Search results for: architectural evaluation criteria

Authors: Tooba Sabir, Asima Jaffar, Namra Sabir, Mohammad Amjad Sabir

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Ecocriticism is the study of relationship between human and environment which has been represented in literature since the very beginning in pastoral tradition. However, the analysis of such representation is new as compared to the other critical evaluations like Psychoanalysis, Marxism, Post-colonialism, Modernism and many others. Ecocritics seek to find information like anthropocentrism, ecocentrism, ecofeminism, eco-Marxism, representation of environment and environmental concept and several other topics. In the current study the representation of environmental concepts, were ecocritically analyzed in Paulo Coelho’s The Alchemist, one of the most read novels throughout the world, having been translated into many languages. Analysis of the text revealed, the representations of environmental ideas like landscapes and tourism, biodiversity, land-sea displacement, environmental disasters and warfare, desert winds and sand dunes. 'This desert was once a sea' throws light on different theories of land-sea displacement, one being the plate-tectonic theory which proposes Earth’s lithosphere to be divided into different large and small plates, continuously moving toward, away from or parallel to each other, resulting in land-sea displacement. Another theory is the continental drift theory which holds onto the belief that one large landmass—Pangea, broke down into smaller pieces of land that moved relative to each other and formed continents of the present time. The cause of desertification may, however, be natural i.e. climate change or artificial i.e. by human activities. Imagery of the environmental concepts, at some instances in the novel, is detailed and at other instances, is not as striking, but still is capable of arousing readers’ imagination. The study suggests that ecocritical justifications of environmental concepts in the text will increase the interactions between literature and environment which should be encouraged in order to induce environmental awareness among the readers.

Keywords: biodiversity, ecocritical analysis, ecocriticism, environmental disasters, landscapes

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Authors: Jesús Horacio, Alfredo Ollero, Víctor Bouzas-Blanco, Augusto Pérez-Alberti

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Rivers have traditionally been classified, assessed and managed in terms of hydrological, chemical and / or biological criteria. Geomorphological classifications had in the past a secondary role, although proposals like River Styles Framework, Catchment Baseline Survey or Stroud Rural Sustainable Drainage Project did incorporate geomorphology for management decision-making. In recent years many studies have been attracted to the geomorphological component. The geomorphological processes and their associated forms determine the structure of a river system. Understanding these processes and forms is a critical component of the sustainable rehabilitation of aquatic ecosystems. The fluvial auto-classification approach suggests that a river is a self-built natural system, with processes and forms designed to effectively preserve their ecological function (hydrologic, sedimentological and biological regime). Fluvial systems are formed by a wide range of elements with multiple non-linear interactions on different spatial and temporal scales. Besides, the fluvial auto-classification concept is built using data from the river itself, so that each classification developed is peculiar to the river studied. The variables used in the classification are specific stream power and mean grain size. A discriminant analysis showed that these variables are the best characterized processes and forms. The statistical technique applied allows to get an individual discriminant equation for each geomorphological type. The geomorphological classification was developed using sites with high naturalness. Each site is a control point of high ecological and geomorphological quality. The changes in the conditions of the control points will be quickly recognizable, and easy to apply a right management measures to recover the geomorphological type. The study focused on Galicia (NW Spain) and the mapping was made analyzing 122 control points (sites) distributed over eight river basins. In sum, this study provides a method for fluvial geomorphological classification that works as an open and flexible tool underlying the fluvial auto-classification concept. The hydrographic mapping is the visual expression of the results, such that each river has a particular map according to its geomorphological characteristics. Each geomorphological type is represented by a particular type of hydraulic geometry (channel width, width-depth ratio, hydraulic radius, etc.). An alteration of this geometry is indicative of a geomorphological disturbance (whether natural or anthropogenic). Hydrographic mapping is also dynamic because its meaning changes if there is a modification in the specific stream power and/or the mean grain size, that is, in the value of their equations. The researcher has to check annually some of the control points. This procedure allows to monitor the geomorphology quality of the rivers and to see if there are any alterations. The maps are useful to researchers and managers, especially for conservation work and river restoration.

Keywords: fluvial auto-classification concept, mapping, geomorphology, river

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Authors: Szymon Szemik, Małgorzata Kowalska

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Objective: Medical students experience numerous demands during the education process, determining their quality of life (QoL) and health status. POLLEK (POLski LEKarz, eng. Polish Physician) study aims to identify and evaluate the quality of life, mental health status, and ever-recognized chronic diseases by simultaneously assessing their determinants in Polish medical students during long-term observation. Material and Methods: The POLLEK is the follow-up cohort study conducted among medical students at the Medical University of Silesia in Katowice. Students were followed during two observation periods: in their first year of studies, the academic year 2021/2022 (T1), and in their second year, the academic year 2022/2023 (T2). Results: The total number of participants in the first year of observation (T1) was 427 while in the second year (T2) was 335. Obtained results confirmed that the QoL score significantly decreased in their second year of studies mainly in the somatic and psychological domains. Moreover, we observed a significant increase in self-declared scoring of somatic symptoms year by year (from M=4.75 at T1 to M=8.06 at T2, p<0.001) in the GHQ-28 questionnaire survey. The determinants of QoL domains common to T1 and T2 remained self-declared health status, frequency of physical activity, and current financial situation. In the first year of evaluation, 56 students (13.10%) were overweight or obese, and 52 (15.8%) in the second. Regardless of the academic year, the increased risk of being overweight or obese was significantly associated with dissatisfaction with personal health, financial deficiencies, and a diet abundant in meat consumption. Conclusions: The QoL in medical students and selected determinants of their health status deteriorated during the observation period. Our findings suggest that medical schools should actively promote the activity needed to achieve a balance between schoolwork and the personal life of medical students from the beginning of university study.

Keywords: quality of life, mental health, medical students, follow-up study

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Authors: Basanti Ekka, Talis Juhna

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Dairy industrial effluents originated by the typical processing activities are composed of various organic and inorganic constituents, and these include proteins, fats, inorganic salts, antibiotics, detergents, sanitizers, pathogenic viruses, bacteria, etc. These contaminants are harmful to not only human beings but also aquatic flora and fauna. Because consisting of large classes of contaminants, the specific targeted removal methods available in the literature are not viable solutions on the industrial scale. Therefore, in this on-going research, a series of coagulation, electrochemical, and catalytic methods will be employed. The bulk coagulation and electrochemical methods can wash off most of the contaminants, but some of the harmful chemicals may slip in; therefore, specific catalysts designed and synthesized will be employed for the removal of targeted chemicals. In the context of Latvian dairy industries, presently, work is under progress on the characterization of dairy effluents by total organic carbon (TOC), Inductively Coupled Plasma Mass Spectrometry (ICP-MS)/ Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES), High-Performance Liquid Chromatography (HPLC), Gas Chromatography-Mass Spectrometry (GC-MS), and Mass Spectrometry. After careful evaluation of the dairy effluents, a cost-effective natural coagulant will be employed prior to advanced electrochemical technology such as electrocoagulation and electro-oxidation as a secondary treatment process. Finally, graphene oxide (GO) based hybrid materials will be used for post-treatment of dairy wastewater as graphene oxide has been widely applied in various fields such as environmental remediation and energy production due to the presence of various oxygen-containing groups. Modified GO will be used as a catalyst for the removal of remaining contaminants after the electrochemical process.

