Search results for: the health belief model

Authors: Mohd Adib Abd Muin, Shuhairimi Abdullah, Azizan Bahari

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Problem: The research problem is lacking of model on social entrepreneurship that focus on Islamic perspective. Objective: The objective of this paper is to analyse the existing model on social entrepreneurship and to identify the research gap on Islamic perspective from existing models. Research Methodology: The research method used in this study is literature review and comparative analysis from 6 existing models of social entrepreneurship. Finding: The research finding shows that 6 existing models on social entrepreneurship has been analysed and it shows that the existing models on social entrepreneurship do not emphasize on Islamic perspective.

Keywords: social entrepreneurship, Islamic perspective, research gap, business management

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Authors: Helena Costa Oliveira, Carmem Oliveira, Rita Moutinho

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The Balanced Scorecard (BSC) is a continuous strategic monitoring model focused not only on financial issues but also on internal processes, patients/users, and learning and growth. Initially dedicated to business management, it currently serves organizations of other natures - such as hospitals. This paper presents a BSC designed for a Portuguese Acute Pain Unit (APU). This study is qualitative and based on the experience of collaborators at the APU. The management of APU is based on four perspectives – users, internal processes, learning and growth, and financial and legal. For each perspective, there were identified strategic objectives, critical factors, lead indicators and initiatives. The strategic map of the APU outlining sustained strategic relations among strategic objectives. This study contributes to the development of research in the health management area as it explores how organizational insufficiencies and inconsistencies in this particular case can be addressed, through the identification of critical factors, to clearly establish core outcomes and initiatives to set up.

Keywords: acute pain unit, balanced scorecard, hospital management, organizational performance, Portugal

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Authors: Rebecca Oakes

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In the New Zealand public health system, work has been taking place to use electronic systems to convey data from the ‘floor to the board’ that makes patient needs, and therefore nursing work, visible. For nurses, these developments in health information technology puts us in a very new and exciting position of being able to articulate the work of nursing through a language understood at all levels of an organisation, the language of acuity. Nurses increasingly have a considerable stake-hold in patient acuity data. Patient acuity systems, when used well, can assist greatly in demonstrating how much work is required, the type of work, and when it will be required. The New Zealand Safe Staffing Unit is supporting New Zealand nurses to create a culture of shared governance, where nursing data is informing policies, staffing methodologies and forecasting within their organisations. Assisting organisations to understand their acuity data, strengthening user confidence in using electronic patient acuity systems, and ensuring nursing and midwifery workload is accurately reflected is critical to the success of the safe staffing programme. Nurses and midwives have the capacity via an acuity tool to become key informers of organisational planning. Quality patient care, best use of health resources and a quality work environment are essential components of a safe, resilient and well resourced organisation. Nurses are the key informers of this information. In New Zealand a national level approach is paving the way for significant changes to the understanding and use of patient acuity and nursing workload information.

Keywords: nursing workload, patient acuity, safe staffing, New Zealand

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Authors: Iyad A. A. Abusahloub

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This research aimed to measure the level of perception and application of Integrated Talent Management according to IBM standards, by the upper and middle categories in Palestinian government institutions in Gaza, using a descriptive-analytical method. Using a questionnaire based on the standards of the IBM Institute for Business Value, the researcher added a second section to measure the perception of integrated talent management, the sample was 248 managers. The SPSS package was used for statistical analysis. The results showed that government institutions in Gaza apply Integrated Talent Management according to IBM standards at a medium degree did not exceed 59.8%, there is weakness in the perception of integrated talent management at the level of 53.6%, and there is a strong correlation between (Integrated Talent Management) and (the perception of the integrated talent management) amounted to 92.9%, and 88.9% of the change in the perception of the integrated talent management is by (motivate and develop, deploy and manage, connect and enable, and transform and sustain) talents, and 11.1% is by other factors. Conclusion: This study concluded that the integrated talent management model presented by IBM with its six dimensions is an effective model to reach your awareness and understanding of talent management, especially that it must rely on at least four basic dimensions out of the six dimensions: 1- Stimulating and developing talent. 2- Organizing and managing talent. 3- Connecting with talent and empowering it. 4- Succession and sustainability of talent. Therefore, this study recommends the adoption of the integrated talent management model provided by IBM to any organization across the world, regardless of its specialization or size, to reach talent sustainability.

Keywords: HR, talent, talent management, IBM

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Authors: Xi Vivien Wu, Emily Neo Kim Ang, Yi Jung Tung, Wenru Wang

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Background and Objective: The increase in life expectancy and emphasis on self-reliance for the older adults are global phenomena. As such, lifelong learning in the community is considered a viable means of promoting successful and active aging. This systematic review aims to examine various lifelong learning programs for community-dwelling older adults and to synthesize the contents and outcomes of these lifelong learning programs. Methods: A systematic search was conducted in July to December 2016. Two reviewers were engaged in the process to ensure creditability of the selection process. Narrative description and analysis were applied with the support of a tabulation of key data including study design, interventions, and outcomes. Results: Eleven articles, which consisted of five randomized controlled trials and six quasi-experimental studies, were included in this review. Interventions included e-health literacy programs with the aid of computers and the Internet (n=4), computer and Internet training (n=3), physical fitness programs (n=2), music program (n=1), and intergenerational program (n=1). All studies used objective measurement tools to evaluate the outcomes of the study. Conclusion: The systematic review indicated lifelong learning programs resulted in positive outcomes in terms of physical health, mental health, social behavior, social support, self-efficacy and confidence in computer usage, and increased e-health literacy efficacy. However, the lifelong learning programs face challenges such as funding shortages, program cuts, and increasing costs. A comprehensive lifelong learning program could be developed to enhance the well-being of the older adults at a more holistic level. Empirical research can be done to explore the effectiveness of this comprehensive lifelong learning program.

