Search results for: Cross Correlation (CC)

Authors: Kathrina Aseanne Acapulco-Gomez, Shayne Julieane Morales, Tzar Francis Verame

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Mean platelet volume (MPV) is the most accurate measure of the size of platelets and is routinely measured by most automated hematological analyzers. Several studies have shown associations between MPV and cardiovascular risks and outcomes. Although its measurement may provide useful data, MPV remains to be a diagnostic tool that is yet to be included in routine clinical decision making. The aim of this systematic review and meta-analysis is to determine summary estimates of the diagnostic accuracy of mean platelet volume for the diagnosis of myocardial infarction among adult patients with angina and/or its equivalents in terms of sensitivity, specificity, diagnostic odds ratio, and likelihood ratios, and to determine the difference of the mean MPV values between those with MI and those in the non-MI controls. The primary search was done through search in electronic databases PubMed, Cochrane Review CENTRAL, HERDIN (Health Research and Development Information Network), Google Scholar, Philippine Journal of Pathology, and Philippine College of Physicians Philippine Journal of Internal Medicine. The reference list of original reports was also searched. Cross-sectional, cohort, and case-control articles studying the diagnostic performance of mean platelet volume in the diagnosis of acute myocardial infarction in adult patients were included in the study. Studies were included if: (1) CBC was taken upon presentation to the ER or upon admission (within 24 hours of symptom onset); (2) myocardial infarction was diagnosed with serum markers, ECG, or according to accepted guidelines by the Cardiology societies (American Heart Association (AHA), American College of Cardiology (ACC), European Society of Cardiology (ESC); and, (3) if outcomes were measured as significant difference AND/OR sensitivity and specificity. The authors independently screened for inclusion of all the identified potential studies as a result of the search. Eligible studies were appraised using well-defined criteria. Any disagreement between the reviewers was resolved through discussion and consensus. The overall mean MPV value of those with MI (9.702 fl; 95% CI 9.07 – 10.33) was higher than in those of the non-MI control group (8.85 fl; 95% CI 8.23 – 9.46). Interpretation of the calculated t-value of 2.0827 showed that there was a significant difference in the mean MPV values of those with MI and those of the non-MI controls. The summary sensitivity (Se) and specificity (Sp) for MPV were 0.66 (95% CI; 0.59 - 0.73) and 0.60 (95% CI; 0.43 – 0.75), respectively. The pooled diagnostic odds ratio (DOR) was 2.92 (95% CI; 1.90 – 4.50). The positive likelihood ratio of MPV in the diagnosis of myocardial infarction was 1.65 (95% CI; 1.20 – 22.27), and the negative likelihood ratio was 0.56 (95% CI; 0.50 – 0.64). The intended role for MPV in the diagnostic pathway of myocardial infarction would perhaps be best as a triage tool. With a DOR of 2.92, MPV values can discriminate between those who have MI and those without. For a patient with angina presenting with elevated MPV values, it is 1.65 times more likely that he has MI. Thus, it is implied that the decision to treat a patient with angina or its equivalents as a case of MI could be supported by an elevated MPV value.

Keywords: mean platelet volume, MPV, myocardial infarction, angina, chest pain

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Authors: Champika Amarasinghe

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Introduction: Covid 19 pandemic was badly hit to the Sri Lankan economy during the year 2021. More than 65% of the Sri Lankan work force is engaged with small and medium scale businesses which no doubt that they had to struggle for their survival and business continuity during the pandemic. Objective: To assess the association of adherence to the new norms during the Covid 19 pandemic and maintenance of healthy working environmental conditions for business continuity. A cross sectional study was carried out to assess the OSH status and adequacy of Covid 19 preventive strategies among the 200 SME’S in selected two districts in Sri Lanka. These two districts were selected considering the highest availability of SME’s. Sample size was calculated, and probability propionate to size was used to select the SME’s which were registered with the small and medium scale development authority. An interviewer administrated questionnaire was used to collect the data, and OSH risk assessment was carried out by a team of experts to assess the OSH status in these industries. Results: According to the findings, more than 90% of the employees in these industries had a moderate awareness related to COVID 19 disease and preventive strategies such as the importance of Mask use, hand sainting practices, and distance maintenance, but the only forty percent of them were adhered to implementation of these practices. Furthermore, only thirty five percent of the employees and employers in these SME’s new the reasons behind the new norms, which may be the reason for reluctance to implement these strategies and reluctance to adhering to the new norms in this sector. The OSH risk assessment findings revealed that the working environmental organization while maintaining the distance between two employees was poor due to the inadequacy of space in these entities. More than fifty five percent of the SME’s had proper ventilation and lighting facilities. More than eighty five percent of these SME’s had poor electrical safety measures. Furthermore, eighty two percent of them had not maintained fire safety measures. Eighty five percent of them were exposed to heigh noise levels and chemicals where they were not using any personal protectives nor any other engineering controls were not imposed. Floor conditions were poor, and they were not maintaining the occupational accident nor occupational disease diseases. Conclusions: Based on the findings, proper awareness sessions were carried out by NIOSH. Six physical training sessions and continues online trainings were carried out to overcome these issues, which made a drastic change in their working environments and ended up with hundred percent implementation of the Covid 19 preventive strategies, which intern improved the worker participation in the businesses. Reduced absentees and improved business opportunities, and continued their businesses without any interruption during the third episode of Covid 19 in Sri Lanka.

Keywords: working environment, Covid 19, occupational diseases, occupational accidents

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Authors: Remy Mpulumba Badiambile, Paul Musa Obadia, Malick Useni Mutayo, Jeef Numbi Mukanya, Patient Nkulu Banza, Tony Kayembe Kitenge, Erik Smolders, Jean-François Picron, Vincent Haufroid, Célestin Banza Lubaba Nkulu, Benoit Nemery

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Background: In July 2021, the Tshikapa river became heavily polluted by mining wastes from a diamond mine in neighboring Angola, leading to massive killing of fish, as well as disease and even deaths among residents living along the Tshikapa and Kasai rivers, a major contributory of the Congo river. The exact nature of the pollutants was unknown. Methods: In a cross-sectional study conducted in the city of Tshikapa in August 2021, we enrolled by opportunistic sampling 65 residents (11 children < 16y) living alongside the polluted rivers and 65 control residents (5 children) living alongside a non-affected portion of the Kasai river (upstream from the Tshikapa-Kasai confluence). We administered a questionnaire and obtained spot urine samples for measurements of thiocyanate (a metabolite of cyanide) and 26 trace metals (by ICP-MS). Metals (and pH) were also measured in samples of river water. Results: Participants from both groups consumed river water. In the area affected by the pollution, most participants had eaten dead fish. Prevalences of reported health symptoms were higher in the exposed group than among controls: skin rashes (52% vs 0%), diarrhea (40% vs 8%), abdominal pain (8% vs 3%), nausea (3% vs 0%). In polluted water, concentrations [median (range)] were only higher for nickel [(2.2(1.4–3.5)µg/L] and uranium [78(71–91)ng/L] than in non-polluted water [0.8(0.6–1.9)µg/L; 9(7–19)ng/L]. In urine, concentrations [µg/g creatinine, median(IQR)] were significantly higher in the exposed group than in controls for lithium [19.5(12.4–27.3) vs 6.9(5.9–12.1)], thallium [0.41(0.31–0.57) vs 0.19(0.16–0.39)], and uranium [0.026(0.013–0.037)] vs 0.012(0.006–0.024)]. Other elements did not differ between the groups, but levels were higher than reference values for several metals (including manganese, cobalt, nickel, and lead). Urinary thiocyanate concentrations did not differ. Conclusion: This study, after an ecological disaster in the DRC, has documented contamination of river water by nickel and uranium and high urinary levels of some trace metals among affected riverine populations. However, the exact cause of the massive fish kill and disease among residents remains elusive. The capacity to rapidly investigate toxic pollution events must be increased in the area.

Keywords: metal contaminants, river water and human urine, pollution by mining wastes, DR Congo

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Authors: Helen J. Spray, Karina J. Linnell

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Local-global bias in adulthood is strongly dependent on environmental factors and a global bias is not the universal characteristic of adult perception it was once thought to be: whilst Western adults typically demonstrate a global bias, Namibian adults living in traditional villages possess a strong local bias. Furthermore, environmental effects on local-global bias have been shown to be highly gender-specific; whereas urbanisation promoted a global bias in urbanised Namibian women but not men, education promoted a global bias in urbanised Namibian men but not women. Adult populations, however, provide only a snapshot of the gene-environment interactions which shape perceptual bias. Yet, to date, there has been little work on the development of local-global bias across environmental settings. In the current study, local-global bias was assessed using a similarity-matching task with Navon figures in children aged between 4 and 15 years from across three populations: traditional Namibians, urban Namibians, and urban British. For the two Namibian groups, measures of urbanisation and education were obtained. Data were subjected to both between-group and within-group analyses. Between-group analyses compared developmental trajectories across population and gender. These analyses revealed a global bias from even as early as 4 in the British sample, and showed that the developmental onset of a global bias is not fixed. Urbanised Namibian children ultimately developed a global bias that was indistinguishable from British children; however, a global bias did not emerge until much later in development. For all populations, the greatest developmental effects were observed directly following the onset of formal education. No overall gender effects were observed; however, there was a significant gender by age interaction which was difficult to reconcile with existing biological-level accounts of gender differences in the development of local-global bias. Within-group analyses compared the effects of urbanisation and education on local-global bias for traditional and urban Namibian boys and girls separately. For both traditional and urban boys, education mediated all effects of age and urbanisation; however, this was not the case for girls. Traditional Namibian girls retained a local bias regardless of age, education, or urbanisation, and in urbanised girls, the development of a global bias was not attributable to any one factor specifically. These results are broadly consistent with aforementioned findings that education promoted a global bias in urbanised Namibian men but not women. The development of local-global bias does not follow a fixed trajectory but is subject to environmental control. Understanding how variability in the development of local-global bias might arise, particularly in the context of gender, may have far-reaching implications. For example, a number of educationally important cognitive functions (e.g., spatial ability) are known to show consistent gender differences in childhood and local-global bias may mediate some of these effects. With education becoming an increasingly prevalent force across much of the developing world it will be important to understand the processes that underpin its effects and their implications.

