Search results for: multiple themes

Authors: Eman H. El-Gamal, Mai E. Khedr, Randa Ghonim, Mohamed Rashad

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In the past few years, biochar - a highly carbon-rich material produced from agro-wastes by pyrolysis process - was used as an effective adsorbent for heavy metals removal from polluted water. In this study, different types of biochar (rice straw 'RSB', corn cob 'CCB', and Jatropha shell 'JSB' were used to evaluate the adsorption capacity of heavy metals removal from multiple-metal solutions (Cu, Mn, Zn, and Cd). Kinetics modeling has been examined to illustrate potential adsorption mechanisms. The results showed that the potential removal of metal is dependent on the metal and biochar types. The adsorption capacity of the biochars followed the order: RSB > JSB > CCB. In general, RSB and JSB biochars presented high potential removal of heavy metals from polluted water, which was higher than 90 and 80% after 2 hrs of contact time for all metals, respectively. According to the kinetics data, the pseudo-second-order model was agreed strongly with Cu, Mn, Zn, and Cd adsorption onto the biochars (R2 ≥ 0.97), indicating the dominance of specific adsorption process, i.e., chemisorption. In conclusion, this study revealed that RSB and JSB biochar have the potential to be a strong adsorbent for multiple-metal removal from wastewater.

Keywords: adsorption, biochar, chemisorption, polluted water

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Authors: Jonathan Heng, Yoong Cheah Huei

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A strategic model that does not trigger any false alarms to detect anomalies in Secure Water Treatment (SWaT) test bed is presented. This model uses machine learning invariants formulated from streamlining the general form of Auto-Regressive models with eXogenous input. A creative generalized CUSUM algorithm to integrate the invariants and the detection strategy technique is successfully developed and tested in the SWaT Programmable Logic Controllers (PLCs). Three steps to fine-tune parameters, b and τ in the generalized algorithm are stated and an example used to demonstrate the tuning process is discussed. This approach can swiftly and effectively detect various scopes of cyber-attacks such as multiple points single stage and multiple points multiple stages in SWaT. This technique can be applied in water treatment plants and other cyber physical systems like power and gas plants too.

Keywords: machine learning invariants, generalized CUSUM algorithm with invariants and detection strategy, scope of cyber attacks, strategic model, tuning parameters

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Authors: Dina Tareq Ismail, Alexandria A. Proff

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The United Arab Emirates (UAE) is a nation seeking to advance in all fields, particularly education. One area of focus for UAE 2021 agenda is to restructure UAE schools and universities by equipping them with highly developed technology. The agenda also advises educational institutions to prepare students with applicable and transferrable Information and Communication Technology (ICT) skills. Despite the emphasis on ICT and computer literacy skills, there exists limited empirical data on the use of M-Learning in the literature. This qualitative study explores the motivation of higher primary Arabic teachers in private schools toward implementing and integrating M-Learning apps in their classrooms. This research employs a phenomenological approach through the use of semistructured interviews with nine purposefully selected Arabic teachers. The data were analyzed using a content analysis via multiple stages of coding: open, axial, and thematic. Findings reveal three primary themes: (1) Arabic teachers with high levels of procedural knowledge in ICT are more motivated to implement M-Learning; (2) Arabic teachers' perceptions of self-efficacy influence their motivation toward implementation of M-Learning; (3) Arabic teachers implement M-Learning when they possess high utility and/or intrinsic value in these applications. These findings indicate a strong need for further training, equipping, and creating buy-in among Arabic teachers to enhance their ICT skills in implementing M-Learning. Further, given the limited availability of M-Learning apps designed for use in the Arabic language on the market, it is imperative that developers consider designing M-Learning tools that Arabic teachers, and Arabic-speaking students, can use and access more readily. This study contributes to closing the knowledge gap on teacher-motivation for implementing M-Learning in their classrooms in the UAE.

Keywords: ICT skills, m-learning, self-efficacy, teacher-motivation

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Authors: Mayantoinette F. Watson

