Search results for: assessment criteria framework

Authors: Azeez Balogun

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Inexperienced building score practices are continually evolving and vary across areas. Yet, a few middle ideas stay steady, such as website selection, design, energy efficiency, water and material conservation, indoor environmental great, operational optimization, and waste discount. The essence of green building lies inside the optimization of 1 or more of those standards. This paper conducts a comparative analysis of 7 extensively recognized sustainable score structures—BREEAM, CASBEE, green GLOBES, inexperienced superstar, HK-BEAM, IGBC green homes, and LEED—based totally on the perceptions and opinions of stakeholders in Nigeria certified in green constructing rating systems. The purpose is to pick out and adopt an appropriate green building rating device for Nigeria. Numerous components of those systems had been tested to determine the high-quality health of the Nigerian built environment. The findings imply that LEED, the important machine within the USA and Canada, is the most suitable for Nigeria due to its sturdy basis, extensive funding, and confirmed blessings. LEED obtained the highest rating of eighty out of one hundred points on this assessment.

Keywords: structure, built surroundings, inexperienced building score gadget, Nigeria Inexperienced Constructing Council, sustainability

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Authors: Lars Hornuf, Valeriia Khlopchyk

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The labor market is experiencing a significant transformation as traditional employment is being progressively supplemented or replaced by temporary, platform-mediated work. However, the full extent and impact of this shift remain not fully measured yet. In this study, we explore the size and dynamics of the crowdworking industry. Most existing studies on the number and earnings of crowdworkers are based on surveys and interviews and can be subject to reporting bias. To overcome this limitation, we adopt a hard data approach by leveraging data from multiple online platforms to provide a more comprehensive and unbiased assessment of the crowdworking industry. We estimate the number of crowdworkers, crowdworking platform revenues, and crowdworkers earnings. Additionally, we analyze the existing labor relationships and tax implications in the crowdworking industry. Our findings indicate that the number of crowdworkers shows a substantial annual growth of 11.28%. Furthermore, our study estimates the revenues of crowdworking platforms and the earnings of crowdworkers showing consistent annual growth, which demonstrates the shift in perception from crowdwork being a supplementary income to a primary source of income. We also reveal that most crowdworkers are classified as independent contractors and are solely responsible for taxation, highlighting the lack of labor protection for crowdworkers and the challenges for tax authorities in tracking taxation and recovering unpaid taxes.

Keywords: crowdsourcing, online labor, platform economy, online work, labor supply

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Authors: Jummalla Aashrith, N. L. Shiva Sai, K. Bhavya Sri

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The swift progress of web technology has not only amassed a vast reservoir of internet data but also triggered a substantial surge in data generation. The internet has metamorphosed into one of the dynamic hubs for online education, idea dissemination, as well as opinion-sharing. Notably, the widely utilized social networking platform Twitter is experiencing considerable expansion, providing users with the ability to share viewpoints, participate in discussions spanning diverse communities, and broadcast messages on a global scale. The upswing in online engagement has sparked a significant curiosity in subjective analysis, particularly when it comes to Twitter data. This research is committed to delving into sentiment analysis, focusing specifically on the realm of Twitter. It aims to offer valuable insights into deciphering information within tweets, where opinions manifest in a highly unstructured and diverse manner, spanning a spectrum from positivity to negativity, occasionally punctuated by neutrality expressions. Within this document, we offer a comprehensive exploration and comparative assessment of modern approaches to opinion mining. Employing a range of machine learning algorithms such as Naive Bayes and Logistic Regression, our investigation plunges into the domain of Twitter data streams. We delve into overarching challenges and applications inherent in the realm of subjectivity analysis over Twitter.

Keywords: machine learning, sentiment analysis, visualisation, python

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Authors: Eleni Giouli

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Distance learning provides a flexible approach to education, enabling busy learners to complete their coursework at their own pace, on their own schedule, and from a convenient location. This flexibility combined with a series of other issues; make the benefits of lifelong distance learning numerous. The purpose of the paper is to investigate whether distance education can contribute to the improvement of adult skills in Greece, highlighting in this way the necessity of the lifelong distance learning. To investigate this goal, a questionnaire is constructed and analyzed based on responses from 3,016 attendees of lifelong distance learning programs in the e-learning of the National and Kapodistrian University of Athens in Greece. In order to do so, a series of relationships is examined including the effects of a) the gender, b) the previous educational level, c) the current employment status, and d) the method used in the distance learning program, on the development of new general, technical, administrative, social, cultural, entrepreneurial and green skills. The basic conclusions that emerge after using a binary logistic framework are that the following factors are critical in order to develop new skills: the gender, the education level and the educational method used in the lifelong distance learning program. The skills more significantly affected by those factors are the acquiring new skills in general, as well as acquiring general, language and cultural, entrepreneurial and green skills, while for technical and social skills only gender and educational method play a crucial role. Moreover, routine skills and social skills are not affected by the four factors included in the analysis.