Keywords: cross-cultural, development, education, gender, local-global bias, perception, urbanisation, urbanization

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Authors: Sima E. Rugarabamu, Mecky I. Matee, Elison N. M. Simon

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Background: In Tanzania bacteriological studies of etiological agents of oro-facial infections are very limited, and very few have investigated anaerobes. The aim of this study was to determine the spectrum of bacterial agents involved in oral and maxillofacial infections in patients attending Muhimbili National Hospital, Dar-es-salaam, Tanzania. Method: This was a hospital based descriptive cross-sectional study that was conducted in the Department of Oral and Maxillofacial Surgery of the Muhimbili National Hospital in Dar es Salaam, Tanzania from 1st January 2014 to 31st August 2014. Seventy (70) patients with various forms of oral and maxillofacial infections who were recruited for the study. The study participants were interviewed using a prepared questionnaire after getting their consent. Pus aspirate was cultured on Blood agar, Chocolate Agar, MacConkey agar and incubated aerobically at 37°C. Imported blood agar was used for anaerobic culture whereby they were incubated at 37°Cin anaerobic jars in an atmosphere of generated using commercial gas-generating kits in accordance with manufacturer’s instructions. Plates were incubated at 37°C for 24 hours (For aerobic culture and 48 hours for anaerobic cultures). Gram negative rods were identified using API 20E while all other isolates were identified by conventional biochemical tests. Antibiotic sensitivity testing for isolated aerobic and anaerobic bacteria was detected by the disk diffusion, agar dilution and E-test using routine and commercially available antibiotics used to treat oral facial infections. Results: This study comprised of 41 (58.5%) males and 29 (41.5%) females with a mean age of 32 years SD +/-15.1 and a range of 19 to 70 years. A total of 161 bacteria strains were isolated from specimens obtained from 70 patients which were an average of 2.3 isolates per patient. Of these 103 were aerobic organism and 58 were strict anaerobes. A complex mix of strict anaerobes and facultative anaerobes accounted for 87% of all infections.The most frequent aerobes isolated was streptococcus spp 70 (70%) followed by Staphylococcus spp 18 (18%). Other organisms such as Klebsiella spp 4 (4%), Proteus spp 5 (5%) and Pseudomonas spp 2 (2%) were also seen. The anaerobic group was dominated by Prevotella spp 25 (43%) followed by Peptostreptococcus spp 18 (31%); other isolates were Pseudomonas spp 2 (1%), black pigmented Pophyromonas spp 4 (5%), Fusobacterium spp 3 (3%) and Bacteroides spp 5 (8%). Majority of these organisms were sensitive to Amoxicillin (98%), Gentamycin (89%), and Ciprofloxacin (100%). A 40% resistance to metronidazole was observed in Bacteroides spp otherwise this drug and others displayed good activity against anaerobes. Conclusions: Oral and maxillofacial facial infections at Muhimbili National Hospital are mostly caused by streptococcus spp and Prevotella spp. Strict anaerobes accounted for 36% of all isolates. The profile of isolates should assist in selecting empiric therapy for infections of the oral and maxillofacial region. Inclusion of antimicrobial agents against anaerobic bacteria is highly recommended.

Keywords: bacteria, oral and maxillofacial infections, antibiotic susceptibility, Tanzania

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Authors: Jianan Sun, Ziwen Ye

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Multidimensional computerized adaptive testing (MCAT) is a popular research topic in psychometrics. It is important for practitioners to clearly know the item-trait patterns of administered items when a test like MCAT is operated. Item-trait pattern recognition refers to detecting which latent traits in a psychological test are measured by each of the specified items. If the item-trait patterns of the replenished items in MCAT item pool are well detected, the interpretability of the items can be improved, which can further promote the abilities of the examinees who attending the MCAT to be accurately estimated. This research explores to solve the item-trait pattern recognition problem of the replenished items in MCAT item pool from the perspective of statistical variable selection. The popular multidimensional item response theory model, multidimensional two-parameter logistic model, is assumed to fit the response data of MCAT. The proposed method uses the least absolute shrinkage and selection operator (LASSO) to detect item-trait patterns of replenished items based on the essential information of item responses and ability estimates of examinees collected from a designed MCAT procedure. Several advantages of the proposed method are outlined. First, the proposed method does not strictly depend on the relative order between the replenished items and the selected operational items, so it allows the replenished items to be mixed into the operational items in reasonable order such as considering content constraints or other test requirements. Second, the LASSO used in this research improves the interpretability of the multidimensional replenished items in MCAT. Third, the proposed method can exert the advantage of shrinkage method idea for variable selection, so it can help to check item quality and key dimension features of replenished items and saves more costs of time and labors in response data collection than traditional factor analysis method. Moreover, the proposed method makes sure the dimensions of replenished items are recognized to be consistent with the dimensions of operational items in MCAT item pool. Simulation studies are conducted to investigate the performance of the proposed method under different conditions for varying dimensionality of item pool, latent trait correlation, item discrimination, test lengths and item selection criteria in MCAT. Results show that the proposed method can accurately detect the item-trait patterns of the replenished items in the two-dimensional and the three-dimensional item pool. Selecting enough operational items from the item pool consisting of high discriminating items by Bayesian A-optimality in MCAT can improve the recognition accuracy of item-trait patterns of replenished items for the proposed method. The pattern recognition accuracy for the conditions with correlated traits is better than those with independent traits especially for the item pool consisting of comparatively low discriminating items. To sum up, the proposed data-driven method based on the LASSO can accurately and efficiently detect the item-trait patterns of replenished items in MCAT.

Keywords: item-trait pattern recognition, least absolute shrinkage and selection operator, multidimensional computerized adaptive testing, variable selection

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Authors: Akinola Helen Olufunke, Soetan Olatunbosun Jonathan, Adeleye Oludamola

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Introduction: Antibiotic resistance has grown significantly, which is a major cause for concern. There have not been many significant developments in antibiotics over the past few decades, and practically all of the ones that are currently in use are losing effectiveness against pathogenic germs. Researchers are starting to focus more on the physiologically active compounds found in plants, particularly phytobiotics in poultry production. Consumption of chicken products is among the greatest in the country, but numerous nations, including Nigeria, use excessive amounts of necessary antibiotics in poultry farming, endangering the safety of such goods (through antimicrobial residues). Drug resistance has become a widespread issue as a result of the risky use of antibiotics in the chicken production industry. In order to replace antibiotics, biotic or natural products like phytobiotics (also known as botanicals or phytogenics) have drawn a lot of interest. Phytobiotics or their components are thought to be a relatively recent category of natural herbs that have acquired acceptance and favor among chicken farmers. The addition of several phytobiotic additions to poultry feed has demonstrated its capacity to improve both the broiler and layer populations' productivity. Design: Experimental research design and cross-sectional study was carried out at every 300 purposively selected farming household in the six-geopolitical zone in Nigeria. Data Analysis: A semi-structured questionnaire was administered to each farmer, and quantitative data were analyzed using Statistical Package for Social Science (SPSS) while the Chi-square test was used to analyze factors mitigating the use of Phytobiotics. Result: The result shows that the benefits associated with the use of phytobiotics are contributed to growth promotion in chickens and enhancement of productive performance of broiler and layer, which could be attributed to their antioxidant activity. The result further revealed that factors mitigating the use of phytobiotics were lack of knowledge in the use of phytobiotics, overdose or underdose usage, and seasonal availability of the phytobiotics. Others are the educational level of the farmers, intrinsic motivation, income poultry farming experience, price of phytobiotics based additives feeds, and intensity of extension agents in visiting them. Conclusion: The difficulties associated with using phytobiotics in chicken farms limit their willingness to boost productivity. The study found that most farmers were ignorant, which prevented them from handling this notion and turning their poultry into a viable enterprise while also allowing them to be creative. They believed that packing phytobiotics-based additive feed was expensive, and lastly, the seasonal availability of some phytobiotics. Recommendation: Further research in phytobiotics use in Nigeria should be carried out in order to establish its efficiency, safety, and awareness.

