Search results for: meta learning

Authors: Isabella Lobo Sasaoka, Felipe Q. da Luz, Zubeyir Salis, Phillipa Hay, Tamiris Gaeta, Paula Costa Teixeira, Táki Cordás, Amanda Sainsbury

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Background: A significant number of people with obesity that seek weight loss treatments experience binge eating episodes. Nonetheless, it is unknown whether binge eating episodes can hinder weight loss outcomes. Objective: To compare weight change in people with or without binge eating submitted to bariatric surgery, pharmacotherapy, nutritional orientation, and/or psychological therapies. Method: We conducted a systematic review with meta-analyses by searching studies in PubMed, American Psychological Association (APA), and Embase. Results: Thirty-four studies were included in our systematic review, and 17 studies were included in the meta-analyses. Overall, we found no significant difference in weight loss between people with or without binge eating submitted to any type of weight loss treatment. Additionally, we found no statistically significant differences in body weight between people with or without binge eating at short and long follow-up assessments following any type of weight loss treatment. We also examined changes in body weight in people with or without binge eating in three additional meta-analyses categorized by the type of weight loss treatment (i.e., behavioural and/or nutritional interventions; bariatric surgery; pharmacotherapy isolated or combined with behavior interventions) and found no difference in weight loss. Eleven out of the 17 studies that were assessed qualitatively (i.e., not included in meta-analyses) did not show differences in weight loss in people with or without binge eating submitted to any type of weight loss treatment. Conclusion: This systematic review with meta-analyses showed no difference in weight loss in people with or without binge eating submitted to a variety of weight loss treatments. Nonetheless, specialized therapies can be required to address eating disorder psychopathology and recurrent binge eating in people with obesity that seek weight loss.

Keywords: obesity, binge eating, weight loss, systematic review, meta-analysis

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Authors: Sadeq Al Yaari, Muhammad Alkhunayn, Montaha Al Yaari, Ayman Al Yaari, Aayah Al Yaari, Adham Al Yaari, Sajedah Al Yaari, Fatehi Eissa

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Background: In spite of the fact that several language deficits, both internalizing and externalizing, have been documented in comorbidity with Asperger Syndrome (AS) and High Functioning Autism (HFA), there is a paucity of the continuity of these deficits in these individuals’ life span. Furthermore, findings regarding differences in the occurrence of these language deficits both in HFA and AS males and females are mixed. Aims: Systematic Literature Review and meta-analysis (SLR & Meta-analysis) provides a more valid indicator; that is why it has been used here to distinguish HFA and AS individuals in terms of (a) When does language deficits prevails in these individuals’ life and (b) in which gender the prevalence of these language deficits is seen more. Materials and Method: In this SLR & Meta-analysis, PubMed, ScienceDirect, SpringerLink, SAGE journals online, WILEY online library, Google Scholar, CINAHL, EMBASE, Scopus, and ERIC databases in addition to unpublished literature were systematically searched between 1st of January 1980 and 30th of May 2022. Interpretations: Although overall sample sizes were small, the combined results do permit the tentative conclusion that prevalence of language deficits both in AS and HFA children and adults with more prevalence of phonological deficit in HFA male children and pragmatic deficits in AS male children. Further research should be separately undertaken in each linguistic branch to verify the occlusions of this study.

Keywords: high-functioning autism, Asperger syndrome, systematic literature review, meta-analysis

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Authors: Ouzayr Rabhi, Ibtissam Arrassen

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To provide a complete analysis of the organization and to help decision-making, leaders need to have relevant data; Data Warehouses (DW) are designed to meet such needs. However, designing DW is not trivial and there is no formal method to derive a multidimensional schema from heterogeneous databases. In this article, we present a Model-Driven based approach concerning the design of data warehouses. We describe a multidimensional meta-model and also specify a set of transformations starting from a Unified Modeling Language (UML) metamodel. In this approach, the UML metamodel and the multidimensional one are both considered as a platform-independent model (PIM). The first meta-model is mapped into the second one through transformation rules carried out by the Query View Transformation (QVT) language. This proposal is validated through the application of our approach to generating a multidimensional schema of a Balanced Scorecard (BSC) DW. We are interested in the BSC perspectives, which are highly linked to the vision and the strategies of an organization.

Keywords: data warehouse, meta-model, model-driven architecture, transformation, UML

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Authors: Hanady Hamdallah, H. Elyse Ireland, John H. H. Williams