Keywords: catalysis, dairy wastewater, electrochemical method, graphene oxide

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Authors: Francesca Favero, Despina Learmonth

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Carbohydrate addiction is said to be the sustained dependence on hyperpalatable foods rich in carbohydrates and sugar. This addiction manifests in increased consumption of carbohydrates through binging: a behaviour typically associated with eating disorders. There is a lack of consensus amongst relevant experts as to whether carbohydrates are physiologically or psychologically addictive. With an increased focus on carbohydrate addiction, an outpatient treatment programme, HELP, has been established in Cape Town, South Africa, to specifically address this issue. This research aimed to explore, pre-and post-intervention, the possible presence of, and subsequent shifts in, the maintaining mechanisms identified in the transdiagnostic model for eating disorders. However, the potential for the emergence of other perpetuating factors was not discounted and the nature of the analysis allowed for this possibility. Eight women between the ages of twenty-two and fifty, who had completed the outpatient treatment programme in the last six months, were interviewed. They were asked to speak retrospectively about their personal difficulties, eating and food, and their experience of the treatment. Thematic analysis was employed to identify themes arising from the data. Five themes congruent with the transdiagnostic model’s factors emerged: over-evaluation of weight and shape, core low self-esteem, interpersonal difficulties, clinical perfectionism and mood intolerance. A variety of sub-themes, elaborating upon the various ways in which the disordered eating was maintained, also emerged from the data. Shifts in these maintaining mechanisms were identified. Although not necessarily indicative of recovery, the results suggest that the outpatient HELP programme had a positive overall influence on the participants; and that the transdiagnostic model may be useful in understanding and guiding the treatment of clients who engage in this type of treatment programme.

Keywords: eating disorders, binge eating disorder, carbohydrate addiction, transdiagnostic model, maintaining mechanisms, thematic analysis, outpatient treatment

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Authors: Kevin Montanez, Patricia Garcia

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The confinement and restrictions adopted to avoid an exponential spread of the COVID-19 have negatively impacted the Peruvian economy. In this context, Industries offering essential products could continue operating, but they have to follow safety protocols and implement strategies to ensure employee health. In view of the increasing internet access and mobile phone ownership, “Alerta Temprana”, a mobile app, was developed to self-report COVID-19 symptoms in the work context. In this study, the usability of the mobile app “Alerta Temprana” was evaluated from the perspective of health monitors and workers. In addition to reporting the metrics related to the usability of the application, the utility of the system is also evaluated from the monitors' perspective. In this descriptive study, the participants used the mobile app for two months. Afterwards, System Usability Scale (SUS) questionnaire was answered by the workers and monitors. A Usefulness questionnaire with open questions was also used for the monitors. The data related to the use of the application was collected during one month. Furthermore, descriptive statistics and bivariate analysis were used. The workers rated the application as good (70.39). In the case of the monitors, usability was excellent (83.0). The most important feature for the monitors were the emails generated by the application. The average interaction per user was 30 seconds and a total of 6172 self-reports were sent. Finally, a statistically significant association was found between the acceptability scale and the work area. The results of this study suggest that Alerta Temprana has the potential to be used for surveillance and health monitoring in any context of face-to-face modality. Participants reported a high degree of ease of use. However, from the perspective of workers, SUS cannot diagnose usability issues and we suggest we use another standard usability questionnaire to improve "Alerta Temprana" for future use.

Keywords: public health in informatics, mobile app, usability, self-report

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Authors: Elvin Çomo, Edlira Tako, Albana Hasimi, Rrapo Ormeni, Olger Gjuzi, Mirela Ndrita

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In Albania, only low enthalpy geothermal springs and wells are known, the temperatures of some of them are almost at the upper limits of low enthalpy, reaching over 60°C. These resources can be used to improve the country's energy balance, as well as for profitable economic purposes. The region of Elbasan has the greatest geothermal energy potential in Albania. This bass is one of the most popular and used in our country. This area is a surface with a number of sources, located in the form of a chain, in the sector between Llixha and Hidraj and constitutes a thermo-mineral basin with stable discharge and high temperature. The sources of Elbasan Springs, with the current average flow of thermo mineral water of 12-18 l/s and its temperature 55-65oC, have specific reserves of 39.6 GJ/m2 and potential power to install 2760 kW. For the assessment of physico-chemical parameters and heavy metals, water samples were taken at 5 monitoring stations throughout the year 2022. The levels of basic parameters were analyzed using ISO, EU and APHA 21-th edition standard methods. This study presents the current state of the physico-chemical parameters of this thermal basin, the evaluation of these parameters for curative activities and for industrial processes, as well as the integrated utilization of geothermal energy. Possibilities for using thermomineral waters for heating homes in the area around them or even further, depending on the flow from the source or geothermal well. Sensitization of Albanian investors, medical research and the community for the high economic and curative effectiveness, for the integral use of geothermal energy in this area and the development of the tourist sector. An analysis of the negative environmental impact from the use of thermal water is also provided.

Keywords: geothermal energy, Llixha, physic-chemical parameters, thermal water

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Authors: Arbolino Roberta, Boffardi Raffaele

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Achieving the highest effectiveness for the National Plans for Recovery and Resilience (NPRR) while strengthening the objectives of cohesion and reduction of intra-EU unbalances is only possible by means of strategic, coordinated, and coherent policy planning. Therefore, the present research aims at assessing and quantifying the potential impact of NPRRs across the twenty-seven European Member States in terms of economic convergence, considering disaggregated data on industrial, construction, and service sectors. The first step of the research involves a performance analysis of the main macroeconomic indicators describing the trends of twenty-seven EU economies before the pandemic outbreak. Subsequently, in order to define the potential effect of the resources allocated, we perform an impact analysis of previous similar EU investment policies, estimating national-level sectoral elasticity associated with the expenditure of the 2007-2013 and 2014-2020 Cohesion programmes funds. These coefficients are then exploited to construct adjustment scenarios. Finally, convergence analysis is performed on the data used for constructing scenarios in order to understand whether the expenditure of funds might be useful to foster economic convergence besides driving recovery. The results of our analysis show that the allocation of resources largely mirrors the aims of the policy framework underlying the NPRR, thus reporting the largest investments in both those sectors most affected by the economic shock (services) and those considered fundamental for the digital and green transition. Notwithstanding an overall positive effect, large differences exist among European countries, while no convergence process seems to be activated or fostered by these interventions.

