Search results for: multi variable decision making

Authors: Danielle A. Walker, Kyle L. Johnson, Patrick J. Fox, Jacen S. Moore

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The HIV Continuum of Care has become a universal model to provide context for the process of HIV testing, linkage to care, treatment, and viral suppression. HIV testing is the first step in moving toward community viral suppression. Countries with a lower socioeconomic status experience the lowest rates of testing and access to care. The Democratic Republic of the Congo is located in the heart of sub-Saharan Africa, where testing and access to care are low and women experience higher HIV prevalence compared to men. In the Democratic Republic of the Congo there is only a 21.6% HIV testing rate among women. Because a critical gap exists between a woman’s risk of contracting HIV and the decision to be tested, this study was conducted to obtain a better understanding of the relationship between factors that could influence HIV testing among women. The datasets analyzed were from the 2013-14 Democratic Republic of the Congo Demographic and Health Survey Program. The data was subset for women with an age range of 18-49 years. All missing cases were removed and one variable was recoded. The total sample size analyzed was 14,982 women. The results showed that there did not seem to be a difference in HIV testing by mean age. Out of 11 religious categories (Catholic, Protestant, Armee de salut, Kimbanguiste, Other Christians, Muslim, Bundu dia kongo, Vuvamu, Animist, no religion, and other), those who identified as Other Christians had the highest testing rate of 25.9% and those identified as Vuvamu had a 0% testing rate (p<0.001). There was a significant difference in testing by religion. Only 0.7% of women surveyed identified as having no religious affiliation. This suggests partnerships with key community and religious leaders could be a tool to increase testing. Over 60% of women who had never been tested for HIV did not know where to be tested. This highlights the need to educate communities on where testing facilities can be located. Almost 80% of women who believed HIV could be transmitted by supernatural means and/or witchcraft had never been tested before (p=0.08). Cultural beliefs could influence risk perception and testing decisions. Consequently, misconceptions need to be considered when implementing HIV testing and prevention programs. Location by province, years of education, and wealth index were also analyzed to control for socioeconomic status. Kinshasa had the highest testing rate of 54.2% of women living there, and both Equateur and Kasai-Occidental had less than a 10% testing rate (p<0.001). As the education level increased up to 12 years, testing increased (p<0.001). Women within the highest quintile of the wealth index had a 56.1% testing rate, and women within the lowest quintile had a 6.5% testing rate (p<0.001). This study concludes that further research is needed to identify culturally competent methods to increase HIV education programs, build partnerships with key community leaders, and improve knowledge on access to care.

Keywords: Democratic Republic of the Congo, cultural beliefs, education, HIV testing

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Authors: Ida Bruheim Jensen, Hulda Mjöll Gunnarsdottir, Ingunn T. Ellingsen

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Digital government is often seen as an enabler or even driver of transformation of public administration, with the objective of creating public value. The increasing use of digital solutions in public services comes with great expectations of new and/or more efficient service provision. Digitalizing public sector services involve multi-level implementation. It involves national policy negotiations and decisions of digital government solutions. It involves co-creation/-production of ideas where planning, design, and implementation involves several groups of actors targeting end-users. Norway is among the most digitalised countries in the world, and Government spendings on digital technologies in public services are high compared to other OECD countries. This contribution studies an ongoing digital transformation in the Norwegian child welfare services. DigiBarnevern (Digi child welfare) is a nationwide project promising better and more efficient child welfare services through various digital technologies. The digitalization process, which is managed by the state and municipalities, is still in its early stages, and as of 2022, only a few services are operative. Digital technologies such as DigiBarnevern are implemented with promises of qualitatively improving child protection work, making the services more effective, foster user participation, and increase availability. There is limited research on the implications of using digital technologies in child protection work. We aim to present findings from an ongoing research project (2022-2024). Drawing on data from focus group interviews with social workers in 5 municipal child welfare services in Norway, we explore social workers’ experiences and expectations towards using digital technologies in child welfare services. Technological solutions may change the services and child protection work in numerous ways. Potential points of departure for discussion are how technologies may change the relationships between social workers, children, youth, and their families, how technologies can alter and obscure responsibilities, and how technologies may demand digital competence among social workers and service recipients.

Keywords: child welfare, social work, technology, digitalisation

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Authors: Yiping Meng, Yiming Sun

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The traditional construction industry is unable to meet the requirements for novel fabrication and construction. Automated construction and digital design have emerged as industry development trends that compensate for this shortcoming under the backdrop of Industrial Revolution 4.0. Benefitting from more flexible working space and more various end-effector tools compared to CNC methods, robot fabrication and construction techniques have been used in irregular architectural design. However, there is a lack of a systematic and comprehensive design and optimisation workflow considering geometric form, material, and fabrication methods. This paper aims to propose a design optimisation workflow for improving the rationality of a free-form timber structure fabricated by the robotic arm. Firstly, the free-form surface is described by NURBS, while its structure is calculated using the finite element analysis method. Then, by considering the characteristics and limiting factors of robotic timber fabrication, strain energy and robustness are set as optimisation objectives to optimise structural morphology by gradient descent method. As a result, an optimised structure with axial force as the main force and uniform stress distribution is generated after the structure morphology optimisation process. With the decreased strain energy and the improved robustness, the generated structure's bearing capacity and mechanical properties have been enhanced. The results prove the feasibility and effectiveness of the proposed optimisation workflow for free-form timber structure morphology design.

Keywords: robotic fabrication, free-form timber structure, Multi-objective optimisation, Structural morphology, rational design

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Authors: Yu-ding Du, Qi-lian Bao, Nassim Bessaad, Lin Liu

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The Global Navigation Satellite System (GNSS) is regarded as an effective approach for the purpose of replacing the large amount used track-side balises in modern train localization systems. This paper describes a method based on the data fusion of a GNSS receiver sensor and an odometer sensor that can significantly improve the positioning accuracy. A digital track map is needed as another sensor to project two-dimensional GNSS position to one-dimensional along-track distance due to the fact that the train’s position can only be constrained on the track. A model trained by BP neural network is used to estimate the trend positioning error which is related to the specific location and proximate processing of the digital track map. Considering that in some conditions the satellite signal failure will lead to the increase of GNSS positioning error, a detection step for GNSS signal is applied. An adaptive weighted fusion algorithm is presented to reduce the standard deviation of train speed measurement. Finally an Extended Kalman Filter (EKF) is used for the fusion of the projected 1-D GNSS positioning data and the 1-D train speed data to get the estimate position. Experimental results suggest that the proposed method performs well, which can reduce positioning error notably.