Keywords: adult skills, distance learning, education, lifelong learning

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Authors: A. A. Yakub, Omavudu Ikogho

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Land subdivision in most peri-urban areas of Kano metropolis is the entrenched prerogative of ‘KAFADA’ a group of informal plot partitioners who oversee the demarcation of mainly previous farmland into residential plots popularly called 'awon igiya' for those in need. With time these areas are engulfed in the milieu of the rapidly expanding urban landscape and form clusters of poorly planned settlements with tendencies to become future slums. This paper studies the practice of informal land subdivision in Kano metropolis with emphasis on the practitioners, the institutional framework, and the demand and supply scenario that sustains this trend as well as the extent of infrastructural development in these areas. Using three selected informally planned settlements as case-studies, a series of interviews and questionnaires are administered to 'KAFADA,' residents and the state land officers to generate data in these areas. Another set of data was similarly generated in three government subdivided residential layouts, and both sets analysed comparatively. The findings identify varying levels of infrastructural deficits in the informal communities compared to the planned neighbourhoods which are seen to be as a result of the absence of government participation and an informal subdivision process which did not provide for proper planning standards. This study recommends that the regulatory agencies concerned register and partner with KAFADA to ensure that minimal planning standards are maintained in future settlements.

Keywords: peri-urban, informal land markets, land subdivision, infrastructure

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Authors: Alireza Monzavi Chaleshtori, Mahnaz Aliakbari Dehkordi, Maryam Aliakbari, Solmaz Seyed Mostafaii

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Objective: Considering the growing obesity among children and the role of mother's psychological factors as well as the need to prevent childhood obesity, this study aimed to investigate the mediating role of mother's self-efficacy in the relationship between mother's stress and depression and child obesity. Method: For this purpose, in a descriptive-correlation study, 222 mothers and children aged 1 to 5 years in Tehran, who had the opportunity to answer an online questionnaire, were selected by random sampling and to the depression scales of the Kroenke and Spitzer Patient Health Questionnaire, Cohen's stress and Self-efficacy of Berkeley mothers answered. Pearson correlation test and path analysis were used for data analysis. Findings: The findings showed that maternal depression had an indirect and significant effect on child obesity, and the effect of stress and depression on child obesity was indirect and non-significant. Therefore, the model has a good fit with the research data, and stress and depression indirectly predicted child obesity with the mediating role of self-efficacy. Conclusion: The hypothesized model tested based on mother's stress and depression with the mediating role of mother's self-efficacy was a good model in explaining the prediction of child obesity. Based on the findings of this research, a practical framework can be provided to explain the psychological factors of the mother in relation to child obesity and its treatment.

Keywords: stress, self-efficacy, child obesity, depression

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Authors: Recep Kesli, Gulşah Asik, Cengiz Demir, Onur Turkyilmaz

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Objective: Acinetobacter baumannii (A. baumannii) can cause health-care associated infections, such as bacteremia, urinary tract and wound infections, endocarditis, meningitis, and pneumonia, particularly in intensive care unit patients. In this study, we aimed to evaluate A. baumannii production in sputum and bronchoalveolar lavage and susceptibilities for antibiotics in a 24 months period. Methods: Between October 2013 and September 2015, Acinetobacter baumannii isolated from respiratory tract speciments were evaluated retrospectively. The strains were isolated from the different intensive care units patients. A. baumannii strains were identified by both the conventional methods and aoutomated identification system -VITEK 2 (bio-Merieux, Marcy l’etoile, France). Antibiotic resistance testing was performed by Kirby-Bauer disc diffusion method according to CLSI criteria. Results: All the ninety isolates included in the study were from respiratory tract specimens. While of all the isolated 90 Acinetobacter baumannii strains were found to be resistant (100%), against ceftriaxone, ceftazidime, ciprofloxacin and piperacillin/ tazobactam, resistance rates against other tested antibiotics found as follows; meropenem 77, 86%, imipenem 75, 83%, trimethoprim-sulfamethoxazole (TMP-STX) 69, 76,6%, gentamicin 51, 56,6% and amikacin 48, 53,3%. Colistin was found as the most effective antibiotic against Acinetobacter baumannii, and there were not found any resistant (0%) strain against colistin. Conclusion: This study demonstrated that the no resistance was found in Acinetobacter baumannii against to colistin. High rates of resistance to carbapenems (imipenem and meropenem) and other tested antibiotics (ceftiaxone, ceftazidime, ciprofloxacine, piperacilline-tazobactam, TMP-STX gentamicin and amikacin) also have remarkable resistance rates. There was a significant relationship between demographic features of patients such as age, undergoing mechanical ventilation, length of hospital stay with resistance rates. High resistance rates against antibiotics require implementation of the infection control program and rational use of antibiotics. In the present study, while there were not found colistin resistance, panresistance were found against to ceftriaxone, ceftazidime, ciprofloxacin and piperacillin/ tazobactam.

Keywords: acinetobacter baumannii, antibiotic resistance, multi drug resistance, intensive care unit

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Authors: Gina Cynthia Raphita Hasibuan

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The housing sector in Indonesia is in critical condition where majority of low-income citizens live in substandard dwellings, and the number housing backlog is increasing every year. The housing problem becomes more urgent when the term 'sustainability' is considered, and sustainable affordable housing is yet to gain its successful implementation. Global urbanization develops fastest in developing countries like Indonesia where informal settlements are rapidly escalating, hence, making sustainable affordable housing strategies very critical in this context. The problem in developing countries like Indonesia lies on the institutional capacity of newly-established local governments having greater power to determine a development policy but apparently still lacking institutional capability and coordination with the central government and collaborative governance are still not established yet. The concept of upgrading informal settlements are seen changed over time and inconsistent. Despite much research on theme such as sustainable housing concept within Indonesian context, there has been a dearth of research examining the role of collaborative governance, as the current approach still shows fragmented approach between the stakeholders and the lack of community participation as the end user, and thus this research attempts to fill the gap on the aforementioned problems. By using case study with multi-methods conducted in Jakarta, this research has an overall aim to critically assess the role of collaborative governance in addressing sustainable affordable housing in Indonesia and to understand informal settlements and interventions in Indonesia rather than imposing a framework from western perspectives.