Keywords: NPRR, policy evaluation, cohesion policy, scenario Nalsysi

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Authors: Pooja Kumbhare

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Water is an important resource for the survival of life. The inadequate availability of surface water makes people depend on ground water for fulfilling their needs. However, ground water is generally too hard to satisfy the requirements for domestic as well as industrial applications. Removal of hardness involves various techniques such as lime soda process, ion exchange, reverse osmosis, nano-filtration, distillation, and, evaporation, etc. These techniques have individual problems such as high annual operating cost, sediment formation on membrane, sludge disposal problem, etc. Electrocoagulation (EC) is being explored as modern and cost-effective technology to cope up with the growing demand of high water quality at the consumer end. In general, earlier studies on electrocoagulation for hardness removal are found to deploy batch processes. As batch processes are always inappropriate to deal with large volume of water to be treated, it is essential to develop continuous flow EC process. So, in the present study, an attempt is made to investigate continuous flow EC process for decreasing excessive hardness of bore-well water. The experimental study has been conducted using 12 aluminum electrodes (25cm*10cm, 1cm thick) provided in EC reactor with volume of 8 L. Bore well water sample, collected from a local bore-well (i.e. at – Vishrambag, Sangli; Maharashtra) having average initial hardness of 680 mg/l (Range: 650 – 700 mg/l), was used for the study. Continuous flow electrocoagulation experiments were carried out by varying operating parameters specifically reaction time (Range: 10 – 60 min), voltage (Range: 5 – 20 V), current (Range: 1 – 5A). Based on the experimental study, it is found that hardness removal to the desired extent could be achieved even for continuous flow EC reactor, so the use of it is found promising.

Keywords: hardness, continuous flow EC process, aluminum electrode, optimal operating parameters

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Authors: Jung Ae Park, Jooyong Park

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Writing is an important learning activity that cultivates higher level thinking. Effective and immediate feedback is necessary to help improve students' writing skills. Peer assessment can be an effective method in writing tasks because it makes it possible for students not only to receive quick feedback on their writing but also to get a chance to examine different perspectives on the same topic. Peer assessment can be practiced frequently and has the advantage of immediate feedback. However, there is controversy about the accuracy of peer assessment. In this study, we tried to demonstrate experimentally how the accuracy of peer assessment could be improved. Participants (n=76) were randomly assigned to groups of 4 members. All the participant graded two sets of 4 essays on the same topic. They graded the first set twice, and the second set or the posttest once. After the first grading of the first set, each group in the experimental condition 1 (discussion group), were asked to discuss the results of the peer assessment and then to grade the essays again. Each group in the experimental condition 2 (reading group), were asked to read the assessment on each essay by an expert and then to grade the essays again. In the control group, the participants were asked to grade the 4 essays twice in different orders. Afterwards, all the participants graded the second set of 4 essays. The mean score from 4 participants was calculated for each essay. The accuracy of the peer assessment was measured by Pearson correlation with the scores of the expert. The results were analyzed by two-way repeated measure ANOVA. The main effect of grading was observed: Grading accuracy got better as the number of grading experience increased. Analysis of posttest accuracy revealed that the score variations within a group of 4 participants decreased in both discussion and reading conditions but not in the control condition. These results suggest that having students discuss their grading together can be an efficient means to improve peer assessment accuracy. By discussing, students can learn from others about what to consider in grading and whether their grading is too strict or lenient. Further research is needed to examine the exact cause of the grading accuracy.

Keywords: peer assessment, evaluation accuracy, discussion, score variations

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Authors: Behzad Babaei, B. Gangadhara Prusty

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The objective of this study is to assess the hypotheses that a restored tooth with a class II occlusal-distal (OD) cavity can be strengthened by designing an optimized cavity geometry, as well as selecting the composite restoration with optimized elastic moduli when there is a sharp de-bonded edge at the interface of the tooth and restoration. Methods: A scanned human maxillary molar tooth was segmented into dentine and enamel parts. The dentine and enamel profiles were extracted and imported into a finite element (FE) software. The enamel rod orientations were estimated virtually. Fifteen models for the restored tooth with different cavity occlusal depths (1.5, 2, and 2.5 mm) and internal cavity angles were generated. By using a semi-circular stone part, a 400 N load was applied to two contact points of the restored tooth model. The junctions between the enamel, dentine, and restoration were considered perfectly bonded. All parts in the model were considered homogeneous, isotropic, and elastic. The quadrilateral and triangular elements were employed in the models. A mesh convergence analysis was conducted to verify that the element numbers did not influence the simulation results. According to the criteria of a 5% error in the stress, we found that a total element number of over 14,000 elements resulted in the convergence of the stress. A Python script was employed to automatically assign 2-22 GPa moduli (with increments of 4 GPa) for the composite restorations, 18.6 GPa to the dentine, and two different elastic moduli to the enamel (72 GPa in the enamel rods’ direction and 63 GPa in perpendicular one). The linear, homogeneous, and elastic material models were considered for the dentine, enamel, and composite restorations. 108 FEA simulations were successively conducted. Results: The internal cavity angles (α) significantly altered the peak maximum principal stress at the interface of the enamel and restoration. The strongest structures against the contact loads were observed in the models with α = 100° and 105. Even when the enamel rods’ directional mechanical properties were disregarded, interestingly, the models with α = 100° and 105° exhibited the highest resistance against the mechanical loads. Regarding the effect of occlusal cavity depth, the models with 1.5 mm depth showed higher resistance to contact loads than the model with thicker cavities (2.0 and 2.5 mm). Moreover, the composite moduli in the range of 10-18 GPa alleviated the stress levels in the enamel. Significance: For the class II OD cavity models in this study, the optimal geometries, composite properties, and occlusal cavity depths were determined. Designing the cavities with α ≥100 ̊ was significantly effective in minimizing peak stress levels. The composite restoration with optimized properties reduced the stress concentrations on critical points of the models. Additionally, when more enamel was preserved, the sturdier enamel-restoration interface against the mechanical loads was observed.

Keywords: dental composite restoration, cavity geometry, finite element approach, maximum principal stress

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Authors: Merve Uzuner Sahin, Kumru D. Atalay, Berna Dengiz

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In today’s competitive market, there are many alternative products that can be used in similar manner and purpose. Therefore, the utility of the product is an important issue for the preferability of the brand. This utility could be measured in terms of its functionality, durability, reliability. These all are affected by the system capabilities. Reliability is an important system design criteria for the manufacturers to be able to have high availability. Availability is the probability that a system (or a component) is operating properly to its function at a specific point in time or a specific period of times. System availability provides valuable input to estimate the production rate for the company to realize the production plan. When considering only the corrective maintenance downtime of the system, mean time between failure (MTBF) and mean time to repair (MTTR) are used to obtain system availability. Also, the MTBF and MTTR values are important measures to improve system performance by adopting suitable maintenance strategies for reliability engineers and practitioners working in a system. Failure and repair time probability distributions of each component in the system should be known for the conventional availability analysis. However, generally, companies do not have statistics or quality control departments to store such a large amount of data. Real events or situations are defined deterministically instead of using stochastic data for the complete description of real systems. A fuzzy set is an alternative theory which is used to analyze the uncertainty and vagueness in real systems. The aim of this study is to present a novel approach to compute system availability using representation of MTBF and MTTR in fuzzy numbers. Based on the experience in the system, it is decided to choose 3 different spread of MTBF and MTTR such as 15%, 20% and 25% to obtain lower and upper limits of the fuzzy numbers. To the best of our knowledge, the proposed method is the first application that is used fuzzy MTBF and fuzzy MTTR for fuzzy system availability estimation. This method is easy to apply in any repairable production system by practitioners working in industry. It is provided that the reliability engineers/managers/practitioners could analyze the system performance in a more consistent and logical manner based on fuzzy availability. This paper presents a real case study of a repairable multi-stage production line in lead-acid battery production factory in Turkey. The following is focusing on the considered wet-charging battery process which has a higher production level than the other types of battery. In this system, system components could exist only in two states, working or failed, and it is assumed that when a component in the system fails, it becomes as good as new after repair. Instead of classical methods, using fuzzy set theory and obtaining intervals for these measures would be very useful for system managers, practitioners to analyze system qualifications to find better results for their working conditions. Thus, much more detailed information about system characteristics is obtained.

