Search results for: mixed methods approach

Authors: Hala Obeid

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Among the cities that have been touched by hard events and have been experiencing this polemic of existence, one can quote Beirut. A city that defies and confronts itself for its own existence. Beirut materialized all the social complexity; it has also preserved the memory of a society that has been able to build and reflect a certain unique identity. In spite of its glory, Lebanon’s civil war has marked a turning point in Beirut’s history. It has caused many deaths and opposed religious communities. Once this civil war has ended, the reconstruction of the city center, however, saw the spatial exclusion of manual labor, small local commerce, and middle-class residences. The urban functions that characterized the pre-war center were removed, and the city’s spontaneous evolutions were replaced by a historical urban planning, which neglected the city’s memory and identity. The social and spatial fragmentation that has erupted since the war has led to a breakdown of spatial and social boundaries within the city. The aim of this study is to evaluate the impact of fragmentation and boundaries on the city of Beirut in spatial, social, religious and ethnic terms. The method used in this research is what we call the mixed method which is a combination between the quantitative method and the qualitative one. These two approaches, in this case, do not oppose but complement each other in order to study the city of Beirut physically and socially. The main purpose of the qualitative approach is to describe and analyze the social phenomenon of the fragmentation of the city; this method can be summarized by the field observation and study. While the quantitative approach is based on filling out questionnaires that leads to statistics analyzes. Together, these two approaches will mark the course of the research. As a result, Beirut is not only a divided city but is fragmented spatially into many fragments and socially into many groups. This fragmentation is creating immaterial boundaries between fragments and therefore between groups. These urban and social boundaries are specifically religious and ethnic limits. As a conclusion, one of the most important and discussed boundary in Beirut is a spatial and religious boundary called ‘the green line’ or the demarcation line, a true caesura within the city. It marks the opposition of two urban groups and the aggravated fragmentation between them. This line divided Beirut into two compartments: East Beirut (for Christians) and West Beirut (for Muslims). This green line has become an urban void that holds the past in suspension. Finally, to think of Beirut as an urban unit becomes an insoluble problem.

Keywords: Beirut, boundaries, fragmentation, identity

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Authors: Wan You Ning

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Addressing the rising prevalence of mental health issues among youths, the Multi-dimensional Approach to Resilience and Support in Advanced School-based Mental Health Service Delivery (MARS-ASMHSD) framework proposes the implementation of advanced mental health services in low-resource areas to further instil mental health resilience among students in a school-based setting. Recognizing the unsustainability of direct service delivery due to rapidly growing demands and costs, the MARS-ASMHSD framework endorses the deinstitutionalization of mental healthcare and explores a tiered, multi-dimensional approach in mental healthcare provision, establishing advanced school-based mental health service delivery. The framework is developed based on sustainable and credible evidence-based practices and modifications of existing mental health service deliveries in Asia, including Singapore, Thailand, Malaysia, Japan, and Taiwan. Dissemination of the framework model for implementation will enable a more progressive and advanced school-based mental health service delivery in low-resource areas. Through the evaluation of the mental health landscape and the role of stakeholders in the respective countries, the paper concludes with a multi-dimensional framework model for implementation in low-resource areas. A mixed-method independent research study is conducted to facilitate the framework's development.

Keywords: mental health, youths, school-based services, framework development

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Authors: Berkan Ural, Arif Eser, Sinan Apaydin

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Medical image processing is generally become a challenging task nowadays. Indeed, processing of brain MRI images is one of the difficult parts of this area. This study proposes a hybrid well-defined approach which is consisted from tumor detection, extraction and analyzing steps. This approach is mainly consisted from a computer aided diagnostics system for identifying and detecting the tumor formation in any region of the brain and this system is commonly used for early prediction of brain tumor using advanced image processing and probabilistic neural network methods, respectively. For this approach, generally, some advanced noise removal functions, image processing methods such as automatic segmentation and morphological operations are used to detect the brain tumor boundaries and to obtain the important feature parameters of the tumor region. All stages of the approach are done specifically with using MATLAB software. Generally, for this approach, firstly tumor is successfully detected and the tumor area is contoured with a specific colored circle by the computer aided diagnostics program. Then, the tumor is segmented and some morphological processes are achieved to increase the visibility of the tumor area. Moreover, while this process continues, the tumor area and important shape based features are also calculated. Finally, with using the probabilistic neural network method and with using some advanced classification steps, tumor area and the type of the tumor are clearly obtained. Also, the future aim of this study is to detect the severity of lesions through classes of brain tumor which is achieved through advanced multi classification and neural network stages and creating a user friendly environment using GUI in MATLAB. In the experimental part of the study, generally, 100 images are used to train the diagnostics system and 100 out of sample images are also used to test and to check the whole results. The preliminary results demonstrate the high classification accuracy for the neural network structure. Finally, according to the results, this situation also motivates us to extend this framework to detect and localize the tumors in the other organs.