Keywords: community-dwelling older adults, e-health literacy program, lifelong learning program, the wellbeing of the older adults

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Authors: Lokes Parvatha Kumaran S., Sakthi Jay Mahenthar C., Sathyaprakash P., Jayakumar V., Shobanadevi A.

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With the evolution of technology, the need to solve complex computational problems like machine learning and deep learning has shot up. But even the most powerful classical supercomputers find it difficult to execute these tasks. With the recent development of quantum computing, researchers and tech-giants strive for new quantum circuits for machine learning tasks, as present works on Quantum Machine Learning (QML) ensure less memory consumption and reduced model parameters. But it is strenuous to simulate classical deep learning models on existing quantum computing platforms due to the inflexibility of deep quantum circuits. As a consequence, it is essential to design viable quantum algorithms for QML for noisy intermediate-scale quantum (NISQ) devices. The proposed work aims to explore Variational Quantum Circuits (VQC) for Deep Reinforcement Learning by remodeling the experience replay and target network into a representation of VQC. In addition, to reduce the number of model parameters, quantum information encoding schemes are used to achieve better results than the classical neural networks. VQCs are employed to approximate the deep Q-value function for decision-making and policy-selection reinforcement learning with experience replay and the target network.

Keywords: quantum computing, quantum machine learning, variational quantum circuit, deep reinforcement learning, quantum information encoding scheme

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Authors: Atje Setiawan Abdullah, Budi Nurani Ruchjana, I. Gede Nyoman Mindra Jaya, Eddy Hermawan

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Ethnoscience is used to see the culture with a scientific perspective, which may help to understand how people develop various forms of knowledge and belief, initially focusing on the ecology and history of the contributions that have been there. One of the areas studied in ethnoscience is etno-informatics, is the application of informatics in the culture. In this study the science of informatics used is data mining, a process to automatically extract knowledge from large databases, to obtain interesting patterns in order to obtain a knowledge. While the application of culture described by naming database village on the island of Java were obtained from Geographic Indonesia Information Agency (BIG), 2014. The purpose of this study is; first, to classify the naming of the village on the island of Java based on the structure of the word naming the village, including the prefix of the word, syllable contained, and complete word. Second to classify the meaning of naming the village based on specific categories, as well as its role in the community behavioral characteristics. Third, how to visualize the naming of the village to a map location, to see the similarity of naming villages in each province. In this research we have developed two theorems, i.e theorems area as a result of research studies have collected intersection naming villages in each province on the island of Java, and the composition of the wedge theorem sets the provinces in Java is used to view the peculiarities of a location study. The methodology in this study base on the method of Knowledge Discovery in Database (KDD) on data mining, the process includes preprocessing, data mining and post processing. The results showed that the Java community prioritizes merit in running his life, always working hard to achieve a more prosperous life, and love as well as water and environmental sustainment. Naming villages in each location adjacent province has a high degree of similarity, and influence each other. Cultural similarities in the province of Central Java, East Java and West Java-Banten have a high similarity, whereas in Jakarta-Yogyakarta has a low similarity. This research resulted in the cultural character of communities within the meaning of the naming of the village on the island of Java, this character is expected to serve as a guide in the behavior of people's daily life on the island of Java.

Keywords: ethnoscience, ethno-informatics, data mining, clustering, Java island culture

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Authors: Natarajan Ramasamy, Gurulingamurthy Haralur, Ramesh Nivarthu, Nikhil Kumar Singha

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Elastomers are polymeric materials with varied backbone architectures ranging from linear to dendrimeric structures and wide varieties of monomeric repeat units. These elastomers show strongly viscous and weakly elastic when it is not cross-linked. But when crosslinked, based on the extent the properties of these elastomers can range from highly flexible to highly stiff nature. Lightly cross-linked systems are well studied and reported. Understanding the nature of highly cross-linked rubber based upon chemical structure and architecture is critical for varieties of applications. One of the critical parameters is cross-link density. In the current work, we have studied the highly cross-linked state of linear, lightly branched to star-shaped branched elastomers and determined the cross-linked density by using different models. Change in hardness, shift in Tg, change in modulus and swelling behavior were measured experimentally as a function of the extent of curing. These properties were analyzed using varied models to determine cross-link density. We used hardness measurements to examine cure time. Hardness to the extent of curing relationship is determined. It is well known that micromechanical transitions like Tg and storage modulus are related to the extent of crosslinking. The Tg of the elastomer in different crosslinked state was determined by DMA, and based on plateau modulus the crosslink density is estimated by using Nielsen’s model. Usually for lightly crosslinked systems, based on equilibrium swelling ratio in solvent the cross link density is estimated by using Flory–Rhener model. When it comes to highly crosslinked system, Flory-Rhener model is not valid because of smaller chain length. So models based on the assumption of polymer as a Non-Gaussian chain like 1) Helmis–Heinrich–Straube (HHS) model, 2) Gloria M.gusler and Yoram Cohen Model, 3) Barbara D. Barr-Howell and Nikolaos A. Peppas model is used for estimating crosslink density. In this work, correction factors are determined to the existing models and based upon it structure-property relationship of highly crosslinked elastomers was studied.