Keywords: mitigating, antibiotics, phytobiotics, poultry farming

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Authors: Marine Regnier, Pascal Bost, Matthieu Horgnies

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Some of the problems to be solved for the concrete industry are linked to the use of low-reactivity cement, the hardening of concrete under cold-weather and the manufacture of pre-casted concrete without costly heating step. The development of these applications needs to accelerate the hydration kinetics, in order to decrease the setting time and to obtain significant compressive strengths as soon as possible. The mechanisms enhancing the hydration kinetics of alite or Portland cement (e.g. the creation of nucleation sites) were already studied in literature (e.g. by using distinct additions such as titanium dioxide nanoparticles, calcium carbonate fillers, water-soluble polymers, C-S-H, etc.). However, the goal of this study was to establish a clear ranking of the efficiency of several types of additions by using a robust and reproducible methodology based on isothermal calorimetry (performed at 20°C). The cement was a CEM I 52.5N PM-ES (Blaine fineness of 455 m²/kg). To ensure the reproducibility of the experiments and avoid any decrease of the reactivity before use, the cement was stored in waterproof and sealed bags to avoid any contact with moisture and carbon dioxide. The experiments were performed on Portland cement pastes by using a water-to-cement ratio of 0.45, and incorporating different compounds (industrially available or laboratory-synthesized) that were selected according to their main composition and their specific surface area (SSA, calculated using the Brunauer-Emmett-Teller (BET) model and nitrogen adsorption isotherms performed at 77K). The intrinsic effects of (i) dry powders (e.g. fumed silica, activated charcoal, nano-precipitates of calcium carbonate, afwillite germs, nanoparticles of iron and iron oxides , etc.), and (ii) aqueous solutions (e.g. containing calcium chloride, hydrated Portland cement or Master X-SEED 100, etc.) were investigated. The influence of the amount of addition, calculated relatively to the dry extract of each addition compared to cement (and by conserving the same water-to-cement ratio) was also studied. The results demonstrated that the X-SEED®, the hydrated calcium nitrate, the calcium chloride (and, at a minor level, a solution of hydrated Portland cement) were able to accelerate the hydration kinetics of Portland cement, even at low concentration (e.g. 1%wt. of dry extract compared to cement). By using higher rates of additions, the fumed silica, the precipitated calcium carbonate and the titanium dioxide can also accelerate the hydration. In the case of the nano-precipitates of calcium carbonate, a correlation was established between the SSA and the accelerating effect. On the contrary, the nanoparticles of iron or iron oxides, the activated charcoal and the dried crystallised hydrates did not show any accelerating effect. Future experiments will be scheduled to establish the ranking of these additions, in terms of accelerating effect, by using low-reactivity cements and other water to cement ratios.

Keywords: acceleration, hydration kinetics, isothermal calorimetry, Portland cement

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Authors: A. Onur Kutlu, H. Tolga Bolukbasi

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Since the 1990s, governments, international organizations and scholars have drawn increasing attention to the significance of women in the labour force. While advanced industrial countries in North Western Europe and North America have managed to increase female labour force participation (FLFP) in the early post world war two period, emerging economies of the 1970s have only been able to increase FLFP only a decade later. Among these areas, Southern Europe features a wave of remarkable bounce backs in FLFP. However, despite striking similarities between the features in Southern Europe and those in Turkey, Turkey has not been able to pull women into the labour force. Despite a host of institutional similarities, Turkey has failed to reach to the level of her Southern European neighbours. This paper addresses the puzzle why Turkey lag behind in FLFP in comparison to her Southern European neighbours. There are signs showing that FLFP is currently reaching a critical threshold at a time when structural factors may allow a trend. It is not known, however, the constellation of conditions which may bring rising FLFP in Turkey. In order to gain analytical leverage from similar transitions in countries that share similar labour market and welfare state regime characteristics, this paper identifies the conditions in Southern Europe that brought rising FLFP to be able to explore the prospects for Turkey. Second, this paper takes these variables in the fuzzy set Qualitative Comparative Analysis (fsQCA) as conditions which can potentially explain the outcome of rising FLFP in Portugal, Spain, Italy, Greece and Turkey. The purpose here is to identify any causal pathway there may exist that lead to rising FLFP in Southern Europe. In order to do so, this study analyses two time periods in all cases, which represent different periods for different countries. The first period is identified on the basis of low FLFP and the second period on the basis of the transition to significantly higher FLFP. Third, the conditions are treated following the standard procedures in fsQCA, which provide equifinal: two distinct paths to higher levels of FLFP in Southern Europe, each of which may potentially increase FLFP in Turkey. Based on this analysis, this paper proposes that there exist two distinct paths leading to higher levels of FLFP in Southern Europe. Among these paths, salience of left parties emerges as a sufficient condition. In cases where this condition was not present, a second path combining enlarging service sector employment, increased tertiary education among women and increased childcare enrolment rates led to increasing FLFP.

Keywords: female labour force participation, fsQCA, Southern Europe, Turkey

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Authors: Laura Isabel Guarin, Juliana Vargas, Philippe Chang

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The analysis and study of Open Channel flow dynamics for River applications has been based on flow modelling using discreet numerical models based on hydrodynamic equations. The overall spatial characteristics of rivers, i.e. its length to depth to width ratio generally allows one to correctly disregard processes occurring in the vertical or transverse dimensions thus imposing hydrostatic pressure conditions and considering solely a 1D flow model along the river length. Through a calibration process an accurate flow model may thus be developed allowing for channel study and extrapolation of various scenarios. The Magdalena River in Colombia is a large river basin draining the country from South to North with 1550 km with 0.0024 average slope and 275 average width across. The river displays high water level fluctuation and is characterized by a series of meanders. The city of La Dorada has been affected over the years by serious flooding in the rainy and dry seasons. As the meander is evolving at a steady pace repeated flooding has endangered a number of neighborhoods. This study has been undertaken in pro of correctly model flow characteristics of the river in this region in order to evaluate various scenarios and provide decision makers with erosion control measures options and a forecasting tool. Two field campaigns have been completed over the dry and rainy seasons including extensive topographical and channel survey using Topcon GR5 DGPS and River Surveyor ADCP. Also in order to characterize the erosion process occurring through the meander, extensive suspended and river bed samples were retrieved as well as soil perforation over the banks. Hence based on DEM ground digital mapping survey and field data a 2DH flow model was prepared using the Iber freeware based on the finite volume method in a non-structured mesh environment. The calibration process was carried out comparing available historical data of nearby hydrologic gauging station. Although the model was able to effectively predict overall flow processes in the region, its spatial characteristics and limitations related to pressure conditions did not allow for an accurate representation of erosion processes occurring over specific bank areas and dwellings. As such a significant helical flow has been observed through the meander. Furthermore, the rapidly changing channel cross section as a consequence of severe erosion has hindered the model’s ability to provide decision makers with a valid up to date planning tool.

Keywords: erosion, finite volume method, flow dynamics, flow modelling, meander

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Authors: Vilma Zydziunaite, Monika Kelpsiene

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In early childhood and preschool education, play has an important role in learning and cognitive processes. In the context of a changing world, personal autonomy and the use of technology are becoming increasingly important for the development of a wide range of learner competencies. By integrating technology into learning environments, the educational reality is changed, promoting unusual learning experiences for children through play-based activities. Alongside this, teachers are challenged to develop encouragement and motivation strategies that empower children to act independently. The aim of the study was to reveal the changes in the roles and experiences of teachers in the application of AR technology for the enrichment of the learning process. A quantitative research approach was used to conduct the study. The data was collected through an electronic questionnaire. Participants: 319 teachers of 5-6-year-old children using AR technology tools in their educational process. Methods of data analysis: Cronbach alpha, descriptive statistical analysis, normal distribution analysis, correlation analysis, regression analysis (SPSS software). Results. The results of the study show a significant relationship between children's learning and the educational process modeled by the teacher. The strongest predictor of child learning was found to be related to the role of the educator. Other predictors, such as pedagogical strategies, the concept of AR technology, and areas of children's education, have no significant relationship with child learning. The role of the educator was found to be a strong determinant of the child's learning process. Conclusions. The greatest potential for integrating AR technology into the teaching-learning process is revealed in collaborative learning. Teachers identified that when integrating AR technology into the educational process, they encourage children to learn from each other, develop problem-solving skills, and create inclusive learning contexts. A significant relationship has emerged - how the changing role of the teacher relates to the child's learning style and the aspiration for personal leadership and responsibility for their learning. Teachers identified the following key roles: observer of the learning process, proactive moderator, and creator of the educational context. All these roles enable the learner to become an autonomous and active participant in the learning process. This provides a better understanding and explanation of why it becomes crucial to empower the learner to experiment, explore, discover, actively create, and foster collaborative learning in the design and implementation of the educational content, also for teachers to integrate AR technologies and the application of the principles of shared leadership. No statistically significant relationship was found between the understanding of the definition of AR technology and the teacher’s choice of role in the learning process. However, teachers reported that their understanding of the definition of AR technology influences their choice of role, which has an impact on children's learning.