Keywords: multi-sensor data fusion, train positioning, GNSS, odometer, digital track map, map matching, BP neural network, adaptive weighted fusion, Kalman filter

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Authors: Milena Nanova, Martin Georgiev, Damyan Damov

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Modern residential architecture is increasingly influenced by rapid urbanization, technological advancements, and growing investor expectations. The integration of AI and digital tools such as CAD and BIM (Building Information Modelling) is transforming the design process by improving efficiency, accuracy, and speed. However, urban development faces challenges, including the high competition for viable sites and the time-consuming nature of traditional investment feasibility studies and architectural planning. Finding and analyzing suitable sites for residential development is complicated by intense competition and rising investor demands. Investors require quick assessments of property potential to avoid missing opportunities, while traditional architectural design processes rely on the experience of the team and can be time-consuming, adding pressure to make fast, effective decisions. The widespread use of CAD tools has sped up the drafting process, enhancing both accuracy and efficiency. Digital tools allow designers to manipulate drawings quickly, reducing the time spent on revisions. BIM further advances this by enabling native 3D modelling, where changes to a design in one view are automatically reflected in all others, minimizing errors and saving time. AI is becoming an integral part of architectural design software. While AI is currently being incorporated into existing programs like AutoCAD, Revit, and ArchiCAD, its full potential is reached in parametric modelling. In this process, designers define parameters (e.g., building size, layout, and materials), and the software generates multiple design variations based on those inputs. This method accelerates the design process by automating decisions and enabling the quick generation of alternative solutions. The study utilizes generative design, a specific application of parametric modelling that uses Machine Learning (ML) to explore a wide range of design possibilities based on predefined criteria. It optimizes designs through iterations, testing many variations to find the best solutions. This process is particularly beneficial in the early stages of design, where multiple options are explored before refining the best ones. ML’s ability to handle complex mathematical tasks allows it to generate unconventional yet effective designs that a human designer might overlook. Residential architecture, with its anticipated and typical layouts and modular nature, is especially suitable for generative design. The relationships between rooms and the overall organization of apartment units follow logical patterns, making it an ideal candidate for parametric modelling. Using these tools, architects can quickly explore various apartment configurations, considering factors like apartment sizes, types, and circulation patterns, and identify the most efficient layout for a given site. Parametric modelling and generative design offer significant benefits to residential architecture by streamlining the design process, enabling faster decision-making, and optimizing building layouts. These technologies allow architects and developers to analyze numerous design possibilities, improving outcomes while responding to the challenges of urban development. By integrating ML-driven generative design, the architecture industry can enhance creativity, efficiency, and adaptability in residential projects.

Keywords: architectural design, generative design, parametric models, residential buildings, workflow optimization

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Authors: Chia-Jung Chen, Yu-Chi Hsu, June-Dong Lin, Kun-Chen Chan, Chieh-Tien Wang, Li-Ching Wu, Chung-Feng Liu

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With fast advances in healthcare technology, various total laboratory automation (TLA) processes have been proposed. However, adopting TLA needs quite high funding. This study explores an early adoption experience by Taiwan’s large-scale hospital group, the Chimei Hospital Group (CMG), which owns three branch hospitals (Yongkang, Liouying and Chiali, in order by service scale), based on the five stages of Everett Rogers’ Diffusion Decision Process. 1.Knowledge stage: Over the years, two weaknesses exists in laboratory department of CMG: 1) only a few examination categories (e.g., sugar testing and HbA1c) can now be completed and reported within a day during an outpatient clinical visit; 2) the Yongkang Hospital laboratory space is dispersed across three buildings, resulting in duplicated investment in analysis instruments and inconvenient artificial specimen transportation. Thus, the senior management of the department raised a crucial question, was it time to process the redesign of the laboratory department? 2.Persuasion stage: At the end of 2013, Yongkang Hospital’s new building and restructuring project created a great opportunity for the redesign of the laboratory department. However, not all laboratory colleagues had the consensus for change. Thus, the top managers arranged a series of benchmark visits to stimulate colleagues into being aware of and accepting TLA. Later, the director of the department proposed a formal report to the top management of CMG with the results of the benchmark visits, preliminary feasibility analysis, potential benefits and so on. 3.Decision stage: This TLA suggestion was well-supported by the top management of CMG and, finally, they made a decision to carry out the project with an instrument-leasing strategy. After the announcement of a request for proposal and several vendor briefings, CMG confirmed their laboratory automation architecture and finally completed the contracts. At the same time, a cross-department project team was formed and the laboratory department assigned a section leader to the National Taiwan University Hospital for one month of relevant training. 4.Implementation stage: During the implementation, the project team called for regular meetings to review the results of the operations and to offer an immediate response to the adjustment. The main project tasks included: 1) completion of the preparatory work for beginning the automation procedures; 2) ensuring information security and privacy protection; 3) formulating automated examination process protocols; 4) evaluating the performance of new instruments and the instrument connectivity; 5)ensuring good integration with hospital information systems (HIS)/laboratory information systems (LIS); and 6) ensuring continued compliance with ISO 15189 certification. 5.Confirmation stage: In short, the core process changes include: 1) cancellation of signature seals on the specimen tubes; 2) transfer of daily examination reports to a data warehouse; 3) routine pre-admission blood drawing and formal inpatient morning blood drawing can be incorporated into an automatically-prepared tube mechanism. The study summarizes below the continuous improvement orientations: (1) Flexible reference range set-up for new instruments in LIS. (2) Restructure of the specimen category. (3) Continuous review and improvements to the examination process. (4) Whether installing the tube (specimen) delivery tracks need further evaluation.

Keywords: innovation decision process, total laboratory automation, health care

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Authors: V. V. Lakshmi, Y. V. S. Annapurna

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Urinary tract infection (UTI) is one of the most common infectious diseases seen in the community. Susceptible individuals experience multiple episodes, and progress to acute pyelonephritis or uro-sepsis or develop asymptomatic bacteriuria (ABU). Ability to cause extraintestinal infections depends on several virulence factors required for survival at extraintestinal sites. Presence of virulence phenotypes enhances the pathogenicity of these otherwise commensal organisms and thus augments its ability to cause extraintestinal infections, the most frequent in urinary tract infections(UTI). The present study focuses on detection of the virulence characters exhibited by the uropathogenic organism and most common factors exhibited in the local pathogens. A total of 700 isolates of E.coli and Klebsiella spp were included in the study. These were isolated from patients from local hospitals reported to be suffering with UTI over a period of three years. Isolation and identification was done based on Gram character and IMVIC reactions. Antibiotic sensitivity profile was carried out by disc diffusion method and multi drug resistant strains with MAR index of 0.7 were further selected.. Virulence features examined included their ability to produce exopolysaccharides, protease- gelatinase production, hemolysin production, haemagglutination and hydrophobicity test. Exopolysaccharide production was most predominant virulence feature among the isolates when checked by congo red method. The biofilms production examined by microtitre plates using ELISA reader confirmed that this is the major factor contributing to virulencity of the pathogens followed by hemolysin production

Keywords: Escherichia coli, Klebsiella sp, Uropathogens, Virulence features.