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During such an unprecedented time of the largest public health crisis, the COVID-19 pandemic, nursing students are of the utmost concern regarding their psychological and physical well-being. Questions are emerging and circulating about what will happen to the nursing students and the long-term effects of the pandemic, especially now that hospitals are being overwhelmed with a significant need for nursing staff. Expectations, demands, change, and the fear of the unknown during this unprecedented time can only contribute to the many stressors that accompany nursing students through laborious clinical and didactic courses in nursing programs. The risk of psychological distress is at a maximum, and its effects can negatively impact not only nursing students but also nursing education and academia. The high exposures to interpersonal, economic, and academic demands contribute to the major health concerns, which include a potential risk for psychological distress. Achievement of educational success among nursing students is directly affected by the high exposure to anxiety and depression from experiences within the program. Working relationships and achieving academic success is imperative to positive student outcomes within the nursing program. The purpose of this study is to identify and establish influences and associations within multilevel factors, including the effects of the COVID-19 pandemic on psychological distress in nursing students. Neuman’s Systems Model Theory was used to determine nursing students’ responses to internal and external stressors. The research in this study utilized a mixed-methods, convergent study design. The study population included undergraduate nursing students from Southeastern U.S. The research surveyed a convenience sample of undergraduate nursing students. The quantitative survey was completed by 202 participants, and 11 participants participated in the qualitative follow-up interview surveys. Participants completed the Kessler Psychological Distress Scale (K6), the Perceived Stress Scale (PSS4), and the Dundee Readiness Educational Environment Scale (DREEM12) to measure psychological distress, perceived stress, and perceived educational environment. Participants also answered open-ended questions regarding their experience during the COVID-19 pandemic. Statistical tests, including bivariate analyses, multiple linear regression analyses, and binary logistics regression analyses were performed in effort to identify and highlight the effects of independent variables on the dependent variable, psychological distress. Coding and qualitative content analysis were performed to identify overarching themes within participants’ interviews. Quantitative data were sufficient in identifying correlations between psychological distress and multilevel factors of coping, marital status, COVID-19 stress, perceived stress, educational environment, and social support in nursing students. Qualitative data were sufficient in identifying common themes of students’ perceptions during COVID-19 and included online learning, workload, finances, experience, breaks, time, unknown, support, encouragement, unchanged, communication, and transmission. The findings are significant, specifically regarding contributing factors to nursing students’ psychological distress, which will help to improve learning in the academic environment.

Keywords: nursing education, nursing students, pandemic, psychological distress

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Authors: Ali A. Abdollahi

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During the last several decades, scientists have consistently applied Multiple Criteria Decision-Making methods in making decisions about multi-faceted, complicated subjects. While making such decisions and in order to achieve more accurate evaluations, they have regularly used a variety of criteria instead of applying just one Optimum Evaluation Criterion. The method presented here utilizes both ‘quantity’ and ‘quality’ to assess the function of the Multiple-Criteria method. Applying Data envelopment analysis (DEA), weighted aggregated sum product assessment (WASPAS), Weighted Sum Approach (WSA), Analytic Network Process (ANP), and Charnes, Cooper, Rhodes (CCR) methods, we have analyzed thirteen parks in Kerman city. It further indicates that the functions of WASPAS and WSA are compatible with each other, but also that their deviation from DEA is extensive. Finally, the results for the CCR technique do not match the results of the DEA technique. Our study indicates that the ANP method, with the average rate of 1/51, ranks closest to the DEA method, which has an average rate of 1/49.

Keywords: multiple criteria decision making, Data envelopment analysis (DEA), Charnes Cooper Rhodes (CCR), Weighted Sum Approach (WSA)

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Authors: Fatima-Zahra Eddoug, Jamal Benhra, Rajaa Benabbou

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Several project management models exist in the literature and the most used ones are the hybrids for their multiple advantages. Our objective in this paper is to analyze the existing models, which are based on the Lean and Agile approaches and to propose a novel framework with the convenient tools that will allow efficient management of a general project. To create the desired framework, we were based essentially on 7 existing models. Only the Scrum tool among the agile tools was identified by several authors to be appropriate for project management. In contrast, multiple lean tools were proposed in different phases of the project.

Keywords: agility, hybrid project management, lean, scrum

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Authors: A. A. Adedini, B. A. Aina, P. U. Ogbo

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Child obesity is on the rise globally. According to the World Health Organization, the number of obese children would increase to 70 million by 2025 if no intervention is made. An increase in the prevalence of overweight and obesity amongst school children in Lagos State, Nigeria has been established but specific factors promoting its prevalence are unknown. This aim of this study is to identify the commonly expressed factor(s) responsible for the rise in prevalence of child overweight and obesity in Lagos, Nigeria. Five focus group discussions were conducted with different groups of stake-holders involved in child care, namely: parents, teachers and health workers. Participants were recruited using a purposive sampling method; a validated question guide was employed for the discussion sessions. The discussions were recorded, collated, analysed using Grounded theory to extract themes. Six themes emerged from the discussions as follows: Civilization and lifestyle imbalance resulting from busy work schedules of young mothers leading to adoption of westernized culture promoting preference for processed and fast food meals; insecurity and congestion of the state which discourages out-door activities; ignorance of the populace on the prevalence of child obesity in the state; inadequate educative and enlightenment programmes in schools and by the Nigerian government; myths on child care and body physique and societal perceptions of the children born into affluent homes. Some of the factors responsible for the rise in the prevalence of child obesity in Lagos, Nigeria have been identified. Preventive strategies to control the prevalence of obesity in children residing in Lagos state is considered for further studies.

Keywords: Childhood Obesity, factors, lagos state, stakeholders

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Authors: Nusrat T. Chowdhury

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Green Supply Chain Management (GSCM) is becoming a key to success for profitable businesses. The various activities contributing to carbon emissions in a supply chain are transportation, ordering and holding of inventory. This research work develops a mixed-integer nonlinear programming (MINLP) model that considers the scenario of a supply chain with multiple periods, multiple products and multiple suppliers. The model assumes that the demand is deterministic, the buyer has a limited storage space in each period, the buyer is responsible for the transportation cost, a supplier-dependent ordering cost applies for each period in which an order is placed on a supplier and inventory shortage is permissible. The model provides an optimal decision regarding what products to order, in what quantities, with which suppliers, and in which periods in order to maximize the profit. For the purpose of evaluating the carbon emissions, three different carbon regulating policies i.e., carbon cap-and-trade, the strict cap on carbon emission and carbon tax on emissions, have been considered. The proposed MINLP has been validated using a randomly generated data set.