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Conjugated linoleic acid (CLA) is a food supplement that is reported to have multiple beneficial health effects, including being anti-carcinogenic, anti-inflammatory and anti-obesity. Animal studies have shown a significant anti-obesity effect of CLA, but results in humans were inconsistent, where some of the studies found an anti-obesity effect while other studies failed to find any decline in obesity markers after CLA supplementation. This meta-analysis aimed to determine if oral CLA supplementation has been shown to reduce obesity related markers in women. Pub Med, Cochrane Library, and Google Scholar were used to identify the eligible trials using two main searching strategies: the first one was to search eligible trials using keywords 'Conjugated linoleic acid', 'CLA', 'Women', and the second strategy was to extract the eligible trials from previously published systematic reviews and meta-analyses. The eligible trials were placebo control trials where women supplemented with CLA mixture in the form of oral capsules for 6 months or less. Also, these trials provided information about body composition expressed as body weight (BW), body mass index (BMI), total body fat (TBF), percentage body fat (BF %), and/ or lean body mass (LBM). The quality of each included study was assessed using both JADAD scale and an adapted CONSERT checklist. Meta-analysis of 8 eligible trials showed that CLA supplementation was significantly associated with reduced BW (Mean ± SD, 1.2 ± 0.26 kg, p < 0.001), BMI (0.6 ± 0.13kg/m², p < 0.001) and TBF (0.76 ± 0.26 kg, p= 0.003) in women, when supplemented over 6-16 weeks. Subgroup meta-analysis demonstrated a significant reduction in BW (1.29 ± 0.31 kg, p < 0.001), BMI (0.60 ± 0.14 kg/m², p < 0.001) and TBF (0.82 ± 0.28 kg, p= 0.003) in the trials that had recruited overweight-obese women. The second subgroup meta-analysis, that considered the menopausal status of the participants, found that CLA was significantly associated with reduced BW (1.35 ± 0.37 kg, p < 0.001; 1.05 ± 0.36 kg, p= 0.003) and BMI (0.50 ± 0.17 kg/m², p= 0.003; 0.75 ± 0.2 kg/m², p < 0.001) in both pre and post-menopausal age women, respectively. A reduction in TBF (1.09 ± 0.37 kg, p= 0.003) was only significant in post-menopausal women. Interestingly, CLA supplementation was associated with a significant reduction in BW (1.05 ± 0.35 kg, p< 0.003), BMI (0.73 ± 0.2 kg/m², p < 0.001) and TBF (1.07 ± 0.36 kg, p= 0.003) in the trials without lifestyle monitoring or interventions. No significant effect of CLA on LBM was detected in this meta-analysis. This meta-analysis suggests a moderate anti-obesity effect of CLA on BW, BMI and TBF reduction in women, when supplemented over 6-16 weeks, particularly in overweight-obese women and post-menopausal women. However, this finding requires careful interpretation due to several issues in the designs of available CLA supplementation trials. More well-designed trials are required to confirm this meta-analysis results.

Keywords: body composition, body mass index, body weight, conjugated linoleic acid

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Authors: K. M. Shahunja, Peter D. Sly, Tahmina Begum, Tuhin Biswas, Abdullah Mamun

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Background: Various associations between different environmental exposures and asthma have been reported in different countries and populations. We aimed to investigate the associations between family, neighbourhood, and psychosocial environmental factors and asthma in Australia by conducting a systematic review and meta-analysis. Methods: We analysed the primary research studies conducted in Australia across multiple databases, including PubMed, EMBASE, and Scopus, and published between 2000 and 2020. The reviews and analyses focused on the overall association of different environmental exposures with the development or exacerbation of asthma symptoms or asthma-related hospital visits. Quality-effect meta-analysis was done to estimate the pooled odds ratio for different environmental exposures for asthma symptoms. Findings: Among the 4,799 unique published articles found, 46 were included here for systematic review and 28 for meta-analysis. Our review found that psychosocial factors, including low socioeconomic condition, maternal depression, mental stress, ethnicity, and discrimination, are associated with asthma symptoms. Pooled analysis was conducted on family and neighbourhood environmental factors and revealed that environmental tobacco smoking (ETS) (OR 1·69, 95% CI 1·19–2.38), synthetic bedding (OR 1·91, 95% CI 1·48–2·47) and gas heaters (OR 1·40, 95% CI 1·12–1·76) had significant overall associations with asthma-symptoms in Australia. Conclusion: Although the studies were heterogeneous, both systematic review and meta-analysis found several psychosocial and family environmental exposures to be significantly associated with asthma symptoms. Further study to identify their causal relationship and modification may reduce asthma symptoms in the Australian population.

Keywords: asthma, Australia, environment, systematic review

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Authors: Sadeq Al Yaari, Muhammad Alkhunayn, Ayman Al Yaari, Montaha Al Yaari, Aayah Al Yaari, Adham Al Yaari, Sajedah Al Yaari, Fatehi Eissa

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Stuttering is a multidimensional disorder that is influenced by different factors. As a result of their un-understanding of the genuine reasons behind stuttering, psychiatrists and Speech and Language Pathologists/Therapists (SLP/Ts) are often unfamiliar with the psychoneurolinguistic characteristics, support needs, and the disability measurement impacting requested rehabilitation of the stuttering population. PubMed, PsycInfo, Web of Science, Scopus, and Google scholar searches, in addition to some unpublished literature, were conducted in this Systematic Literature Review and Meta-analysis (SLR and Meta-analysis) to identify whether stuttering is caused by psychological or neurological reasons. The study concluded that psychological, not neurolinguistic factors were identified as most significant for the causality of childhood stuttering. Stutterers have intact language skills, but impaired ability more to communicate with others than to form letters in the brain or to articulate them. The study recommends research in the future that sheds light on the adult stuttering population often left out of the focus of diagnosis and in need of further exploration vis-a-vis issues they encounter, as well as the possible ways to deal with them psychoneurolinguistically.