Keywords: image processing algorithms, magnetic resonance imaging, neural network, pattern recognition

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Authors: Ruchika Bagga, Mauro Falconieri, Venu Gopal Achanta, José M. F. Ferreira, Ashutosh Goel, Gopi Sharma

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Mixed valence Eu-doped nanocrystalline NaAlSiO4/NaY9Si6O26 glass-ceramics have been prepared by controlled crystallization of melt quenched bulk glasses. XRD and SEM techniques were employed to characterize the crystallization process of the precursor glass and their resultant glass-ceramics. Photoluminescence spectroscopy was used to analyze the formation of divalent europium (Eu2+) from Eu3+ ions during high temperature synthesis under ambient atmosphere and is explained on the basis of optical basicity model. The observed luminescence properties of Eu: NaY9Si6O26 are compared with that of well explored Eu: β-PbF2 nanocrystals and their marked differences are discussed.

Keywords: rare earth, oxyfluoride glasses, nano-crystalline glass-ceramics, photoluminescence spectroscopy

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Authors: Liu Yi Hui, Chun-Liang Lai, Jhang Yu Cih, He You Jing, Chiu Fan-Yun, Lin Yu Fang

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For universities offering long-term care education, the inclusion of adulting learning and practices in professional courses as appropriate based on holistic design and evaluation could improve talent empowerment by leveraging social capital. Moreover, it could make the courses and materials used in long-term care education responsive to real-life needs. A mixed research method was used in the research design. A quantitative study was also conducted using a questionnaire survey, and the data were analyzed by SPSS 22.0 Chinese version. The qualitative data included students’ learning files (learning reflection notes, course reports, and experience records).

Keywords: adult learning, community empowerment, social capital, mixed research

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Authors: Boyu Li

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Mixed matrix membranes (MMMs), as a separation technology, can improve CO₂ recycling efficiency and reduce the environmental impacts associated with huge emissions. Nevertheless, many challenges must be overcome to design excellent selectivity and permeability performance MMMs. Herein, this work demonstrates the design of nano-scale GNPs (Cu-BDC@PEG) with strong compatibility and high free friction volume (FFV) is an effective way to construct non-interfacial voids MMMs with a desirable combination of selectivity and permeability. Notably, the FFV boosted thanks to the chain length and shape of the GNPs. With this, the permeability and selectivity of Cu-BDC@PEG/PVDF MMMs had also been significantly improved. As such, compatible Cu-BDC@PEG proves very efficient for resolving challenges of MMMs with poor compatibility on the basis of the interfacial defect. Poly (Ethylene Glycol) (PEG) with oxygen groups can be finely coordinated with Cu-MOFs to disperse Cu-BDC@PEG homogenously and form hydrogen bonds with matrix to achieve continuous phase. The resultant MMMs exhibited a simultaneous enhancement of gas permeability (853.1 Barrer) and ideal CO₂/N selectivity (41.7), which has surpassed Robenson's upper bound. Moreover, Cu-BDC@PEG/PVDF has a high-temperature resistance and a long time sustainably. This attractive separation performance of Cu-BDC@PEG/PVDF offered an exciting platform for the development of composite membranes for sustainable CO₂ separations.

Keywords: metal organic framework, CO₂ separation, mixed matrix membrane, polymer

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Authors: Prathmesh Vikas Patil, Yashaswini Lomte Patil

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Laminated composite materials have considerable attention in various engineering applications due to their exceptional strength-to-weight ratio and mechanical properties. The analysis of laminated composite plates in three-dimensional (3D) elasticity is a complex problem, as it requires accounting for the orthotropic anisotropic nature of the material and the interactions between multiple layers. Conventional approaches, such as the classical plate theory, provide simplified solutions but are limited in performing exact analysis of the plate. To address such a challenge, the state space method emerges as a powerful numerical technique for modeling the behavior of laminated composites in 3D. The state-space method involves transforming the governing equations of elasticity into a state-space representation, enabling the analysis of complex structural systems in a systematic manner. Here, an effort is made to perform a 3D elasticity analysis of plates with cross-ply and angle-ply laminates using the state space approach. The state space approach is used in this study as it is a mixed formulation technique that gives the displacements and stresses simultaneously with the same level of accuracy.