Keywords: green supply chain, carbon emission, mixed integer non-linear program, inventory shortage, carbon cap-and-trade

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Authors: Hochan Seok, Woosik Jang, Seung-Heon Han

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The stagnant global construction market has intensified competition since 2008 among firms that aim to win overseas contracts. Against this backdrop, subcontractor selection is identified as one of the most critical success factors in overseas construction project. However, it is difficult to select qualified subcontractors due to the lack of evaluation standards and reliability. This study aims to identify the problems associated with existing subcontractor evaluations using a correlations analysis and a multiple regression analysis with pre-qualification and performance evaluation of 121 firms in six countries.

Keywords: subcontractor evaluation system, pre-qualification, performance evaluation, correlation analysis, multiple regression analysis

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Authors: Thirayu Jumsai na Ayudhya

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Initial attempts to understand about what architecture means to people as they go about their everyday life through my previous research revealed that knowledge such as environmental psychology, environmental perception, environmental aesthetics, did not adequately address a perceived need for the contextualized and holistic theoretical framework. In my previous research, it is found that people’s making senses of their everyday architecture can be described in terms of four super‐ordinate themes; (1) building in urban (text), (2) building in (text), (3) building in human (text), (4) and building in time (text). For more comprehensively understanding of how people make sense of their everyday architectural experience, in this ongoing research Phuket Old town was selected as the focal urban context where the distinguish character of Chino-Portuguese is remarkable. It is expected that in a unique urban context like Phuket old town unprecedented super-ordinate themes will be unveiled through the reflection of people’s everyday experiences. The ongoing research of people’s architectural experience conducted in Phuket Island, Thailand, will be presented succinctly. The research will address the question of how do people make sense of their everyday architecture/buildings especially in a unique urban context, Phuket Old town, and identify ways in which people make sense of their everyday architecture. Participant-Produced-Photograph (PPP) and Interpretative Phenomenological Analysis (IPA) are adopted as main methodologies. PPP allows people to express experiences of their everyday urban context freely without any interference or forced-data generating by researchers. With IPA methodology a small pool of participants is considered desirable given the detailed level of analysis required and its potential to produce a meaningful outcome.

Keywords: architectural experience, the everyday architecture, Phuket, Thailand

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Authors: Yongjian Du, Jinhua Sun, Kim M. Liew, Huahua Xiao

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Optimal allocation of emergency resources before a disaster is of great importance for emergency response. In reality, the pre-protection for a single critical node where accidents may occur is common. In this study, a model is developed to determine location and inventory decisions of multiple emergency resources among a set of candidate stations to minimize the total cost based on the constraints of budgetary and capacity. The total cost includes the economic accident loss which is accorded with probability distribution of time and the warehousing cost of resources which is increasing over time. A ratio is set to measure the degree of a storage station only serving the target node that becomes larger with the decrease of the distance between them. For the application of linear program, it is assumed that the length of travel time to the accident scene of emergency resources has a linear relationship with the economic accident loss. A computational experiment is conducted to illustrate how the proposed model works, and the results indicate its effectiveness and practicability.

Keywords: emergency response, integer linear program, multiple emergency resources, pre-allocation decisions, single potential accident node

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Authors: Muhammad Fezan Afzal, Asad Abbas, Imran Khan, Salma Imtiaz

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Software Product Line (SPL) paradigm is used for the development of the family of software products that share common and variable features. Feature model is a domain of SPL that consists of common and variable features with predefined relationships and constraints. Multiple SPLs consist of a number of similar common and variable features, such as mobile phones and Tabs. Reusability of common and variable features from the different domains of SPL is a complex task due to the external relationships and constraints of features in the feature model. To increase the reusability of feature model resources from domain engineering, it is required to manage the commonality of features at the level of SPL application development. In this research, we have proposed an approach that combines multiple SPLs into a single domain and converts them to a common feature model. Extracting the common features from different feature models is more effective, less cost and time to market for the application development. For extracting features from multiple SPLs, the proposed framework consists of three steps: 1) find the variation points, 2) find the constraints, and 3) combine the feature models into a single feature model on the basis of variation points and constraints. By using this approach, reusability can increase features from the multiple feature models. The impact of this research is to reduce the development of cost, time to market and increase products of SPL.

Keywords: software product line, feature model, variability management, multi-SPLs

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Authors: Y. de Smet, J. Hubinont

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PROMETHEE and GAIA are well-known Multiple Criteria Decision Aid methods. Given an evaluation table and preference parameters they allow to rank the alternatives, to visualize the problem, to perform sensitivity and robustness analysis, etc. Unfortunately, it is often hard for the Decision Maker (DM) to estimate the precise values of these parameters. Therefore an alternative option is to give ranges of potential values in order to apply Stochastic Multicriteria Acceptability Analysis. This has been recently studied in the context of the SMAA-PROMETHEE method. The aim of this contribution is to propose an SMAA extension of GAIA. We show how this tool can be useful and provide complementary information to SMAA-PROMETHEE. This is illustrated on a pedagogical example.