Keywords: dynamic mechanical analysis, glass transition temperature, parts per hundred grams of rubber, crosslink density, number of networks per unit volume of elastomer

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Authors: Rezky Rifaini, Raden Bagus Fajriya Hakim

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This research was conducted at the Bolo primary health Care in Bima Regency. The purpose of the research is to find out the association pattern that is formed of medical record database from Bolo Primary health care’s patient. The data used is secondary data from medical records database PHC. Sequential pattern mining technique is the method that used to analysis. Transaction data generated from Patient_ID, Check_Date and diagnosis. Sequential Pattern Discovery Algorithms Using Equivalent Classes (SPADE) is one of the algorithm in sequential pattern mining, this algorithm find frequent sequences of data transaction, using vertical database and sequence join process. Results of the SPADE algorithm is frequent sequences that then used to form a rule. It technique is used to find the association pattern between items combination. Based on association rules sequential analysis with SPADE algorithm for minimum support 0,03 and minimum confidence 0,75 is gotten 3 association sequential pattern based on the sequence of patient_ID, check_Date and diagnosis data in the Bolo PHC.

Keywords: diagnosis, primary health care, medical record, data mining, sequential pattern mining, SPADE algorithm

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Authors: A. Drong, K. S. Kerkhoff

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Migration affects women’s sexual and reproductive health and rights. This paper reports on the social constructs of gender, and livelihood pursuits as beauty parlours workers amongst the young Garo women in Bangladesh, and studies changes in their accessibility to the healthcare services due to migration and livelihood. The paper is based on in-depth interviews and participant-led group discussions with 30 women working in various beauty parlours across the city. The data indicate that social perceptions of ‘good’, ‘bad’ and ‘respectable’ determine the expression of sexuality, and often dictates sexual and reproductive practices for these women. This study also reveals that unregulated work conditions, and the current cost of local healthcare services, have a strong impact on the women’s accessibility to the healthcare services; thus often limiting their choices to only customary and/or unqualified practitioners for abortions and child-births. Development programmes on migrant indigenous women’s health must, therefore, take the contextual gender norms and livelihood choices into account.

Keywords: gender, indigenous women, reproductive rights, sexual rights, Garo, migration, livelihood, healthcare

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Authors: Kunihisa Kakumoto

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This technical paper is for the prototype of solar energy utilization for finding sustainable conditions. This model has been simulated under the climate conditions in Japan. At the beginning of the study, the solar model house was built up on site. And the concerned data was collected in this model house for several years. On the basis of these collected data, the concept on the solar community was built up. For the finding sustainable conditions, the amount of the solar energy generation and its reduction of carbon dioxide and the reduction of carbon dioxide by the green planting and the amount of carbon dioxide according to the normal daily life in the solar community and the amount of the necessary water for the daily life in the solar community and the amount of the water supply by the rainfall on-site were calculated. These all values were taken into consideration. The relations between each calculated result are shown in the expression of inequality. This solar community and its consideration for finding sustainable conditions can be one prototype to do the feasibility study for our life in the future

Keywords: carbon dioxide, green planting, smart city, solar community, sustainable condition, water activity

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Authors: Mehdi Damaliamiri

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Undoubtedly, the power of language is hardly a new topic; indeed, the persuasive power of language accompanied by ideology has long been recognized in different aspects of life. The two and a half thousand-year-old Bisitun inscriptions in Iran, proclaiming the victories of the Persian King, Darius, are considered by some historians to have been an early example of the use of propaganda. Added to this, the modern age is the true cradle of fully-fledged ideologies and the ongoing process of centrifugal ideologization. The most visible work on ideology today within the field of linguistics is “Critical Discourse Analysis” (CDA). The focus of CDA is on “uncovering injustice, inequality, taking sides with the powerless and suppressed” and making “mechanisms of manipulation, discrimination, demagogy, and propaganda explicit and transparent.” possible way of relating language to ideology is to propose that ideology and language are inextricably intertwined. From this perspective, language is always ideological, and ideology depends on the language. All language use involves ideology, and so ideology is ubiquitous – in our everyday encounters, as much as in the business of the struggle for power within and between the nation-states and social statuses. At the same time, ideology requires language. Its key characteristics – its power and pervasiveness, its mechanisms for continuity and for change – all come out of the inner organization of language. The two phenomena are homologous: they share the same evolutionary trajectory. To get a more robust portrait of the power and ideology, we need to examine its potential place in the structure, and consider how such structures pattern in terms of the functional elements which organize meanings in the clause. This is based on the belief that all grammatical, including syntactic, knowledge is stored mentally as constructions have become immensely popular. When the structure of the clause is taken into account, the power and ideology have a preference for Complement over Subject and Adjunct. The subject is a central interpersonal element in discourse: it is one of two elements that form the central interactive nub of a proposition. Conceptually, there are countless ways of construing a given event and linguistically, a variety of grammatical devices that are usually available as alternate means of coding a given conception, such as political crime and corruption. In the theory of construal, then, which, like transitivity in Halliday, makes options available, Cognitive Linguistics can offer a cognitive account of ideology in language, where ideology is made possible by the choices a language allows for representing the same material situation in different ways. The possibility of promoting alternative construals of the same reality means that any particular choice in representation is always ideologically constrained or motivated and indicates the perspective and interests of the text-producer.

