical than ever to develop defences against deep fakes used for nefarious purposes. The goal is implemented using Python and the CNN technique. The model is fed an image dataset of a frequency analysis audio sample. The model uses visual representations of audio clips, which are then fed into resnet34 and trained to achieve accurate accuracy, to distinguish between real and fake audio. Recent breakthroughs in deep learning and other related fields.
Astragaloside IV relieves IL-1β-induced human nucleus pulposus cells degeneration through modulating PI3K/Akt signaling pathway

Background: Intervertebral disc degeneration (IDD) is a multifactorial disease that is associated with nucleus pulposus (NP) apoptosis and extracellular matrix (ECM) degeneration and inflammation. Astragaloside IV (AS IV) has antioxidant, free radical scavenging, anti-inflammatory and anti-apoptosis effects. This study was to investigate whether AS IV could inhibit IL-1β-mediated apoptosis of HNP cells and its possible signal transduction pathway. Methods: Human nucleus pulposus cells (HNPCs) were stimulated with AS IV or LY294002 (PI3K inhibitor), followed by exposure to IL-1β for 24 hours. CCK8, TUNEL analysis and flow cytometry, ELISA and Western blotting were used to analyze the effects of AS IV on cell proliferation, apoptosis, inflammation, ECM and PI3K/Akt pathway signaling path-related proteins in IL-1β-induced HNPCs. Results: Compared with IL-1β-induced HNPCs, AS IV could improve the proliferation activity and the expressions of Collagen II, Aggrecan and Bcl-2 proteins, inhibit the apoptosis rate, inflammation and Bax and cleaved caspase-3 protein expression, and increase the activity of PI3K/Akt pathway. LY294002 attenuated the protective effect of AS IV against IL-1β-induced HNPCs degeneration. Conclusion: AS IV can inhibit IL-1β-induced HNPCs apoptosis inflammation and ECM degeneration by activating PI3K/Akt signaling pathway, which can be an effective drug to reduce disc degeneration.
Consistency Based Weakly Self-Supervised Learning for Human Activity Recognition with Wearables

While the widely available embedded sensors in smartphones and other wearable devices make it easier to obtain data of human activities, recognizing different types of human activities from sensor based data, remains a difﬁcult research topic in ubiquitous computing. One reason for this ismost of the col-lecteddata is unlabeled. However,many current human activity recognition (HAR) systems are based onsupervised meth-ods, which heavily rely on the labels of the data. We describe a weakly self-supervised approach in this paper that consists of two stages: (1) In stage one, the model learns from the nature of human activitiesby projecting the datainto an embed-dingspace where similar activities are grouped together; (2) In stage two, the model is ﬁne-tuned using similarity information in a few-shot learning fashion using the similarity information of the data. This allows downstreamclassiﬁcation or clustering tasksto beneﬁt from the embeddings. Experiments on three benchmark datasets demonstrate the framework’s effectiveness and show that our approach can help the clustering algorithm achievecomparable performance in identifying and categorizing the underlying human activities as pure supervised techniques applied directly to a corresponding fully labeled data set.
Developing and Evaluating Complex Interventions: New Guidance

Peter Craig, MRC Population Health Sciences Research Network Paul Dieppe, Nuffield Department of Orthopaedic Surgery, University of Oxford Sally Macintyre, MRC Social and Public Health Sciences Unit Susan Michie, Centre for Outcomes Research and Effectiveness, University College London Irwin Nazareth, MRC General Practice Research Framework Mark Petticrew, Department of Public Health and Policy, London School of Hygiene and Tropical Medicine
Coal Quality Exploration Technology Based on an Incremental Multilayer Extreme Learning Machine and Remote Sensing Images

This paper proposes a new coal quality exploration method that detects coal quality in coal mining areas and explores and monitors the distribution and change of coal through remote sensing images. First, we collected a large number of coal and noncoal samples such as sandstones, shales, and coal gangues. Second, we measured the actual spectral data of these samples using a spectrometer. For coal mines, we used the chemical analysis method to quantify coal’s fixed carbon and categorize the coal mines into three types based on the fixed carbon content present in coal. Third, we collected satellite remote sensing images of coal mining areas and established spectral data relations between the measured spectral data of the samples and the remote sensing images. Fourth, we proposed an incremental multilayer learning machine algorithm and used the algorithm combined with spectral data to build a coal quality classification model to identify coal quality in remote sensing images. Finally, the model accurately described the distribution map of coal quality. Compared with traditional coal exploration methods, this method has the advantages of high speed, high accuracy, and low price.