Keywords: availability analysis, battery production system, fuzzy sets, triangular fuzzy numbers (TFNs)

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Authors: Mohammed AL-Hasani

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The Pandemic COVID-19 altered the daily habits and affected the functional performance of the cities after this crisis leaving remarkable impacts on many metropolises worldwide. It is so obvious that having more densification in the city leads to more threats altering this main approach that was called for achieving sustainable development. The main goal to achieve resiliency in the cities, especially in forcing risks, is to deal with a planning system that is able to resist, absorb, accommodate and recover from the impacts that had been affected. Many Cities in London, Wuhan, New York, and others worldwide carried different planning approaches and varied in reaction to safeguard the impacts of the pandemic. The cities globally varied from the radiant pattern predicted by Le Corbusier, or having multi urban centers more like the approach of Frank Lloyd Wright’s Broadacre City, or having linear growth or gridiron expansion that was common by Doxiadis, compact pattern, and many other hygiene patterns. These urban patterns shape the spatial distribution and Identify both open and natural spaces with gentrified and gentrifying areas. This crisis paid attention to reassess many planning approaches and examine the existing urban patterns focusing more on the aim of continuity and resiliency in managing the crises within the rapid transformation and the power of market forces. According to that, this paper hypothesized that those urban planning patterns determine the method of reaction in assuring quarantine for the inhabitance and the performance of public services and need to be updated through carrying out an innovative urban management system and adopt further resilience patterns in prospective urban planning approaches. This paper investigates the adaptivity and resiliency of variant urban planning patterns regarding selected cities worldwide that affected by COVID-19 and their role in applying certain management strategies in controlling the pandemic spread, finding out the main potentials that should be included in prospective planning approaches. The examination encompasses the spatial arrangement, blocks definition, plots arrangement, and urban space typologies. This paper aims to investigate the urban patterns to deliberate also the debate between densification as one of the more sustainable planning approaches and disaggregation tendency that was followed after the pandemic by restructuring and managing its application according to the assessment of the spatial distribution and urban patterns. The biggest long-term threat to dense cities proves the need to shift to online working and telecommuting, creating a mixture between using cyber and urban spaces to remobilize the city. Reassessing spatial design and growth, open spaces, urban population density, and public awareness are the main solutions that should be carried out to face the outbreak in our current cities that should be managed from global to tertiary levels and could develop criteria for designing the prospective cities

Keywords: COVID-19, densification, resiliency, urban patterns

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Authors: Samaneh Yavari, Christiane Pferrer, Elisabeth Engelke, Alexander Starke, Juergen Rehage

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Background: Three nociceptive thresholds of thermal, electrical, and mechanical thresholds commonly use to evaluate the local anesthesia in many species, for instance, cow, horse, cat, dog, rabbit, and so on. Due to the lack of investigations to evaluate and/or validate such those nociceptive thresholds, our plan was the comparison of two-foot local anesthesia methods of Intravenous Regional Anesthesia (IVRA) and our modified four-point Nerve Block Anesthesia (NBA). Materials and Methods: Eight healthy nonpregnant nondairy Holstein Frisian cows in a cross-over study design were selected for this study. All cows divided into two different groups to receive two local anesthesia techniques of IVRA and our modified four-point NBA. Three thermal, electrical, and mechanical force and pinpricks were applied to evaluate the quality of local anesthesia methods before and after local anesthesia application. Results: The statistical evaluation demonstrated that our four-point NBA has a qualification to select as a standard foot local anesthesia. However, the recorded results of our study revealed no significant difference between two groups of local anesthesia techniques of IVRA and modified four-point NBA related to quality and duration of anesthesia stimulated by electrical, mechanical and thermal nociceptive stimuli. Conclusion and discussion: All three nociceptive threshold stimuli of electrical, mechanical and heat nociceptive thresholds can be applied to measure and evaluate the efficacy of foot local anesthesia of dairy cows. However, our study revealed no superiority of those three nociceptive methods to evaluate the duration and quality of bovine foot local anesthesia methods. Veterinarians to investigate the duration and quality of their selected anesthesia method can use any of those heat, mechanical, and electrical methods.

Keywords: mechanical, thermal, electrical threshold, IVRA, NBA, hind limb, dairy cow

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Authors: Sue Hershberger Yoder, Jon Yoder

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“The appearance does not hide the essence, it reveals it; it is the essence.”—Jean-Paul Sartre, Being and Nothingness Three decades ago, transarchitect Marcos Novak developed an early form of algorithmic animation he called “liquid architecture.” In that project, digitally floating forms morphed seamlessly in cyberspace without claiming to evolve or improve. Change itself was seen as inevitable. And although some imagistic moments certainly stood out, none was hierarchically privileged over another. That project challenged longstanding assumptions about creativity and artistic genius by posing infinite parametric possibilities as inviting alternatives to traditional notions of stability, originality, and evolution. Through ephemeral processes of printing, milling, and projecting, the exhibition “Liquid Illumination” destabilizes the solid foundations of fashion and architecture. The installation is neither worn nor built in the conventional sense, but—like the sensual art forms of fashion and architecture—it is still radically embodied through the logics and techniques of design. Appearances are everything. Surface pattern and color are no longer understood as minor afterthoughts or vapid carriers of dubious content. Here, they become essential but ever-changing aspects of precisely fabricated images. Fourteen silk “colorways” (a term from the fashion industry) are framed selections from ongoing experiments with intricate pattern and complex color configurations. Whether these images are printed on fabric, milled in foam, or illuminated through projection, they explore and celebrate the untapped potentials of the surficial and superficial. Some components of individual prints appear to float in front of others through stereoscopic superimpositions; some figures appear to melt into others due to subtle changes in hue without corresponding changes in value; and some layers appear to vibrate via moiré effects that emerge from unexpected pattern and color combinations. The liturgical atmosphere of Liquid Illumination is intended to acknowledge that, like the simultaneously sacred and superficial qualities of rose windows and illuminated manuscripts, artistic and religious ideologies are also always malleable. The intellectual provocation of this paper pushes the boundaries of current thinking concerning viable applications for fashion print designs and architectural images—challenging traditional boundaries between fine art and design. The opportunistic installation of digital printing, CNC milling, and video projection mapping in a gallery that is normally reserved for fine art exhibitions raises important questions about cultural/commercial display, mass customization, digital reproduction, and the increasing prominence of surface effects (color, texture, pattern, reflection, saturation, etc.) across a range of artistic practices and design disciplines.