Keywords: cross ply laminates, angle ply laminates, state space method, three-dimensional elasticity analysis

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Authors: Sharifah Mousli, Sona Taheri, Jiayuan He

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Autism spectrum disorder (ASD) is a complex developmental condition involving persistent difficulties with social communication, restricted interests, and repetitive behavior. The challenges associated with ASD can interfere with an affected individual’s ability to function in social, academic, and employment settings. Although there is no effective medication known to treat ASD, to our best knowledge, early intervention can significantly improve an affected individual’s overall development. Hence, an accurate diagnosis of ASD at an early phase is essential. The use of machine learning approaches improves and speeds up the diagnosis of ASD. In this paper, we focus on the application of unsupervised clustering methods in ASD as a large volume of ASD data generated through hospitals, therapy centers, and mobile applications has no pre-existing labels. We conduct a comparative analysis using seven clustering approaches such as K-means, agglomerative hierarchical, model-based, fuzzy-C-means, affinity propagation, self organizing maps, linear vector quantisation – as well as the recently developed optimization-based clustering (COMSEP-Clust) approach. We evaluate the performances of the clustering methods extensively on real-world ASD datasets encompassing different age groups: toddlers, children, adolescents, and adults. Our experimental results suggest that the COMSEP-Clust approach outperforms the other seven methods in recognizing ASD with well-separated clusters.

Keywords: autism spectrum disorder, clustering, optimization, unsupervised machine learning

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Authors: Chahrazed Zouaoui

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In recent years, the volume of geospatial information is increasing due to the evolution of communication technologies and information, this information is presented often by geographic information systems (GIS) and stored on of spatial databases (BDS). The classical data mining revealed a weakness in knowledge extraction at these enormous amounts of data due to the particularity of these spatial entities, which are characterized by the interdependence between them (1st law of geography). This gave rise to spatial data mining. Spatial data mining is a process of analyzing geographic data, which allows the extraction of knowledge and spatial relationships from geospatial data, including methods of this process we distinguish the monothematic and thematic, geo- Clustering is one of the main tasks of spatial data mining, which is registered in the part of the monothematic method. It includes geo-spatial entities similar in the same class and it affects more dissimilar to the different classes. In other words, maximize intra-class similarity and minimize inter similarity classes. Taking account of the particularity of geo-spatial data. Two approaches to geo-clustering exist, the dynamic processing of data involves applying algorithms designed for the direct treatment of spatial data, and the approach based on the spatial data pre-processing, which consists of applying clustering algorithms classic pre-processed data (by integration of spatial relationships). This approach (based on pre-treatment) is quite complex in different cases, so the search for approximate solutions involves the use of approximation algorithms, including the algorithms we are interested in dedicated approaches (clustering methods for partitioning and methods for density) and approaching bees (biomimetic approach), our study is proposed to design very significant to this problem, using different algorithms for automatically detecting geo-spatial neighborhood in order to implement the method of geo- clustering by pre-treatment, and the application of the bees algorithm to this problem for the first time in the field of geo-spatial.

Keywords: mining, GIS, geo-clustering, neighborhood

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Authors: Colleen McMillan, Alice Schmidt-Hanbidge, Beth Archer-Kuhn, Heather Boynton, Judith Hughes

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It is well known that social work students enter the profession with higher scores of adverse childhood experiences (ACE). Add to that the fact that COVID-19 has forced higher education institutions to shift to online teaching and learning, where students, faculty and field educators in social work education have reported increased stressors as well as posing challenges in developing relationships with students and being able to identify mental health challenges including those related to trauma. This multi-institutional project included three Canadian post-secondary institutions at five sites (the University of Waterloo, the University of Calgary and the University of Manitoba) and partners; Desire To Learn (D2L), The Centre for Teaching Excellence at the University of Waterloo and the Taylor Institute for Teaching and Learning. A sequential mixed method research design was used. Survey data was collected from students, faculty and field education staff from the 3 universities using the Qualtrics Insight Platform, followed by virtual focus group data with students to provide greater clarity to the quantitative data. Survey data was analyzed using SPSS software, while focus group data was transcribed verbatim and organized with N-Vivo 12. Thematic analysis used line-by-line coding and constant comparative methods within and across focus groups. The following three objectives of the study were achieved: 1) Establish a Canadian baseline on trauma informed pedagogy and student experiences of trauma informed teaching in the online higher education environment during a pandemic; 2) Identify and document educator and student experiences of online learning regarding the ability to process trauma experiences; and, 3) Transfer the findings into a trauma informed pedagogical model for Social Work as a first step toward developing a universal trauma informed teaching model. The trauma informed pedagogy model would be presented in relation to the study findings.

Keywords: trauma informed pedagogy, higher education, social work, mental health

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Authors: El Hassene Osmani, Mounir Haddou, Naceurdine Bensalem

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In this paper, we investigate optimal control problems governed by semilinear elliptic variational inequalities involving constraints on the state, and more precisely, the obstacle problem. We present a relaxed formulation for the problem using smoothing functions. Since we adopt a numerical point of view, we first relax the feasible domain of the problem, then using both mathematical programming methods and penalization methods, we get optimality conditions with smooth Lagrange multipliers. Some numerical experiments using IPOPT algorithm (Interior Point Optimizer) are presented to verify the efficiency of our approach.