Keywords: multiple criteria decision making, PROMETHEE, GAIA, SMAA

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Authors: Hanieh Tarbiat Khosrowshahi, Mojtaba Shakeri

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Wireless Sensor Networks (WSNs) consist of a set of sensor nodes with limited capability. WSNs may suffer from multiple node failures when they are exposed to harsh environments such as military zones or disaster locations and lose connectivity by getting partitioned into disjoint segments. Relay nodes (RNs) are alternatively introduced to restore connectivity. They cost more than sensors as they benefit from mobility, more power and more transmission range, enforcing a minimum number of them to be used. This paper addresses the problem of RN placement in a multiple disjoint network by developing a genetic algorithm (GA). The problem is reintroduced as the Steiner tree problem (which is known to be an NP-hard problem) by the aim of finding the minimum number of Steiner points where RNs are to be placed for restoring connectivity. An upper bound to the number of RNs is first computed to set up the length of initial chromosomes. The GA algorithm then iteratively reduces the number of RNs and determines their location at the same time. Experimental results indicate that the proposed GA is capable of establishing network connectivity using a reasonable number of RNs compared to the best existing work.

Keywords: connectivity restoration, genetic algorithms, multiple-node failure, relay nodes, wireless sensor networks

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Authors: Sabiu Bala Muhammad, Rosli Saad

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Multiple linear regression (MLR) models for fast estimation of true subsurface resistivity from apparent resistivity field measurements are developed and assessed in this study. The parameters investigated were apparent resistivity (ρₐ), horizontal location (X) and depth (Z) of measurement as the independent variables; and true resistivity (ρₜ) as the dependent variable. To achieve linearity in both resistivity variables, datasets were first transformed into logarithmic domain following diagnostic checks of normality of the dependent variable and heteroscedasticity to ensure accurate models. Four MLR models were developed based on hierarchical combination of the independent variables. The generated MLR coefficients were applied to another data set to estimate ρₜ values for validation. Contours of the estimated ρₜ values were plotted and compared to the observed data plots at the colour scale and blanking for visual assessment. The accuracy of the models was assessed using coefficient of determination (R²), standard error (SE) and weighted mean absolute percentage error (wMAPE). It is concluded that the MLR models can estimate ρₜ for with high level of accuracy.

Keywords: apparent resistivity, depth, horizontal location, multiple linear regression, true resistivity

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Authors: Hua Cao, Laurent Peyrodie, Olivier Agnani, Cecile Donze

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Multiple sclerosis (MS) is a disease, which affects the central nervous system, and causes balance problem. In clinical, this disorder is usually evaluated using static posturography. Some linear or nonlinear measures, extracted from the posturographic data (i.e. center of pressure, COP) recorded during a balance test, has been used to analyze postural control of MS patients. In this study, the trend (TREND) and the sample entropy (SampEn), two nonlinear parameters were chosen to investigate their relationships with the expanded disability status scale (EDSS) score. Forty volunteers with different EDSS scores participated in our experiments with eyes open (EO) and closed (EC). TREND and two types of SampEn (SampEn1 and SampEn2) were calculated for each combined COP’s position signal. The results have shown that TREND had a weak negative correlation to EDSS while SampEn2 had a strong positive correlation to EDSS. Compared to TREND and SampEn1, SampEn2 showed a better significant correlation to EDSS and an ability to discriminate the MS patients in the EC case. In addition, the outcome of the study suggests that the multi-dimensional nonlinear analysis could provide some information about the impact of disability progression in MS on dynamics of the COP data.

Keywords: balance, multiple sclerosis, nonlinear analysis, postural sway

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Authors: Aliyu Damri

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In every educational institution, students of mass communication receive training to report events and issues accurately and objectively in accordance with official controls. However, the complex nature of society today made it possible to use WhatsApp platform that revolutionizes the means of sharing information, ideas, and experiences. This paper examined how students in the Department of Mass Communication, Abdu Gusau Polytechnic, Talata Mafara used WhatsApp platform in spreading fake news. It used in depth interview techniques and focus group discussion with students as well as the use of published materials to gather related and relevant data. Also, the paper used procedures involved to analyze long interview content. This procedure includes observation of a useful utterance, development of expanded observation, examination of interconnection of observed comments, collective scrutiny of observation for patterns and themes, and review and analysis of the themes across all interviews for development of thesis. The result indicated that inadequate and absent of official controls guiding the conduct of online information sharing, inaccuracies and poor source verification, lack of gate keeping procedures to ensure ethical and legal provisions, bringing users into the process, sharing all information, availability of misinformation, disinformation and rumor and problem of conversation strongly encouraged the emergence of fake news. Surprisingly, the idea of information as a commodity has increased, and transparency of a source as new ethics emerged.