Keywords: affordable housing, collaborative governance, sustainability, urban planning

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Authors: Hamid Mustafa, Huson J. Heather, Kim Eiusoo, McClure Matt, Khalid Javed, Talat Nasser Pasha, Afzal Ali1, Adeela Ajmal, Tad Sonstegard

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Genetic differences associated with speciation, breed formation or local adaptation can help to preserve and effective utilization of animals in selection programs. Analyses of population structure and breed diversity have provided insight into the origin and evolution of cattle. In this study, we used a high-density panel of SNP markers to examine population structure and diversity among ten Pakistani indigenous cattle breeds. In total, 25 individuals from three cattle populations, including Achi (n=08), Bhagnari (n=04) and Cholistani (n=13) were genotyped for 777, 962 single nucleotide polymorphism (SNP) markers. Population structure was examined using the linkage model in the program STRUCTURE. After characterizing SNP polymorphism in the different populations, we performed a detailed analysis of genetic structure at both the individual and population levels. The whole-genome SNP panel identified several levels of population substructure in the set of examined cattle breeds. We further searched for spatial patterns of genetic diversity among these breeds under the recently developed spatial principal component analysis framework. Overall, such high throughput genotyping data confirmed a clear partitioning of the cattle genetic diversity into distinct breeds. The resulting complex historical origins associated with both natural and artificial selection have led to the differentiation of numerous different cattle breeds displaying a broad phenotypic variety over a short period of time.

Keywords: Pakistan, cattle, genetic diversity, population structure

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Authors: Sharadha G., Suresh Kanakkanavar

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Background: Placenta previa is a condition characterized by partial or complete implantation of the placenta in the lower uterine segment. It is one of the main causes of vaginal bleeding in the third trimester and a significant cause of maternal and perinatal morbidity and mortality. Materials and Methods: This is an observational study involving 130 patients diagnosed with placenta previa and satisfying inclusion criteria. The demographic data, clinical, surgical, and treatment, along with maternal and neonatal outcome parameters, were noted in proforma. Results: The incidence of placenta previa among scarred uterus was 1.32%, and in unscarred uterus was 0.67%. The mean age of the study population was 27.12±4.426years. High parity, high abortion rate, multigravida status, and less gestational age at delivery were commonly seen in scarred uterus compared to unscarred uterus. Complete placenta previa, anterior placental position, and adherent placenta were significantly associated with a scarred uterus compared to an unscarred uterus. The rate of caesarean hysterectomy was higher in the scarred uterus, along with statistical association to previous lower-segment caesarean sections. Intraoperative procedures like uterine artery ligation, bakri balloon insertion, and iliac artery ligation were higher in the scarred group. The maternal intensive care unit admission rate was higher in the scarred group and also showed its statistical association with previous lower segment caesarean section. Neonatal outcomes in terms of pre-term birth, still birth, neonatal intensive care unit admission, and neonatal death, though higher in the scarred group, did not differ statistically among the groups. Conclusion: Advancing maternal age, multiparity, prior uterine surgeries, and abortions are independent risk factors for placenta previa. Maternal morbidity is higher in the scarred uterus group compared to the unscarred group. Neonatal outcomes did not differ statistically among the groups. This knowledge would help the obstetricians to take measures to reduce the incidence of placenta previa and scarred uterus which would improve the fetomaternal outcome of placenta previa.

Keywords: placenta previa, scarred uterus, unscarred uterus, adherent placenta

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Authors: Ibtisam Al-Zaru

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Background: Worldwide, depression among coronary artery disease (CAD) patients is considered a serious problem that may cause many complications and negative consequences; particularly serious being increased mortality and morbidity rate. Studying depression among CAD patients in Jordan has not been investigated thoroughly and thus a need for further studies has been a priority. Aims: To assess depression in non-hospitalized Jordanian patients with CAD; to describe the relationship between socio-demographic data, health related factors, and depression; and to examine the best predictors of depression in non-hospitalized Jordanian patients with CAD. Method: A cross-sectional-descriptive design was used to collect data from 174 non-hospitalized Jordanian patients diagnosed with CAD in outpatients’ cardiac clinics, using a self- administered questionnaires and Cardiac Depression Scale. Results: 53.4% of CAD patients reported mild/moderate, and severe depressive symptoms. Significant relationships between depressive symptoms and some demo-clinical characteristics (i.e. being female gender; having of chronic disease and surgical history; being physically inactive, and perceived their sexual activity, physical and psychological as poor). The preceding factors are also found to be statistically significant predictors for depression among this patients’ group. Conclusion: Jordanian patients with CAD had various levels of severity regarding their depressive symptoms. Therefore, health care providers need to introduce depression assessment and treatment in cardiac rehabilitation to control depression and its impact on the patient. Consequently, such control will reduce co-morbidity, mortality, complications and health costs among CAD patients and enhance the quality of their lives.

Keywords: coronary artery disease, predictors, depression, prevalence

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Authors: Mina Samizadeh

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In the past few decades, there has been an explosion in the amount of available data produced from various sources with different topics. The availability of this enormous data necessitates us to adopt effective computational tools to explore the data. This leads to an intense growing interest in the research community to develop computational methods focused on processing this text data. A line of study focused on condensing the text so that we are able to get a higher level of understanding in a shorter time. The two important tasks to do this are keyword extraction and text summarization. In keyword extraction, we are interested in finding the key important words from a text. This makes us familiar with the general topic of a text. In text summarization, we are interested in producing a short-length text which includes important information about the document. The TextRank algorithm, an unsupervised learning method that is an extension of the PageRank (algorithm which is the base algorithm of Google search engine for searching pages and ranking them), has shown its efficacy in large-scale text mining, especially for text summarization and keyword extraction. This algorithm can automatically extract the important parts of a text (keywords or sentences) and declare them as a result. However, this algorithm neglects the semantic similarity between the different parts. In this work, we improved the results of the TextRank algorithm by incorporating the semantic similarity between parts of the text. Aside from keyword extraction and text summarization, we develop a topic clustering algorithm based on our framework, which can be used individually or as a part of generating the summary to overcome coverage problems.