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Authors: Mohammed Abdullah Alshahrani

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The research focuses on investigating the use of partial least squares (PLS) methodology for addressing challenges associated with high-dimensional correlated data. Recent technological advancements have led to experiments producing data characterized by a large number of variables compared to observations, with substantial inter-variable correlations. Such data patterns are common in chemometrics, where near-infrared (NIR) spectrometer calibrations record chemical absorbance levels across hundreds of wavelengths, and in genomics, where thousands of genomic regions' copy number alterations (CNA) are recorded from cancer patients. PLS serves as a widely used method for analyzing high-dimensional data, functioning as a regression tool in chemometrics and a classification method in genomics. It handles data complexity by creating latent variables (components) from original variables. However, applying PLS can present challenges. The study investigates key areas to address these challenges, including unifying interpretations across three main PLS algorithms and exploring unusual negative shrinkage factors encountered during model fitting. The research presents an alternative approach to addressing the interpretation challenge of predictor weights associated with PLS. Sparse estimation of predictor weights is employed using a penalty function combining a lasso penalty for sparsity and a Cauchy distribution-based penalty to account for variable dependencies. The results demonstrate sparse and grouped weight estimates, aiding interpretation and prediction tasks in genomic data analysis. High-dimensional data scenarios, where predictors outnumber observations, are common in regression analysis applications. Ordinary least squares regression (OLS), the standard method, performs inadequately with high-dimensional and highly correlated data. Copy number alterations (CNA) in key genes have been linked to disease phenotypes, highlighting the importance of accurate classification of gene expression data in bioinformatics and biology using regularized methods like PLS for regression and classification.

Keywords: partial least square regression, genetics data, negative filter factors, high dimensional data, high correlated data

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Authors: Tibah Alharbi, Renzo Cordina, David Power

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Relatively few studies have explored how venture capitalist investors (VCs) make investment decisions and the information they rely on when taking an equity stake in an investee company. In addition, little is known about how much investors monitor start-ups after the decision to invest has been made. The VC scene in the US or European context is understood better than that of developing countries such as those in the Middle East. Although some differences among VC investors have been identified, the reasons behind such differences have not been fully explored – especially in a country such as Saudi Arabia. Therefore, this research seeks to understand the impact of external factors on the VC investor’ behaviour. The unique cultural and legal environments in the Kingdom of Saudi Arabia, the growing VC sector in the country, and the increasing importance attached to start-ups under the Saudi Government’s Vision 2030 program make such an investigation timely. Ascertaining the perceptions of VC investors in such a context will provide a deeper understanding of the determinants of VC investment in a novel setting. Using semi-structured interviews with over 20 participants, the research explores the structure of VC funds, the cycle of the VC investment in a start-up from the sourcing of deals, the screening and evaluation of such deals, the closing of such deals, and finally, the monitoring of such investments before the decision to exit such deals at the appropriate time. The results show some similarities to the VC model, which characterizes such investment in the US and Europe, but several differences emerge given the unique cultural and legal settings within the Kingdom. The results provide an in-depth understanding of the VC investors’ mindset relative to the existing studies in the literature.

Keywords: exit, monitoring, start-ups, venture capital

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Authors: Bruno Nascimento, Cristina Wanzeller, Jorge Silva, João A. Dias, André Barbosa, José Ribeiro

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The increasing complexity of logistics operations stems from evolving business needs, such as the shift from mass production to mass customization, which demands greater efficiency and flexibility. In response, Industry 4.0 and 5.0 technologies provide improved solutions to enhance operational agility and better meet market demands. The management of kitting zones, combined with the use of Autonomous Mobile Robots, faces challenges related to coordination, resource optimization, and rapid response to customer demand fluctuations. Additionally, implementing lean manufacturing practices in this context must be carefully orchestrated by intelligent systems and human operators to maximize efficiency without sacrificing the agility required in an advanced production environment. This paper proposes and implements a microservices-based architecture integrating principles from Industry 4.0 and 5.0 with lean manufacturing practices. The architecture enhances communication and coordination between autonomous vehicles and kitting management systems, allowing more efficient resource utilization and increased scalability. The proposed architecture focuses on the modularity and flexibility of operations, enabling seamless flexibility to change demands and the efficient allocation of resources in realtime. Conducting this approach is expected to significantly improve logistics operations’ efficiency and scalability by reducing waste and optimizing resource use while improving responsiveness to demand changes. The implementation of this architecture provides a robust foundation for the continuous evolution of kitting management and process optimization. It is designed to adapt to dynamic environments marked by rapid shifts in production demands and real-time decision-making. It also ensures seamless integration with automated systems, aligning with Industry 4.0 and 5.0 needs while reinforcing Lean Manufacturing principles.

Keywords: microservices, event-driven, kitting, AMR, lean manufacturing, industry 4.0, industry 5.0

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Authors: Tewele Gerlase Haile

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Like any other country, Ethiopia's state government has reached today by undergoing many political changes. Until the last quarter of the 19th century, the aristocratic regimes of Ethiopia were using their infinite mystical power to shape the traditional public administrative institutions of the country. Mystical, feudal, social, and revolutionary political systems were used as sources of ruling power to the long-lasted monarchical, military and dictatorial regimes. For a country that is struggling to escape from the vicious cycle of poverty, famines, and civil wars, understanding how political regimes reform public policies and institutions is necessary for several reasons. A retrospective policy analysis approach is employed to determine how public policies are shaped by institutional factors and why the traditional public administration paradigm of Ethiopia continues to date despite regime changes. Using the experiences of political reforms practiced in four successive regimes (1916-2023), this retrospective analysis reveals a causal relationship among policy, institutional, and political failures. Moreover, Ethiopia's law-making and policy-making background significantly reflects the behavior of governments and their institutions. With a macro-level policy analysis in mind, the paper analyzes why the recent policy and institutional reforms twisted the country into unresolved military catastrophes.