Keywords: teacher, learner, augmented reality, collaboration, shared leadership, preschool education

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Authors: Sina Kazemi, Farshid Torabi, Todd Peterson

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Drilling in shale formations is frequently time-consuming, challenging, and fraught with mechanical failures such as stuck pipes or hole packing off when the cutting removal rate is not sufficient to clean the bottom hole. Crossing the heavy oil shale and sand reservoirs with active shale and microfractures is generally associated with severe fluid losses causing a reduction in the rate of the cuttings removal. These circumstances compromise a well’s integrity and result in a lower rate of penetration (ROP). This study presents collective results of field studies and theoretical analysis conducted on data from South Pars and North Dome in an Iran-Qatar offshore field. Solutions to complications related to drilling in shale formations are proposed through systemically analyzing and applying modeling techniques to select field mud logging data. Field data measurements during actual drilling operations indicate that in a shale formation where the return flow of polymer mud was almost lost in the upper dolomite layer, the performance of hole cleaning and ROP progressively change when higher string rotations are initiated. Likewise, it was observed that this effect minimized the force of rotational torque and improved well integrity in the subsequent casing running. Given similar geologic conditions and drilling operations in reservoirs targeting shale as the producing zone like the Bakken formation within the Williston Basin and Lloydminster, Saskatchewan, a drill bench dynamic modeling simulation was used to simulate borehole cleaning efficiency and mud optimization. The results obtained by altering RPM (string revolution per minute) at the same pump rate and optimized mud properties exhibit a positive correlation with field measurements. The field investigation and developed model in this report show that increasing the speed of string revolution as far as geomechanics and drilling bit conditions permit can minimize the risk of mechanically stuck pipes while reaching a higher than expected ROP in shale formations. Data obtained from modeling and field data analysis, optimized drilling parameters, and hole cleaning procedures are suggested for minimizing the risk of a hole packing off and enhancing well integrity in shale reservoirs. Whereas optimization of ROP at a lower pump rate maintains the wellbore stability, it saves time for the operator while reducing carbon emissions and fatigue of mud motors and power supply engines.

Keywords: ROP, circulating density, drilling parameters, return flow, shale reservoir, well integrity

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Authors: Nathaniel Oladimeji Dixon, Adekemi Dorcas Fadun

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Educational managers have observed a downward trend in the administrative effectiveness of non-teaching staff in federal universities in South-west Nigeria. This is evident in the low-quality service delivery of administrators and unaccomplished institutional goals and missions of higher education. Scholars have thus indicated the need for the deployment and adoption of a practice that encourages information collection and sharing among stakeholders with a view to improving service delivery and outcomes. This study examined the extent to which knowledge management correlated with the administrative effectiveness of non-teaching staff in federal universities in South-west Nigeria. The study adopted the survey design. Three federal universities (the University of Ibadan, Federal University of Agriculture, Abeokuta, and Obafemi Awolowo University) were purposively selected because administrative ineffectiveness was more pronounced among non-teaching staff in government-owned universities, and these federal universities were long established. The proportional and stratified random sampling was adopted to select 1156 non-teaching staff across the three universities along the three existing layers of the non-teaching staff: secretarial (senior=311; junior=224), non-secretarial (senior=147; junior=241) and technicians (senior=130; junior=103). Knowledge Management Practices Questionnaire with four sub-scales: knowledge creation (α=0.72), knowledge utilization (α=0.76), knowledge sharing (α=0.79) and knowledge transfer (α=0.83); and Administrative Effectiveness Questionnaire with four sub-scales: communication (α=0.84), decision implementation (α=0.75), service delivery (α=0.81) and interpersonal relationship (α=0.78) were used for data collection. Data were analyzed using descriptive statistics, Pearson product-moment correlation and multiple regression at 0.05 level of significance, while qualitative data were content analyzed. About 59.8% of the non-teaching staff exhibited a low level of knowledge management. The indices of administrative effectiveness of non-teaching staff were rated as follows: service delivery (82.0%), communication (78.0%), decision implementation (71.0%) and interpersonal relationship (68.0%). Knowledge management had significant relationships with the indices of administrative effectiveness: service delivery (r=0.82), communication (r=0.81), decision implementation (r=0.80) and interpersonal relationship (r=0.47). Knowledge management had a significant joint prediction on administrative effectiveness (F (4;1151)= 0.79, R=0.86), accounting for 73.0% of its variance. Knowledge sharing (β=0.38), knowledge transfer (β=0.26), knowledge utilization (β=0.22), and knowledge creation (β=0.06) had relatively significant contributions to administrative effectiveness. Lack of team spirit and withdrawal syndrome is the major perceived constraints to knowledge management practices among the non-teaching staff. Knowledge management positively influenced the administrative effectiveness of the non-teaching staff in federal universities in South-west Nigeria. There is a need to ensure that the non-teaching staff imbibe team spirit and embrace teamwork with a view to eliminating their withdrawal syndromes. Besides, knowledge management practices should be deployed into the administrative procedures of the university system.

Keywords: knowledge management, administrative effectiveness of non-teaching staff, federal universities in the south-west of nigeria., knowledge creation, knowledge utilization, effective communication, decision implementation

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Authors: Mihail Calalb

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The aim of this research is to identify ways for achieving sustainable conceptual understanding within science lessons. For this purpose, a set of teaching and learning strategies, parts of the theory of visible teaching and learning (VTL), is studied. As a result, a new didactic approach named "learning by being" is proposed and its correlation with educational paradigms existing nowadays in science teaching domain is analysed. In the context of VTL the author describes the main strategies of "learning by being" such as guided self-scaffolding, structuring of information, and recurrent use of previous knowledge or help seeking. Due to the synergy effect of these learning strategies applied simultaneously in class, the impact factor of learning by being on cognitive achievement of students is up to 93 % (the benchmark level is equal to 40% when an experienced teacher applies permanently the same conventional strategy during two academic years). The key idea in "learning by being" is the assumption by the student of cognitive goals. From this perspective, the article discusses the role of student’s personal learning effort within several teaching strategies employed in VTL. The research results emphasize that three mandatory student – related moments are present in each constructivist teaching approach: a) students’ personal learning effort, b) student – teacher mutual feedback and c) metacognition. Thus, a successful educational strategy will target to achieve an involvement degree of students into the class process as high as possible in order to make them not only know the learning objectives but also to assume them. In this way, we come to the ownership of cognitive goals or students’ deep intrinsic motivation. A series of approaches are inherent to the students’ ownership of cognitive goals: independent research (with an impact factor on cognitive achievement equal to 83% according to the results of VTL); knowledge of success criteria (impact factor – 113%); ability to reveal similarities and patterns (impact factor – 132%). Although it is generally accepted that the school is a public service, nonetheless it does not belong to entertainment industry and in most of cases the education declared as student – centered actually hides the central role of the teacher. Even if there is a proliferation of constructivist concepts, mainly at the level of science education research, we have to underline that conventional or frontal teaching, would never disappear. Research results show that no modern method can replace an experienced teacher with strong pedagogical content knowledge. Such a teacher will inspire and motivate his/her students to love and learn physics. The teacher is precisely the condensation point for an efficient didactic strategy – be it constructivist or conventional. In this way, we could speak about "hybridized teaching" where both the student and the teacher have their share of responsibility. In conclusion, the core of "learning by being" approach is guided learning effort that corresponds to the notion of teacher–student harmonic oscillator, when both things – guidance from teacher and student’s effort – are equally important.

Keywords: conceptual understanding, learning by being, ownership of cognitive goals, science learning

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Authors: Simon Caba, Raja Abou Ackl, Svend Rasmussen, Nicholas E. Pedersen

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It is a challenge to directly monitor cavitation in a pump application during operation because of a lack of visual access to validate the presence of cavitation and its form of appearance. In this work, experimental investigations are carried out in an inline single-stage centrifugal pump with optical access. Hence, it gives the opportunity to enhance the value of CFD tools and standard cavitation measurements. Experiments are conducted using two impellers running in the same volute at 3000 rpm and the same flow rate. One of the impellers used is optimized for lower NPSH₃% by its blade design, whereas the other one is manufactured using a standard casting method. The cavitation is detected by pump performance measurements, vibration measurements and high-speed image recordings. The head drop and the pump casing vibration caused by cavitation are correlated with the visual appearance of the cavitation. The vibration data is recorded in an axial direction of the impeller using accelerometers recording at a sample rate of 131 kHz. The vibration frequency domain data (up to 20 kHz) and the time domain data are analyzed as well as the root mean square values. The high-speed recordings, focusing on the impeller suction side, are taken at 10,240 fps to provide insight into the flow patterns and the cavitation behavior in the rotating impeller. The videos are synchronized with the vibration time signals by a trigger signal. A clear correlation between cloud collapses and abrupt peaks in the vibration signal can be observed. The vibration peaks clearly indicate cavitation, especially at higher NPSHA values where the hydraulic performance is not affected. It is also observed that below a certain NPSHA value, the cavitation started in the inlet bend of the pump. Above this value, cavitation occurs exclusively on the impeller blades. The impeller optimized for NPSH₃% does show a lower NPSH₃% than the standard impeller, but the head drop starts at a higher NPSHA value and is more gradual. Instabilities in the head drop curve of the optimized impeller were observed in addition to a higher vibration level. Furthermore, the cavitation clouds on the suction side appear more unsteady when using the optimized impeller. The shape and location of the cavitation are compared to 3D fluid flow simulations. The simulation results are in good agreement with the experimental investigations. In conclusion, these investigations attempt to give a more holistic view on the appearance of cavitation by comparing the head drop, vibration spectral data, vibration time signals, image recordings and simulation results. Data indicates that a criterion for cavitation detection could be derived from the vibration time-domain measurements, which requires further investigation. Usually, spectral data is used to analyze cavitation, but these investigations indicate that the time domain could be more appropriate for some applications.