Keywords: power, ideology, court, discourse

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Authors: Li-Ching Chen

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The case-control design has been widely applied in clinical and epidemiological studies to investigate the association between risk factors and a given disease. The retrospective design can be easily implemented and is more economical over prospective studies. To adjust effects for confounding factors, methods such as stratification at the design stage and may be adopted. When some major confounding factors are difficult to be quantified, a matching design provides an opportunity for researchers to control the confounding effects. The matching effects can be parameterized by the intercepts of logistic models and the conditional logistic regression analysis is then adopted. This study demonstrates an information-matrix-based goodness-of-fit statistic to test the validity of the logistic regression model for matched case-control data. The asymptotic null distribution of this proposed test statistic is inferred. It needs neither to employ a simulation to evaluate its critical values nor to partition covariate space. The asymptotic power of this test statistic is also derived. The performance of the proposed method is assessed through simulation studies. An example of the real data set is applied to illustrate the implementation of the proposed method as well.

Keywords: conditional logistic model, goodness-of-fit, information matrix, matched case-control studies

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Authors: Jacques Lamarche, Juhani Dickinson

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This paper introduces a computational model of a Grammar as Logic of Labeling (GLL), where the lexical primitives of morphosyntax are phonological matrixes, the form of words, understood as labels that apply to realities (or targets) assumed to be outside of grammar altogether. The hypothesis is that even though a lexical label relates to its target arbitrarily, this label in a complex (constituent) label is part of a labeling pattern which, depending on its value (i.e., N, V, Adj, etc.), imposes language-specific restrictions on what it targets outside of grammar (in the world/semantics or in cognitive knowledge). Lexical forms categorized as nouns, verbs, adjectives, etc., are effectively targets of labeling patterns in use. The paper illustrates GLL through a computer model of basic patterns in English NPs. A constituent label is a binary object that encodes: i) alignment of input forms so that labels occurring at different points in time are understood as applying at once; ii) endocentric structuring - every grammatical constituent has a head label that determines the target of the constituent, and a limiter label (the non-head) that restricts this target. The N or A values are restricted to limiter label, the two differing in terms of alignment with a head. Consider the head initial DP ‘the dog’: the label ‘dog’ gets an N value because it is a limiter that is evenly aligned with the head ‘the’, restricting application of the DP. Adapting a traditional analysis of ‘the’ to GLL – apply label to something familiar – the DP targets and identifies one reality familiar to participants by applying to it the label ‘dog’ (singular). Consider next the DP ‘the large dog’: ‘large dog’ is nominal by even alignment with ‘the’, as before, and since ‘dog’ is the head of (head final) ‘large dog’, it is also nominal. The label ‘large’, however, is adjectival by narrow alignment with the head ‘dog’: it doesn’t target the head but targets a property of what dog applies to (a property or value of attribute). In other words, the internal composition of constituents determines that a form targets a property or a reality: ‘large’ and ‘dog’ happen to be valid targets to realize this constituent. In the presentation, the computer model of the analysis derives the 8 possible sequences of grammatical values with three labels after the determiner (the x y z): 1- D [ N [ N N ]]; 2- D [ A [ N N ] ]; 3- D [ N [ A N ] ]; 4- D [ A [ A N ] ]; 5- D [ [ N N ] N ]; 5- D [ [ A N ] N ]; 6- D [ [ N A ] N ] 7- [ [ N A ] N ] 8- D [ [ Adv A ] N ]. This approach that suggests that a computer model of these grammatical patterns could be used to construct ontologies/knowledge using speakers’ judgments about the validity of lexical meaning in grammatical patterns.

Keywords: syntactic theory, computational linguistics, logic and grammar, semantics, knowledge and grammar

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Authors: Bandar Alahmadi, Manohar Mareboyana, Lethia Jackson

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Today, there are many applications that are using computer vision models, such as face recognition, image classification, and object detection. The accuracy of these models is very important for the performance of these applications. One challenge that facing the computer vision models is the adversarial examples attack. In computer vision, the adversarial example is an image that is intentionally designed to cause the machine learning model to misclassify it. One of very well-known method that is used to attack the Convolution Neural Network (CNN) is Fast Gradient Sign Method (FGSM). The goal of this method is to find the perturbation that can fool the CNN using the gradient of the cost function of CNN. In this paper, we introduce a novel model that can attack Regional-Convolution Neural Network (R-CNN) that use FGSM. We first extract the regions that are detected by R-CNN, and then we resize these regions into the size of regular images. Then, we find the best perturbation of the regions that can fool CNN using FGSM. Next, we add the resulted perturbation to the attacked region to get a new region image that looks similar to the original image to human eyes. Finally, we placed the regions back to the original image and test the R-CNN with the attacked images. Our model could drop the accuracy of the R-CNN when we tested with Pascal VOC 2012 dataset.