Keywords: causality, childhood stuttering, psychology, neurolinguistics, systematic literature review, meta-analysis

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Authors: Ammar Aljabri, Alhussain Halawani, Alaa Ashqar, Omar Alageely

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Objective: mild Traumatic Brain Injury (mTBI) or concussion is a common yet undermanaged and underreported condition. This systematic review and meta-analysis aim to determine the efficacy of VRT as a treatment option for mTBI. Method: This review and meta-analysis was performed following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and included RCTs and pre-VRT/post-VRT retrospective chart reviews. Records meeting the inclusion criteria were extracted from the following databases: Medline, Embase, and Cochrane Register of Controlled Trials (CENTRAL). Results: Eight articles met the inclusion criteria, and six RCTs were included in the meta-analysis. VRT demonstrated significant improvement in decreasing perceived dizziness at the end of the intervention program, as shown by DHI scores (SMD= -0.33, 95% CI -0.62 to -0.03, p=0.03, I2= 0%). However, no significant reduction in DHI was evident after two months of follow-up (SMD= 0.15, 95% CI -0.23 to 0.52, p=0.44, I2=0%). Quantitative analysis also depicts significant reduction in both VOMS (SMD=-0.40, 95% CI -0.60 to -0.20, p<0.0001, I2=0%) and PCSS (SMD= -0.39, 95% CI -0.71 to -0.07, p=0.02, I2=0%) following the intervention. Lastly, there was no significant difference between intervention groups on BESS scores (SMD= -31, 95% CI -0.71 to 0.10, p=0.14, I2=0%) and return to sport/function (95% CI 0.32 to 30.80, p=0.32, I2=82%). Conclusions: Current evidence on the efficacy of VRT for mTBI is limited. This review and analysis provide evidence that supports the role of VRT in improving perceived symptoms following concussion. There is still a need for high-quality trials evaluating the benefit of VRT using a standardized approach.

Keywords: concussion, traumatic brain injury, vestibular rehabilitation, neurorehabilitation

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Authors: Parsa Mahdavi, M. Amin Hariri-Ardebili

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The development of accurate machine learning and deep learning models traditionally demands hands-on expertise and a solid background to fine-tune hyperparameters. With the continuous expansion of datasets in various scientific and engineering domains, researchers increasingly turn to machine learning methods to unveil hidden insights that may elude classic regression techniques. This surge in adoption raises concerns about the adequacy of the resultant meta-models and, consequently, the interpretation of the findings. In response to these challenges, automated machine learning (AutoML) emerges as a promising solution, aiming to construct machine learning models with minimal intervention or guidance from human experts. AutoML encompasses crucial stages such as data preparation, feature engineering, hyperparameter optimization, and neural architecture search. This paper provides a comprehensive overview of the principles underpinning AutoML, surveying several widely-used AutoML platforms. Additionally, the paper offers a glimpse into the application of AutoML on various engineering datasets. By comparing these results with those obtained through classical machine learning methods, the paper quantifies the uncertainties inherent in the application of a single ML model versus the holistic approach provided by AutoML. These examples showcase the efficacy of AutoML in extracting meaningful patterns and insights, emphasizing its potential to revolutionize the way we approach and analyze complex datasets.

Keywords: automated machine learning, uncertainty, engineering dataset, regression

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Authors: Brian Kristopher Cambra

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Millions of displaced families are seeking refuge in countries that are not their own due to war, violence, persecution, political unrest, and natural disasters. This global crisis is forcing researchers and practitioners to consider how refugees are coping with the trauma associated with their migration process. Effective therapeutic approaches are needed in a global effort to address the traumatic impact of forced migration. This meta-analytical study investigates the effectiveness of expressive therapeutic modalities, including play, art, music, sandplay, theatre, and writing therapies, in helping children and adolescents cope with refugee trauma. Seventeen pre-post and between-group comparison studies were analyzed using a random-effects model. The combined effect size for pre-post comparisons was medium (g = 0.58), whereas the combined effect size for between-group comparisons was small (g = 0.32). Overall, art therapy was found to be most effective in treating stress symptoms. Heterogeneity tests, however, suggest effect sizes cannot be interpreted as meaningful due to substantial variance. Nevertheless, findings of this meta-analysis indicate that expressive therapies may be among beneficial modalities to integrate with other trauma-informed approaches.

Keywords: expressive therapies, forced migration, meta-analysis, refugees, trauma

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Authors: Urwah Ali

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The aim of this study is to carry out a meta-analysis in order to establish an overall international figure and to summarize the evidence relating to the possible relationship between child sexual abuse and subsequent mental and physical health outcomes. A systematic review was conducted using the HEC Digital Library, Pub Med, PsycINFO and SAHIL databases published after 2010 containing empirical data pertaining to CSA. Out of 124 articles assessed for eligibility, 32 studies provided evidence of a relationship between sexual child maltreatment and various health outcomes for use in subsequent meta-analyses. Statistical significance associations were observed between childhood sexual victimization and psychological problems in their adulthood [odds ratio (OR) = 1.5; 95%Cl 3.07–4.43]. For most studies included for meta-analysis, the odds ratio falls above 1.00, indicating that patients having history of childhood sexual victimization were more likely to develop psychological disorders.