Keywords: cavitation, centrifugal pump, head drop, high-speed image recordings, pump vibration

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Authors: Anita Richter

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Innovation is one of the key foundations of competitive advantage, generating growth and welfare worldwide. Consequently, all firms should innovate to bring new ideas to the market. Innovation is a vital growth driver, particularly for transition countries to move towards knowledge-based, high-income economies. However, numerous barriers, such as financial, regulatory or infrastructural constraints prevent, in particular, new and small firms in transition countries from innovating. Thus SMEs’ innovation output may benefit substantially from government support. This research paper aims to assess the effect of government interventions on innovation activities in SMEs in emerging countries. Until now academic research related to the innovation policies focused either on single country and/or high-income countries assessments and less on cross-country and/or low and middle-income countries. Therefore the paper seeks to close the research gap by providing empirical evidence from 8,500 firms in 15 transition countries (Eastern Europe, South Caucasus, South East Europe, Middle East and North Africa). Using firm-level data from the Business Environment and Enterprise Performance Survey of the World Bank and EBRD and policy data from the SME Policy Index of the OECD, the paper investigates how government interventions affect SME’s likelihood of investing in any technological and non-technological innovation. Using the Standard Linear Regression, the impact of government interventions on SMEs’ innovation output and R&D activities is measured. The empirical analysis suggests that a firm’s decision to invest into innovative activities is sensitive to government interventions. A firm’s likelihood to invest into innovative activities increases by 3% to 8%, if the innovation eco-system noticeably improves (measured by an increase of 1 level in the SME Policy Index). At the same time, a better eco-system encourages SMEs to invest more in R&D. Government reforms in establishing a dedicated policy framework (IP legislation), institutional infrastructure (science and technology parks, incubators) and financial support (public R&D grants, innovation vouchers) are particularly relevant to stimulate innovation performance in SMEs. Particular segments of the SME population, namely micro and manufacturing firms, are more likely to benefit from an increased innovation framework conditions. The marginal effects are particularly strong on product innovation, process innovation, and marketing innovation, but less on management innovation. In conclusion, government interventions supporting innovation will likely lead to higher innovation performance of SMEs. They increase productivity at both firm and country level, which is a vital step in transitioning towards knowledge-based market economies.

Keywords: innovation, research and development, government interventions, economic development, small and medium-sized enterprises, transition countries

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Authors: Jemely M. Punzalan, Christine B. Bernal, Beatrice B. Canonigo, Maria Rosario F. Cabansag, Dennis S. Flores, Paul Joseph T. Galutira, Remedios D. Chan

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Background: Systemic lupus erythematosus (SLE) is one of the most common autoimmune disorders predominates in women of childbearing age. Simple Measure of Impact of Lupus Erythematosus in Youngsters (SMILEY) is the only health specific quality of life tool for pediatric SLE, which has been translated to different languages except in Filipino. Objective: The primary objective of this study was to develop a Filipino translation of the SMILEY and to examine the validity and reliability of this translation. Methodology: The SMILEY was translated into Filipino by a bilingual individual and back-translated by another bilingual individual blinded from the original English version. The translation was evaluated for content validity by a panel of experts and subjected to pilot testing. The pilot-tested translation was used in the validity and reliability testing proper. The SMILEY, together with the previously validated PEDSQL 4.0 Generic Core Scale was administered to lupus pediatric patients and their parent at two separate occasions: a baseline and a re-test seven to fourteen days apart. Tests for convergent validity, internal consistency, and test-retest reliability were performed. Results: A total of fifty children and their parent were recruited. The mean age was 15.38±2.62 years (range 8-18 years), mean education at high school level. The mean duration of SLE was 28 months (range 1-81 months). Subjects found the questionnaires to be relevant, easy to understand and answer. The validity of the SMILEY was demonstrated in terms of content validity, convergent validity, internal consistency, and test-retest reliability. Age, socioeconomic status and educational attainment did not show a significant effect on the scores. The difference between scores of child and parent report was showed to be significant with SMILEY total (p=0.0214), effect on social life (p=0.0000), and PEDSQL physical function (p=0.0460). Child reports showed higher scores for the following domains compared to their parent. Conclusion: SMILEY is a brief, easy to understand, valid and reliable tool for assessing pediatric SLE specific HRQOL. It will be useful in providing better care, understanding and may offer critical information regarding the effect of SLE in the quality of life of our pediatric lupus patients. It will help physician understands the needs of their patient not only on treatment of the specific disease but as well as the impact of the treatment on their daily lives.

Keywords: systemic lupus erythematosus, pediatrics, quality of life, Simple Measure of Impact of Lupus Erythematosus in Youngsters (SMILEY)

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Authors: Ning Chang, Zelong Yuan, Yunpeng Wang, Jianchun Wang

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Large eddy simulation (LES) has been extensively used in the investigation of turbulence. LES calculates the grid-resolved large-scale motions and leaves small scales modeled by sublfilterscale (SFS) models. Among the existing SFS models, the deconvolution model has been used successfully in the LES of the engineering flows and geophysical flows. Despite the wide application of deconvolution models, the effects of subfilter scale dynamics and filter anisotropy on the accuracy of SFS modeling have not been investigated in depth. The results of LES are highly sensitive to the selection of filters and the anisotropy of the grid, which has been overlooked in previous research. In the current study, two critical aspects of LES are investigated. Firstly, we analyze the influence of sub-filter scale (SFS) dynamics on the accuracy of direct deconvolution models (DDM) at varying filter-to-grid ratios (FGR) in isotropic turbulence. An array of invertible filters are employed, encompassing Gaussian, Helmholtz I and II, Butterworth, Chebyshev I and II, Cauchy, Pao, and rapidly decaying filters. The significance of FGR becomes evident, as it acts as a pivotal factor in error control for precise SFS stress prediction. When FGR is set to 1, the DDM models cannot accurately reconstruct the SFS stress due to the insufficient resolution of SFS dynamics. Notably, prediction capabilities are enhanced at an FGR of 2, resulting in accurate SFS stress reconstruction, except for cases involving Helmholtz I and II filters. A remarkable precision close to 100% is achieved at an FGR of 4 for all DDM models. Additionally, the further exploration extends to the filter anisotropy to address its impact on the SFS dynamics and LES accuracy. By employing dynamic Smagorinsky model (DSM), dynamic mixed model (DMM), and direct deconvolution model (DDM) with the anisotropic filter, aspect ratios (AR) ranging from 1 to 16 in LES filters are evaluated. The findings highlight the DDM's proficiency in accurately predicting SFS stresses under highly anisotropic filtering conditions. High correlation coefficients exceeding 90% are observed in the a priori study for the DDM's reconstructed SFS stresses, surpassing those of the DSM and DMM models. However, these correlations tend to decrease as lter anisotropy increases. In the a posteriori studies, the DDM model consistently outperforms the DSM and DMM models across various turbulence statistics, encompassing velocity spectra, probability density functions related to vorticity, SFS energy flux, velocity increments, strain-rate tensors, and SFS stress. It is observed that as filter anisotropy intensify, the results of DSM and DMM become worse, while the DDM continues to deliver satisfactory results across all filter-anisotropy scenarios. The findings emphasize the DDM framework's potential as a valuable tool for advancing the development of sophisticated SFS models for LES of turbulence.

Keywords: deconvolution model, large eddy simulation, subfilter scale modeling, turbulence

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Authors: Gautier Girard, Marion Martiny, Sebastien Mercier, Mohamad Jrad, Mohamed-Slim Bahi, Laurent Bodin, Francois Lechleiter, David Nevo, Sophie Dareys

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Reliability of electronic devices has always been of highest interest for Aero-MIL and space applications. In any electronic device, Printed Circuit Board (PCB), providing interconnection between components, is a key for reliability. During the last decades, PCB technologies evolved to sustain and/or fulfill increased original equipment manufacturers requirements and specifications, higher densities and better performances, faster time to market and longer lifetime, newer material and mixed buildups. From the very beginning of the PCB industry up to recently, qualification, experiments and trials, and errors were the most popular methods to assess system (PCB) reliability. Nowadays OEM, PCB manufacturers and scientists are working together in a close relationship in order to develop predictive models for PCB reliability and lifetime. To achieve that goal, it is fundamental to characterize precisely base materials (laminates, electrolytic copper, …), in order to understand failure mechanisms and simulate PCB aging under environmental constraints by means of finite element method for example. The laminates are woven composites and have thus an orthotropic behaviour. The in-plane properties can be measured by combining classical uniaxial testing and digital image correlation. Nevertheless, the out-of-plane properties cannot be evaluated due to the thickness of the laminate (a few hundred of microns). It has to be noted that the knowledge of the out-of-plane properties is fundamental to investigate the lifetime of high density printed circuit boards. A homogenization method combining analytical and numerical approaches has been developed in order to obtain the complete elastic orthotropic behaviour of a woven composite from its precise 3D internal structure and its experimentally measured in-plane elastic properties. Since the mechanical properties of the resin surrounding the fibres are unknown, an inverse method is proposed to estimate it. The methodology has been applied to one laminate used in hyperfrequency spatial applications in order to get its elastic orthotropic behaviour at different temperatures in the range [-55°C; +125°C]. Next; numerical simulations of a plated through hole in a double sided PCB are performed. Results show the major importance of the out-of-plane properties and the temperature dependency of these properties on the lifetime of a printed circuit board. Acknowledgements—The support of the French ANR agency through the Labcom program ANR-14-LAB7-0003-01, support of CNES, Thales Alenia Space and Cimulec is acknowledged.