Keywords: public administration, public policy, institutional reform, political structure

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Authors: Atiya Khan

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Recent research on the condition of school education in India has reaffirmed the importance of quality teacher professional development, especially in light of the rapid changes in teaching methods, learning theories, curriculum, and major shifts in information and technology that education systems are experiencing around the world. However, the quality of programs of teacher professional development in India is often uneven, in some cases non-existing. The educational authorities in India have long recognized this and have developed a range of programs to assist in-service teacher education. But, these programs have been mostly inadequate at improving the quality of teachers in India. Policy literature and reports indicate that the unevenness of these programs and more generally the lack of quality teacher professional development in India are due to factors such as a large number of teachers, budgetary constraints, top-down decision making, teacher overload, lack of infrastructure, and little or no follow-up. The disparity between the government stated goals for quality teacher professional development in India and its inability to meet the learning needs of teachers suggests that new interventions are needed. The realization that globalization has brought about an increase in the social, cultural, political and economic interconnectedness between countries has also given rise to transnational opportunities for education systems, such as India’s, aiming to build their capacity to support teacher professional development. Moreover, new developments in communication technologies seem to present a plausible means of achieving high-quality professional development for teachers through the creation of social learning spaces, such as transnational learning networks. This case study investigates the potential of one such transnational learning network to support the quality of teacher professional development in India, namely the Australia-Asia BRIDGE School Partnerships Project. It explores the participation of some fifteen teachers and their principals from BRIDGE participating schools in Delhi region of India; focusing on their professional development expectations from the BRIDGE program and account for their experiences in the program, in order to determine the program’s potential for the professional development of teachers in this study.

Keywords: case study, Australia-Asia BRIDGE Project, teacher professional development, transnational learning networks

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Authors: Nicolas M. Beleski, Gustavo A. G. Lugo

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Robotic agents are taking more and increasingly important roles in society. In order to make these robots and agents more autonomous and efficient, their systems have grown to be considerably complex and convoluted. This growth in complexity has led recent researchers to investigate forms to explain the AI behavior behind these systems in search for more trustworthy interactions. A current problem in explainable AI is the inner workings with the logic inference process and how to conduct a sensibility analysis of the process of valuation and alteration of beliefs. In a social HRI (human-robot interaction) setup, theory of mind is crucial to ease the intentionality gap and to achieve that we should be able to infer over observed human behaviors, such as cases of cognitive dissonance. One specific case inspired in human cognition is the role emotions play on our belief system and the effects caused when observed behavior does not match the expected outcome. In such scenarios emotions can make a person wrongly assume the antecedent P for an observed consequent Q, and as a result, incorrectly assert that P is true. This form of cognitive dissonance where an unproven cause is taken as truth induces changes in the belief base which can directly affect future decisions and actions. If we aim to be inspired by human thoughts in order to apply levels of theory of mind to these artificial agents, we must find the conditions to replicate these observable cognitive mechanisms. To achieve this, a computational architecture is proposed to model the modulation effect emotions have on the belief system and how it affects logic inference process and consequently the decision making of an agent. To validate the model, an experiment based on the prisoner's dilemma is currently under development. The hypothesis to be tested involves two main points: how emotions, modeled as internal argument strength modulators, can alter inference outcomes, and how can explainable outcomes be produced under specific forms of cognitive dissonance.

Keywords: cognitive architecture, cognitive dissonance, explainable ai, sensitivity analysis, theory of mind

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Authors: Pradeep G. Siddheshwar, K. M. Lakshmi

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The present study deals with weakly non-linear stability analysis of Rayleigh-Benard-Brinkman convection in nanoliquid-saturated porous enclosures. The modified-Buongiorno-Brinkman model (MBBM) is used for the conservation of linear momentum in a nanoliquid-saturated-porous medium under the assumption of Boussinesq approximation. Thermal equilibrium is imposed between the base liquid and the nanoparticles. The thermophysical properties of nanoliquid are modeled using phenomenological laws and mixture theory. The fifth-order Lorenz model is derived for the problem and is then reduced to the first-order Ginzburg-Landau equation (GLE) using the multi-scale method. The analytical solution of the GLE for the amplitude is then used to quantify the heat transport in closed form, in terms of the Nusselt number. It is found that addition of dilute concentration of nanoparticles significantly enhances the heat transport and the dominant reason for the same is the high thermal conductivity of the nanoliquid in comparison to that of the base liquid. This aspect of nanoliquids helps in speedy removal of heat. The porous medium serves the purpose of retainment of energy in the system due to its low thermal conductivity. The present model helps in making a unified study for obtaining the results for base liquid, nanoliquid, base liquid-saturated porous medium and nanoliquid-saturated porous medium. Three different types of enclosures are considered for the study by taking different values of aspect ratio, and it is observed that heat transport in tall porous enclosure is maximum while that of shallow is the least. Detailed discussion is also made on estimating heat transport for different volume fractions of nanoparticles. Results of single-phase model are shown to be a limiting case of the present study. The study is made for three boundary combinations, viz., free-free, rigid-rigid and rigid-free.

Keywords: Boungiorno model, Ginzburg-Landau equation, Lorenz equations, porous medium

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Authors: Dong Seop Lee, Byung Sik Kim

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In the 4th Industrial Revolution, various intelligent technologies have been developed in many fields. These artificial intelligence technologies are applied in various services, including disaster management. Disaster information management does not just support disaster work, but it is also the foundation of smart disaster management. Furthermore, it gets historical disaster information using artificial intelligence technology. Disaster information is one of important elements of entire disaster cycle. Disaster information management refers to the act of managing and processing electronic data about disaster cycle from its’ occurrence to progress, response, and plan. However, information about status control, response, recovery from natural and social disaster events, etc. is mainly managed in the structured and unstructured form of reports. Those exist as handouts or hard-copies of reports. Such unstructured form of data is often lost or destroyed due to inefficient management. It is necessary to manage unstructured data for disaster information. In this paper, the Optical Character Recognition approach is used to convert handout, hard-copies, images or reports, which is printed or generated by scanners, etc. into electronic documents. Following that, the converted disaster data is organized into the disaster code system as disaster information. Those data are stored in the disaster database system. Gathering and creating disaster information based on Optical Character Recognition for unstructured data is important element as realm of the smart disaster management. In this paper, Korean characters were improved to over 90% character recognition rate by using upgraded OCR. In the case of character recognition, the recognition rate depends on the fonts, size, and special symbols of character. We improved it through the machine learning algorithm. These converted structured data is managed in a standardized disaster information form connected with the disaster code system. The disaster code system is covered that the structured information is stored and retrieve on entire disaster cycle such as historical disaster progress, damages, response, and recovery. The expected effect of this research will be able to apply it to smart disaster management and decision making by combining artificial intelligence technologies and historical big data.