Keywords: fashion, print design, architecture, projection mapping, image, fabrication

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Authors: Mohamed Aly, Aliaa Rehan Youssef, Emad Sawerees, Mounir Guirgis

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Relevance: Osteoarthritis (OA) is the most common degenerative disease seen in all populations. It causes disability and substantial socioeconomic burden. Evidence supports that exercise are the most effective conservative treatment for patients with OA. Therapists experience and clinical judgment play major role in exercise prescription and scientific evidence for this regard is lacking. The development of clinical prediction rules to identify patients who are most likely benefit from exercise may help solving this dilemma. Purpose: This study investigated whether body mass index and functional ability at baseline can predict patients’ response to a selected exercise program. Approach: Fifty-six patients, aged 35 to 65 years, completed an exercise program consisting of open kinetic chain strengthening and passive stretching exercises. The program was given for 3 sessions per week, 45 minutes per session, for 6 weeks Evaluation: At baseline and post treatment, pain severity was assessed using the numerical pain rating scale, whereas functional ability was being assessed by step test (ST), time up and go test (TUG) and 50 feet time walk test (50 FTW). After completing the program, global rate of change (GROC) score of greater than 4 was used to categorize patients as successful and non-successful. Thirty-eight patients (68%) had successful response to the intervention. Logistic regression showed that BMI and 50 FTW test were the only significant predictors. Based on the results, patients with BMI less than 34.71 kg/m2 and 50 FTW test less than 25.64 sec are 68% to 89% more likely to benefit from the exercise program. Conclusions: Clinicians should consider the described strengthening and flexibility exercise program for patents with BMI less than 34.7 Kg/m2 and 50 FTW faster than 25.6 seconds. The validity of these predictors should be investigated for other exercise.

Keywords: clinical prediction rule, knee osteoarthritis, physical therapy exercises, validity

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Authors: Martins Y. Otache, John J. Musa, Abayomi I. Kuti, Mustapha Mohammed

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The performance of an artificial neural network (ANN) is contingent on a host of factors, for instance, the network optimisation scheme. In view of this, the study examined the general implications of the ANN training optimisation algorithm on its forecast performance. To this end, the Bayesian regularisation (Br), Levenberg-Marquardt (LM), and the adaptive learning gradient descent: GDM (with momentum) algorithms were employed under different ANN structural configurations: (1) single-hidden layer, and (2) double-hidden layer feedforward back propagation network. Results obtained revealed generally that the gradient descent with momentum (GDM) optimisation algorithm, with its adaptive learning capability, used a relatively shorter time in both training and validation phases as compared to the Levenberg- Marquardt (LM) and Bayesian Regularisation (Br) algorithms though learning may not be consummated; i.e., in all instances considering also the prediction of extreme flow conditions for 1-day and 5-day ahead, respectively especially using the ANN model. In specific statistical terms on the average, model performance efficiency using the coefficient of efficiency (CE) statistic were Br: 98%, 94%; LM: 98 %, 95 %, and GDM: 96 %, 96% respectively for training and validation phases. However, on the basis of relative error distribution statistics (MAE, MAPE, and MSRE), GDM performed better than the others overall. Based on the findings, it is imperative to state that the adoption of ANN for real-time forecasting should employ training algorithms that do not have computational overhead like the case of LM that requires the computation of the Hessian matrix, protracted time, and sensitivity to initial conditions; to this end, Br and other forms of the gradient descent with momentum should be adopted considering overall time expenditure and quality of the forecast as well as mitigation of network overfitting. On the whole, it is recommended that evaluation should consider implications of (i) data quality and quantity and (ii) transfer functions on the overall network forecast performance.

Keywords: streamflow, neural network, optimisation, algorithm

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Authors: Harsha B. R., Anil Kumar K. S.

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Climate and soils are the two most dynamic entities among the factors affecting growth and grapes productivity. Studying of prevailing climate over the years in a region provides sufficient information related to management practices to be carried out in vineyards. Evaluating the suitability of vineyard soils under different climatic conditions serves as the yardstick to analyse the performance of grapevines. This study was formulated to study the climate and evaluate the site-suitability of soils in vineyards of southern Karnataka, which has registered its superiority in the quality production of wine. Ten soil profiles were excavated for suitability evaluation of soils, and six taluks were studied for climatic analysis. In almost all the regions studied, recharge starts at the end of the May or June months, peaking in either September or October months. Soil Starts drying from mid of December months in the taluks studied. Bangalore North (Rajanukunte) soils were highly suited for grapes cultivation with no or slight limitations. Bangalore North (GKVK Farm) was moderately suited with slight to moderate limitations of slope and available nitrogen content. Moderate suitability was observed in the rest of the profiles studied in Eastern dry zone soils with the slight to moderate limitations of either organic carbon or available nitrogen or both in the Eastern dry zone. Magadi (Southern dry zone) soils were moderately suitable with slight to moderate limitations of graveliness, available nitrogen, organic carbon, and exchangeable sodium percentage. Sustainable performance of vineyards in terms of yield can be achieved in these taluks by managing the constraints existing in soils.

Keywords: climatic analysis, dry zone, water recharge, growing period, suitability, sustainability

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Authors: Huey-Fang Sun, Wei-Kai Weng, Mei-Kuang Chao, Hui-Shan Hsu, Tsai-Yin Shih

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Psycho-social stress is important for mental illness and the presence of emotional and behavioral symptoms to an identifiable event is the central feature of adjustment disorders. However, whether patients with adjustment disorders have been raised in family with poor family functions and social supports and have higher stress perception than their peer group when they both experienced a similar stressful environment remains unknown. The specific aims of the study are to investigate the correlation among the family function, social supports and the level of stress perception and to test the hypothesis that military patients with adjustment disorders would have lower family function, lower social supports and higher stress perception than their healthy colleagues recruited in the same cohort for military services given their common exposure to similar stressful environments. Methods: The study was conducted in four hospitals of northern part of Taiwan from July 1, 2015 to June 30, 2017 and a matched case-control study design was used. The inclusion criteria for potential patient participants were psychiatric inpatients that serviced in military during the study period and met the diagnosis of adjustment disorders. Patients who had been admitted to psychiatric ward before or had illiteracy problem were excluded. A healthy military control sample matched by the same military service unit, gender, and recruited cohort was invited to participate the study as well. Totally 74 participants (37 patients and 37 controls) completed the consent forms and filled out the research questionnaires. Questionnaires used in the study included Perceived Stress Scale (PSS) as a measure of stress perception; Family APGAR as a measure of family function, and Multidimensional Scale of Perceived Social Support (MSPSS) as a measure of social supports. Pearson correlation analysis and t-test were applied for statistical analysis. Results: The analysis results showed that PSS level significantly negatively correlated with three social support subscales (family subscale, r= -.37, P < .05; friend subscale, r= -.38, P < .05; significant other subscale, r= -.39, P < .05). A negative correlation between PSS level and Family APGAR only reached a borderline significant level (P= .06). The t-test results for PSS scores, Family APGAR levels, and three subscale scores of MSPSS between patient and control participants were all significantly different (P < .001, P < .05, P < .05, P < .05, P < .05, respectively) and the patient participants had higher stress perception scores, lower social supports and lower family function scores than the healthy control participants. Conclusions: Our study suggested that family function and social supports were negatively correlated with patients’ subjective stress perception. Military patients with adjustment disorders tended to have higher stress perception and lower family function and social supports than those military peers who remained healthy and still provided services in their military units.