Keywords: keyword extraction, n-gram extraction, text summarization, topic clustering, semantic analysis

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Authors: Majid Samiee Zonoozian

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For such important constructions as jacket type platforms, scrupulous attention in analysis, design and calculation processes is needed. The reliability assessment method has been established into an extensively used method to behavior safety calculation of jacket platforms. In the present study, a methodology for the reliability calculation of an offshore jacket platform in contradiction of the extreme wave loading state is available. Therefore, sensitivity analyses are applied to acquire the nonlinear response of jacket-type platforms against extreme waves. The jacket structure is modeled by applying a nonlinear finite-element model with regards to the tubular members' behave. The probability of a member’s failure under extreme wave loading is figured by a finite-element reliability code. The FORM and SORM approaches are applied for the calculation of safety directories and reliability indexes have been detected. A case study for a fixed jacket-type structure positioned in the Persian Gulf is studied by means of the planned method. Furthermore, to define the failure standards, equations suggested by the 21st version of the API RP 2A-WSD for The jacket-type structures’ tubular members designing by applying the mixed axial bending and axial pressure. Consequently, the effect of wave Loades in the reliability index was considered.

Keywords: Jacket-Type structure, reliability, failure probability, tubular members

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Authors: Dongjoo Chin

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The purpose of this study was to investigate the effectiveness of an Early Intensive Behavioral Intervention (EIBI) program on infants with autism spectrum disorder (ASD) and to explore the factors predicting the effectiveness of the program, focusing on the infant's age, language ability, problem behaviors, and parental stress. 19 pairs of infants aged between 2 and 5 years who have had been diagnosed with ASD, and their parents participated in an EIBI program at a clinic providing evidence-based treatment based on applied behavior analysis. The measurement tools which were administered before and after the EIBI program and compared, included PEP-R, a curriculum evaluation, K-SIB-R, K-Vineland-II, K-CBCL, and PedsQL for the infants, and included PSI-SF and BDI-II for the parents. Statistical analysis was performed using a sample t-test and multiple regression analysis and the results were as follows. The EIBI program showed significant improvements in overall developmental age, curriculum assessment, and quality of life for infants. There was no difference in parenting stress or depression. Furthermore, measures for both children and parents at the start of the program predicted neither PEP-R nor the degree of improvement in curriculum evaluation measured six months later at the end of the program. Based on these results, the authors suggest future directions for developing an effective intensive early intervention (EIBI) program for infants with ASD in Korea, and discuss the implications and limitations of this study.

Keywords: applied behavior analysis, autism spectrum disorder, early intensive behavioral intervention, parental stress

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Authors: Hayder H. Kareem, Ayad K. Hussein, Aseel A. Alkatib

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Groundwater accumulated at geological formations constitutes a worldwide vital water resource component which can be used to supply agriculture, industry, and domestic uses. The subsurface environment is affected by human activities; consequently, planning and sustainable management of aquifers require serious attention, especially as the world is exposed to the problem of global warming. Establishing accurate and efficient groundwater models will provide confident results for the behavior of the aquifer's system. The new approach, 'Distributed Value Property Zones,' available in Visual MODFLOW, is used to reconstruct the subsurface zones of the Al-Najaf region aquifer, and then its effect is compared with those manual and automated (PEST) approaches. Results show that the model has become more accurate with the use of the new approach, as the calibration and results analyses revealed. The assessment of the Al-Najaf region groundwater aquifer has revealed a degree of insufficiency of the required pumping demand, which reflects dry areas in both of the aquifer's layers. In addition, with pumping, the Euphrates River loses water of 7458 m³/day to the aquifer, while without pumping, it gains 28837 m³/day from the rainfall's recharge. The distributed value property zones approach achieves a precise groundwater model to assess the state of the Al-Najaf region aquifer.

Keywords: Al-Najaf region, distributed value property zones approach, hydraulic conductivity, groundwater modelling using visual MODFLOW

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Authors: Ezomoh O. Olubunmi, Chukwuma S. Anakwe, Bekewei Progress, Prohp The Prophet

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Benzene is a volatile organic compound that is recognised as carcinogenic to humans. The objective of the current investigation was to ascertain the impact of the administration of benzene at varying concentrations on the livers of Wistar rats. The 40 adult female Wistar rats were divided into 10 groups, each consisting of four rats. For 28 days, Group 1 received distilled water, while Groups 2 to 10 were administered 0.04,0.06,0.08,0.2,0.4,0.6,0.8,1.0, and 1.2 ml/kg body weight of analytical grade benzene. Blood samples were obtained through cardiac puncture for liver function assessment, while the animals in groups 1 to 5 were euthanised after the 28th day under chloroform anaesthesia. The animals in groups 6 to 10 died midway through the study period. Antioxidant analysis was conducted on liver tissues that were collected and homogenised. The results indicated a substantial (p<0.05), dose-dependent increase in serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), and alkaline phosphatase (ALP) activities as a result of benzene exposure. Additionally, benzene resulted in a substantial reduction in the activities of superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx) in liver tissue, as well as an increase in malondialdehyde (MDA) concentrations, and this effect was dose-dependent. These findings emphasise the hepatotoxic effects of benzene, even at concentrations that are relatively low.