Keywords: disaster information management, unstructured data, optical character recognition, machine learning

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Authors: W. H. Lee, T. W. Cheng, K. Y. Lin, S. W. Huang, Y. C. Ding

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Basic Oxygen Furnace (BOF) Slag and electric arc furnace (EAF) slag is the by-product of iron making and steel making. Each of slag with produced over 100 million tons annually in Taiwan. The type of slag has great engineering properties, such as, high hardness and density, high compressive strength, low abrasion ratio, and can replace natural aggregate for building materials. However, no matter BOF or EAF slag, both have the expansion problem, due to it contains free lime. The purpose of this study was to stabilize the BOF and EAF slag by using geopolymer technology, hoping can prevent and solve the expansion problem. The experimental results showed that using geopolymer technology can successfully solve and prevent the expansion problem. Their main properties are analyzed with regard to their use as building materials. Autoclave is used to study the volume stability of these specimens. Finally, the compressive strength of geopolymer mortar with BOF/FAF slag can be reached over 21MPa after curing for 28 days. After autoclave testing, the volume expansion does not exceed 0.2%. Even after the autoclave test, the compressive strength can be grown to over 35MPa. In this study have success using these results on ready-mixed concrete plant, and have the same experimental results as laboratory scale. These results gave encouragement that the stabilized and reutilized BOF/EAF slag could be replaced as a feasible natural fine aggregate by using geopolymer technology.

Keywords: BOF slag, EAF slag, autoclave test, geopolymer

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Authors: Yanjie Zhu, André Jesus, Irwanda Laory

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Structural Health Monitoring (SHM), involving data acquisition, data interpretation and decision-making system aim to continuously monitor the structural performance of civil infrastructures under various in-service circumstances. The main value and purpose of SHM is identifying damages through data interpretation system. Research on SHM has been expanded in the last decades and a large volume of data is recorded every day owing to the dramatic development in sensor techniques and certain progress in signal processing techniques. However, efficient and reliable data interpretation for damage detection under environmental variations is still a big challenge. Structural damages might be masked because variations in measured data can be the result of environmental variations. This research reports a novel method based on single-channel Blind Signal Separation (BSS), which extracts environmental effects from measured data directly without any prior knowledge of the structure loading and environmental conditions. Despite the successful application in audio processing and bio-medical research fields, BSS has never been used to detect damage under varying environmental conditions. This proposed method optimizes and combines Ensemble Empirical Mode Decomposition (EEMD), Principal Component Analysis (PCA) and Independent Component Analysis (ICA) together to separate structural responses due to different loading conditions respectively from a single channel input signal. The ICA is applying on dimension-reduced output of EEMD. Numerical simulation of a truss bridge, inspired from New Joban Line Arakawa Railway Bridge, is used to validate this method. All results demonstrate that the single-channel BSS-based method can recover temperature effects from mixed structural response recorded by a single sensor with a convincing accuracy. This will be the foundation of further research on direct damage detection under varying environment.

Keywords: damage detection, ensemble empirical mode decomposition (EEMD), environmental variations, independent component analysis (ICA), principal component analysis (PCA), structural health monitoring (SHM)

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Authors: Anum Obaid, Iman Fatima, Wanisha Feroz, Haleema Imran, Hammad Tariq

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In Pakistan, the health of unmarried women over thirty is an emerging public health concern due to its increasing prevalence. Achieving the Sustainable Development Goals (SDGs) requires addressing nutrition and public health issues. This research investigates these goals through the lens of nutrition and public health, specifically examining the challenges faced by unmarried women over thirty in Faisalabad, Pakistan. According to a recent United Nations report, there are 10 million unmarried women over the age of 35 in Pakistan. The United Nations defines health as "a state of complete physical, mental, and social well-being, and not merely the absence of disease or infirmity." Being unmarried and under constant societal pressure profoundly influences the dietary behaviors and nutritional status of these women, affecting their overall health, including physical, mental, and social well-being. A qualitative research approach was employed, involving interviews with both unmarried and married women over thirty. This research examines how marital status influences dietary practices, nutritional status, mental and social health, and their subsequent impacts. Factors such as physical health, mental and emotional status, societal pressure, social health, economic independence, and decision-making power were analyzed to understand the effect of singleness on overall wellness. Findings indicated that marital status significantly affects the dietary patterns and nutritional practices among women in Faisalabad. It was also revealed that unmarried women experienced more stress and had a less optimistic mindset compared to married women, due to loneliness or the absence of a spouse in their lives. Nutritional knowledge varied across marital status, impacting the overall health triangle, including physical, mental, and social health. Understanding these dynamics is crucial for developing targeted interventions to improve nutritional outcomes and overall health among unmarried women in Faisalabad. This study highlights the importance of fostering supportive environments and raising awareness about the health needs of unmarried women over thirty to enhance their overall well-being.

Keywords: health triangle, unmarried woman over thirty, socio-cultural barriers, women’s health

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Authors: Teresa Wills, Geraldine Mccarthy, Nicola Cornally

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Background: Obesity is an emerging healthcare epidemic affecting virtually all age and socio-economic groups and is one of the most serious and prevalent diseases of the 21st century. It is a public health challenge because of its prevalence, associated costs and health effects. The increasing prevalence of obesity has created a social perception that overweight body sizes are healthy and normal. This normalization of obesity within our society and the acceptance of higher body weights have led to individuals being unaware of the reality of their weight status and gravity of this situation thus impeding recognition of obesity. Given the escalating global health problem of obesity and its co-morbidities, the need to re-appraise its management is more compelling than ever. It is widely accepted that the causes of obesity are complex and multi-factorial. Engagement of individuals in weight management programmes is difficult if they do not perceive they have a problem with their weight. Recognition of the problem is a key component of obesity management and identifying the main predictors of behaviour is key to designing health behaviour interventions. Aim: The aim of the research was to determine factors relating to motivation to change behaviours in individuals who perceive themselves to be overweight. Method: The research design was quantitative, correlational and cross-sectional. The design was guided by the Health Belief Model. Data were collected online using a multi-section and multi-item questionnaire, developed from a review of the theoretical and empirical research. A sample of 202 men and women who perceived themselves to be overweight participated in the research. Descriptive and inferential statistical analyses were employed to describe relationships between variables. Findings: Following multivariate regression analysis, perceived barriers to weight loss and perceived benefits of weight loss were significant predictors of motivation to change behaviour. The perceived barriers to weight loss which were significant were psychological barriers to weight loss (p = < 0.019) and environmental barriers to physical activity (p= < 0.032).The greatest predictor of motivation to change behaviour was the perceived benefits of weight loss (p < 0.001). Perceived susceptibility to obesity and perceived severity of obesity did not emerge as significant predictors in this model. Total variance explained by the model was 33.5%. Conclusion: Perceived barriers to weight loss and perceived benefits of weight loss are important determinants of motivation to change behaviour. These findings have important implications for health professionals to help inform their practice and for the development of intervention programmes to prevent and control obesity.