Keywords: homogenization, orthotropic behaviour, printed circuit board, woven composites

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Authors: Fouzia Khanam, Tridib Chowdhury, Belal Hossain, Sajedur Rahman, Mahfuzar Rahman

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Introduction: Over the last decades, the world has achieved a noticeable success in preventing malaria. Nevertheless, malaria, a vector-borne infectious disease, remains a major public health burden globally as well as in Bangladesh. To achieve the goal of eliminating malaria, BRAC, a leading organization of Bangladesh in collaboration with government, is distributing free LLIN to the 13 endemic districts of the country. The study was conducted with the aim of assessing the gap between coverage, access, and utilization of LLIN among the people of the 13 malaria endemic districts of Bangladesh. Methods: This baseline study employed a community cross-sectional design triangulated with qualitative methods to measure households’ ownership, access and use of 13 endemic districts. A multistage cluster random sampling was employed for the quantitative part and for qualitative part a purposive sampling strategy was done. Thus present analysis included 2640 households encompassing a total of 14475 populations. Data were collected using a pre-tested structured questionnaire through one on one face-to-face interview with respondents. All analyses were performed using STATA (Version 13.0). For the qualitative part participant observation, in-depth interview, focus group discussion, key informant interview and informal interview was done to gather the contextual data. Findings: According to our study, 99.8% of households possessed at least one-bed net in both study areas. 77.4% households possessed at least two LLIN and 43.2% households had access to LLIN for all the members. So the gap between coverage and access is 34%. 91.8% people in the 13 districts and 95.1% in Chittagong Hill Tracts areas reported having had slept under a bed net the night before interviewed. And despite the relatively low access, in 77.8% of households, all the members were used the LLIN the previous night. This higher utilization compared to access might be due to the increased awareness among the community people regarding LLIN uses. However, among those people with sufficient access to LLIN, 6% of them still did not use the LLIN which reflects the behavioral failure that needs to be addressed. The major reasons for not using LLIN, identified by both qualitative and quantitative findings, were insufficient access, sleeping or living outside the home, migration, perceived low efficacy of LLIN, fear of physical side effects or feeling uncomfortable. Conclusion: Given that LLIN access and use was a bit short of the targets, it conveys important messages to the malaria control program. Targeting specific population segments and groups for achieving expected LLIN coverage is very crucial. And also, addressing behavior failure by well-designed behavioral change interventions is mandatory.

Keywords: long lasting insecticide net, malaria, malaria control programme, World Health Organisation

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Authors: Aziz Ikhlef

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Most of multi-slices CT scanners are built with detectors composed of scintillator - photodiodes arrays. The photodiodes arrays are mainly based on front-illuminated technology for detectors under 64 slices and on back-illuminated photodiode for systems of 64 slices or more. The designs based on back-illuminated photodiodes were being investigated for CT machines to overcome the challenge of the higher number of runs and connection required in front-illuminated diodes. In backlit diodes, the electronic noise has already been improved because of the reduction of the load capacitance due to the routing reduction. This translated by a better image quality in low signal application, improving low dose imaging in large patient population. With the fast development of multi-detector-rows CT (MDCT) scanners and the increasing number of examinations, the clinical community has raised significant concerns on radiation dose received by the patient in both medical and regulatory community. In order to reduce individual exposure and in response to the recommendations of the International Commission on Radiological Protection (ICRP) which suggests that all exposures should be kept as low as reasonably achievable (ALARA), every manufacturer is trying to implement strategies and solutions to optimize dose efficiency and image quality based on x-ray emission and scanning parameters. The added demands on the CT detector performance also comes from the increased utilization of spectral CT or dual-energy CT in which projection data of two different tube potentials are collected. One of the approaches utilizes a technology called fast-kVp switching in which the tube voltage is switched between 80kVp and 140kVp in fraction of a millisecond. To reduce the cross-contamination of signals, the scintillator based detector temporal response has to be extremely fast to minimize the residual signal from previous samples. In addition, this paper will present an overview of detector technologies and image chain improvement which have been investigated in the last few years to improve the signal-noise ratio and the dose efficiency CT scanners in regular examinations and in energy discrimination techniques. Several parameters of the image chain in general and in the detector technology contribute in the optimization of the final image quality. We will go through the properties of the post-patient collimation to improve the scatter-to-primary ratio, the scintillator material properties such as light output, afterglow, primary speed, crosstalk to improve the spectral imaging, the photodiode design characteristics and the data acquisition system (DAS) to optimize for crosstalk, noise and temporal/spatial resolution.

Keywords: computed tomography, X-ray detector, medical imaging, image quality, artifacts

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Authors: Ahmad S. Darwish, Tarek Lemaoui, Hanifa Taher, Inas M. AlNashef, Fawzi Banat

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This research reports a systematic top-down approach for designing neoteric hydrophobic solvents –particularly, deep eutectic solvents (DES) and ionic liquids (IL)– as furfural extractants from aqueous media for the application of sustainable biomass conversion. The first stage of the framework entailed screening 32 neoteric solvents to determine their efficacy against toluene as the application’s conventional benchmark for comparison. The selection criteria for the best solvents encompassed not only their efficiency in extracting furfural but also low viscosity and minimal toxicity levels. Additionally, for the DESs, their natural origins, availability, and biodegradability were also taken into account. From the screening pool, two neoteric solvents were selected: thymol:decanoic acid 1:1 (Thy:DecA) and trihexyltetradecyl phosphonium bis(trifluoromethylsulfonyl) imide [P₁₄,₆,₆,₆][NTf₂]. These solvents outperformed the toluene benchmark, achieving efficiencies of 94.1% and 97.1% respectively, compared to toluene’s 81.2%, while also possessing the desired properties. These solvents were then characterized thoroughly in terms of their physical properties, thermal properties, critical properties, and cross-contamination solubilities. The selected neoteric solvents were then extensively tested under various operating conditions, and an exceptional stable performance was exhibited, maintaining high efficiency across a broad range of temperatures (15–100 °C), pH levels (1–13), and furfural concentrations (0.1–2.0 wt%) with a remarkable equilibrium time of only 2 minutes, and most notably, demonstrated high efficiencies even at low solvent-to-feed ratios. The durability of the neoteric solvents was also validated to be stable over multiple extraction-regeneration cycles, with limited leachability to the aqueous phase (≈0.1%). Moreover, the extraction performance of the solvents was then modeled through machine learning, specifically multiple non-linear regression (MNLR) and artificial neural networks (ANN). The models demonstrated high accuracy, indicated by their low absolute average relative deviations with values of 2.74% and 2.28% for Thy:DecA and [P₁₄,₆,₆,₆][NTf₂], respectively, using MNLR, and 0.10% for Thy:DecA and 0.41% for [P₁₄,₆,₆,₆][NTf₂] using ANN, highlighting the significantly enhanced predictive accuracy of the ANN. The neoteric solvents presented herein offer noteworthy advantages over traditional organic solvents, including their high efficiency in both extraction and regeneration processes, their stability and minimal leachability, making them particularly suitable for applications involving aqueous media. Moreover, these solvents are more environmentally friendly, incorporating renewable and sustainable components like thymol and decanoic acid. This exceptional efficacy of the newly developed neoteric solvents signifies a significant advancement, providing a green and sustainable alternative for furfural production from biowaste.