Keywords: adjustment disorders, family function, social support, stress perception

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Authors: Bushra Zafar, Usman Qamar

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Large data sample size and dimensions render the effectiveness of conventional data mining methodologies. A data mining technique are important tools for collection of knowledgeable information from variety of databases and provides supervised learning in the form of classification to design models to describe vital data classes while structure of the classifier is based on class attribute. Classification efficiency and accuracy are often influenced to great extent by noisy and undesirable features in real application data sets. The inherent natures of data set greatly masks its quality analysis and leave us with quite few practical approaches to use. To our knowledge first time, we present a new approach for investigation of structure and quality of datasets by providing a targeted analysis of localization of noisy and irrelevant features of data sets. Machine learning is based primarily on feature selection as pre-processing step which offers us to select few features from number of features as a subset by reducing the space according to certain evaluation criterion. The primary objective of this study is to trim down the scope of the given data sample by searching a small set of important features which may results into good classification performance. For this purpose, a heuristic for wrapper-based feature selection using genetic algorithm and for discriminative feature selection an external classifier are used. Selection of feature based on its number of occurrence in the chosen chromosomes. Sample dataset has been used to demonstrate proposed idea effectively. A proposed method has improved average accuracy of different datasets is about 95%. Experimental results illustrate that proposed algorithm increases the accuracy of prediction of different diseases.

Keywords: data mining, generic algorithm, KNN algorithms, wrapper based feature selection

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Authors: Kunwar Paritosh, Sanjay Mathur, Monika Yadav, Paras Gandhi, Subodh Kumar, Nidhi Pareek, Vivekanand Vivekanand

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A significant fraction of energy is wasted every year managing the biodegradable organic waste inadequately as development and sustainability are the inherent enemies. The management of these waste is indispensable to boost its optimum utilization by converting it to renewable energy resource (here biogas) through anaerobic digestion and to mitigate greenhouse gas emission. Food and yard wastes may prove to be appropriate and potential feedstocks for anaerobic co-digestion for biogas production. The present study has been performed to explore the synergistic effect of co-digesting food waste and yard trimmings from MNIT campus for enhanced biogas production in different ratios in batch tests (37±10C, 90 rpm, 45 days). The results were overwhelming and showed that blending two different organic waste in proper ratio improved the biogas generation considerably, with the highest biogas yield (2044±24 mLg-1VS) that was achieved at 75:25 of food waste to yard waste ratio on volatile solids (VS) basis. The yield was 1.7 and 2.2 folds higher than the mono-digestion of food or yard waste (1172±34, 1016±36mLg-1VS) respectively. The increase in biogas production may be credited to optimum C/N ratio resulting in higher yield. Also Adding TiO2 nanoparticles showed virtually no effect on biogas production as sometimes nanoparticles enhance biogas production. ICP-MS, FTIR analysis was carried out to gain an insight of feedstocks. Modified Gompertz and logistics models were applied for the kinetic study of biogas production where modified Gompertz model showed goodness-of-fit (R2=0.9978) with the experimental results.

Keywords: anaerobic co-digestion, biogas, kinetics, nanoparticle, organic waste

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Authors: Afshan Saad, Muhammad Saad, Shah Muhammad Emaduddin

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Nowadays the business condition is so quick paced that enhancing ourselves consistently has turned into a huge factor for the presence of an undertaking. We can check this for structural building and significantly more so in the quick-paced universe of data innovation and programming designing. The lithe philosophies, similar to Scrum, have a devoted advance in the process that objectives the enhancement of the improvement procedure and programming items. Pivotal to process enhancement is to pick up data that grants you to assess the condition of the procedure and its items. From the status data, you can design activities for the upgrade and furthermore assess the accomplishment of those activities. This investigation builds a model that measures the product nature of the improvement procedure. The product quality is dependent on the useful and auxiliary nature of the product items, besides the nature of the advancement procedure is likewise vital to enhance programming quality. Utilitarian quality covers the adherence to client prerequisites, while the auxiliary quality tends to the structure of the product item's source code with reference to its practicality. The procedure quality is identified with the consistency and expectedness of the improvement procedure. The product quality model is connected in a business setting by social occasion the information for the product measurements in the model. To assess the product quality model, we investigate the information and present it to the general population engaged with the light-footed programming improvement process. The outcomes from the application and the client input recommend that the model empowers a reasonable evaluation of the product quality and that it very well may be utilized to help the persistent enhancement of the advancement procedure and programming items.

Keywords: Agile SDLC Tools, Agile Software development, business value, enterprise applications, IBM, IBM Rational Team Concert, RTC, software quality, software metrics

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Authors: Meng-Na Dai, Bao-Fang Wen, Gao-Pei Zhu, Chen-Xi Zhang, Jing Sun, Chang-Hai Tang, Zhi-Qiang Feng, Wen-Qiang Yin

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Based on the analysis of literature in the health emergency management in China with recent 10 years, this paper discusses the Chinese current research hotspots, development trends and shortcomings in this field, and provides references for scholars to conduct follow-up research. CNKI(China National Knowledge Infrastructure), Weipu, and Wanfang were the databases of this literature. The key words during the database search were health, emergency, and management with the time from 2009 to 2018. The duplicate, non-academic, and unrelated documents were excluded. 901 articles were included in the literature review database. The main indicators of abstraction were, the number of articles published every year, authors, institutions, periodicals, etc. There are some research findings through the analysis of the literature. Overall, the number of literature in the health emergency management in China has shown a fluctuating downward trend in recent 10 years. Specifically, there is a lack of close cooperation between authors, which has not constituted the core team among them yet. Meanwhile, in this field, the number of high-level periodicals and quality literature is scarce. In addition, there are a lot of research hotspots, such as emergency management system, mechanism research, capacity evaluation index system research, plans and capacity-building research, etc. In the future, we should increase the scientific research funding of the health emergency management, encourage collaborative innovation among authors in multi-disciplinary fields, and create high-quality and high-impact journals in this field. The states should encourage scholars in this field to carry out more academic cooperation and communication with the whole world and improve the research in breadth and depth. Generally speaking, the research in health emergency management in China is still insufficient and needs to be improved.