Keywords: adversarial examples, attack, computer vision, image processing

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Authors: Fabio L. Vieira, Micaelle F. C. Lemos, Luciano C. Lemos, Rafaela S. Oliveira, Ian A. Cunha

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Brazil has some challenges ahead related to population oral health, most of them associated with the need of expanding into the local level its promotion and prevention activities, offer equal access to services and promote changes in the lifestyle of the population. The program implemented an oral health initiative in public schools in the city of Salvador, Bahia. The mission was to improve oral health among students on primary and secondary education, from 2 to 15 years old, using the school as a pathway to increase access to healthcare. The main actions consisted of a team's visit to the schools with educational sessions for dental cavity prevention and individual assessment. The program incorporated a clinical surveillance component through a dental evaluation of every student searching for dental disease and caries, standardization of the dentists’ team to reach uniform classification on the assessments, and the use of an online platform to register data directly from the schools. Sequentially, the students with caries were referred for free clinical treatment on the program’s Health Centre. The primary purpose of this study was to analyze the effects and outcomes of this school-based oral health program. The study sample was composed by data of a period of 3 years - 2015 to 2017 - from 13 public schools on the suburb of the city of Salvador with a total number of assessments of 9,278 on this period. From the data collected the prevalence of children with decay on permanent teeth was chosen as the most reliable indicator. The prevalence was calculated for each one of the 13 schools using the number of children with 1 or more dental caries on permanent teeth divided by the total number of students assessed for school each year. Then the percentage change per year was calculated for each school. Some schools presented a higher variation on the total number of assessments in one of the three years, so for these, the percentage change calculation was done using the two years with less variation. The results show that 10 of the 13 schools presented significative improvements for the indicator of caries in permanent teeth. The mean for the number of students with caries percentage reduction on the 13 schools was 26.8%, and the median was 32.2% caries in permanent teeth institution. The highest percentage of improvement reached a decrease of 65.6% on the indicator. Three schools presented a rise in caries prevalence (8.9, 18.9 and 37.2% increase) that, on an initial analysis, seems to be explained with the students’ cohort rotation among other schools, as well as absenteeism on the treatment. In conclusion, the program shows a relevant impact on the reduction of caries in permanent teeth among students and the need for the continuity and expansion of this integrated healthcare approach. It has also been evident the significative of the articulation between health and educational systems representing a fundamental approach to improve healthcare access for children especially in scenarios such as presented in Brazil.

Keywords: primary care, public health, oral health, school-based oral health, data management

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Authors: Muhammad Abubakar Alhassan, Diane Pennington

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Social networking sites have become a space for people to discuss public health issues such as non-suicidal self-injury (NSSI). There are thousands of tweets containing self-harm and self-injury hashtags on Twitter. It is difficult to distinguish between different users who participate in self-injury discussions on Twitter and how their opinions change over time. Also, it is challenging to understand the topics surrounding NSSI discussions on Twitter. We retrieved tweets using #selfham and #selfinjury hashtags and investigated those from the United kingdom. We applied inductive coding and grouped tweeters into different categories. This study used the Latent Dirichlet Allocation (LDA) algorithm to infer the optimum number of topics that describes our corpus. Our findings revealed that many of those participating in NSSI discussions are non-professional users as opposed to medical experts and academics. Support organisations, medical teams, and academics were campaigning positively on rais-ing self-injury awareness and recovery. Using LDAvis visualisation technique, we selected the top 20 most relevant terms from each topic and interpreted the topics as; children and youth well-being, self-harm misjudgement, mental health awareness, school and mental health support and, suicide and mental-health issues. More than 50% of these topics were discussed in England compared to Scotland, Wales, Ireland and Northern Ireland. Our findings highlight the advantages of using the Twitter social network in tackling the problem of self-injury through awareness. There is a need to study the potential risks associated with the use of social networks among self-injurers.

Keywords: self-harm, non-suicidal self-injury, Twitter, social networks

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Authors: Ritsuko Kawasaki, Takeshi Hiromatsu

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Management is required to understand all information security risks within an organization, and to make decisions on which information security risks should be treated in what level by allocating how much amount of cost. However, such decision-making is not usually easy, because various measures for risk treatment must be selected with the suitable application levels. In addition, some measures may have objectives conflicting with each other. It also makes the selection difficult. Therefore, this paper provides a model which supports the selection of measures by applying multi-objective analysis to find an optimal solution. Additionally, a list of measures is also provided to make the selection easier and more effective without any leakage of measures.

Keywords: information security risk treatment, selection of risk measures, risk acceptance, multi-objective optimization

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Authors: Laura Valdés-Santiago, José Luis Castro-Guillén, Jorge Noé García-Chávez, Rosalba Alonso-Rodríguez, Rafael Vargas-Bernal

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The quality and availability of the water contained in dams (artificial bodies of water) are at risk due to the presence of uncontrolled growths of cyanobacteria capable of producing cyanotoxins that affect the ecosystem and harm the health of humans and animals. The physicochemical properties were measured, and the degree of eutrophy of four dams from Guanajuato was determined. They presented a pH of 6.1 to 8.4, conductivity of 121 to 415 μS/cm², chlorophyll of 0.43-42.43 μg/L, NO₃- 0-1.2 mg/L and PO₄3- 0.11 to 0.84 mg/L; considering these parameters, the prey most prone to the development of cyanobacterial blooms were El Palote dam, La Purísima dam, and Allende dam, but not El Conejo dam. The potentially toxic cyanobacteria identified were Planktothrix agardhii, Oscillatoria sp., Raphidiopsis sp., and Microcystis sp., Microcystin-LR, Nodularin, and Cylindrospermopsin were quantified, presenting values between 0.08-0.42 and 0.02-2.05 ppb, respectively, the water bodies with the highest concentration were El Palote dam and La Purísima dam. Microcystin-LR and/or Nodularin levels are within the guideline values for human consumption in drinking water established by the World Health Organization for Microcystin-LR and for Cylindrospermopsin by the Oregon Health Authority (OHA) in all dams. This work is relevant due to the use of these bodies of water for agriculture and human consumption in the state, and the presence of toxin-producing cyanobacteria can represent an environmental, ecotoxicological, and health problem, so it is recommended to establish a program of frequent monitoring of cyanobacteria and cyanotoxins in the state's dams.