Keywords: complementarity problem, IPOPT, Lagrange multipliers, mathematical programming, optimal control, smoothing methods, variationally inequalities

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Authors: Laura Beckmann, Sabrina Rutter, Isabell Van Ackeren, Nina Bremm, Esther Dominique Klein, Kathrin Racherbäumer

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Current evidence demonstrates that schools in socially disadvantaged contexts are often characterized by lower school performance and lower educational qualifications among the student body, compared to schools in more privileged socio-spacial contexts. At the same time, national and international findings on schools with structural and social challenges show that certain school and classroom development strategies, as well as human and material resources, can significantly contribute to improved school performance of students. The aim of this contribution is to present a 6-year mixed-methods study (Talent Schools in North Rhine-Westphalia), which is designed as a school experiment addressing the well-acknowledged inequality of educational opportunities in the German school system. Started in the year 2019 and funded by the Ministry for School and Education of the State of North Rhine-Westphalia, the study targets schools in socio-spatially disadvantaged areas, which have increasingly been the focus of both public debate and educational policy. In the German-speaking countries, however, there is little knowledge available on the structure and design of complex strategies for school and classroom development that describe successful approaches to the further development of schools in disadvantaged locations in a process-oriented manner. Given these shortcomings, the present study aims at a longitudinal analysis of school and classroom development processes within 60 ‘talent schools’, whereby concrete micro-progressions within individual schools are documented and aggregated to general processes that may either impede or promote development. The main research question is the following: With the help of which strategies and (teaching) concepts, with which use of resources and with which forms of cooperation can schools contribute to the development of student achievement, including educational qualifications and transition rates in education and employment? Thus, the ‘talent schools’ may serve as examples of how social background can successfully be decoupled from educational success at schools with special structural and procedural challenges. The major chances and challenges of this project will be discussed.

Keywords: educational inequality, school development, student achievement, mixed-methods study

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Authors: Jesryl B. Paulite, Irene Alcantara-Papa, Teofila O. Zulaybar, Jocelyn T. Zarate, Virgie Ugay

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Banana is one of the major fruits in the Philippines in terms of volume of production and export earnings. The Philippines export of fresh Cavendish banana ranked No.1 with 22% share. One major threat to the industry is Fusarium wilt caused by Fusarium oxysporum f. sp. cubense. It tops as a major concern today affecting the Philippine banana industry since 2002 up to the present in Mindanao. Because of environmental and health issues concerning the use of chemical pesticides in the control of diseases, utilization of microorganisms has been significant in recent years as a promising alternative. This study aims to evaluate the potential of actinomycetes to control Fusarium wilt in Cavendish banana. The in-vitro experiments was carried out in Complete Randomized Design (CRD) while field experiment was laid out in a Randomized Complete Block Design (RCBD) with three treatments and three replications. Actinomycetes were isolated from mangrove soils in areas in Quezon and Bataan, Philippines. A total of 199 actinomycetes were isolated and 82 actinomycetes showed activity against the local Fusarium oxysporum (Foc) by agar plug assay. The test for antagonisms (AQ6, AQ30, and AQ121) of three best isolates Foc to were selected inhibiting Foc by 21.0mm, 22.0mm and 20.5mm, respectively. The same actinomycetes inhibited well Foc Tropical Race 4 showing 24.6 mm, 20.2mm and 19.0 mm zones of inhibition by agar plug assay, respectively. Combinations of the three isolates yielded an inhibition of 13.5 mm by cup cylinder assay. These findings led to the formulation of the mixed actinomycetes as biocontrol agents against Foc. A field experiment to evaluate the formulated mixed actinomycetes against Foc in a Foc infested field in Kinamayan, Sto Tomas, Davao Del Norte, Philippines. was conducted. Results showed that preventive method of application of the mixed actinomycetes against Foc showed promising results. A 56.66% mortality was observed in control set-up (no biocontrol agent added) compared to 33.33% mortality in preventive method. Further validation of the effectiveness of the mixed actinomycetes as biocontrol agent is presently being conducted in Asuncion, Davao Del Norte, Philippines.

Keywords: actinomycetes, biocontrol agents, cavendish banana, Fusarium oxysporum f. sp. cubense

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Authors: Hanadi Mubarak Al-Mubaraki, Michael Busler

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Innovation is the powerful tools for economic growth and diversification, which lead to smart growth. The objective of this paper is to identify the opportunities and challenges of innovation programs discuss and analyse the implementation of the innovation program in the United States (US) and United Kingdom (UK). To achieve the objectives, the research used a mixed methods approach, quantitative (survey), and qualitative (multi-case study) to examine innovation best practices in developed countries. In addition, the selection of 4 interview case studies of innovation organisations based on the best practices and successful implementation worldwide. The research findings indicated the two challenges such as 1) innovation required business ecosystem support to deliver innovation outcomes such as new product and new services, and 2) foster the climate of innovation &entrepreneurship for economic growth and diversification. Although the two opportunities such as 1) sustainability of the innovation events which lead smart growth, and 2) establish the for fostering the artificial intelligence hub entrepreneurship networking at multi-levels. The research adds value to academicians and practitioners such as government, funded organizations, institutions, and policymakers. The authors aim to conduct future research a comparative study of innovation case studies between developed and developing countries for policy implications worldwide. The Originality of This study contributes to current literature about the innovation best practice in developed and developing countries.