Keywords: health emergency management, research situation, bibliometrics, literature

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Authors: Christine Böckmann, Julia Rosemann

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We present an inversion algorithm that is used in the European Aerosol Lidar Network for the inversion of data collected with multi-wavelength Raman lidar. These instruments measure backscatter coefficients at 355, 532, and 1064 nm, and extinction coefficients at 355 and 532 nm. The algorithm is based on manually controlled inversion of optical data which allows for detailed sensitivity studies and thus provides us with comparably high quality of the derived data products. The algorithm allows us to derive particle effective radius, volume, surface-area concentration with comparably high confidence. The retrieval of the real and imaginary parts of the complex refractive index still is a challenge in view of the accuracy required for these parameters in climate change studies in which light-absorption needs to be known with high accuracy. Single-scattering albedo (SSA) can be computed from the retrieve microphysical parameters and allows us to categorize aerosols into high and low absorbing aerosols. From mathematical point of view the algorithm is based on the concept of using truncated singular value decomposition as regularization method. This method was adapted to work for the retrieval of the particle size distribution function (PSD) and is called hybrid regularization technique since it is using a triple of regularization parameters. The inversion of an ill-posed problem, such as the retrieval of the PSD, is always a challenging task because very small measurement errors will be amplified most often hugely during the solution process unless an appropriate regularization method is used. Even using a regularization method is difficult since appropriate regularization parameters have to be determined. Therefore, in a next stage of our work we decided to use two regularization techniques in parallel for comparison purpose. The second method is an iterative regularization method based on Pade iteration. Here, the number of iteration steps serves as the regularization parameter. We successfully developed a semi-automated software for spherical particles which is able to run even on a parallel processor machine. From a mathematical point of view, it is also very important (as selection criteria for an appropriate regularization method) to investigate the degree of ill-posedness of the problem which we found is a moderate ill-posedness. We computed the optical data from mono-modal logarithmic PSD and investigated particles of spherical shape in our simulations. We considered particle radii as large as 6 nm which does not only cover the size range of particles in the fine-mode fraction of naturally occurring PSD but also covers a part of the coarse-mode fraction of PSD. We considered errors of 15% in the simulation studies. For the SSA, 100% of all cases achieve relative errors below 12%. In more detail, 87% of all cases for 355 nm and 88% of all cases for 532 nm are well below 6%. With respect to the absolute error for non- and weak-absorbing particles with real parts 1.5 and 1.6 in all modes the accuracy limit +/- 0.03 is achieved. In sum, 70% of all cases stay below +/-0.03 which is sufficient for climate change studies.

Keywords: aerosol particles, inverse problem, microphysical particle properties, regularization

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Authors: Shiamaa Eltantawy, Gihan Sobhy, Alif Alaam

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Wilson disease, or hepatolenticular degeneration, is an autosomal recessive disease that results in excess copper buildup in the body. It primarily affects the liver and basal ganglia of the brain, but it can affect other organ systems. Musculoskeletal abnormalities, including premature osteoarthritis, skeletal deformity, and pathological bone fractures, can occasionally be found in WD patients with a hepatic or neurologic type. The aim was to assess the prevalence of osteoporosis and osteopenia in Wilson’s disease patients. This case-control study was conducted on ninety children recruited from the inpatient ward and outpatient clinic of the Paediatric Hepatology, Gastroenterology, and Nutrition department of the National Liver Institute at Menofia University, aged from 1 to 18 years. Males were 49, and females were 41. Children were divided into three groups: (Group I) consisted of thirty patients with WD; (Group II) consisted of thirty patients with chronic liver disease other than WD; (Group III) consisted of thirty age- and sex-matched healthy The exclusion criteria were patients with hyperparathyroidism, hyperthyroidism, renal failure, Cushing's syndrome, and patients on certain drugs such as chemotherapy, anticonvulsants, or steroids. All patients were subjected to the following: 1- Full history-taking and clinical examination. 2-Laboratory investigations: (FBC,ALT,AST,serum albumin, total protein, total serum bilirubin,direct bilirubin,alkaline phosphatase, prothrombin time, serum critine,parathyroid hormone, serum calcium, serum phosphrus). 3-Bone mineral density (BMD, gm/cm2) values were measured by dual-energy X-ray absorptiometry (DEXA). The results revealed that there was a highly statistically significant difference between the three groups regarding the DEXA scan, and there was no statistically significant difference between groups I and II, but the WD group had the lowest bone mineral density. The WD group had a large number of cases of osteopenia and osteoporosis, but there was no statistically significant difference with the group II mean, while a high statistically significant difference was found when compared to group III. In the WD group, there were 20 patients with osteopenia, 4 patients with osteoporosis, and 6 patients who were normal. The percentages were 66.7%, 13.3%, and 20%, respectively. Therefore, the largest number of cases in the WD group had osteopenia. There was no statistically significant difference found between WD patients on different treatment regimens regarding DEXA scan results (Z-Score). There was no statistically significant difference found between patients in the WD group (normal, osteopenic, or osteoporotic) regarding phosphorus (mg/dL), but there was a highly statistically significant difference found between them regarding ionised Ca (mmol/L). Therefore, there was a decrease in bone mineral density when the Ca level was decreased. In summary, Wilson disease is associated with bone demineralization. The largest number of cases in the WD group in our study had osteopenia (66.7%). Different treatment regimens (zinc monotherapy, Artamin, and zinc) as well as different laboratory parameters have no effect on bone mineralization in WD cases. Decreased ionised Ca is associated with low BMD in WD patients. Children with WD should be investigated for BMD.

Keywords: wilson disease, Bone mineral density, liver disease, osteoporosis

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Authors: M. Alsharqawi, T. Zayed, S. Abu Dabous

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To ensure safety and serviceability of bridge infrastructure, accurate condition assessment and rating methods are needed to provide basis for bridge Maintenance, Repair and Replacement (MRR) decisions. In North America, the common practices to assess condition of bridges are through visual inspection. These practices are limited to detect surface defects and external flaws. Further, the thresholds that define the severity of bridge deterioration are selected arbitrarily. The current research discusses the main deteriorations and defects identified during visual inspection and Non-Destructive Evaluation (NDE). NDE techniques are becoming popular in augmenting the visual examination during inspection to detect subsurface defects. Quality inspection data and accurate condition assessment and rating are the basis for determining appropriate MRR decisions. Thus, in this paper, a novel method for bridge condition assessment using the Quality Function Deployment (QFD) theory is utilized. The QFD model is designed to provide an integrated condition by evaluating both the surface and subsurface defects for concrete bridges. Moreover, an integrated condition rating index with four thresholds is developed based on the QFD condition assessment model and using K-means clustering technique. Twenty case studies are analyzed by applying the QFD model and implementing the developed rating index. The results from the analyzed case studies show that the proposed threshold model produces robust MRR recommendations consistent with decisions and recommendations made by bridge managers on these projects. The proposed method is expected to advance the state of the art of bridges condition assessment and rating.