Keywords: motivation to change behaviours, obesity, predictors of behavior, interventions, overweight

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Authors: Adel Nikfarjam, Hamed Tayebi, Sadoullah Ebrahimnejad

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This paper considers a two-echelon inventory system with a number of warehouses and a single retailer. The retailer replenishes its required items from warehouses, and assembles them into a single final product. We assume that each warehouse supplies only one kind of the raw material for the retailer. The demand process of the final product is assumed to be Poissson, and unsatisfied demand of the final product will be lost. The retailer applies one-for-one-period ordering policy which is also known as (1, T) ordering policy. In this policy the retailer orders to each warehouse a fixed quantity of each item at fixed time intervals, which the fixed quantity is equal to the utilization of the item in the final product. Since, this policy eliminates all demand uncertainties at the upstream echelon, the standard lot sizing model can be applied at all warehouses. In this paper, we calculate the total cost function of the inventory system. Then, based on this function, we present a procedure to obtain the optimal time interval between two consecutive order placements from retailer to the warehouses, and the optimal order quantities of warehouses (assuming that there are positive ordering costs at warehouses). Finally, we present some numerical examples, and conduct numerical sensitivity analysis for cost parameters.

Keywords: two-echelon supply chain, multi-vendor-single-buyer inventory system, lost sales, Poisson demand, one-for-one-period policy, lot sizing model

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Authors: Taiwo Hassanat Bawa-Muhammad, Opeoluwa Hope Adegoke

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Introduction: This study aims to examine the knowledge and perceptions of preconception care among healthcare workers in Nigeria, recognizing its crucial role in ensuring safe pregnancies. Despite its significance, awareness of preconception care remains low in the country. The study seeks to assess the understanding of preconception services and identify the barriers that hinder their efficacy. Methods: Through semi-structured interviews, 129 healthcare workers across six states in Nigeria were interviewed between January and March 2023. The interviews explored the healthcare workers' knowledge of preconception care practices, the socio-cultural influences shaping decision-making, and the challenges that limit accessibility and utilization of preconception care services. Results: The findings reveal a limited knowledge of preconception care among healthcare workers, primarily due to inadequate information dissemination within the healthcare system. Additionally, cultural beliefs significantly influence perceptions surrounding preconception care. Furthermore, financial constraints, distance to healthcare facilities, and poor health infrastructure disproportionately restrict access to preconception services, particularly for vulnerable populations. The study also highlights insufficient skills and outdated training among healthcare workers regarding preconception guidance, primarily attributed to limited opportunities for professional development. Discussion: To improve preconception care in Nigeria, comprehensive education programs must be implemented, taking into account the societal influences that shape perceptions and behaviors. These programs should aim to dispel myths and promote evidence-based practices. Additionally, training healthcare workers and integrating preconception care services into primary care settings, with support from religious and community leaders, can help overcome barriers to access. Strategies should prioritize affordability while emphasizing the broader benefits of preconception care beyond fertility concerns alone. Lastly, widespread literacy campaigns utilizing trusted channels are crucial for effectively disseminating information and promoting the adoption of preconception practices in Nigeria.

Keywords: preconception care, knowledge, healthcare workers, Nigeria, barriers, education, training

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Authors: V. V. Lakshmi, Y. V. S. Annapurna

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Urinary tract infection (UTI) is one of the most common infectious diseases seen in the community. Susceptible individuals experience multiple episodes, and progress to acute pyelonephritis or uro-sepsis or develop asymptomatic bacteriuria (ABU). Ability to cause extraintestinal infections depends on several virulence factors required for survival at extraintestinal sites. Presence of virulence phenotypes enhances the pathogenicity of these otherwise commensal organisms and thus augments its ability to cause extraintestinal infections, the most frequent in urinary tract infections(UTI). The present study focuses on detection of the virulence characters exhibited by the uropathogenic organism and most common factors exhibited in the local pathogens. A total of 700 isolates of E.coli and Klebsiella spp were included in the study.These were isolated from patients from local hospitals reported to be suffering with UTI over a period of three years. Isolation and identification was done based on Gram character and IMVIC reactions. Antibiotic sensitivity profile was carried out by disc diffusion method and multi drug resistant strains with MAR index of 0.7 were further selected. Virulence features examined included their ability to produce exopolysaccharides, protease- gelatinase production, hemolysin production, haemagglutination and hydrophobicity test. Exopolysaccharide production was most predominant virulence feature among the isolates when checked by congo red method. The biofilms production examined by microtitre plates using ELISA reader confirmed that this is the major factor contributing to virulencity of the pathogens followed by hemolysin production.

Keywords: Escherichia coli, Klebsiella spp, Uropathogens, virulence features

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Authors: Chetna Mohabeer, Luis Reyes, Lokmane Abdelouahed, Bechara Taouk

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In the transition to sustainability and the increasing use of renewable energy, hydrogen will play a key role as an energy carrier. Biomass has the potential to accelerate the realization of hydrogen as a major fuel of the future. Pyro-gasification allows the conversion of organic matter mainly into synthesis gas, or “syngas”, majorly constituted by CO, H2, CH4, and CO2. A second, condensable fraction of biomass pyro-gasification products are “tars”. Under certain conditions, tars may decompose into hydrogen and other light hydrocarbons. These conditions include two types of cracking: homogeneous cracking, where tars decompose under the effect of temperature ( > 1000 °C), and heterogeneous cracking, where catalysts such as olivine, dolomite or biochar are used. The latter process favors cracking of tars at temperatures close to pyro-gasification temperatures (~ 850 °C). Pyro-gasification of biomass coupled with water-gas shift is the most widely practiced process route for biomass to hydrogen today. In this work, an innovating solution will be proposed for this conversion route, in that all the pyro-gasification products, not only methane, will undergo processes that aim to optimize hydrogen production. First, a heterogeneous cracking step was included in the reaction scheme, using biochar (remaining solid from the pyro-gasification reaction) as catalyst and CO2 and H2O as gasifying agents. This process was followed by a catalytic steam methane reforming (SMR) step. For this, a Ni-based catalyst was tested under different reaction conditions to optimize H2 yield. Finally, a water-gas shift (WGS) reaction step with a Fe-based catalyst was added to optimize the H2 yield from CO. The reactor used for cracking was a fluidized bed reactor, and the one used for SMR and WGS was a fixed bed reactor. The gaseous products were analyzed continuously using a µ-GC (Fusion PN 074-594-P1F). With biochar as bed material, it was seen that more H2 was obtained with steam as a gasifying agent (32 mol. % vs. 15 mol. % with CO2 at 900 °C). CO and CH4 productions were also higher with steam than with CO2. Steam as gasifying agent and biochar as bed material were hence deemed efficient parameters for the first step. Among all parameters tested, CH4 conversions approaching 100 % were obtained from SMR reactions using Ni/γ-Al2O3 as a catalyst, 800 °C, and a steam/methane ratio of 5. This gave rise to about 45 mol % H2. Experiments about WGS reaction are currently being conducted. At the end of this phase, the four reactions are performed consecutively, and the results analyzed. The final aim is the development of a global kinetic model of the whole system in a multi-stage fluidized bed reactor that can be transferred on ASPEN PlusTM.