Keywords: disinformation, fake news, group, mass communication, misinformation, WhatsApp

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Authors: Suzanne Strauss, Leandi Steenkamp

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The Finnish symphonic metal band Nightwish is the brainchild of songwriter and lyricist TuomasHolopainen and the band recorded their first demonstration recording in 1996. The band has since produced nine full-length studio albums, the most recent being the 2020 album Human. :||: Nature., and has reached massive international success. The band is well known for songs about fantasy and escapism and employs many sonic, visual and branding tools and techniques to communicate these constructs to the audience. Among these, is the band’s creation of the so-called “Nightwish world and mythology” with a set of recurring characters and narratives which, in turn, creates a psychological anchor and safe space for Nightwish fans around the globe. Nature and the reverence of nature are central themes in Nightwish’s self-created mythology.Swiss psychologist Carl Jung’s theory of the collective unconscious identified a mysterious reservoir of psychological constructs common to all people, being derived from ancestral memory and experience, common to all humankind, and distinct from the individual’s personal unconscious. Furthermore, he defined archetypes as timeless collective patterns and images that springs forth from the collective unconscious. Archetypes can be actualized when they enter consciousness as images in interaction with the outside world. Archetypal patterns or images can manifest in different ways across world cultures, but follow common patterns, also known as archetypal themes and symbols. The Jungian approach to the psyche places great emphasis on nature, positing a direct link betweenthe concept of wholeness and responsible care for nature and the environment.In our proposed paper, we examine, by means of thematic content analysis, how Nightwish makes use of archetypal themes and symbols referring to nature and the environment in selected songs from their ninth full-length album Human. II Nature. Furthermore, we argue that the longing for and reverence of nature in selected Nightwish songs may serve as a type of “social intervention” and social critique on modern capitalist society. The type of social critique that the band offers is generally connoted intertextually and is not equally explicit in their songs. The band uses a unique combination of escapism, fantasy, and nature narratives to inspire a sense of wonder, enchantment, and magic in the listener. In this way, escapism, fantasy, and nature serve as postmodern frames of reference that aim to “re-enchant” the disenchanted and de-spiritualized. In this way, re-enchantment could also refer to spiritual and/or psychological healing and rebirth.

Keywords: archetypes, metal music, nature, Nightwish, social interventions

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Authors: Olayinka Ariba, Abe Oudshoorn, Steve Rolfe, Carrie Anne Marshall, Deanna Befus, Jason Gilliland, Miranda Crockett, Susana Caxaj, Sarah McLean, Amy Van Berkum, Natasha Thuemler

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Background: Secure housing is a platform for health and well-being. Those who struggle with housing stability have complex life and health histories and often require some support services such as the provision of permanent supportive housing. Poor access to supportive resources creates an exacerbation of chronic homelessness, particularly affecting individuals who need immediate access to mental health and addiction supports. This paper presents the first phase of a three-part study examining how on-site support impacts housing stability for recently-re-housed persons. Method: This study utilized a community-based participatory research methodology. Twenty in-depth interviews were conducted with permanent supportive housing residents from a single-site dwelling. Interpretative description analysis was used to draw common themes and understand the experiences and challenges of housing support. Results: Three interconnected themes were identified: 1) Available and timely supports; 2) Affordability; and 3) Community, but with independence as desired. These interconnected components are helping residents transition from homelessness or long-term mental health inpatient care to live in the community. Despite some participant concerns about resident conflicts, staff availability, and affordability, this has been a welcome and successful move for most. Conclusion: Supportive housing is essential for successful tenancies as a platform for health and well-being among Canada’s most vulnerable and, from the perspective of persons recently re-housed, permanent supportive housing is a worthwhile investment.

Keywords: homelessness, supportive housing, rehoused, housing stability

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Authors: Majid Pourahmadi

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The performance of time-reversal MUSIC algorithm will be dramatically degrades in presence of strong noise and multiple scattering (i.e. when scatterers are close to each other). This is due to error in determining the number of scatterers. The present paper provides a new approach to alleviate such a problem using an information theoretic criterion referred as minimum description length (MDL). The merits of the novel approach are confirmed by the numerical examples. The results indicate the time-reversal MUSIC yields accurate estimate of the target locations with considerable noise and multiple scattering in the received signals.

Keywords: microwave imaging, time reversal, MUSIC algorithm, minimum description length (MDL)

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Authors: Myriam Castonguay, Florence Vinit

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This study aims to gain a better understanding of the lived experience of seven children growing up in a family where another child is severely disabled, informed by family systems theory and the socio-ecological model of development. In depth semi-structured interviews were conducted with seven children who described they everyday life since their brother’s or sister’s diagnosis. Thematic analysis revealed four themes : struggling with loneliness inside the family, supporting the disabled child through its journey, accommodating to a changing routine and keeping a “bubble” for oneself. Brothers and sisters depict a family life characterized by much loneliness, with severe disabilities requiring ongoing care and prolonged hospitalizations. In the midst of adversity, siblings describe themselves as highly committed to supporting the disabled child and to preserve family cohesion, even if that means getting exposed to emotionally challenging situations and adjusting their daily routine frequently. Children recount that keeping up with schoolwork and leisure activities of their own is central to their well-being. Having a space where one can reconnect with his ordinary life as a kid is also deemed very important. This study reminds us that more needs to be done to counteract the loneliness experienced by siblings through the family experience of disability. Family members and clinicians need to be extra vigilant to ensure siblings’ needs don’t go unnoticed or dismissed, as it may be difficult for this population of children to voice their own experience and needs. Family, school and other actors in the community may help brothers and sisters pursue their personal dreams, goals and projects, to continue experiencing well-being despite adverse life circumstances.