Keywords: abuse, sexual abuse, childhood sexual abuse, mental health

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Authors: Hongxin Zhao, Shibing Yang, Bingming Yi, Yi Ning

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Background: A few studies have found evidence that exposure to endogenous or postmenopausal exogenous estrogens may be associated with a lower prevalence of age-related macular degeneration (AMD), but dispute over this association is ongoing due to inconsistent results reported by different studies. Objectives: To conduct a systematic review and meta-analysis to investigate the association between hormone replacement therapy (HRT) use and AMD. Methods: Relevant studies that assessed the association between HRT and AMD were searched through four databases (PubMed, Web of Science, Cochrane Library, EMBASE) and reference lists of retrieved studies. Study selection, data extraction and quality assessment were conducted by three independent reviewers. The fixed-effect meta-analyses were performed to estimate the association between HRT ever-use and AMD by pooling risk ratio (RR) or odds ratio (OR) across studies. Results: The review identified 2 prospective and 7 cross-sectional studies with 93992 female participants that reported an estimate of the association between HRT ever-use and presence of early AMD or late AMD. Meta-analyses showed that there were no statistically significant associations between HRT ever-use and early AMD (pooled RR for cohort studies was 1.04, 95% CI 0.86 - 1.24; pooled OR for cross-sectional studies was 0.91, 95% CI 0.82 - 1.01). The pooled results from cross-sectional studies also showed no statistically significant association between HRT ever-use and late AMD (OR 1.01; 95% CI 0.89 - 1.15). Conclusions: The pooled effects from observational studies published to date indicate that HRT use is associated with neither early nor late AMD. Exposure to HRT may not protect women from developing AMD.

Keywords: hormone replacement therapy, age-related macular degeneration, meta-analysis, systematic review

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Authors: Kawthar F. Albasri, Abdullah M. AlHudaithi, Dana B. AlTurairi, Abdullaziz S. AlQuraini, Adoub Y. AlDerazi, Reem A. Hubail, Haitham A. Jahrami

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Several studies have found that medical students have a significant prevalence of anxiety. The purpose of this review paper is to carefully evaluate the current research on anxiety among medical students in the MENA region and, as a result, estimate the prevalence of these disturbances. Multiple databases, including the CINAHL (Cumulative Index to Nursing and Allied Health Literature), Cochrane Library, Embase, MEDLINE (Medical Literature Analysis and Retrieval System Online), PubMed, PsycINFO (Psychological Information Database), Scopus, Web of Science, UpToDate, ClinicalTrials.gov, WHO Global Health Library, EbscoHost, ProQuest, JAMA Network, and ScienceDirect, were searched. The retrieved article reference lists were rigorously searched and rated for quality. A random effects meta-analysis was performed to compute estimates. The current meta-analysis revealed an alarming estimated pooled prevalence of anxiety (K = 46, N = 27023) of 52.5% [95%CI: 43.3%–61.6%]. A total of 62.0% [95% CI 42.9%; 78.0%] of the students (K = 18, N = 16466) suffered from anxiety during the COVID-19 pandemic, while 52.5% [95% CI 43.3%; 61.6%] had anxiety before COVID-19. Based on the GAD-7 measure, a total of 55.7% [95%CI 30.5%; 78.3%] of the students (K = 10, N = 5830) had anxiety, and a total of 54.7% of the students (K = 18, N = 12154) [95%CI 42.8%; 66.0%] had anxiety using the DASS-21 or 42 measure. Anxiety is a common issue among medical students, making it a genuine problem. Further research should be conducted post-COVD 19, with a focus on anxiety prevention and intervention initiatives for medical students.

Keywords: anxiety, medical students, MENA, meta-analysis, prevalence

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Authors: S. Boria

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In the last years, the crashworthiness of an automotive body structure can be improved, since the beginning of the design stage, thanks to the development of specific optimization tools. It is well known how the finite element codes can help the designer to investigate the crashing performance of structures under dynamic impact. Therefore, by coupling nonlinear mathematical programming procedure and statistical techniques with FE simulations, it is possible to optimize the design with reduced number of analytical evaluations. In engineering applications, many optimization methods which are based on statistical techniques and utilize estimated models, called meta-models, are quickly spreading. A meta-model is an approximation of a detailed simulation model based on a dataset of input, identified by the design of experiments (DOE); the number of simulations needed to build it depends on the number of variables. Among the various types of meta-modeling techniques, Kriging method seems to be excellent in accuracy, robustness and efficiency compared to other ones when applied to crashworthiness optimization. Therefore the application of such meta-model was used in this work, in order to improve the structural optimization of a bumper for a racing car in composite material subjected to frontal impact. The specific energy absorption represents the objective function to maximize and the geometrical parameters subjected to some design constraints are the design variables. LS-DYNA codes were interfaced with LS-OPT tool in order to find the optimized solution, through the use of a domain reduction strategy. With the use of the Kriging meta-model the crashworthiness characteristic of the composite bumper was improved.

Keywords: composite material, crashworthiness, finite element analysis, optimization

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Authors: Konstantinos Sofianos, Michael Stefanidakis

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Nowadays, advances in information and communication technologies offer a range of opportunities for new approaches, methods, and tools in the field of education and training. Teacher-centered learning has changed to student-centered learning. E-learning has now matured and enables the design and construction of intelligent learning systems. A smart learning system fully adapts to a student's needs and provides them with an education based on their preferences, learning styles, and learning backgrounds. It is a wise friend and available at any time, in any place, and with any digital device. In this paper, we propose an intelligent learning system, which includes an ontology with all elements of the learning process (learning objects, learning activities) and a massive open online course (MOOC) system. This intelligent learning system can be used in music education.