Keywords: economic development, technology transfer, entrepreneurship, innovation program

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Authors: Anastassis Kozanitis, Diane Leduc, Alain Stockless

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This paper presents preliminary results from a two-year funded research program looking to analyze and understand the relationship between high cognitive engagement, higher order cognitive processes employed in situations of complex learning tasks, and the use of active learning pedagogies in engineering undergraduate programs. A mixed method approach was used to gauge student engagement and their cognitive processes when accomplishing complex tasks. Quantitative data collected from the self-report cognitive engagement scale shows that deep learning approach is positively correlated with high levels of complex learning tasks and the level of student engagement, in the context of classroom active learning pedagogies. Qualitative analyses of in depth face-to-face interviews reveal insights into the mechanisms influencing students’ cognitive processes when confronted with open-ended problem resolution. Findings also support evidence that students will adjust their level of cognitive engagement according to the specific didactic environment.

Keywords: cognitive engagement, deep and shallow strategies, engineering programs, higher order cognitive processes

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Authors: Shima Soltanzadeh, Mohammad Hosain Fazel Zarandi, Mojtaba Barzegar Astanjin

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Diagnosis of male infertility by the laboratory tests is expensive and, sometimes it is intolerable for patients. Filling out the questionnaire and then using classification method can be the first step in decision-making process, so only in the cases with a high probability of infertility we can use the laboratory tests. In this paper, we evaluated the performance of four classification methods including naive Bayesian, neural network, logistic regression and fuzzy c-means clustering as a classification, in the diagnosis of male infertility due to environmental factors. Since the data are unbalanced, the ROC curves are most suitable method for the comparison. In this paper, we also have selected the more important features using a filtering method and examined the impact of this feature reduction on the performance of each methods; generally, most of the methods had better performance after applying the filter. We have showed that using fuzzy c-means clustering as a classification has a good performance according to the ROC curves and its performance is comparable to other classification methods like logistic regression.

Keywords: classification, fuzzy c-means, logistic regression, Naive Bayesian, neural network, ROC curve

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Authors: Boualla Nabila

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The increasing demand on water, either for the drinkable water supply, or for the agricultural and industrial custom, requires a very thorough hydrochemical study to protect better and manage this resource. Oran is relatively a city with the worst quality of the water. Recently, the growing populations may put stress on natural waters by impairing the quality of the water. Campaign of water sampling of 55 points capturing different levels of the aquifer system was done for chemical analyzes of nutriments elements. The results allowed us to approach the problem of contamination based on the largely uniform nationwide approach LAWA (LänderarbeitsgruppeWasser), based on the EU CIS guidance, has been applied for the identification of pressures and impacts, allowing for easy comparison. Groundwater samples were analyzed, also, for physico-chemical parameters such as pH, sodium, potassium, calcium, magnesium, chloride, sulphate, carbonate and bicarbonate. The analytical results obtained in this hydrochemistry study were interpreted using Durov diagram. Based on these representations, the anomaly of high groundwater salinity observed in Oran Sebkha basin was explained by the high chloride concentration and to the presence of inverse cation exchange reaction. Durov diagram plot revealed that the groundwater has been evolved from Ca-HCO3 recharge water through mixing with the pre-existing groundwater to give mixed water of Mg-SO4 and Mg-Cl types that eventually reached a final stage of evolution represented by a Na-Cl water type.

Keywords: contamination, water quality, nutrients elements, approach LAWA, durov diagram

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Authors: Muhammad Naweed, Usman Tariq Murtaza, Waseem Siddique

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A pallet body approach is a finite element-based computational approach used for the modeling and assessment of a three-dimensional surface crack. The approach is capable of inserting the crack in an engineering structure and generating high-quality hexahedral mesh in the cracked region of the structure. The approach is capable of computing the stress intensity factors along a semi-elliptical surface crack numerically. The objective of this work is to present that the stress intensity factors produced by the approach can be used with confidence for capturing the parameters during the fatigue crack growth.