Keywords: Planktrothrix agardhii, Raphidiopsis sp., Microcystis sp., Cyanobacterial blooms, Cyanotoxins

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Authors: Folorunsho J. O., Umar M. A.

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Access to potable water supply in both the rural and urban regions of the world has been neglected, and this has severely affected man and the aesthetics of the natural environment of man. This has further worsened the issue of diseases prevalence. This study considered the effects of inadequate domestic water supply on human health in selected neighbourhoods of Lokoja. The study used descriptive statistics such as relative frequencies, percentages and inferential statistics to analyse the data obtained through the use of structured questionnaire. The results revealed that the females and male constituted 56% and 44% of the respondents respectively; 62% of the respondents married and 32% are unmarried; respondents between ages 31 and 40 years constitute majority of the study population, while respondents with tertiary education constituted 35%, and those with secondary education were 32% of the total respondents. Furthermore, civil servants constituted 40% and unemployed 16% of the total respondents. In terms of monthly income, 40% of the respondents was found to earn between ₦31,000 - 40,000 monthly. On the perception of households on the availability and adequacy of domestic water supply, the study revealed that 64.7% of the respondents have pipe-borne water as their main source of water supply, with only 28.5% out of the 64.7% have pipe-borne water supply daily. On the relationship between water supply characteristics and health status among households, the result shows that 76% of the respondents perceived a strong relationship between water supply and health status. Cumulatively, 67% of the respondents confirm that both the quality and quantity of water supplied play a critical role in determining health status of residents of the study area. The respondents also reported skin diseases (96%), diarrhoea (96%), malaria (91%), cholera (67%), dysentery (67%), and respiratory diseases (67%) as the most perceived and experienced in the area, the disease rate in the prevalence order of malaria (81%), diarrhoea (61%), skin diseases (58%), cholera (34%), dysentery (31%) and respiratory disease (14%) respectively. Finally, the results further showed how households cope with inadequate water supply with 52% of the respondents confirm that they regularly treat their water before it was deployed for domestic uses, while 35%, 26%, 25%, 10% and 4% of the 52% respectively, adopted boiling, addition of alums, filtering with fabrics, chlorination and bleaching as the preferred treatment methods. The study thus recommended policy options that will aggressively launch adequate potable water supply infrastructure in the study area.Keywords: Potable Water, Supply, Human Health, Perception, Chlorination

Keywords: potable water, human health, perception, chlorination

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Authors: Godwin Chigozie Okpara, William Chimee Nwaoha

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The paper set out to stress on how financial inclusion index could be calculated and also investigated the impact of inclusive finance on inclusive growth in an emerging economy. In the light of these objectives, chi-wins method was used to calculate indexes of financial inclusion while co-integration and error correction model were used for evaluation of the impact of financial inclusion on inclusive growth. The result of the analysis revealed that financial inclusion while having a long-run relationship with GDP growth is an insignificant function of the growth of the economy. The speed of adjustment is correctly signed and significant. On the basis of these results, the researchers called for tireless efforts of government and banking sector in promoting financial inclusion in developing countries.

Keywords: chi-wins index, co-integration, error correction model, financial inclusion

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Authors: Kyaw Zin Htut

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In this article, the synthesis of the efficiency of intelligent diagnostic system in the aircraft measuring devices is described. The technology developments of the diagnostic system are considered based on the model errors of the gyro instruments, which are used to measure the parameters of the aircraft. The synthesis of the diagnostic intelligent system is considered on the example of the problem of assessment and forecasting errors of the gyroscope devices on the onboard aircraft. The result of the system is to detect of faults of the aircraft measuring devices as well as the analysis of the measuring equipment to improve the efficiency of its work.

Keywords: diagnostic, dynamic system, errors of gyro instruments, model errors, assessment, prognosis

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Authors: Chiao-Chen Chang, Yang-Chieh Chin

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Social media has created a change in the way the network community is clustered, especially from the location of the community, from the original virtual space to the intertwined network, and thus the communication between people will change from face to face communication to social media-based communication model. However, social media users who have had a fixed engagement may have an intention to switch to another service provider because of the emergence of new forms of social media. For example, some of Facebook or Twitter users switched to Instagram in 2014 because of social media messages or image overloads, and users may seek simpler and instant social media to become their main social networking tool. This study explores the impact of system features overload, information overload, social monitoring concerns, problematic use and privacy concerns as the antecedents on social media fatigue, dissatisfaction, and alternative attractiveness; further influence social media switching. This study also uses the online questionnaire survey method to recover the sample data, and then confirm the factor analysis, path analysis, model fit analysis and mediating analysis with the structural equation model (SEM). Research findings demonstrated that there were significant effects on multiple paths. Based on the research findings, this study puts forward the implications of theory and practice.