Keywords: sibling’s lived experience of disability, sibling’s needs at various levels of the ecosystem, family adjustment to the disability experience, supporting family wellness through the disability experience

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Authors: Abolfazl Hosseinkhani, Sepehr Sanaye

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Different approaches have been used to predict the performance of the vertical axis wind turbines (VAWT), such as experimental, computational fluid dynamics (CFD), and analytical methods. Analytical methods, such as momentum models that use streamtubes, have low computational cost and sufficient accuracy. The double multiple streamtube (DMST) is one of the most commonly used of momentum models, which divide the rotor plane of VAWT into upwind and downwind. In fact, results from the DMST method have shown some discrepancy compared with experiment results; that is because the Darrieus turbine is a complex and aerodynamically unsteady configuration. In this study, analytical-experimental-based corrections, including dynamic stall, streamtube expansion, and finite blade length correction are used to improve the DMST method. Results indicated that using these corrections for a SANDIA 17-m VAWT will lead to improving the results of DMST.

Keywords: vertical axis wind turbine, analytical, double multiple streamtube, streamtube expansion model, dynamic stall model, finite blade length correction

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Authors: Rafael Zhindon Almeida

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Surface water quality is an important concern for the evaluation and prediction of water quality conditions. The objective of this study is to develop a statistical model that can accurately predict the water quality of the El Macho estuary in the city of Machala, El Oro province. The methodology employed in this study is of a basic type that involves a thorough search for theoretical foundations to improve the understanding of statistical modeling for water quality analysis. The research design is correlational, using a multivariate statistical model involving multiple linear regression and principal component analysis. The results indicate that water quality parameters such as fecal coliforms, biochemical oxygen demand, chemical oxygen demand, iron and dissolved oxygen exceed the allowable limits. The water of the El Macho estuary is determined to be below the required water quality criteria. The multiple linear regression model, based on chemical oxygen demand and total dissolved solids, explains 99.9% of the variance of the dependent variable. In addition, principal component analysis shows that the model has an explanatory power of 86.242%. The study successfully developed a statistical model to evaluate the water quality of the El Macho estuary. The estuary did not meet the water quality criteria, with several parameters exceeding the allowable limits. The multiple linear regression model and principal component analysis provide valuable information on the relationship between the various water quality parameters. The findings of the study emphasize the need for immediate action to improve the water quality of the El Macho estuary to ensure the preservation and protection of this valuable natural resource.

Keywords: statistical modeling, water quality, multiple linear regression, principal components, statistical models

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Authors: Nesrine Boussaoui

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Background: International students often encounter challenges while studying in the UK, including communication and language barriers, lack of social networks, and socio-cultural differences that adversely impact on their mental health. For Algerian international students (AISs), these challenges may be heightened as English is not their first language and the culture of their homeland is substantially different from British culture, yet research has to incorporate their experiences and perspectives. Aim: The current study aimed to explore AISs’ 1) understandings of mental health; 2) issues of disclosure for mental health difficulties; and 3) mental health help-seeking and coping strategies. Method: In-depth, audio recorded semi-structured interviews (n = 20) with AISs in UK universities were conducted. An inductive, reflective thematic approach analysis was used. Finding: The following themes and associated sub-themes were developed: (1) Algerian cultural influences on mental health understanding(socio-cultural comparisons); (2) the paradox of the family (pressure vs. support); (3) stigma and fear of disclosure; (4) Barriers to formal help-seeking (informal disclosure as first step to seeking help); (5) Communication barriers (resort to mother tongue to disclose); (6) Self-reliance and religious coping. Conclusion: Recognising and understanding the challenges faced by AISs in terms of disclosure and mental health help-seeking is essential to reduce barriers to formal help-seeking. Informal disclosure among peers is often the first step to seeking help. Enhancing practitioners’ cultural competences and awareness of diverse understandings of mental health and the role of religious coping among AISs’ may have transferable benefits to a wider international student population.