Keywords: sustainable biomass conversion, furfural extraction, ionic liquids, deep eutectic solvents

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Authors: S. Chuenchooklin, S. Taweepong, U. Pangnakorn

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This research was conducted in the Mae Sot Watershed whereas located in the Moei River Basin at the Upper Salween River Basin in Tak Province, Thailand. The Mae Sot Municipality is the largest urbanized in Tak Province and situated in the midstream of the Mae Sot Watershed. It usually faces flash flood problem after heavy rain due to poor flood management has been reported since economic rapidly bloom up in recently years. Its catchment can be classified as ungauged basin with lack of rainfall data and no any stream gaging station was reported. It was attached by most severely flood event in 2013 as the worst studied case for those all communities in this municipality. Moreover, other problems are also faced in this watershed such shortage water supply for domestic consumption and agriculture utilizations including deterioration of water quality and landslide as well. The research aimed to increase capability building and strengthening the participation of those local community leaders and related agencies to conduct better water management in urban area was started by mean of the data collection and illustration of appropriated application of some short period rainfall forecasting model as the aim for better flood relief plan and management through the hydrologic model system and river analysis system programs. The authors intended to apply the global rainfall data via the integrated data viewer (IDV) program from the Unidata with the aim for rainfall forecasting in short period of 7 - 10 days in advance during rainy season instead of real time record. The IDV product can be present in advance period of rainfall with time step of 3 - 6 hours was introduced to the communities. The result can be used to input to either the hydrologic modeling system model (HEC-HMS) or the soil water assessment tool model (SWAT) for synthesizing flood hydrographs and use for flood forecasting as well. The authors applied the river analysis system model (HEC-RAS) to present flood flow behaviors in the reach of the Mae Sot stream via the downtown of the Mae Sot City as flood extents as water surface level at every cross-sectional profiles of the stream. Both models of HMS and RAS were tested in 2013 with observed rainfall and inflow-outflow data from the Mae Sot Dam. The result of HMS showed fit to the observed data at dam and applied at upstream boundary discharge to RAS in order to simulate flood extents and tested in the field, and the result found satisfied. The result of IDV’s rainfall forecast data was compared to observed data and found fair. However, it is an appropriate tool to use in the ungauged catchment to use with flood hydrograph and river analysis models for future efficient flood relief plan and management.

Keywords: global rainfall, flood forecast, hydrologic modeling system, river analysis system

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Authors: Shrabani Ghosh

Abstract:

Automatic offensive language detection in social media has become a stirring task in today's NLP. Manual Offensive language detection is tedious and laborious work where automatic methods based on machine learning are only alternatives. Previous works have done sentiment analysis over social media in different ways such as supervised, semi-supervised, and unsupervised manner. Domain adaptation in a semi-supervised way has also been explored in NLP, where the source domain and the target domain are different. In domain adaptation, the source domain usually has a large amount of labeled data, while only a limited amount of labeled data is available in the target domain. Pretrained transformers like BERT, RoBERTa models are fine-tuned to perform text classification in an unsupervised manner to perform further pre-train masked language modeling (MLM) tasks. In previous work, hate speech detection has been explored in Gab.ai, which is a free speech platform described as a platform of extremist in varying degrees in online social media. In domain adaptation process, Twitter data is used as the source domain, and Gab data is used as the target domain. The performance of domain adaptation also depends on the cross-domain similarity. Different distance measure methods such as L2 distance, cosine distance, Maximum Mean Discrepancy (MMD), Fisher Linear Discriminant (FLD), and CORAL have been used to estimate domain similarity. Certainly, in-domain distances are small, and between-domain distances are expected to be large. The previous work finding shows that pretrain masked language model (MLM) fine-tuned with a mixture of posts of source and target domain gives higher accuracy. However, in-domain performance of the hate classifier on Twitter data accuracy is 71.78%, and out-of-domain performance of the hate classifier on Gab data goes down to 56.53%. Recently self-supervised learning got a lot of attention as it is more applicable when labeled data are scarce. Few works have already been explored to apply self-supervised learning on NLP tasks such as sentiment classification. Self-supervised language representation model ALBERTA focuses on modeling inter-sentence coherence and helps downstream tasks with multi-sentence inputs. Self-supervised attention learning approach shows better performance as it exploits extracted context word in the training process. In this work, a self-supervised attention mechanism has been proposed to detect hate speech on Gab.ai. This framework initially classifies the Gab dataset in an attention-based self-supervised manner. On the next step, a semi-supervised classifier trained on the combination of labeled data from the first step and unlabeled data. The performance of the proposed framework will be compared with the results described earlier and also with optimized outcomes obtained from different optimization techniques.

Keywords: attention learning, language model, offensive language detection, self-supervised learning

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Authors: M. Iqbal Hossain, Azharul Islam Khan, S. M. Rafiqul Islam, Tahmeed Ahmed

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Objective: Moderate acute malnutrition (MAM) is a major cause of morbidity and mortality in under-5 children of low-income countries. Approximately 14.6% of all under-5 mortality worldwide is attributed to MAM with >3 times increased risk of death compared to well-nourished peers. Prevalence of MAM among under-5 children in Bangladesh is ~12% (~1.7 million). Providing a diet containing adequate nutrients is the mainstay of treatment of children with MAM. It is now possible to process fish into fish peptides with longer shelf-life without refrigerator, known as ‘Fish Surimi peptide’ and this could be an attractive alternative to supply fish protein in the diet of children in low-income countries like Bangladesh. We conducted this study to assess the acceptability of Fish Surimi peptide given with various foods/meals in 2-5 years old children with MAM. Design/methods: Fish Surimi peptide is broken down from white fish meat using plant-derived enzyme and the ingredient is just fish meat consisted of 20 different kinds of amino acids including nine essential amino acids. In a convenience sample of 34 children we completed the study ward of Dhaka Hospital of icddr,b in Bangladesh during November 2014 through February 2015. For each child the study was for two consecutive days: i.e. direct observation of food intake of two lunches and two suppers. In a randomly and blinded manner and cross over design an individual child received Fish Surimi peptide (5g at lunch and 5g at supper) mixed meal [e.g. 30g rice and 30g dahl (thick lentil soup) or 60g of a vegetables-lentil-rice mixed local dish known as khichuri in one day and the same meal on other day without any Fish Surimi peptide. We observed the completeness and eagerness of eating and any possible side effect (e.g. allergy, vomiting, diarrhea etc.) over these two days. Results: The mean±SD age of the enrolled children was 38.4±9.4 months, weight 11.22±1.41 kg, height 91.0±6.3 cm, and WHZ was -2.13±0.76. Their mean±SD total feeding time (minutes) for lunch was 25.4±13.6 vs. 20.6±11.1 (p=0.130) and supper was 22.3±9.7 vs. 19.7±11.2 (p=0.297), and total amount (g) of food eaten in lunch and supper was found similar 116.1±7.0 vs. 117.7±8.0 (p=3.01) in A (Fish Surimi) and B group respectively. Score in Hedonic scale by mother on test of food given to children at lunch or supper was 3.9±0.2 vs. 4.0±0.2 (p=0.317) and on overall acceptance (including the texture, smell, and appearance) of food at lunch or supper was 3.9±0.2 vs. 4.0±0.2 (p=0.317) for A and B group respectively. No adverse event was observed in any food group during the study period. Conclusions: Fish Surimi peptide may be a cost effective supplementary food, which should be tested by appropriately designed randomized community level intervention trial both in wasted children and stunted children.

Keywords: protein-energy malnutrition, moderate acute malnutrition, weight-for-height z-score, mid upper arm circumference, acceptability, fish surimi peptide, under-5 children

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Authors: Rasha Waheeb, Bjorn Andersen, Rafa Shakir

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Purpose The purpose of this study is to avoid delays that occur in emergency reconstruction projects especially in post disaster circumstances whether if they were natural or manmade due to their particular national and humanitarian importance. We presented a theoretical and practical concepts for projects management in the field of construction industry that deal with a range of global and local trails. This study aimed to identify the factors of effective delay in construction projects in Iraq that affect the time and the specific quality cost, and find the best solutions to address delays and solve the problem by setting parameters to restore balance in this study. 30 projects were selected in different areas of construction were selected as a sample for this study. Design/methodology/approach This study discusses the reconstruction strategies and delay in time and cost caused by different delay factors in some selected projects in Iraq (Baghdad as a case study).A case study approach was adopted, with thirty construction projects selected from the Baghdad region, of different types and sizes. Project participants from the case projects provided data about the projects through a data collection instrument distributed through a survey. Mixed approach and methods were applied in this study. Mathematical data analysis was used to construct models to predict delay in time and cost of projects before they started. The artificial neural networks analysis was selected as a mathematical approach. These models were mainly to help decision makers in construction project to find solutions to these delays before they cause any inefficiency in the project being implemented and to strike the obstacles thoroughly to develop this industry in Iraq. This approach was practiced using the data collected through survey and questionnaire data collection as information form. Findings The most important delay factors identified leading to schedule overruns were contractor failure, redesigning of designs/plans and change orders, security issues, selection of low-price bids, weather factors, and owner failures. Some of these are quite in line with findings from similar studies in other countries/regions, but some are unique to the Iraqi project sample, such as security issues and low-price bid selection. Originality/value we selected ANN’s analysis first because ANN’s was rarely used in project management , and never been used in Iraq to finding solutions for problems in construction industry. Also, this methodology can be used in complicated problems when there is no interpretation or solution for a problem. In some cases statistical analysis was conducted and in some cases the problem is not following a linear equation or there was a weak correlation, thus we suggested using the ANN’s because it is used for nonlinear problems to find the relationship between input and output data and that was really supportive.