Keywords: social media, switching, social media fatigue, alternative attractiveness

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Authors: Eyad Almaita

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In this paper, a novel adaptive Radial Basis Function Neural Networks (RBFNN) algorithm is used to forecast the hour by hour electrical load demand in Jordan. A small and effective RBFNN model is used to forecast the hourly total load demand based on a small number of features. These features are; the load in the previous day, the load in the same day in the previous week, the temperature in the same hour, the hour number, the day number, and the day type. The proposed adaptive RBFNN model can enhance the reliability of the conventional RBFNN after embedding the network in the system. This is achieved by introducing an adaptive algorithm that allows the change of the weights of the RBFNN after the training process is completed, which will eliminates the need to retrain the RBFNN model again. The data used in this paper is real data measured by National Electrical Power co. (Jordan). The data for the period Jan./2012-April/2013 is used train the RBFNN models and the data for the period May/2013- Sep. /2013 is used to validate the models effectiveness.

Keywords: load forecasting, adaptive neural network, radial basis function, short-term, electricity consumption

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Authors: Liam Martin, Martha Watson

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Patients with learning disabilities (LD) are at increased risk of physical and mental illness due to health inequality. To address this, NICE recommends that people from the age of 14 with a learning disability should have an annual LD health check. This consultation should include a holistic review of the patient’s physical, mental and social health needs with a view of creating an action plan to support the patient’s care. The expected standard set by the Quality and Outcomes Framework (QOF) is that each general practice should review at least 75% of their LD patients annually. During COVID-19, there have been barriers to primary care, including health anxiety, the shift to online general practice and the increase in GP workloads. A surgery in North London wanted to assess whether they were falling short of the expected standard for LD patient annual reviews in order to optimize care post Covid-19. A baseline audit was completed to assess how many LD patients were receiving their annual reviews over the period of 29th September 2020 to 29th September 2021. This information was accessed using EMIS Web Health Care System (EMIS). Patients included were aged 14 and over as per QOF standards. Doctors were not notified of this audit taking place. Following the results of this audit, the creation of learning disability clinics was recommended. These clinics were recommended to be on the ground floor and should be a dedicated time for LD reviews. A re-audit was performed via the same process 6 months later in March 2022. At the time of the baseline audit, there were 71 patients aged 14 and over that were on the LD register. 54% of these LD patients were found to have documentation of an annual LD review within the last 12 months. None of the LD patients between the ages of 14-18 years old had received their annual review. The results were discussed with the practice, and dedicated clinics were set up to review their LD patients. A second pass of the audit was completed 6 months later. This showed an improvement, with 84% of the LD patients registered at the surgery now having a documented annual review within the last 12 months. 78% of the patients between the ages of 14-18 years old had now been reviewed. The baseline audit revealed that the practice was not meeting the expected standard for LD patient’s annual health checks as outlined by QOF, with the most neglected patients being between the ages of 14-18. Identification and awareness of this vulnerable cohort is important to ensure measures can be put into place to support their physical, mental and social wellbeing. Other practices could consider an audit of their annual LD health checks to make sure they are practicing within QOF standards, and if there is a shortfall, they could consider implementing similar actions as used here; dedicated clinics for LD patient reviews.

Keywords: COVID-19, learning disability, learning disability health review, quality and outcomes framework

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Authors: Catherine Bradshaw

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Educators often report difficulty managing behavior problems and other mental health concerns that students display at school. These concerns also interfere with the learning process and can create distraction for teachers and other students. As such, schools play an important role in both preventing and intervening with students who experience these types of challenges. A number of models have been proposed to serve as a framework for delivering prevention and early intervention services in schools. One such model is called Positive Behavioral Interventions and Supports (PBIS), which has been scaled-up to over 26,000 schools in the U.S. and many other countries worldwide. PBIS aims to improve a range of student outcomes through early detection of and intervention related to behavioral and mental health symptoms. PBIS blends and applies social learning, behavioral, and organizational theories to prevent disruptive behavior and enhance the school’s organizational health. PBIS focuses on creating and sustaining tier 1 (universal), tier 2 (selective), and tier 3 (individual) systems of support. Most schools using PBIS have focused on the core elements of the tier 1 supports, which includes the following critical features. The formation of a PBIS team within the school to lead implementation. Identification and training of a behavioral support ‘coach’, who serves as a on-site technical assistance provider. Many of the individuals identified to serve as a PBIS coach are also trained as a school psychologist or guidance counselor; coaches typically have prior PBIS experience and are trained to conduct functional behavioral assessments. The PBIS team also identifies a set of three to five positive behavioral expectations that are implemented for all students and by all staff school-wide (e.g., ‘be respectful, responsible, and ready to learn’); these expectations are posted in all settings across the school, including in the classroom, cafeteria, playground etc. All school staff define and teach the school-wide behavioral expectations to all students and review them regularly. Finally, PBIS schools develop or adopt a school-wide system to reward or reinforce students who demonstrate those 3-5 positive behavioral expectations. Staff and administrators create an agreed upon system for responding to behavioral violations that include definitions about what constitutes a classroom-managed vs. an office-managed discipline problem. Finally, a formal system is developed to collect, analyze, and use disciplinary data (e.g., office discipline referrals) to inform decision-making. This presentation provides a brief overview of PBIS and reports findings from a series of four U.S. based longitudinal randomized controlled trials (RCTs) documenting the impacts of PBIS on school climate, discipline problems, bullying, and academic achievement. The four RCTs include 80 elementary, 40 middle, and 58 high schools and results indicate a broad range of impacts on multiple student and school-wide outcomes. The session will highlight lessons learned regarding PBIS implementation and scale-up. We also review the ways in which PBIS can help educators and school leaders engage in data-based decision-making and share data with other decision-makers and stakeholders (e.g., students, parents, community members), with the overarching goal of increasing use of evidence-based programs in schools.