Keywords: benzene, alanine aminotransferase, aspartate aminotransferase, alkaline phosphate, antioxidants, superoxide dismutase, catalase, glutathione peroxidase

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Authors: Rodolfo Lorbieski, Silvia Modesto Nassar

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Many supervised machine learning tasks require decision making across numerous different classes. Multi-class classification has several applications, such as face recognition, text recognition and medical diagnostics. The objective of this article is to analyze an adapted method of Stacking in multi-class problems, which combines ensembles within the ensemble itself. For this purpose, a training similar to Stacking was used, but with three levels, where the final decision-maker (level 2) performs its training by combining outputs from the tree-based pair of meta-classifiers (level 1) from Bayesian families. These are in turn trained by pairs of base classifiers (level 0) of the same family. This strategy seeks to promote diversity among the ensembles forming the meta-classifier level 2. Three performance measures were used: (1) accuracy, (2) area under the ROC curve, and (3) time for three factors: (a) datasets, (b) experiments and (c) levels. To compare the factors, ANOVA three-way test was executed for each performance measure, considering 5 datasets by 25 experiments by 3 levels. A triple interaction between factors was observed only in time. The accuracy and area under the ROC curve presented similar results, showing a double interaction between level and experiment, as well as for the dataset factor. It was concluded that level 2 had an average performance above the other levels and that the proposed method is especially efficient for multi-class problems when compared to binary problems.

Keywords: stacking, multi-layers, ensemble, multi-class

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Authors: M. Eckert, D. Mendes, J P. Gonçalves, C. Moço, M. Oliveira

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The intensive extraction of natural aggregates leads to both depletion of natural resources and unwanted environmental impacts. On the other hand, uncontrolled disposal of Construction and Demolition Wastes (C&DW) causes the lifetime reduction of landfills. It is known that the European Union produces, each year, about 850 million tons of C&DW. For all the member States of the European Union, one of the milestones to be reached by 2020, according to the Resource Efficiency Roadmap (COM (2011) 571) of the European Commission, is to recycle 70% of the C&DW. In this work, properties of different types of recycled C&DW aggregates and natural aggregates were compared. Assays were performed according to European Standards (EN 13285; EN 13242+A1; EN 12457-4; EN 12620; EN 13139) for the characterization of there: physical, mechanical and chemical properties. Not standardized tests such as water absorption over time, mass stability and post compaction sieve analysis were also carried out. The tested recycled C&DW aggregates were classified according to the requirements of the European Standards regarding there potential use in concrete, mortar, unbound layers of road pavements and embankments. The results of the physical and mechanical properties of recycled C&DW aggregates indicated, in general, lower quality properties when compared to natural aggregates, particularly, for concrete preparation and unbound layers of road pavements. The results of the chemical properties attested that the C&DW aggregates constitute no environmental risk. It was concluded that recycled aggregates produced from C&DW have the potential to be used in many applications.

Keywords: recycled aggregate, sustainability, aggregate properties, European Standard Classification

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Authors: Konesh Navsaria, Itumeleng Ramodumo

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The study explored university students’ perceptions of cannabis use on academic life at a higher education institution (HEI) in Nelson Mandela Bay, South Africa. Cannabis is described as the most commonly-used drug by youth, especially those who are in tertiary institutions. The use of cannabis has both negative and positive effects; this is evident in different areas of human functioning. Cannabis usage has been debated upon in courts regarding its legalization and decriminalization, and on the 18th of September 2018, the South African High Court decriminalized cannabis for personal use. Cannabis use has increased in academic settings, and this has raised concerns about how it affects the mental health of students. A qualitative approach was used for the study with an explorative, descriptive design. Purposive sampling was used to select 15 participants for the study. Data were collected using focused-group interviews, following ethical clearance from the HEI. The collected data were analyzed and interpreted using thematic analysis, and cognitive behavioural theory was used as the theoretical framework. The research findings indicated both positive and negative influences of cannabis use on mental health. Most participants who expressed positive effects have used cannabis before, whereas most participants with negative perspectives of cannabis use on mental health are non-cannabis users. The findings revealed that participants perceived that the quantity of cannabis smoked determined whether there was a positive or negative effect on mental health; that is, large doses of cannabis were perceived as having negative effects. The research findings also revealed that the legalization of cannabis is very likely to increase its use and also highlighted precautionary measures users take to avoid the substance’s negative effects on mental health.

Keywords: cannabis use, mental health, university students, legalization

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Authors: Ikram Metalsi

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English as a Medium of Instruction known as (EMI) is expanding rapidly in the world. A growing volume of research has been dedicated to investigating its implementation. However, considerably less attention has been given to understanding EMI in a context where its implementation has been discussed but not yet put into practice. One such context is Algeria, where talks about a possible implementation of EMI have been going on for some time. The present study examines the current discourses and university lecturers’ attitudes towards the potential implementation of EMI as well as investigating the current implicit and explicit language policies in scientific courses in Algerian state universities. The focus is specifically on Engineering departments, as this field has gained worldwide importance in EMI research (Macaro et al. 2018), and, traditionally, French has been the MOI for Engineering in Algerian universities. Using the ROADMAPPING framework (Dafouz and Smit 2016) and the mixed method research approach, the present work explores the language in education policy (LEP) and planning situation in Algeria, the current media of instruction as well as the status and use of the English language in the scientific courses of the tertiary sector. Finally, the current study explores the perceived challenges and benefits of the implementation of EMI programmes from teachers’ perspectives with a particular focus on agency and how this potential policy implementation and teachers’ perceptions of agency around it may reflexively influence their professional identity.