Keywords: mental health, stegma, coping, disclosure

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Authors: Sina Mahdavi

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Background and Objective: Multiple sclerosis (MS) is the most common inflammatory autoimmune disease of the central nervous system (CNS) that affects the myelination process in the CNS. Complex interactions of various "environmental or infectious" factors may act as triggers in autoimmunity and disease progression. The association between viral infections, especially Epstein-Barr virus (EBV) and MS, is one potential cause that is not well understood. In this study, we aim to summarize the available data on EBV infection in MS disease progression. Materials and Methods: For this study, the keywords "Multiple sclerosis," "Epstein-Barr virus," and "central nervous system" in the databases PubMed, Google Scholar, Sid, and MagIran between 2016 and 2022 were searched, and 14 articles were chosen, studied, and analyzed. Results: Demyelinated lesions isolated from MS patients contain EBNAs from EBV proteins. The EBNA1 domain contains a pentapeptide fragment identical to B-crystallin, a heat shock peptide, that is increased in peripheral B cells in response to B-crystallin infection, resulting in myelin-directed autoimmunity mediated by proinflammatory T cells. EBNA2, which is involved in the regulation of viral transcription, may enhance transcription from MS risk loci. A 7-fold increase in the risk of MS has been observed in EBV infection with HLA-DR15 synergy. Conclusion: EBV infection along with a variety of specific genetic risk alleles, cause inflammatory cascades in the CNS by infected B cells. There is a high expression of EBV during the course of MS, which indicates the relationship between EBV and MS, that this virus can play a role in the development of MS by creating an inflammatory state. Therefore, measures to modulate the expression of EBV may be effective in reducing inflammatory processes in demyelinated areas of MS patients.

Keywords: multiple sclerosis, Epstein-Barr virus, central nervous system, EBNAs

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Authors: Rui Brito

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This contribution regards a literature review of inventory management that is a relevant topic for the firms, due to its important use of capital with implications in firm’s profitability within the complexity of a more competitive and globalized world. Firms look for small inventories in order to reduce holding costs, namely opportunity cost, warehousing and handling costs, deterioration and being out of style, but larger inventories are required by some reasons, such as customer service, ordering cost, transportation cost, supplier’s payment to reduce unit costs or to take advantage of price increase in the near future, and equipment setup cost. Thus, management shall address a trade-off between small inventories and larger inventories. This literature review concerns three types of inventory (spare parts, safety stock, and vendor) whose management usually is beyond the scope of logistics. The applied methodology consisted of an online search of databases regarding scientific documents in English, namely Elsevier, Springer, Emerald, Wiley, and Taylor & Francis, but excluding books except if edited, using search engines, such as Google Scholar and B-on. The search was based on three keywords/strings (themes) which had to be included just as in the article title, suggesting themes were very relevant to the researchers. The whole search period was between 2009 and 2018 with the aim of collecting between twenty and forty studies considered relevant within each of the key words/strings specified. Documents were sorted by relevance and to prevent the exclusion of the more recent articles, based on lower quantity of citations partially due to less time to be cited in new research articles, the search period was divided into two sub-periods (2009-2015 and 2016-2018). The number of surveyed articles by theme showed a variation from 40 to 200 and the number of citations of those articles showed a wider variation from 3 to 216. Selected articles from the three themes were analyzed and the first seven of the first sub-period and the first three of the second sub-period with more citations were read in full to make a synopsis of each article. Overall, the findings show that the majority of article types were models, namely mathematical, although with different sub-types for each theme. Almost all articles suggest further studies, with some mentioning it for their own author(s), which widen the diversity of the previous research. Identified research gaps concern the use of surveys to know which are the models more used by firms, the reasons for not using the models with more performance and accuracy, and which are the satisfaction levels with the outcomes of the inventories management and its effect on the improvement of the firm’s overall performance. The review ends with the limitations and contributions of the study.

Keywords: inventory management, safety stock, spare parts inventory, vendor managed inventory

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Authors: Amy M. Kwon

Abstract:

Support vector machine (SVM) is a well-known algorithm in machine learning due to its superior performance, and it also functions well in multiple-instance (MI) problems. Our study proposes a schematic algorithm to select instances based on Hausdorff distance, which can be adapted to SVMs as input vectors under the MI setting. Based on experiments on five benchmark datasets, our strategy for adapting representation outperformed in comparison with original approach. In addition, task execution times (TETs) were reduced by more than 80% based on MissSVM. Hence, it is noteworthy to consider this representation adaptation to SVMs under MI-setting.

Keywords: support vector machine, Margin, Hausdorff distance, representation selection, multiple-instance learning, machine learning

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Authors: Carolyn J. Ortega, Stephen E. Berger

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The role of the custody evaluator is perhaps one of the most controversial and risky endeavors in clinical practice. Complaints filed with licensing boards regarding a child-custody evaluation constitute the second most common reason for such an event. Although the evaluator is expected to answer for the family-law court what is in the “best interest of the child,” there is a lack of clarity on how to establish this in any empirically validated manner. Hence, practitioners must contend with a nebulous framework in formulating their methodological procedures that inherently places them at risk in an already litigious context. This study sought to qualitatively investigate patterns of practice among doctoral practitioners conducting child custody evaluations in the area of Southern California. Ten psychologists were interviewed who devoted between 25 and 100% of their California private practice to custody work. All held Ph.D. degrees with a range of eight to 36 years of experience in custody work. Semi-structured interviews were used to investigate assessment practices, ensure adherence to guidelines, risk management, and qualities of evaluators. Forty-three Specific Themes were identified using Interpretive Phenomenological Analysis (IPA). Seven Higher Order Themes clustered on salient factors such as use of Ethics, Law, Guidelines; Parent Variables; Child Variables; Psychologist Variables; Testing; Literature; and Trends. Evaluators were aware of the ever-present reality of a licensure complaint and thus presented idiosyncratic descriptions of risk management considerations. Ambiguity about quantifying and validly tapping parenting abilities was also reviewed. Findings from this study suggested a high reliance on unstructured and observational methods in child custody practices.