Keywords: pallet body approach, semi-elliptical surface crack, stress intensity factors, fatigue crack growth

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Authors: Yena Lee, Vassilis M. Charitopoulos, Karthik Thyagarajan, Ian Morris, Jose M. Pinto, Lazaros G. Papageorgiou

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With globalisation, the need to have better coordination of production and distribution decisions has become increasingly important for industrial gas companies in order to remain competitive in the marketplace. In this work, we investigate a problem that integrates production, inventory, and routing decisions in a liquid oxygen supply chain. The oxygen supply chain consists of production facilities, external third-party suppliers, and multiple customers, including hospitals and industrial customers. The product produced by the plants or sourced from the competitors, i.e., third-party suppliers, is distributed by a fleet of heterogenous vehicles to satisfy customer demands. The objective is to minimise the total operating cost involving production, third-party, and transportation costs. The key decisions for production include production and inventory levels and product amount from third-party suppliers. In contrast, the distribution decisions involve customer allocation, delivery timing, delivery amount, and vehicle routing. The optimisation of the coordinated production, inventory, and routing decisions is a challenging problem, especially when dealing with large-size problems. Thus, we present a two-stage procedure to solve the integrated problem efficiently. First, the problem is formulated as a mixed-integer linear programming (MILP) model by simplifying the routing component. The solution from the first-stage MILP model yields the optimal customer allocation, production and inventory levels, and delivery timing and amount. Then, we fix the previous decisions and solve a detailed routing. In the second stage, we propose a column generation scheme to address the computational complexity of the resulting detailed routing problem. A case study considering a real-life oxygen supply chain in the UK is presented to illustrate the capability of the proposed models and solution method. Furthermore, a comparison of the solutions from the proposed approach with the corresponding solutions provided by existing metaheuristic techniques (e.g., guided local search and tabu search algorithms) is presented to evaluate the efficiency.

Keywords: production planning, inventory routing, column generation, mixed-integer linear programming

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Authors: Hanadi Mubarak AL-Mubaraki, Michael Busler

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Innovation is the process of making changes, differences, and novelties in the products and services, adding values and business practices to create economic and social benefit. The purpose of this paper is to identify the strengths and weaknesses of innovation programs in developed and developing countries. We used a mixed-methods approach, quantitative as survey and qualitative as a multi-case study to examine innovation best practices in developed and developing countries. In addition, four case studies of innovation organisations based on the best practices and successful implementation in the developed and developing countries are selected for examination. The research findings provide guidance, suggestions, and recommendations for future implementation in developed and developing countries for practitioners such as policy makers, governments, funded organizations, and strategic institutions. In conclusion, innovation programs are vital tools for economic growth, knowledge, and technology transfer based on the several indicators such as creativity, entrepreneurship, role of government, role of university, strategic focus, new products, survival rate, job creation, start-up companies, and number of patents. The authors aim to conduct future research which will include a comparative study of innovation case studies between developed and developing countries for policy implications worldwide. The originality of this study makes a contribution to the current literature about the innovation best practice in developed and developing countries.

Keywords: economic development, entrepreneurship, innovation program, developed countries

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Authors: Hossein Tavallali, Mohammad Ali Karimi, Gohar Deilamy-Rad

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The proposed method for speciation, preconcentration and determination of Fe(II) and Fe(III) in pharmaceutical products was developed using of alumina-coated magnetite nanoparticles (Fe₃O₄/Al₂O₃ NPs) as solid phase extraction (SPE) sorbent in magnetic mixed hemimicell solid phase extraction (MMHSPE) technique followed by flame atomic absorption spectrometry analysis. The procedure is based on complexation of Fe(II) with 1, 10-phenanthroline (OP) as complexing reagent for Fe(II) that immobilized on the modified Fe₃O₄/Al₂O₃ NPs. The extraction and concentration process for pharmaceutical sample was carried out in a single step by mixing the extraction solvent, magnetic adsorbents under ultrasonic action. Then, the adsorbents were isolated from the complicated matrix easily with an external magnetic field. Fe(III) ions determined after facility reduced to Fe(II) by added a proper reduction agent to sample solutions. Compared with traditional methods, the MMHSPE method simplified the operation procedure and reduced the analysis time. Various influencing parameters on the speciation and preconcentration of trace iron, such as pH, sample volume, amount of sorbent, type and concentration of eluent, were studied. Under the optimized operating conditions, the preconcentration factor of the modified nano magnetite for Fe(II) 167 sample was obtained. The detection limits and linear range of this method for iron were 1.0 and 9.0 - 175 ng.mL⁻¹, respectively. Also the relative standard deviation for five replicate determinations of 30.00 ng.mL^-1 Fe²⁺ was 2.3%.

Keywords: Alumina-Coated magnetite nanoparticles, Magnetic Mixed Hemimicell Solid-Phase Extraction, Fe(ΙΙ) and Fe(ΙΙΙ), pharmaceutical sample

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Authors: C. E. Nugraheni, L. Abednego

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This paper is concerned with minimization of mean tardiness and flow time in a real single machine production scheduling problem. Two variants of genetic algorithm as meta-heuristic are combined with hyper-heuristic approach are proposed to solve this problem. These methods are used to solve instances generated with real world data from a company. Encouraging results are reported.