Keywords: media of instruction, language in education policy, lecturers attitudes, teacher agency, professional identity

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Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

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In this paper, we propose a novel inference algorithm for the multi-class Gaussian process classification model that can be used in the field of human behavior recognition. This algorithm can drive simultaneously both a posterior distribution of a latent function and estimators of hyper-parameters in a Gaussian process classification model with multi-class. Our algorithm is based on the Laplace approximation (LA) technique and variational EM framework. This is performed in two steps: called expectation and maximization steps. First, in the expectation step, using the Bayesian formula and LA technique, we derive approximately the posterior distribution of the latent function indicating the possibility that each observation belongs to a certain class in the Gaussian process classification model. Second, in the maximization step, using a derived posterior distribution of latent function, we compute the maximum likelihood estimator for hyper-parameters of a covariance matrix necessary to define prior distribution for latent function. These two steps iteratively repeat until a convergence condition satisfies. Moreover, we apply the proposed algorithm with human action classification problem using a public database, namely, the KTH human action data set. Experimental results reveal that the proposed algorithm shows good performance on this data set.

Keywords: bayesian rule, gaussian process classification model with multiclass, gaussian process prior, human action classification, laplace approximation, variational EM algorithm

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Authors: Umair Nadeem, Sidra Umair

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Political behavior of voters and democratic values have been observed an emerging phenomenon in recent years in Pakistan. Privatized TV news channels are taking one sided position on the political issues, corresponding with respective political parties. Since last decade, TV News Channels have undermined this monopoly. Elections 2013 were unique in Pakistan with reference to political behavior and democratic values. Partisan narratives and counter narratives have been witnessed on different TV channels, in last few years. These mediated events seem very important to study the political behavior and democratic values as the country is approaching towards elections 2018. This endeavor is an attempt to capture the framing of the parties, issues in the partisan media culture and framing effects on political behavior of voters. Data for this research come from two data set. Content analysis of selected representative talks shows broadcast on mainstream news channels provide an assessment of the framing while quantitative survey of the discussion program’s viewers from Lahore city provide an evidence of framing effects on political behavior on voters and on democratic values. Regression results help us to argue that the highly partisan shows are strong predictors of polarized views among the audience. Study also grasp the attention of scholars towards the implications of this phenomenon.

Keywords: democratic values, partisan media, polarized views, political behavior

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Authors: Ganesh Dattatraya Saratale, Min Kyu Oh

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Rice straw is one of the most abundant lignocellulosic waste materials and its annual production is about 731 Mt in the world. This study treats the subject of effective utilization of this waste biomass for biofuels production. We have showed a comparative assessment of numerous pretreatment strategies for rice straw, comprising of major physical, chemical and physicochemical methods. Among the different methods employed for pretreatment alkaline pretreatment in combination with sodium chlorite/acetic acid delignification found efficient pretreatment with significant improvement in the enzymatic digestibility of rice straw. A cellulase dose of 20 filter paper units (FPU) released a maximum 63.21 g/L of reducing sugar with 94.45% hydrolysis yield and 64.64% glucose yield from rice straw, respectively. The effects of different pretreatment methods on biomass structure and complexity were investigated by FTIR, XRD and SEM analytical techniques. Finally the enzymatic hydrolysate of rice straw was used for ethanol production using developed Saccharomyces cerevisiae SR8. The developed yeast strain enabled efficient fermentation of xylose and glucose and produced higher ethanol production. Thus development of bioethanol production from lignocellulosic waste biomass is generic, applicable methodology and have great implication for using ‘green raw materials’ and producing ‘green products’ much needed today.

Keywords: rice straw, pretreatment, enzymatic hydrolysis, FPU, Saccharomyces cerevisiae SR8, ethanol fermentation

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Authors: Teklay Gebrecherkos, Mahmud Abdulkader, Tobias Rinke De Wit, Britta C. Urban, Feyissa Chala, Yazezew Kebede, Dawit Welday

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Background: C-reactive protein (CRP) levels are a reliable surrogate for interleukin-6 bioactivity that plays a pivotal role in the pathogenesis of cytokine storm associated with severe COVID-19. There is a lack of data on the role of CRP as a determinant of COVID-19 severity status in the African context. Methods: We determined the longitudinal kinetics of CRP levels on 78 RT-PCR-confirmed COVID-19 patients (49 non-severe and 29 severe cases) and 50 PCR-negative controls. Results: COVID-19 patients had overall significantly elevated CRP at baseline when compared to PCR-negative controls [median 11.1 (IQR: 2.0-127.8) mg/L vs. 0.9 (IQR: 0.5-1.9) mg/L; p=0.0004)]. Moreover, severe COVID-19 patients had significantly higher median CRP levels than non-severe cases [166.1 (IQR: 48.6-332.5) mg/L vs. 2.4 (IQR: 1.2-7.6) mg/L; p<0.00001)]. In addition, persistently elevated levels of CRP were exhibited among those with comorbidities and higher age groups. Area under receiver operating characteristic curve (AUC) analysis of CRP levels distinguished PCR-confirmed COVID-19 patients from the ones with PCR-negative non-COVID-19 individuals, with an AUC value of 0.77 (95% CI: 0.68-0.84; p=0.001). Moreover, it clearly distinguished severe from non-severe COVID-19 patients, with an AUC value of 0.83 (95% CI: 0.73-0.91). After adjusting for age and the presence of comorbidities, CRP levels above 30 mg/L were significantly associated with an increased risk of developing severe COVID-19 (adjusted relative risk 3.99 (95%CI: 1.35-11.82; p=0.013). Conclusions: Determining CRP levels in COVID-19 patients in African settings may provide a simple, prompt, and inexpensive assessment of the severity status at baseline and monitoring of treatment outcomes.