Keywords: intelligent learning systems, e-learning, music education, ontology, semantic web

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Authors: Simin Zarea Karizi, Somaye Fatahi, Amirhossein Hosseni

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Background: There are conflicting findings regarding the effect of vitamin D supplementation on obesity-related factors. This study aimed to investigate the effect of vitamin D supplementation on changes in anthropometric indicators of adiposity and fat distribution in children and adolescents. Methods: Original databases were searched using standard keywords to identify all controlled trials investigating the effects of vitamin D supplementation on obesity-related factors in children and adolescents. Pooled weighted mean difference and 95% confidence intervals were achieved by random-effects model analysis. Results: Fourteen treatment arms were included in this systematic review and meta-analysis. The quantitative meta-analysis revealed no significant effect of vitamin D supplement on BMI (-0.01 kg/m2; 95% CI: -0.09, 0.12; p= 0.74; I2=0.0%), BMI z score (0.02; 95% CI: -0.04, 0.07; p= 0.53; I2=0.0%) and fat mass (0.07%; 95% CI: -0.09 to 0.24; p= 0.38; I2=31.2%). However, the quantitative meta-analysis displayed a significant effect of vitamin D supplementation on WC compared with the control group (WMD=-1.17 cm, 95% CI: -2.05, -0.29, p=0.009; I2=32.0 %). It seems that this effect was greater in healthy children with duration>12 weeks, dose<=400 IU and baseline less than 50 nmol/l vitamin D than others. Conclusions: Our findings suggest that vitamin D supplementation may be a protective factor of abdominal obesity and should be evaluated on an individual basis in clinical practice.

Keywords: weight loss, vitamin D, anthropometry, children, adolescent

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Authors: Daniela V. Bavaresco, Tamy Colonetti, Antonio Jose Grande, Francesc Colom, Joao Quevedo, Samira S. Valvassori, Maria Ines da Rosa

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Objective: Performed a systematic review and meta-analysis to evaluated the potential effect of the cyclo-oxygenases (Cox)-2 inhibitor Celecoxib adjunct treatment in Bipolar Disorder (BD), through of randomized controlled trials. Method: A search of the electronic databases was proceeded, on MEDLINE, EMBASE, Scopus, Cochrane Central Register of Controlled Trials (CENTRAL), Biomed Central, Web of Science, IBECS, LILACS, PsycINFO (American Psychological Association), Congress Abstracts, and Grey literature (Google Scholar and the British Library) for studies published from January 1990 to February 2018. A search strategy was developed using the terms: 'Bipolar disorder' or 'Bipolar mania' or 'Bipolar depression' or 'Bipolar mixed' or 'Bipolar euthymic' and 'Celecoxib' or 'Cyclooxygenase-2 inhibitors' or 'Cox-2 inhibitors' as text words and Medical Subject Headings (i.e., MeSH and EMTREE) and searched. The therapeutic effects of adjunctive treatment with Celecoxib were analyzed, it was possible to carry out a meta-analysis of three studies included in the systematic review. The meta-analysis was performed including the final results of the Young Mania Rating Scale (YMRS) at the end of randomized controlled trials (RCT). Results: Three primary studies were included in the systematic review, with a total of 121 patients. The meta-analysis had significant effect in the YMRS scores from patients with BD who used Celecoxib adjuvant treatment in comparison to placebo. The weighted mean difference was 5.54 (95%CI=3.26-7.82); p < 0.001; I2 =0%). Conclusion: The systematic review suggests that adjuvant treatment with Celecoxib improves the response of major treatments in patients with BD when compared with adjuvant placebo treatment.

Keywords: bipolar disorder, Cox-2 inhibitors, Celecoxib, systematic review, meta-analysis

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Authors: Christian Angerer, Markus Lienkamp

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Electric vehicles offer a high variety of possible drivetrain topologies with up to 4 motors. Multi-motor-designs can have several advantages regarding traction, vehicle dynamics, safety and even efficiency. With a rising number of motors, the whole drivetrain becomes more complex. All permutations of gearings, drivetrain-layouts, motor-types and –sizes lead up in a very large solution space. Single elements of this solution space can be analyzed by simulation methods. In addition to longitudinal vehicle behavior, which most optimization-approaches are restricted to, also lateral dynamics are important for vehicle dynamics, stability and efficiency. In order to compete large solution spaces and to find an optimal result, genetic algorithm based optimization is state-of-the-art. As lateral dynamics simulation is way more CPU-intensive, optimization takes much more time than in case of longitudinal-only simulation. Therefore, this paper shows an approach how to create meta-models from a 14-degree of freedom vehicle model in order to enable a numerically efficient drivetrain-layout optimization process under consideration of lateral dynamics. Different meta-modelling approaches such as neural networks or DoE are implemented and comparatively discussed.