Keywords: concrete bridge decks, condition assessment and rating, quality function deployment, k-means clustering technique

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Authors: Khiari Nor El Houda, Hiouani Amira Sarra

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Many EFL students with high capacities are hidden because they suffer from speaking anxiety (SA). Most of them find public speaking much demanding. They feel unable to communicate, they fear to make mistakes and they fear negative evaluation or being called on. With the growing number of the learners who suffer from foreign language speaking anxiety (FLSA), it is becoming increasingly difficult to ignore its harmful outcomes on their performance and success, especially during their first contact with the pupils, as they will be teaching in the near future. Different researchers suggested different ways to minimize the negative effects of FLSA. The present study sheds light on emotional intelligence skills training as an effective strategy not only to influence public speaking success but also to help pre-service EFL teachers lessen their speaking anxiety and eventually to prepare them for their professional career. A quasi-experiment was used in order to examine the research hypothesis. We worked with two groups of third-year EFL students at Oum El Bouaghi University. The Foreign Language Classroom Anxiety Scale (FLCAS) and the Emotional Quotient Inventory (EQ-i) were used to collect data about the participants’ FLSA and EI levels. The analysis of the data has yielded that the assumption that there is a negative correlation between EI and FLSA was statistically validated by the Pearson Correlation Test, concluding that, the more emotionally intelligent the individual is the less anxious s/he will be. In addition, the lack of amelioration in the results of the control group and the noteworthy improvement in the experimental group results led us to conclude that EI skills training was an effective strategy in minimizing the FLSA level and therefore, we confirmed our research hypothesis.

Keywords: emotional intelligence, emotional intelligence skills training, EQ-I, FLCAS, foreign language speaking anxiety, pre-service EFL teachers

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Authors: Nilda San Miguel, Elymar Pascual

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The main focus of this study is exploring the effective approaches in teaching Mathematics that is being applied in public schools, s.y. 2018-2019. This research was written as connected output to the district-wide School Learning Action Cell (DISLAC) on Math teaching approaches which was recently conducted in Victoria, Laguna. Fifty-four math teachers coming from 17 schools in Victoria became the respondents of this study. Qualitative method of doing research was applied. Teachers’ responses to the following concerns were gathered, analyzed and interpreted: (1) evaluation of the recently conducted DISLAC, (2) status of the use of different approaches, (3) perception on the effective use of approaches, (4) preference of approach to explore in classroom sessions, (5) factors affecting the choice of approach, (6) difficulties encountered, (7) and perceived benefit to learners. Results showed that the conduct of DISLAC was very highly satisfactory (mean 4.41). Teachers looked at collaborative approach as very highly effective (mean 4.74). Fifty-two percent of the teachers is using collaborative approach, 17% constructivist, 11% integrative, 11% inquiry-based, and 9% reflective. Reflective approach was chosen to be explored by most of the respondents (29%) in future sessions. The difficulties encountered by teachers in using the different approaches are: (1) learners’ difficulty in following instructions, (2) lack of focus, (3) lack of willingness and cooperation, (4) teachers’ lack of mastery in using different approaches, and (5) lack of time of doing visual aids because of time mismanagement. Teachers deemed the use of various teaching approaches can help the learners to have (1) mastery of competency, (2) increased communication, (3) improved confidence, (4) facility in comprehension, and (5) better academic output. The result obtained from this study can be used as an input for SLACs. Recommendations at the end of the study were given to school/district heads and future researchers.

Keywords: approaches, collaborative, constructivism, inquiry-based, integrative, reflective

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Authors: Polycarp Igbojekwe

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The main objective of this study was to determine if emotional labour has become a criterion in performance appraisal, job description, selection, and training schemes in the hotel industry in Nigeria. Our main assumption was that majority of hotel organizations have not built emotional labour into their human resources management schemes. Data were gathered by the use of structured questionnaires designed in Likert format, and interviews. The focus group was managers of the selected hotels. Analyses revealed that majority of the hotels have not built emotional labour into their human resources schemes particularly in the 1, 2, and 3-star hotels. It was observed that service employees of 1, 2, and 3-star hotels have not been adequately trained to perform emotional labour; a critical factor in quality service delivery. Managers of 1, 2, and 3-star hotels have not given serious thought to emotional labour as a critical factor in quality service delivery. The study revealed that suitability of an individual’s characteristics is not being considered as a criterion for selection and performance appraisal for service employees. The implication of this is that, person-job-fit is not seriously considered. It was observed that there has been a disconnect between required emotional competency, its recognition, evaluation, and training. Based on the findings of this study, it is concluded that selection, training, job description and performance appraisal instruments in use in hotels in Nigeria are inadequate. Human resource implications of the findings in this study are presented. It is recommended that hotel organizations should re-design and plan the emotional content and context of their human resources practices to reflect the emotional demands of front line jobs in the hotel industry and the crucial role emotional labour plays during service encounters.

Keywords: emotional labour, employee selection, job description, performance appraisal, person-job-fit, employee compensation

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Authors: Rowan P. Martnishn

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During the execution of a National Endowment of the Arts grant, approximately 55 interviews were collected from professionals across various fields. These interviews were used to create deliverables – historical connections for creations that began as art and evolved entirely into computing technology. With dozens of hours’ worth of transcripts to be analyzed by qualitative coders, a quantitative methodology was created to sift through the documents. The initial step was to both clean and format all the data. First, a basic spelling and grammar check was applied, as well as a Python script for normalized formatting which used an open-source grammatical formatter to make the data as coherent as possible. 10 documents were randomly selected to manually review, where words often incorrectly translated during the transcription were recorded and replaced throughout all other documents. Then, to remove all banter and side comments, the transcripts were spliced into paragraphs (separated by change in speaker) and all paragraphs with less than 300 characters were removed. Secondly, a keyword extractor, a form of natural language processing where significant words in a document are selected, was run on each paragraph for all interviews. Every proper noun was put into a data structure corresponding to that respective interview. From there, a Bidirectional and Auto-Regressive Transformer (B.A.R.T.) summary model was then applied to each paragraph that included any of the proper nouns selected from the interview. At this stage the information to review had been sent from about 60 hours’ worth of data to 20. The data was further processed through light, manual observation – any summaries which proved to fit the criteria of the proposed deliverable were selected, as well their locations within the document. This narrowed that data down to about 5 hours’ worth of processing. The qualitative researchers were then able to find 8 more connections in addition to our previous 4, exceeding our minimum quota of 3 to satisfy the grant. Major findings of the study and subsequent curation of this methodology raised a conceptual finding crucial to working with qualitative data of this magnitude. In the use of artificial intelligence there is a general trade off in a model between breadth of knowledge and specificity. If the model has too much knowledge, the user risks leaving out important data (too general). If the tool is too specific, it has not seen enough data to be useful. Thus, this methodology proposes a solution to this tradeoff. The data is never altered outside of grammatical and spelling checks. Instead, the important information is marked, creating an indicator of where the significant data is without compromising the purity of it. Secondly, the data is chunked into smaller paragraphs, giving specificity, and then cross-referenced with the keywords (allowing generalization over the whole document). This way, no data is harmed, and qualitative experts can go over the raw data instead of using highly manipulated results. Given the success in deliverable creation as well as the circumvention of this tradeoff, this methodology should stand as a model for synthesizing qualitative data while maintaining its original form.

Keywords: B.A.R.T.model, keyword extractor, natural language processing, qualitative coding

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