Keywords: CRP, COVID-19, SARS-CoV-2, biomarker

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Authors: Nadya Patel, Jawn Lim

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Foresight 3.0 is a synergistic methodology that encompasses systems analysis, future studies, capacity building, and forward planning. These components are interconnected, fostering a collective anticipatory intelligence that promotes societal resilience (Ravetz, 2020). However, traditional applications of these strands can often fall short, leading to missed opportunities and narrow perspectives. Therefore, Foresight 3.0 champions a holistic approach to tackling complex issues, focusing on systemic transformations and power dynamics. Businesses are pivotal in preparing the workforce for an increasingly uncertain and complex world. This necessitates the adoption of innovative tools and methodologies, such as Foresight 3.0, that can better equip young employees to anticipate and navigate future challenges. Firstly, the incorporation of its methodology into workplace training can foster a holistic perspective among employees. This approach encourages employees to think beyond the present and consider wider social, economic, and environmental contexts, thereby enhancing their problem-solving skills and resilience. This paper discusses our research on integrating Foresight 3.0's transformative principles with a newly developed Critical Design Futures (CDF) framework to equip organisations with the ability to innovate for the world's most complex social problems. This approach is grounded in 'collective forward intelligence,' enabling mutual learning, co-innovation, and co-production among a diverse stakeholder community, where business transformation and innovation are achieved.

Keywords: business transformation, innovation, foresight, critical design

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Authors: Venus Pagare, Amit Kharat, Dhaval K. Thakkar, Tushar J. Palekar

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Introduction: Chronic low back pain (CLBP) is a major public health problem and is the leading musculoskeletal cause of disability. Altered neuromuscular control of core muscles, particulary transverses abdominis (TrA) is thought to be a contributing factor for the development of CLBP. Therefore, various exercises targeting the TrA are commonly incorporated into the rehabilitation. Objectives: To investigate the effects of 3 different core exercises on activation capacity of TrA muscle in individuals with CLBP as compared with healthy controls. Methodology: Thickness of TrA muscle was measured by ultrasound imaging in 30 patients with CLBP and 30 healthy controls. Measurements were taken during 3 different TrA activation exercises i.e Abdominal drawing in maneuver (ADIM), Abdominal drawing in with straight leg raise (ADSLR) and breathe hold at maximum expiration (ME). Thickness of the muscle at rest (at the end of normal tidal expiration) was taken as a baseline measure. Results: There was a significant difference between the healthy subjects and patients with low back pain with regard to the thickness of TrA at rest and thickness during contraction. ADIM produced a significant increase in the thickness of TrA compared to ADSLR and ME (p<0.001). Also, increase in thickness of TrA was more in the control group than patients with low back pain. Conclusion: CLBP patients exhibited atrophy of TrA muscle with delayed activation. Also, of the various core exercises, ADIM can be an effective method for activation of TrA.

Keywords: LBP, CLBP, ADSLR, ADIM

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Authors: A. Ibovi Mouondayi, S. Zaher, R. Assadi, K. Erraoui, S. Sboul, J. Daoudim, S. Bousselham, K. Nassar, S. Janani

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INTRODUCTION: Neuropathic pain (NP) caused by damage to the somatosensory nervous system has a significant impact on quality of life and is associated with a high economic burden on the individual and society. The treatment of neuropathic pain consists of the use of a wide range of therapeutic agents, including gabapentin, which is used in the treatment of neuropathic pain. OBJECTIF: The objective of this study was to evaluate the efficacy and tolerance of gabapentin in the treatment of neuropathic pain. MATERIAL AND METHOD: This is a monocentric, cross-sectional, descriptive, retrospective study conducted in our department over a period of 19 months from October 2020 to April 2022. The missing parameters were collected during phone calls of the patients concerned. The diagnostic tool adopted was the DN4 questionnaire in the dialectal Arabic version. The impact of NP was assessed by the visual analog scale (VAS) on pain, sleep, and function. The impact of PN on mood was assessed by the "Hospital anxiety, and depression scale HAD" score in the validated Arabic version. The exclusion criteria were patients followed up for depression and other psychiatric pathologies. RESULTS: A total of 67 patients' data were collected. The average age was 64 years (+/- 15 years), with extremes ranging from 26 years to 94 years. 58 women and 9 men with an M/F sex ratio of 0.15. Cervical radiculopathy was found in 21% of this population, and lumbosacral radiculopathy in 61%. Gabapentin was introduced in doses ranging from 300 to 1800 mg per day with an average dose of 864 mg (+/- 346) per day for an average duration of 12.6 months. Before treatment, 93% of patients had a non-restorative sleep quality (VAS>3). 54% of patients had a pain VAS greater than 5. The function was normal in only 9% of patients. The mean anxiety score was 3.25 (standard deviation: 2.70), and the mean HAD depression score was 3.79 (standard deviation: 1.79). After treatment, all patients had improved the quality of their sleep (p<0.0001). A significant difference was noted in pain VAS, function, as well as anxiety and depression, and HAD score. Gabapentin was stopped for side effects (dizziness and drowsiness) and/or unsatisfactory response. CONCLUSION: Our data demonstrate a favorable effect of gabapentin on the management of neuropathic pain with a significant difference before and after treatment on the quality of life of patients associated with an acceptable tolerance profile.