Keywords: multi-staged fluidized bed reactor, pyro-gasification, steam methane reforming, water-gas shift

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Authors: Ching-Hsu Huang, Yao-Ling Liu

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Over the past several decades there has been considerable research on the topics of entrepreneurship education and nascent entrepreneurial competence. The purpose of this study is to explore the nascent entrepreneurial competence within entrepreneurship education via the use of three studies. It will be a three-phrases longitudinal study and the effective plan will combine the qualitative and quantitative mixed research methodology in order to understand the issues of nascent entrepreneurship and entrepreneurial competence in hospitality industry in Taiwan. In study one, the systematic literature reviews and twelve nascent entrepreneurs who graduated from hospitality management department will be conducted simultaneously to construct the nascent entrepreneurial competence indicators. Nine subjects who are from industry, government, and academia will be the decision makers in terms of forming the systematic nascent entrepreneurial competence indicators. The relative importance of indicators to each decision maker will be synthesized and compared using the Analytic Hierarchy Process method. According to the results of study one, this study will develop the teaching module of nascent hospitality entrepreneurship. It will include the objectives, context, content, audiences, assessment, pedagogy and outcomes. Based on the results of the second study, the quasi-experiment will be conducted in third study to explore the influence of nascent hospitality entrepreneurship teaching module on learners’ learning effectiveness. The nascent hospitality entrepreneurship education program and entrepreneurial competence will be promoted all around the hospitality industry and vocational universities. At the end, the implication for designing the nascent hospitality entrepreneurship teaching module and training programs will be suggested for the nascent entrepreneurship education. All of the proposed hypotheses will be examined and major finding, implication, discussion, and recommendations will be provided for the government and education administration in hospitality field.

Keywords: entrepreneurial competence, hospitality entrepreneurship, nascent entrepreneurial, training in hospitality entrepreneurship

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Authors: Melissa R. Quispe-Zuniga, Daniel Callo-Concha, Christian Borgemeister, Klaus Greve

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The Peruvian Andes have a high potential for mining, but many of the mining areas overlay with campesino community lands, being these key actors for agriculture and livestock production. Lead by economic incentives, some communities are renting their lands to mining companies for exploration or exploitation. However, a growing number of campesino communities, usually social and economically marginalized, have developed resistance, alluding consequences, such as water pollution, land-use change, insufficient economic compensation, etc. what eventually end up in Socio-Environmental Conflicts (SEC). It is hypothesized that disclosing the information on environmental pollution and enhance the involvement of communities in the decision-making process may contribute to prevent SEC. To assess whether such complains are grounded on the environmental impact of mining activities, we measured the heavy metals concentration in 24 indicative samples from rivers that run across mining exploitations and farming community lands. Samples were taken during the 2016 dry season and analyzed by inductively-coupled-plasma-atomic-emission-spectroscopy. The results were contrasted against the standards of monitoring government institutions (i.e., OEFA). Furthermore, we investigated the water/environmental complains related to mining in the neighboring 14 communities. We explored the relationship between communities and mining companies, via open-ended interviews with community authorities and non-participatory observations of community assemblies. We found that the concentrations of cadmium (0.023 mg/L), arsenic (0.562 mg/L) and copper (0.07 mg/L), surpass the national water quality standards for Andean rivers (0.00025 mg/L of cadmium, 0.15 mg/L of arsenic and 0.01 mg/L of copper). 57% of communities have posed environmental complains, but 21% of the total number of communities were receiving an annual economic benefit from mining projects. However, 87.5% of the communities who had posed complains have high concentration of heavy metals in their water streams. The evidence shows that mining activities tend to relate to the affectation and vulnerability of campesino community water streams, what justify the environmental complains and eventually the occurrence of a SEC.

Keywords: mining companies, campesino community, water, socio-environmental conflict

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Authors: Poonam Sharma, Ankur Srivastav

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Cities are complex and dynamic systems that constitute a significant challenge to urban planning. The increasing size of the built-up area owing to growing population pressure and economic growth have lead to massive Landuse/Landcover change resulted in the loss of natural habitat and thus reducing the green covers in urban areas. Urban environmental quality is influenced by several aspects, including its geographical configuration, the scale, and nature of human activities occurring and environmental impacts generated. Cities have transformed into complex and dynamic systems that constitute a significant challenge to urban planning. Cities and their sustainability are often discussed together as the cities stand confronted with numerous environmental concerns as the world becoming increasingly urbanized, and the cities are situated in the mesh of global networks in multiple senses. A rapid transformed urban setting plays a crucial role to change the green area of natural habitats. To examine the pattern of urban growth and to measure the Landuse/Landcover change in Gurgoan in Haryana, India through the integration of Geospatial technique is attempted in the research paper. Satellite images are used to measure the spatiotemporal changes that have occurred in the land use and land cover resulting into a new cityscape. It has been observed from the analysis that drastically evident changes in land use has occurred with the massive rise in built up areas and the decrease in green cover and therefore causing the sustainability of the city an important area of concern. The massive increase in built-up area has influenced the localised temperatures and heat concentration. To enhance the decision-making process in urban planning, a detailed and real world depiction of these urban spaces is the need of the hour. Monitoring indicators of key processes in land use and economic development are essential for evaluating policy measures.

Keywords: cityscape, geospatial techniques, green cover index, urban environmental quality, urban planning

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Authors: C. K. Peter Chuah

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Essentially, the intention of reflective journal is meant for students to develop higher-order thinking skills and to provide a 'space' to make their learning experience and thinking, making and feeling visible, i.e., it provides students an opportunity to evaluate their learning critically by focusing on the rationale behind their thinking, making and feeling. In addition, reflective journal also gets the students to focus on how could things be done differently—the possibility, alternative point of views, and opportunities for change. It is hoped that by getting communication design students to reflect at various intervals, they could move away from mere working on the design project and pay more attention to what they thought they have learned in relation to the development of their design ability. Unfortunately, a closer examination—through content analysis—of the learning journals submitted by a group of design students revealed that most of the reflections were descriptive and tended to be a summary of what occurred in the learning experience. While many students were able to describe what they did, very few were able to explain how they were able to do something critically. It can be concluded that to get design students to reflect is a fairly easy task, but to get them to reflect critically could be very challenging. To ensure that design students could benefit from the use of reflective journal as a tool to develop their critical thinking skills, a more systematic and structured approach to the introduction of critical thinking and reflective journal should be built into the design curriculum to provide as much practice and sufficient feedback as other studio subjects.