Keywords: driving dynamics, drivetrain layout, genetic optimization, meta-modeling, lateral dynamicx

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Authors: Ksenia Meshkova

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With increasing amount of multimedia data, it is very important to automate and speed up the process of obtaining meta. This process means not just recognition of some object or its movement, but recognition of the entire scene versus separate frames and having timeline segmentation as a final result. Labeling datasets is time consuming, besides, attributing characteristics to particular scenes is clearly difficult due to their nature. In this article, we will consider autoencoders application to unsupervised scene recognition and clusterization based on interpretable features. Further, we will focus on particular types of auto encoders that relevant to our study. We will take a look at the specificity of deep learning related to information theory and rate-distortion theory and describe the solutions empowering poor interpretability of deep learning in media content processing. As a conclusion, we will present the results of the work of custom framework, based on autoencoders, capable of scene recognition as was deeply studied above, with highlights generation resulted out of this recognition. We will not describe in detail the mathematical description of neural networks work but will clarify the necessary concepts and pay attention to important nuances.

Keywords: neural networks, computer vision, representation learning, autoencoders

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Authors: Ran An, Dang Wang

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Background: Mechanical ventilation has been confirmed to increase the incidence of postoperative pulmonary complications (PPCs), and several studies have shown that low tidal volumes combined with positive end-expiratory pressure (PEEP) and recruitment manoeuvres (RM) reduce the incidence of PPCs. However, the optimal lung-protective ventilatory strategy remains unclear. Methods: Multiple databases were searched for randomized controlled trials (RCTs) published prior to October 2023. The association between individual PEEP (iPEEP) or other forms of lung-protective ventilation and the incidence of PPCs was evaluated by Bayesian network meta-analysis. Results: We included 58 studies (11610 patients) in this meta-analysis. The network meta-analysis showed that low ventilation (LVt) combined with iPEEP and RM was associated with significantly lower incidences of PPCs [HVt: OR=0.38 95CrI (0.19, 0.75), LVt: OR=0.33, 95% CrI (0.12, 0.82)], postoperative atelectasis, and pneumonia than was HVt or LVt. In abdominal surgery, LVT combined with iPEEP or medium-to-high PEEP and RM were associated with significantly lower incidences of PPCs, postoperative atelectasis, and pneumonia. LVt combined with iPEEP and RM was ranked the highest, which was based on SUCRA scores. Conclusion: LVt combined with iPEEP and RM decreased the incidences of PPCs, postoperative atelectasis, and pneumonia in noncardiac surgery patients. iPEEP-guided ventilation was the optimal lung protection ventilation strategy. The quality of evidence was moderate.

Keywords: protection ventilation strategies, postoperative pulmonary complications, network meta-analysis, noncardiac surgery

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Authors: Saransh Sharma, Atharv Dekhne

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Passwords stored on central services and hashed are prone to cyberattacks and hacks. Hence, given all these nuisances, there’s a need to eliminate character-based authentication protocols, which would ultimately benefit all developers as well as end-users.To replace this conventional but antiquated protocol with a secure alternative would be Passwordless Authentication. The meta root.id system creates a public and private key, of which the user is only able to access the private key. Further, after signing the key, the user sends the information over the API to the server, which checks its validity with the public key and grants access accordingly.

Keywords: passwordless, OAuth, bitcoin, ZKP, SIN, BIP

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Authors: Tzu-Hao Li, Yen-Ying Kung, Chang-Youh Tsai

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Oral dryness is a common chief complaint among patients with Sjőgren syndrome (SS), which is a disorder currently known as autoantibodies production; however, to author’s best knowledge, there has been no satisfying pharmacy to relieve the associated symptoms. Hence the effectiveness of other non-pharmacological interventions such as acupuncture should be accessed. We conducted a meta-analysis of randomized clinical trials (RCTs) which evaluated the effectiveness of xerostomia in SS. PubMed, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), Chongqing Weipu Database (CQVIP), China Academic Journals Full-text Database, AiritiLibrary, Chinese Electronic Periodicals Service (CEPS), China National Knowledge Infrastructure (CNKI) Database were searches through May 12, 2018 to select studies. Data for evaluation of subjective and objective xerostomia was extracted and was assessed with random-effects meta-analysis. After searching, a total of 541 references were yielded and five RCTs were included, covering 340 patients dry mouth resulted from SS, among whom 169 patients received acupuncture and 171 patients were control group. Acupuncture group was associated with higher subjective response rate (odds ratio 3.036, 95% confidence interval [CI] 1.828 – 5.042, P < 0.001) and increased salivary flow rate (weighted mean difference [WMD] 3.066, 95% CI 2.969 – 3.164, P < 0.001), as an objective marker. In addition, two studies examined IgG levels, which were lower in the acupuncture group (WMD -166.857, 95% CI -233.138 - -100.576, P < 0.001). Therefore, in the present meta-analysis, acupuncture improves both subjective and objective markers of dry mouth with autoantibodies reduction in patients with SS and is considered as an option of non-pharmacological treatment for SS.

Keywords: acupuncture, meta-analysis, Sjogren syndrome, xerostomia

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Authors: Lihong Wu, Raymond Young

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The ability to learn is one of the most critical skills in the information age. However, many students do not have a clear understanding of what learning is, what they are learning, and why they are learning. Many students study simply to pass rather than to learn something useful for their career and their life. They have a misconception about learning and a wrong attitude towards learning. This research explores student attitudes to study in management education and explores how to intercede to lead students from shallow to deeper modes of learning.