Keywords: neuropathic pain, chronic pain, treatment, gabapentin

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Authors: Tania Mannan, Rahelee Zinnat, Fatema Jebunnesa, Israt Ara Hossain

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Background: Exposure to arsenic has known toxic effects but the effect on pregnancy outcomes is not as widely documented especially in women with diabetes. Growing evidence has suggested a potential role of arsenic exposure in the development of gestational diabetes mellitus (GDM). Therefore, we aimed to investigate the association of urinary arsenic (UAs) with birth outcomes in GDM subjects. Methods: Under an observational cross-sectional design a total of 263 GDM subjects (age in years, M±SD, 21±3.7) residing in an arsenic affected area of Bangladesh, were subjected to a 2 sample OGTT at the third trimester of gestation. Among them, 73 GDM and 190 non-GDM subjects enrolled in this study. Clinical and anthropometric measurements were done by standard techniques. Degree of chronic arsenic exposure was assessed by the level of UAs level. According to World Health Organization (WHO) criteria, GDM was diagnosed and neonatal outcomes using APGAR (Activity Pulse Grimace Appearance Respirations) Score, birth weight and size were assessed by a specialist obstetrician. Serum glucose was measured by the Glucose Oxidase method and UAs level was determined by ultraviolet/visible spectrophotometry. Result: Out of the 263 pregnant women, 28% developed GDM. Urinary Arsenic was significantly higher in the GDM as compared to the non-GDM group [UAs, µg/l, M±SD (range), 204.2±67.0 (67.0-377.0) vs 77.3±38.1 (22.0-99.0), p < 0.001]. Activity Pulse Grimace Appearance Respirations Score of the neonates from GDM mothers was significantly lower compared to the neonates from non-GDM mothers [APGAR Score, M±SD, 4.7±0.8 vs. 6.4±0.7, p<0.001]. Pearson’s correlation analysis in GDM subjects revealed that UA levels were found to have a significant positive correlation with both fasting and postprandial serum glucose levels (p < 0.001) and (p < 0.001) respectively. Again, a significant inverse correlation of UAs with birth weight and size was observed (p < 0.001). The APGAR Score of the neonates were found to have a significant negative correlation (p < 0.001) with UAs level. Conclusion: The effect of chronic arsenic exposure is associated with glucose intolerance during pregnancy and it also adversely affects birth outcomes. The study suggests further research on the impact of total arsenic exposure on pregnancy outcomes.

Keywords: APGAR score, arsenic exposure, birth outcome, gestational diabetes mellitus,

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Authors: Sai Sankalp Vemavarapu

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This paper discusses the application of machine learning in the field of transportation engineering for predicting engineering properties of pavement more accurately and efficiently. Predicting the elastic properties aid us in assessing the current road conditions and taking appropriate measures to avoid any inconvenience to commuters. This improves the longevity and sustainability of the pavement layer while reducing its overall life-cycle cost. As an example, we have implemented differential evolution (DE) in the back-calculation of the elastic modulus of multi-layered pavement. The proposed DE global optimization back-calculation approach is integrated with a forward response model. This approach treats back-calculation as a global optimization problem where the cost function to be minimized is defined as the root mean square error in measured and computed deflections. The optimal solution which is elastic modulus, in this case, is searched for in the solution space by the DE algorithm. The best DE parameter combinations and the most optimum value is predicted so that the results are reproducible whenever the need arises. The algorithm’s performance in varied scenarios was analyzed by changing the input parameters. The prediction was well within the permissible error, establishing the supremacy of DE.

Keywords: cost function, differential evolution, falling weight deflectometer, genetic algorithm, global optimization, metaheuristic algorithm, multilayered pavement, pavement condition assessment, pavement layer moduli back calculation

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Authors: Chowon Kim, Yoo-Kyung Kim, Kyeong Yeon Park, Hyun-Shik Lee

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Perfluoroalkyl compounds (PFCs) are globally distributed synthetic compounds that are known to adversely affect human health. Developmental toxicity assessment of PFCs is important to facilitate the evaluation of their environmental impact. In the present study, we assessed the developmental toxicity and teratogenicity of PFCs with different numbers of carbon atoms on Xenopus embryogenesis. An initial frog embryo teratogenicity assay-Xenopus (FETAX) assay was performed that identified perfluorohexanoic (PFHxA) and perfluoroheptanoic (PFHpA) acids as potential teratogens and developmental toxicants. The mechanism underlying this teratogenicity was also investigated by measuring the expression of tissue-specific biomarkers such as phosphotyrosine‑binding protein, xPTB (liver); NKX2.5 (heart); and Cyl18 (intestine). Whole‑mount in situ hybridization, reverse transcriptase‑polymerase chain reaction (RT-PCR), and histologic analyses detected severe defects in the liver and heart following exposure to PFHxA or PFHpA. In addition, immunoblotting revealed that PFHpA significantly increased the phosphorylation of extracellular signal-regulated kinase (ERK) and c-Jun N-terminal kinase (JNK), while PFHxA slightly increased these, as compared with the control. These results suggest that PFHxA and PFHpA are developmental toxicants and teratogens, with PFHpA producing more severe effects on liver and heart development through the induction of ERK and JNK phosphorylation.

Keywords: PFCs, ERK, JNK, xenopus

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