Keywords: positive behavioral interventions and supports, mental health, randomized trials, school-based prevention

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Authors: Hiroaki Hirose, Hiroshi Ikeda, Isao Takeda

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The Japanese version of the SF-36 has been employed to assess individuals’ health-related QOL (HRQOL). This study aimed to clarify the HRQOL of motorists with a spinal cord injury, in order to compare these individuals' SF-36 scores and national standard values. A total of 100 motorists with a spinal cord injury participated in this study. Participants’ HRQOL was evaluated using the Japanese version of the SF-36 (second edition). The score for each subscale was standardized based on data on the Japanese population. The average scores for NPF, NRP, NBP, NGH, NVT, NSF, NRE, and NMH were 10.9, 41.8, 45.9, 47.1, 46.1, 46.7, 46.0, and 47.4 points, respectively. Subjects showed significantly lower scores for NPF and NRP compared with national standard values, which were both ≤ 45.0 points, but relatively normal scores for the other items: NBP, NGH, NVT, NSF, NRE and NMH (> 45.0 points). The average scores for PCS, MCS and RCS were 21.9, 56.0, and 50.0 points, respectively. Subjects showed a significantly lower PCS score (≤ 20.0 points); however, the MCS score was higher (> 55.0 points) along with a relatively normal RCS score in these individuals (= 50.0 points).

Keywords: health-related QOL, HRQOL, SF-36, motorist, spinal cord injury, Japan

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Authors: Fatima Sohail, Faizan Iftikhar

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This paper studies the relationship between digital finance, renewable energy, and the economic development of Pakistan and least developed countries from 2000 to 2022. The paper used panel analysis and generalized method of moments Arellano-Bond approaches. The findings show that under the growth model, renewable energy (RE) has a strong and favorable link with fixed broadband and mobile subscribers. However, FB and MD have a strong but negative association with the uptake of renewable energy (RE) in the average and simple model. This paper provides valuable insights for policymakers, investors of the digital economy.

Keywords: digital finance, renewable energy, economic development, mobile subscription, fixed broadband

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Authors: Farhad Alizadeh, Alireza Faregh Gharamaleki, Mojtaba Jalilzadeh, Houshang Gholami, Ali Akhoundzadeh

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This study presented hybrid pre-processing approach along with a conceptual model to enhance the accuracy of river discharge prediction. In order to achieve this goal, Ensemble Empirical Mode Decomposition algorithm (EEMD), Discrete Wavelet Transform (DWT) and Mutual Information (MI) were employed as a hybrid pre-processing approach conjugated to Least Square Support Vector Machine (LSSVM). A conceptual strategy namely multi-station model was developed to forecast the Souris River discharge more accurately. The strategy used herein was capable of covering uncertainties and complexities of river discharge modeling. DWT and EEMD was coupled, and the feature selection was performed for decomposed sub-series using MI to be employed in multi-station model. In the proposed feature selection method, some useless sub-series were omitted to achieve better performance. Results approved efficiency of the proposed DWT-EEMD-MI approach to improve accuracy of multi-station modeling strategies.

Keywords: river stage-discharge process, LSSVM, discrete wavelet transform, Ensemble Empirical Decomposition Mode, multi-station modeling

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Authors: Yemane Hailu Fissuh, Zhongzhan Zhang

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In biomedical researches and randomized clinical trials, the most commonly interested outcomes are time-to-event so-called survival data. The importance of robust models in this context is to compare the effect of randomly controlled experimental groups that have a sense of causality. Causal estimation is the scientific concept of comparing the pragmatic effect of treatments conditional to the given covariates rather than assessing the simple association of response and predictors. Hence, the causal effect based semiparametric transformation model was proposed to estimate the effect of treatment with the presence of possibly time-varying covariates. Due to its high flexibility and robustness, the semiparametric transformation model which shall be applied in this paper has been given much more attention for estimation of a causal effect in modeling left-truncated and right censored survival data. Despite its wide applications and popularity in estimating unknown parameters, the maximum likelihood estimation technique is quite complex and burdensome in estimating unknown parameters and unspecified transformation function in the presence of possibly time-varying covariates. Thus, to ease the complexity we proposed the modified estimating equations. After intuitive estimation procedures, the consistency and asymptotic properties of the estimators were derived and the characteristics of the estimators in the finite sample performance of the proposed model were illustrated via simulation studies and Stanford heart transplant real data example. To sum up the study, the bias of covariates was adjusted via estimating the density function for truncation variable which was also incorporated in the model as a covariate in order to relax the independence assumption of failure time and truncation time. Moreover, the expectation-maximization (EM) algorithm was described for the estimation of iterative unknown parameters and unspecified transformation function. In addition, the causal effect was derived by the ratio of the cumulative hazard function of active and passive experiments after adjusting for bias raised in the model due to the truncation variable.

Keywords: causal estimation, EM algorithm, semiparametric transformation models, time-to-event outcomes, time-varying covariate

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