Keywords: hyper-heuristics, evolutionary algorithms, production scheduling, meta-heuristic

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Authors: Amira D. Ali

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Action research studies in education often address learners’ needs and empower practitioner-researcher to effectively change instructional practices and school communities. A systematic review of action research (AR) studies undertaken in EFL/ESL settings was conducted in this paper to systematically analyze empirical studies on action research published within a ten-year period (between 2010 and 2019). The review also aimed at investigating the focal strategies in teaching the language skills at school level and evaluating the overall quality of AR studies concerning focus, purpose, methodology and contribution. Inclusion criteria were established and 41 studies that fit were finally selected for the systematic review. Garrard’s (2007) Matrix Method was used to structure and synthesize the literature. Results showed a significant diversity in teaching strategies and implementation of the AR model. Almost a quarter of the studies focused on improving writing skills at elementary school level. In addition, findings revealed that (44%) of the studies used a mixed approach followed by qualitative method approach (41%), whereas only (15%) employed quantitative methodology. Research gaps for future action research in developing language skills were pointed out, and recommendations were offered.

Keywords: action research, EFL/ESL context, language skills, systematic review

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Authors: Mulanga Luscious Mulaudzi, Ignatious Ncube

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In nature, enzymatic degradation of lignocellulose is more efficient compared to in vivo bioprocessing. Thus, a co-culture should enable production of more efficient enzyme preparations that would mimic the natural decomposition of lignocellulose. The aim of the study was to establish a microbial co-culture for the production of highly active cellulase preparations. The objectives were to determine the use of a variety of culture media to isolate cellulose degrading microorganisms from decomposing banana pseudo stem and to optimize production of cellulase by co-cultures of microorganisms producing high levels of cellulose. Screening of fungal isolates was done on carboxylmethylcellulose agar plates which were stained with Congo red to show hydrolytic activity of the isolates. Co-culture and mixed culture of these microorganisms were cultured using Mendel salts with Avicel as the carbon source. Cultures were incubated at 30 °C with shaking at 200 rpm for 240 hrs. Enzyme activity assays were performed to determine endoglycosidase and β-glucosidase. Mixed culture of fungi-dead bacterial cells showed to be the best co-culture/ mixed culture to produce higher levels of cellulase activity in submerged fermentations (SmF) using Avicel™ as a carbon source. The study concludes use microorganism 5A in co-cultures is highly recommended in order to produce high amounts of β-glucosidases, no matter the combination used.

Keywords: avicel, co-culture, submerged fermentation, pseudostem

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Authors: A. Satty, H. Mwambi

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Much clinical trials data-based research are characterized by the unavoidable problem of dropout as a result of missing or erroneous values. This paper aims to review some of the various techniques to address the dropout problems in longitudinal clinical trials. The fundamental concepts of the patterns and mechanisms of dropout are discussed. This study presents five general techniques for handling dropout: (1) Deletion methods; (2) Imputation-based methods; (3) Data augmentation methods; (4) Likelihood-based methods; and (5) MNAR-based methods. Under each technique, several methods that are commonly used to deal with dropout are presented, including a review of the existing literature in which we examine the effectiveness of these methods in the analysis of incomplete data. Two application examples are presented to study the potential strengths or weaknesses of some of the methods under certain dropout mechanisms as well as to assess the sensitivity of the modelling assumptions.

Keywords: incomplete longitudinal clinical trials, missing at random (MAR), imputation, weighting methods, sensitivity analysis

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Authors: Nasra Idilbi, Jalal Tarabeia, Layalleh Masalha, Heiam Shoufani Kassis, Gizell Green

Abstract:

Background: Healthcare professionals working in underground facilities face unique challenges affecting their physical and mental health and team effectiveness. We aimed to examine how an underground work environment affects the physical and mental health and effectiveness of a multi-professional medical team in a medical center under continuous war threats and the contribution of various demographic and professional characteristics. Methods: A cross-sectional survey was disseminated electronically. The questionnaire assessed team effectiveness, the quality of the work, and the health symptoms reported by the team while working in the underground complex. Results: In total, 270 healthcare workers (mean age 40 years, 75.6% females, 88.4% nurses) completed the questionnaire. Women reported statistically significantly higher mean scores of physical strain, fatigue, and eye irritation associated with the work environment compared to men. Multiple regression analysis revealed that psychological distress, noise, and lighting in the underground compound significantly influenced team effectiveness. The qualitative analysis revealed two key themes: the mental health impact of working in an underground environment and the effects of noise and lighting on staff performance. Nurses reported feelings of suffocation, claustrophobia, and difficulty concentrating due to the enclosed space, with some expressing heightened stress levels that impaired their ability to work effectively and safely. Female staff reported more pronounced symptoms of physical strain, fatigue, and eye irritation. Additionally, the underground complex’s poor noise absorption created a highly disruptive work environment, while inadequate lighting hindered accurate patient assessments, leading to potential errors. These challenges were exacerbated by physical symptoms like headaches and nausea, which further impacted job performance. The findings underscore the significant role of environmental factors in influencing both mental health and operational effectiveness, aligning with quantitative data on the predictors of team performance. Conclusions: The underground work environment is crucial in influencing healthcare team effectiveness, with psychological distress, noise, and lighting as key factors. The study highlights the importance of creating a comfortable work environment to foster team efficiency. The findings provide valuable insights for managers in underground healthcare facilities to optimize team performance and well-being.