Keywords: communication design education, critical thinking, reflection, reflective journal

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Authors: Carla Idely Palencia-Aguilar

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Mining in Colombia represents around 2% of the GDP (USD 8 billion in 2018), with main productions represented by coal, nickel, gold, silver, emeralds, iron, limestone, gypsum, among others. Sand and Gravel had been decreasing its participation of the GDP with a reduction of 33.2 million m3 in 2015, to 27.4 in 2016, 22.7 in 2017 and 15.8 in 2018, with a consumption of approximately 3 tons/inhabitant. However, with the new government policies it is expected to increase in the following years. Mining causes temporary environmental impacts, once restoration and rehabilitation takes place, social, environmental and economic benefits are higher than the initial state. A way to demonstrate how the mining interventions had contributed to improve the characteristics of the region after sand and gravel mining, the NDVI (Normalized Difference Vegetation Index) from MODIS and ASTER were employed. The histograms show not only increments of vegetation in the area (8 times higher), but also topographies similar to the ones before the intervention, according to the application for sustainable development selected: either agriculture, forestry, cattle raising, artificial wetlands or do nothing. The decision was based upon a Multicriteria analysis for optimal land use, with three main variables: geostatistics, evapotranspiration and groundwater characteristics. The use of remote sensing, meteorological stations, piezometers, sunphotometers, geoelectric analysis among others; provide the information required for the multicriteria decision. For cattle raising and agricultural applications (where various crops were implemented), conservation of products were tested by means of nanotechnology. The results showed a duration of 2 years with no chemicals added for preservation and concentration of vitamins of the tested products.

Keywords: ASTER, Geostatistics, MODIS, Multicriteria

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Authors: Man Ying Kang, Joshua Kin Man Nan

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The prolonged pandemic has posed alarming public health challenges to various parts of the world, and face-to-face mental health treatment is largely discounted for the control of virus transmission, online psychological services and self-help mental health kits have become essential. Online self-help mindfulness-based interventions have proved their effects on fostering mental health for different populations over the globe. This paper was to test the effectiveness of an online short-term audio-based mindfulness (SAM) program in enhancing wellbeing, dispositional mindfulness, and reducing stress and negative affect in community settings in China, and to explore possible mechanisms of how dispositional mindfulness, stress, and negative affect influenced the intervention effects on wellbeing. Community-dwelling adults were recruited via online social networking sites (e.g., QQ, WeChat, and Weibo). Participants (n=100) were randomized into the mindfulness group (n=50) and a waitlist control group (n=50). In the mindfulness group, participants were advised to spend 10–20 minutes listening to the audio content, including mindful-form practices (e.g., eating, sitting, walking, or breathing). Then practice daily mindfulness exercises for 3 weeks (a total of 21 sessions), whereas those in the control group received the same intervention after data collection in the mindfulness group. Participants in the mindfulness group needed to fill in the World Health Organization Five Well-Being Index (WHO), Positive and Negative Affect Schedule (PANAS), Perceived Stress Scale (PSS), and Freiburg Mindfulness Inventory (FMI) four times: at baseline (T0) and at 1 (T1), 2 (T2), and 3 (T3) weeks while those in the waitlist control group only needed to fill in the same scales at pre- and post-interventions. Repeated-measure analysis of variance, paired sample t-test, and independent sample t-test was used to analyze the variable outcomes of the two groups. The parallel process latent growth curve modeling analysis was used to explore the longitudinal moderated mediation effects. The dependent variable was WHO slope from T0 to T3, the independent variable was Group (1=SAM, 2=Control), the mediator was FMI slope from T0 to T3, and the moderator was T0NA and T0PSS separately. The different levels of moderator effects on WHO slope was explored, including low T0NA or T0PSS (Mean-SD), medium T0NA or T0PSS (Mean), and high T0NA or T0PSS (Mean+SD). The results found that SAM significantly improved and predicted higher levels of WHO slope and FMI slope, as well as significantly reduced NA and PSS. FMI slope positively predict WHO slope. FMI slope partially mediated the relationship between SAM and WHO slope. Baseline NA and PSS as the moderators were found to be significant between SAM and WHO slope and between SAM and FMI slope, respectively. The conclusion was that SAM was effective in promoting levels of mental wellbeing, positive affect, and dispositional mindfulness as well as reducing negative affect and stress in community settings in China. SAM improved wellbeing faster through the faster enhancement of dispositional mindfulness. Participants with medium-to-high negative affect and stress buffered the therapy effects of SAM on wellbeing improvement speed.

Keywords: mindfulness, negative affect, stress, wellbeing, randomized control trial

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Authors: Nadwah Onwi, Puspa Maniam, Azmawanie A. Aziz, Fairus Mukhtar, Nor Azrita Mohamed Zin, Nurul Haslina Mohd Zin, Nurul Fatehah Ismail, Mohamad Safwan Yusoff, Susilidianamanalu Abd Rahman, Siti Munirah Harris, Maryam Aizuddin

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Objective: Malaysia has a growing number of individuals with complex communication needs (CCN). The initiation of augmentative and alternative communication (AAC) intervention may facilitate individuals with CCN to understand and express themselves optimally and actively participate in activities in their daily life. AAC is defined as multimodal use of communication ability to allow individuals to use every mode possible to communicate with others using a set of symbols or systems that may include the symbols, aids, techniques, and strategies. It is consequently critical to evaluate the deficits to inform treatment for AAC intervention. However, no known measurement tools are available to evaluate the user with CCN available locally. Design: A systematic review (SR) is designed to analyze the psychometric properties of AAC assessment for adolescents with CCN published in peer-reviewed journals. Tools are rated by the methodological quality of studies and the psychometric measurement qualities of each tool. Method: A literature search identifying AAC assessment tools with psychometrically robust properties and conceptual framework was considered. Two independent reviewers screened the abstracts and full-text articles and review bibliographies for further references. Data were extracted using standardized forms and study risk of bias was assessed. Result: The review highlights the psychometric properties of AAC assessment tools that can be used by speech-language therapists applicable to be used in the Malaysian context. The work outlines how systematic review methods may be applied to the consideration of published material that provides valuable data to initiate the development of Malay Language AAC assessment tools. Conclusion: The synthesis of evidence has provided a framework for Malaysia Speech-Language therapists in making an informed decision for AAC intervention in our standard operating procedure in the Ministry of Health, Malaysia.

Keywords: augmentative and alternative communication, assessment, adolescents, complex communication needs

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