Keywords: construction projects, delay factors, emergency reconstruction, innovation ANN, post disasters, project management

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Authors: Celestine Odigwe, Epoke Lincoln, Rhoda-Dara Ephraim

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Background; Immunization against the childhood killer diseases is the cardinal strategy for the prevention of these diseases all over the world in under five children, these diseases include; Tuberculosis, Measles, Polio, Tetanus, Diphthria, Pertusis, Yellow Fever, Hepatitis B, Haemophilus Influenza type B. 6.9 million children die before their fifth birthday , 80% of the worlds death in children under 5 years occur in 25 countries most in Africa and Asia and 2 million children can be saved each year with routine immunization Therefore failure to achieve total immunization coverage puts several children at risk. Aim; The aim of the study was to ascertain the prevalence, Investigate the various reasons and causes why several under five children in a suburb of calabar municipal county fail to get the required immunizations as at and when due and possibly the consequences, so that efforts can be re-directed towards the solution of the problems so identified. Methods; the study was a community based cross sectional study. The respondents were the mothers/guardians of the sampled children who were all aged 0-59 months. To be eligible for recruitment into the study, the parent or guardian was required to give an informed consent, reside within the Calabar South County with his/her children aged 0-59 months. We calculated our sample size using the Leslie-Kish formula and we used a two-staged sampling method, first to ballot for the wards to be involved and then to select four of the most populated ones in the wards chosen. Data collection was by interviewer administered structured questionnaire (Appendix I), Data collected was entered and analyzed using Statistical Package for the Social Sciences (SPSS) Version 20. Percentages were calculated and represented using charts and tables Results; The number of children sampled was 159. We found that 150 were fully immunized and 9 were not, the prevalence of missed opportunity was 32% from the study. The reasons for missed opportunities were varied, ranging from false contraindications, logistical problems resulting in very poor access roads to health facilities and poor organization of health centers together with negative health worker attitudes. Some of the consequences of these missed opportunities were increased susceptibility to vaccine preventable diseases, resurgence of the above diseases and increased morbidity and mortality of children aged less than 5 years. Conclusion; We found that ignorance on the part of both parents/guardians and health care staff together with infrastructural inadequacies in the county such as- roads, poor electric power supply for storage of vaccines were hugely responsible for most missed opportunities for immunization. The details of these and suggestions for improvement and the way forward are discussed.

Keywords: missed opportunity, immunization, under five, Calabar south

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Authors: André Jesus, Yanjie Zhu, Irwanda Laory

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Structural health monitoring is one of the most promising technologies concerning aversion of structural risk and economic savings. Analysts often have to deal with a considerable variety of uncertainties that arise during a monitoring process. Namely the widespread application of numerical models (model-based) is accompanied by a widespread concern about quantifying the uncertainties prevailing in their use. Some of these uncertainties are related with the deterministic nature of the model (code uncertainty) others with the variability of its inputs (parameter uncertainty) and the discrepancy between a model/experiment (systematic uncertainty). The actual process always exhibits a random behaviour (observation error) even when conditions are set identically (residual variation). Bayesian inference assumes that parameters of a model are random variables with an associated PDF, which can be inferred from experimental data. However in many Bayesian methods the determination of systematic uncertainty can be problematic. In this work systematic uncertainty is associated with a discrepancy function. The numerical model and discrepancy function are approximated by Gaussian processes (surrogate model). Finally, to avoid the computational burden of a fully Bayesian approach the parameters that characterise the Gaussian processes were estimated in a four stage process (modular Bayesian approach). The proposed methodology has been successfully applied on fields such as geoscience, biomedics, particle physics but never on the SHM context. This approach considerably reduces the computational burden; although the extent of the considered uncertainties is lower (second order effects are neglected). To successfully identify the considered uncertainties this formulation was extended to consider multiple responses. The efficiency of the algorithm has been tested on a small scale aluminium bridge structure, subjected to a thermal expansion due to infrared heaters. Comparison of its performance with responses measured at different points of the structure and associated degrees of identifiability is also carried out. A numerical FEM model of the structure was developed and the stiffness from its supports is considered as a parameter to calibrate. Results show that the modular Bayesian approach performed best when responses of the same type had the lowest spatial correlation. Based on previous literature, using different types of responses (strain, acceleration, and displacement) should also improve the identifiability problem. Uncertainties due to parametric variability, observation error, residual variability, code variability and systematic uncertainty were all recovered. For this example the algorithm performance was stable and considerably quicker than Bayesian methods that account for the full extent of uncertainties. Future research with real-life examples is required to fully access the advantages and limitations of the proposed methodology.

Keywords: bayesian, calibration, numerical model, system identification, systematic uncertainty, Gaussian process

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Authors: Clement Yeboah

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Prior research concludes that environmental commitment positively drives organisational performance. Nonetheless, the nexus and conditions under which environmental commitment capabilities contribute to a firm’s performance are less understood. The purpose of this quantitative relational study was to examine the relationship between environmental commitment and 500 firms’ performances in Ghana. The researchers further seek to draw insights from the resource-based view to conceptualize environmental commitment and green procurement practices as resource capabilities to enhance firm performance. The researchers used insights from the contingent resource-based view to examine green leadership orientation conditions under which environmental commitment capability contributes to firm performance through green procurement practices. The study’s conceptual framework was tested on primary data from some firms in the Ghanaian market. PROCESS Macro was used to test the study’s hypotheses. Beyond that, green procurement practices mediated the association between environmental commitment capabilities and the firm’s performance. The study further seeks to find out whether green leadership orientation positively moderates the indirect relationship between environmental commitment capabilities and firm performance through green procurement practices. While conventional wisdom suggests that improved environmental commitment capabilities help improve a firm’s performance, this study tested this presumed relationship between environmental commitment capabilities and firm performance and provides theoretical arguments and empirical evidence to justify how green procurement practices uniquely and in synergy with green leadership orientation transform this relationship. The study results indicated a positive correlation between environmental commitment and firm performance. This result suggests that firms that prioritize environmental sustainability and demonstrate a strong commitment to environmentally responsible practices tend to experience better overall performance. This includes financial gains, operational efficiency, enhanced reputation, and improved relationships with stakeholders. The study's findings inform policy formulation in Ghana related to environmental regulations, incentives, and support mechanisms. Policymakers can use the insights to design policies that encourage and reward firms for their environmental commitments, thereby fostering a more sustainable and environmentally responsible business environment. The findings from such research can influence the design and development of educational programs in Ghana, specifically in fields related to sustainability, environmental management, and corporate social responsibility (CSR). Institutions may consider integrating environmental and sustainability topics into their business and management courses to create awareness and promote responsible practices among future business professionals. Also the study results can also promote the adoption of environmental accounting practices in Ghana. By recognizing and measuring the environmental impacts and costs associated with business activities, firms can better understand the financial implications of their environmental commitments and develop strategies for improved performance.

Keywords: firm’s performance, green procurement practice, environmental commitment, environmental management, sustainability

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Authors: S. J. Yune, S. Y. Lee, S. J. Im, B. S. Kam, S. Y. Baek

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This study aimed to determine the reliability of clinical performance assessments, having been emphasized by ability-based education, and professors overall assessment methods. We addressed the following problems: First, we try to find out whether there is a difference in what we consider to be the main variables affecting the clinical performance test according to the evaluator’s working period and the number of evaluation experience. Second, we examined the relationship among the global rating score (G), analytic global rating score (Gc), and the sum of the analytical checklists (C). What are the main factors affecting clinical performance assessments in relation to the numbers of times the evaluator had administered evaluations and the length of their working period service? What is the relationship between overall assessment score and analytic checklist score? How does analytic global rating with 6 components in OSCE and 4 components in sub-domains (Gc) CPX: aseptic practice, precision, systemic approach, proficiency, successfulness, and attitude overall assessment score and task-specific analytic checklist score sum (C) affect the professor’s overall global rating assessment score (G)? We studied 75 professors who attended a 2016 Bugyeoung Consortium clinical skills performances test evaluating third and fourth year medical students at the Pusan National University Medical school in South Korea (39 prof. in OSCE, 36 prof. in CPX; all consented to participate in our study). Each evaluator used 3 forms; a task-specific analytic checklist, subsequent analytic global rating scale with sub-6 domains, and overall global scale. After the evaluation, the professors responded to the questionnaire on the important factors of clinical performance assessment. The data were analyzed by frequency analysis, correlation analysis, and hierarchical regression analysis using SPSS 21.0. Their understanding of overall assessment was analyzed by dividing the subjects into groups based on experiences. As a result, they considered ‘precision’ most important in overall OSCE assessment, and ‘precise accuracy physical examination’, ‘systemic approaches to taking patient history’, and ‘diagnostic skill capability’ in overall CPX assessment. For OSCE, there was no clear difference of opinion about the main factors, but there was for CPX. Analytic global rating scale score, overall rating scale score, and analytic checklist score had meaningful mutual correlations. According to the regression analysis results, task-specific checklist score sum had the greatest effect on overall global rating. professors regarded task-specific analytic checklist total score sum as best reflecting overall OSCE test score, followed by aseptic practice, precision, systemic approach, proficiency, successfulness, and attitude on a subsequent analytic global rating scale. For CPX, subsequent analytic global rating scale score, overall global rating scale score, and task-specific checklist score had meaningful mutual correlations. These findings support explanations for validity of professors’ global rating in clinical performance assessment.

Keywords: global rating, clinical performance assessment, medical education, analytic checklist

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