Keywords: knowledge, surface learning, deep learning, education

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Authors: Monika Chuchro

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This paper presents a preliminary attempt to apply classification of time series using meta-clusters in order to improve the quality of regression models. In this case, clustering was performed as a method to obtain a subgroups of time series data with normal distribution from inflow into waste water treatment plant data which Composed of several groups differing by mean value. Two simple algorithms: K-mean and EM were chosen as a clustering method. The rand index was used to measure the similarity. After simple meta-clustering, regression model was performed for each subgroups. The final model was a sum of subgroups models. The quality of obtained model was compared with the regression model made using the same explanatory variables but with no clustering of data. Results were compared by determination coefficient (R2), measure of prediction accuracy mean absolute percentage error (MAPE) and comparison on linear chart. Preliminary results allows to foresee the potential of the presented technique.

Keywords: clustering, data analysis, data mining, predictive models

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Authors: Mara J. Richman, Zsolt Unoka, Robert Dudas, Zsolt Demetrovics

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Borderline personality disorder (BPD) is characterized by deficits in emotion regulation and effective liability. Of this domain, ruminative behaviors have been considered a core feature of emotion dysregulation difficulties. Taking this into consideration, a meta-analysis was performed to assess how BPD symptoms correlate with rumination, while also considering clinical moderator variables such as comorbidity, GAF score, and type of BPD symptom and demographic moderator variables such as age, gender, and education level. Analysis of correlation across rumination domains for the entire sample revealed a medium overall correlation. When assessing types of rumination, the largest correlation was among pain rumination followed by anger, depressive, and anxious rumination. Furthermore, affective instability had the strongest correlation with increased rumination, followed by unstable relationships, identity disturbance, and self-harm/ impulsivity, respectively. Demographic variables showed no significance. Clinical implications are considered and further therapeutic interventions are discussed in the context of rumination.

Keywords: borderline personality disorder, meta-analysis, rumination, symptoms

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Authors: Abdulbaset Saad, Adel Younis, Zuomin Dong

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For design optimization with high-dimensional expensive problems, an effective and efficient optimization methodology is desired. This work proposes a series of modification to the Differential Evolution (DE) algorithm for solving computation Intensive Black-Box Problems. The proposed methodology is called Radial Basis Meta-Model Algorithm Assisted Differential Evolutionary (RBF-DE), which is a global optimization algorithm based on the meta-modeling techniques. A meta-modeling assisted DE is proposed to solve computationally expensive optimization problems. The Radial Basis Function (RBF) model is used as a surrogate model to approximate the expensive objective function, while DE employs a mechanism to dynamically select the best performing combination of parameters such as differential rate, cross over probability, and population size. The proposed algorithm is tested on benchmark functions and real life practical applications and problems. The test results demonstrate that the proposed algorithm is promising and performs well compared to other optimization algorithms. The proposed algorithm is capable of converging to acceptable and good solutions in terms of accuracy, number of evaluations, and time needed to converge.

Keywords: differential evolution, engineering design, expensive computations, meta-modeling, radial basis function, optimization

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Authors: Thomas Vlasak, Tanja Dujlociv, Alfred Barth

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Shift work is an essential element of modern labor, ensuring ideal conditions of service for today’s economy and society. Despite the beneficial properties, its impact on the neurobehavioral performance of exposed subjects remains controversial. This meta-analysis aims to provide first summarizing the effects regarding the association between shift work exposure and different cognitive functions. A literature search was performed via the databases PubMed, PsyINFO, PsyARTICLES, MedLine, PsycNET and Scopus including eligible studies until December 2020 that compared shift workers with non-shift workers regarding neurobehavioral performance tests. A random-effects model was carried out using Hedge’s g as a meta-analytical effect size with a restricted likelihood estimator to summarize the mean differences between the exposure group and controls. The heterogeneity of effect sizes was addressed by a sensitivity analysis using funnel plots, egger’s tests, p-curve analysis, meta-regressions, and subgroup analysis. The meta-analysis included 18 studies resulting in a total sample of 18,802 participants and 37 effect sizes concerning six different neurobehavioral outcomes. The results showed significantly worse performance in shift workers compared to non-shift workers in the following cognitive functions with g (95% CI): processing speed 0.16 (0.02 - 0.30), working memory 0.28 (0.51 - 0.50), psychomotor vigilance 0.21 (0.05 - 0.37), cognitive control 0.86 (0.45 - 1.27) and visual attention 0.19 (0.11 - 0.26). Neither significant moderating effects of publication year or study quality nor significant subgroup differences regarding type of shift or type of profession were indicated for the cognitive outcomes. These are the first meta-analytical findings that associate shift work with decreased cognitive performance in processing speed, working memory, psychomotor vigilance, cognitive control, and visual attention. Further studies should focus on a more homogenous measurement of cognitive functions, a precise assessment of experience of shift work and occupation types which are underrepresented in the current literature (e.g., law enforcement). In occupations where shift work is fundamental (e.g., healthcare, industries, law enforcement), protective countermeasures should be promoted for workers.