Keywords: forensic psychology, psychological testing, assessment methodology, child custody

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Authors: Veronika Lesáková, Silvia Slezáková, František Štěpánek

Abstract:

Additive manufacturing technologies producing drug dosage forms aimed at personalized medicine applications are promising strategies with several advantages over the conventional production methods. One of the emerging technologies is 3D printing which reduces manufacturing steps and thus allows a significant drop in expenses. A decrease in material consumption is also a highly impactful benefit as the tested drugs are frequently expensive substances. In addition, 3D printed dosage forms enable increased patient compliance and prevent misdosing as the dosage forms are carefully designed according to the patient’s needs. The incorporation of multiple drugs into a single dosage form further increases the degree of personalization. Our research focuses on the development of 3D printed tablets incorporating multiple drugs (candesartan, losartan) and thermoplastic polymers (e.g., KlucelTM HPC EF). The filaments, an essential feed material for 3D printing,wereproduced via hot-melt extrusion. Subsequently, the extruded filaments of various formulations were 3D printed into tablets using an FDM 3D printer. Then, we have assessed the influence of the internal structure of 3D printed tablets and formulation on dissolution behaviour by obtaining the dissolution profiles of drugs present in the 3D printed tablets. In conclusion, we have developed tablets containing multiple drugs providing modified release profiles. The 3D printing experiments demonstrate the high tunability of 3D printing as each tablet compartment is constructed with a different formulation. Overall, the results suggest that the 3D printing technology is a promising manufacturing approach to dual tablet preparation for personalized medicine.

Keywords: 3D printing, drug delivery, hot-melt extrusion, dissolution kinetics

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Authors: Kunal Garg, Louise Theusen Hermansan, Kanoktip Puttaraska, Oliver Hendricks, Heidi Pirttinen, Leona Gilbert

Abstract:

The Germ Theory (one infectious determinant is equal to one disease) has unarguably evolved our capability to diagnose and treat infectious diseases over the years. Nevertheless, the advent of technology, climate change, and volatile human behavior has brought about drastic changes in our environment, leading us to question the relevance of the Germ Theory in our day, i.e. will vector-borne disease (VBD) sufferers produce multiple immune responses when tested for multiple microbes? Vector diseased patients producing multiple immune responses to different microbes would evidently suggest human polymicrobial infections (HPI). Ongoing diagnostic tools are exceedingly unequipped with the current research findings that would aid in diagnosing patients for polymicrobial infections. This shortcoming has caused misdiagnosis at very high rates, consequently diminishing the patient’s quality of life due to inadequate treatment. Equipped with the state-of-art scientific knowledge, PolyScan intends to address the pitfalls in current VBD diagnostics. PolyScan is a multiplex and multifunctional enzyme linked Immunosorbent assay (ELISA) platform that can test for numerous VBD microbes and allow simultaneous screening for multiple types of antibodies. To validate PolyScan, Lyme Borreliosis (LB) and spondyloarthritis (SpA) patient groups (n = 54 each) were tested for Borrelia burgdorferi, Borrelia burgdorferi Round Body (RB), Borrelia afzelii, Borrelia garinii, and Ehrlichia chaffeensis against IgM and IgG antibodies. LB serum samples were obtained from Germany and SpA serum samples were obtained from Denmark under relevant ethical approvals. The SpA group represented chronic LB stage because reactive arthritis (SpA subtype) in the form of Lyme arthritis links to LB. It was hypothesized that patients from both the groups will produce multiple immune responses that as a consequence would evidently suggest HPI. It was also hypothesized that the multiple immune response proportion in SpA patient group would be significantly larger when compared to the LB patient group across both antibodies. It was observed that 26% LB patients and 57% SpA patients produced multiple immune responses in contrast to 33% LB patients and 30% SpA patients that produced solitary immune responses when tested against IgM. Similarly, 52% LB patients and an astounding 73% SpA patients produced multiple immune responses in contrast to 30% LB patients and 8% SpA patients that produced solitary immune responses when tested against IgG. Interestingly, IgM immune dysfunction in both the patient groups was also recorded. Atypically, 6% of the unresponsive 18% LB with IgG antibody was recorded producing multiple immune responses with the IgM antibody. Similarly, 12% of the unresponsive 19% SpA with IgG antibody was recorded producing multiple immune responses with the IgM antibody. Thus, results not only supported hypothesis but also suggested that IgM may atypically prevail longer than IgG. The PolyScan concept will aid clinicians to detect patients for early, persistent, late, polymicrobial, & immune dysfunction conditions linked to different VBD. PolyScan provides a paradigm shift for the VBD diagnostic industry to follow that will drastically shorten patient’s time to receive adequate treatment.

Keywords: diagnostics, immune dysfunction, polymicrobial, TICK-TAG

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