Keywords: team effectiveness, underground settings, healthcare, environmental factors, a mixed-methods study

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Authors: Fang-Bo Yu, Li-Bo Guan, Sheng-Dao Shan

Abstract:

Biogas slurry was mixed with six commercial fungicides and screening against 11 phytopathogens was carried out. Results showed that inhibition of biogas slurry was different for the test strains and no significant difference between treatments of Didymella bryoniae, Fusarium oxysporum f. sp. vasinfectum, Aspergillus niger, Rhizoctonia cerealis, F. graminearum and Septoria tritici was observed. However, significant differences were found among Penicillium sp., Botrytis cinerea, Alternaria sonali, F. oxysporum F. sp. melonis and Sclerotinia sclerotiorum. The approach described here presents a promising alternative to current manipulation although some issues still need further examination. This study could contribute to the development of sustainable agriculture and better utilization of biogas slurry.

Keywords: anaerobic digestion, biogas slurry, phytopathogen, sustainable agriculture

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Authors: Bourama Mane, Ibrahima Fall, Mamadou Samba Camara, Alassane Bah

Abstract:

At the level of the National Statistical Institutes, there is a large volume of data which is generally in a format which conditions the method of publication of the information they contain. Each household or business data collection project includes a dissemination platform for its implementation. Thus, these dissemination methods previously used, do not promote rapid access to information and especially does not offer the option of being able to link data for in-depth processing. In this paper, we present an approach to modeling these data to publish them in a format intended for the Semantic Web. Our objective is to be able to publish all this data in a single platform and offer the option to link with other external data sources. An application of the approach will be made on data from major national surveys such as the one on employment, poverty, child labor and the general census of the population of Senegal.

Keywords: Semantic Web, linked open data, database, statistic

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Authors: S. K. Mohapatra, K. Ramanujam, S. Sankararaman

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Redox flow battery (RFB) is a preferred energy storage option for grid stabilisation and energy arbitrage as it offers energy and power decoupling. In contrast to aqueous RFBs (ARFBs), nonaqueous RFBs (NARFBs) could offer high energy densities due to the wider electrochemical window of the solvents used, which could handle high and low voltage organic redox couples without undergoing electrolysis. In this study, a RFB based on benzyl viologen hexafluorophosphate [BV(PF6)2] as anolyte and N-hexyl phenothiazine [HPT] as catholyte demonstrated. A cell operated with mixed electrolyte (1:1) containing 0.2 M [BV(PF₆)₂] and 0.2 M [HPT] delivered a coulombic efficiency (CE) of 95.3 % and energy efficiency (EE) 53%, with nearly 68.9% material utilisation at 40 mA cm-2 current density.

Keywords: non-aqueous redox flow battery, benzyl viologen, N-hexyl phenothiazine, mixed electrolyte

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Authors: Azzaya Enkhjargal

Abstract:

Context: The mining industry has a long history of human rights abuses, including forced labor, environmental pollution, and displacement of communities. In recent years, there has been growing international pressure to hold mining companies accountable for these abuses. Research Aim: This study explores the legal liabilities of mining companies for human rights abuses. The study specifically examines the case of Erdenet Mining Corporation (EMC), a large mining company in Mongolia that has been accused of human rights abuses. Methodology: The study used a mixed-methods approach, which included a review of legal literature, interviews with community members and NGOs, and a case study of EMC. Findings: The study found that mining companies can be held liable for human rights abuses under a variety of regulatory frameworks, including soft law and self-regulatory instruments in the mining industry, international law, national law, and corporate law. The study also found that there are a number of challenges to holding mining companies accountable for human rights abuses, including the lack of effective enforcement mechanisms and the difficulty of proving causation. Theoretical Importance: The study contributes to the growing body of literature on the legal liabilities of mining companies for human rights abuses. The study also provides insights into the challenges of holding mining companies accountable for human rights abuses. Data Collection: The data for the study was collected through a variety of methods, including a review of legal literature, interviews with community members and NGOs, and a case study of EMC. Analysis Procedures: The data was analyzed using a variety of methods, including content analysis, thematic analysis, and case study analysis. Conclusion: The study concludes that mining companies can be held liable for human rights abuses under a variety of legal and regulatory frameworks. There are positive developments in ensuring greater accountability and protection of affected communities and the environment in countries with a strong economy. Regrettably, access to avenues of redress is reasonably low in less developed countries, where the governments have not implemented a robust mechanism to enforce liability requirements in the mining industry. The study recommends that governments and mining companies take more ambitious steps to enhance corporate accountability.

Keywords: human rights, human rights abuses, ESG, litigation, Erdenet Mining Corporation, corporate social responsibility, soft law, self-regulation, mining industry, parent company liability, sustainability, environment, UN

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