Keywords: meta-analysis, neurobehavioral performance, occupational psychology, shift work

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Authors: Hong Lu, Xin Chen, Zhengcheng Fan

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Prior research has claimed a close association between handwriting and mathematics attainment with the help of spatial cognition. However, the exact mechanism behind this relationship remains un-investigated. Focusing on visual-motor integration (VMI), one critical spatial skill, this meta-analysis aims to estimate the size of the handwriting- visual-motor integration relationship and examine the moderating effect of handwriting dimensions on the link. With a random effect model, a medium relation (r=.26, 95%CI [.22, .30]) between handwriting and VMI was summarized in 38 studies with 55 unique samples and 141 effect sizes. Findings suggested handwriting dimensions significantly moderated the handwriting- VMI relationship, with handwriting legibility showing a substantial correlation with VMI, but neither handwriting speed nor pressure. Identifying the essential relationship between handwriting legibility and VMI, this study adds to the literature about the key cognitive processing needs underlying handwriting, and spatial cognition thus highlights the cognitive mechanism regarding handwriting, spatial cognition, and mathematics performances.

Keywords: handwriting, visual-motor integration, legibility, meta-analysis

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Authors: Addisu Tadesse Sahile, Mussie Wubshet Teka, Solomon Muluken Ayehu

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Background: Diabetes is one of the common public health problems of the century that was estimated to affect one in a tenth of the world population by the year 2030, where diabetes ketoacidosis is one of its common acute complications. Objectives: The aim of this review was to assess the magnitude of diabetes ketoacidosis among patients with type 1 diabetes in Ethiopia. Methods: A systematic data search was done across Google Scholar, PubMed, Web of Science, and African Online Journals. Two reviewers carried out the selection, reviewing, screening, and extraction of the data independently by using a Microsoft Excel Spreadsheet. The Joanna Briggs Institute's prevalence critical appraisal tool was used to assess the quality of evidence. All studies conducted in Ethiopia that reported diabetes ketoacidosis rates among type 1 diabetes were included. The extracted data was imported into the comprehensive meta-analysis version 3.0 for further analysis. Heterogeneity was checked by Higgins’s method, whereas the publication bias was checked by using Beggs and Eggers’s tests. A random-effects meta-analysis model with a 95% confidence interval was computed to estimate the pooled prevalence. Furthermore, subgroup analysis based on the study area (Region) and the sample size was carried out. Result and Conclusion: After review made across a total of 51 articles, of which 12 articles fulfilled the inclusion criteria and were included in the meta-analysis. The pooled prevalence of diabetes ketoacidosis among type 1 diabetes in Ethiopia was 53.2% (95%CI: 43.1%-63.1%). The highest prevalence of DKA was reported in the Tigray region of Ethiopia, whereas the lowest was reported in the Southern region of Ethiopia. Concerned bodies were suggested to work on the escalated burden of diabetes ketoacidosis in Ethiopia.

Keywords: DKA, Type 1 diabetes, Ethiopia, systematic review, meta-analysis

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Authors: Lee Bih Ni

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This paper discusses that good learning involves all academic groups in the school. Blended learning is learning outside the classroom. Google Classroom is a free service learning app for schools, non-profit organizations and anyone with a personal Google account. Facilities accessed through computers and mobile phones are very useful for school teachers and students. Blended learning classrooms using both traditional and technology-based methods for teaching have become the norm for many educators. Using Google Classroom gives students access to online learning. Even if the teacher is not in the classroom, the teacher can provide learning. This is the supervision of the form of the teacher when the student is outside the school.

Keywords: blended learning, learning app, google classroom, schools

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Authors: Hande Aladağ, Gökçe Aydın

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The world’s population is increasing continuously and rapidly. Moreover, there are other problems such as the decline of natural energy resources, global warming, and environmental pollution. These facts have made sustainability an important and primary topic from future planning perspective. From this perspective, constituting sustainable cities and communities can be considered as one of the key issues in terms of sustainable development goals. The concept of sustainable cities can be evaluated under three headings such as green/sustainable buildings, self – contained cities and sustainable transportation. This study only concentrates on how to form and support a sustainable urban transportation system to contribute to the sustainable urbanization. Urban transportation system inevitably requires many engineering projects with various sizes. Engineering projects generally have four phases, in the following order: Planning, design, construction, operation. The order is valid but there are feedbacks from every phase to every phase in its upstream. In this regard, engineering projects are iterative processes. Sustainability is an integrated and comprehensive concept thus it should be among the primary concerns in every phase of transportation projects. In the study, a meta-analysis will be performed on the related studies in the literature. It is targeted and planned that, as a result of the findings of this meta-analysis, a framework for the list of principles and actions for sustainable transport will be formed. The meta-analysis will be performed to point out and clarify sustainability approaches in every phase of the related engineering projects, with also paying attention to the iterative nature of the process and relative contribution of the action for the outcomes of the sustainable transportation system. However, the analysis will not be limited to the engineering projects, non-engineering solutions will also be included in the meta-analysis. The most important contribution of this study is a determination of the outcomes of a sustainable urban transportation system in terms of energy efficiency, resource preservation and related social, environmental and economic factors. The study is also important because it will give light to the engineering and management approaches to achieve these outcomes.

Keywords: meta-analysis, sustainability, sustainable cities, sustainable urban transportation, urban transportation

Procedia PDF Downloads 330