Search results for: the health belief model

Authors: Bing-Fang Lee, Srinivasan Periasamy, Ming-Yie Liu

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Shift work sleep disorder is a common problem in industrialized world. It is a type of circadian rhythmic sleep disorders characterized by insomnia and sleep deprivation. Lack of sleep in workers may lead to poor health conditions such as hepatic dysfunction. Melatonin is a hormone secreted by the pineal gland to alleviate insomnia. Moreover, it is a powerful antioxidant and may prevent acute liver injury. Therefore, workers take in melatonin to deal with sleep-related health is an important issue. The aim of this study was to investigate the effect of melatonin on an acute hepatic injury model sinusoidal obstruction syndrome (SOS) in mice. Male C57BL/6 mice were injected with a single dose (500 mg/kg) of monocrotaline (MCT) to induce SOS. Melatonin (1, 3, 10 and 30 mg/kg) was injected 1 h before MCT treatment. After 24 h of MCT treatment, mice were sacrificed. The blood and liver were collected. Organ damage was evaluated by serum biochemistry, hematology analyzer, and histological examination. Low doses of melatonin (1 and 3 mg/kg) had no protective effect on SOS. However, high doses (10 and 30 mg/kg) exacerbated SOS. In addition, it not only increased serum glutamate oxaloacetate transaminase (GOT), glutamate pyruvate transaminase (GPT) and extended liver damage indicated by histological examination but also decreased platelet levels, lymphocyte ratio, and glutathione level; it had no effect on malondialdehyde and nitric oxide level in SOS mice. To conclude, melatonin may exacerbate MCT-induced SOS in mice. Furthermore, melatonin might have a synergistic action with SOS. Usage of melatonin for insomnia by people working in long shift must be cautioned; it might cause acute hepatic injury.

Keywords: acute liver injury, melatonin, shift work, sleep deprivation

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Authors: Marco Avila Lopez, Hasnae Ait-Douchi, Silvia De Los Santos, Badr Eddine Lebrouhi, Pamela Ramírez Vidal

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In the context of the energy transition, fuel cell technology has emerged as a solution for harnessing hydrogen energy and mitigating greenhouse gas emissions. An in-depth study was conducted on a PEMFC-type fuel cell, with an initiation of an analysis of its operational principles and constituent components. Subsequently, the modelling of the fuel cell was undertaken using the Python programming language, encompassing both steady-state and transient regimes. In the case of the steady-state regime, the physical and electrochemical phenomena occurring within the fuel cell were modelled, with the assumption of uniform temperature throughout all cell compartments. Parametric identification was carried out, resulting in a remarkable mean error of only 1.62% when the model results were compared to experimental data documented in the literature. The dynamic model that was developed enabled the scrutiny of the fuel cell's response in terms of temperature and voltage under varying current conditions.

Keywords: fuel cell, modelling, dynamic, thermal model, PEMFC

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Authors: Francesco Marotti de Sciarra, Raffaele Barretta

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Starting from nonlocal continuum mechanics, a thermodynamically new nonlocal model of Euler-Bernoulli nanobeams is provided. The nonlocal variational formulation is consistently provided and the governing differential equation for transverse displacement are presented. Higher-order boundary conditions are then consistently derived. An example is contributed in order to show the effectiveness of the proposed model.

Keywords: Bernoulli-Euler beams, nanobeams, nonlocal elasticity, closed-form solutions

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Authors: Kathaleeya Chanda, Panupong Chanplin, Suppara Charoenpoom

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This purposes of the development of creative instruction model through digital media are to: 1) enable learners to learn from instruction media application; 2) help learners implementing instruction media correctly and appropriately; and 3) facilitate learners to apply technology for searching information and practicing skills to implement technology creatively. The sample group consists of 130 cases of secondary students studying in Bo Kluea School, Bo Kluea Nuea Sub-district, Bo Kluea District, Nan Province. The probability sampling was selected through the simple random sampling and the statistics used in this research are percentage, mean, standard deviation and one group pretest – posttest design. The findings are summarized as follows: The congruence index of instruction media for occupation and technology subjects is appropriate. By comparing between learning achievements before implementing the instruction media and learning achievements after implementing the instruction media, it is found that the posttest achievements are higher than the pretest achievements with statistical significance at the level of .05. For the learning achievements from instruction media implementation, pretest mean is 16.24 while posttest mean is 26.28. Besides, pretest and posttest results are compared and differences of mean are tested, the test results show that the posttest achievements are higher than the pretest achievements with statistical significance at the level of .05. This can be interpreted that the learners achieve better learning progress.

Keywords: teaching learning model, digital media, creative instruction model, Bo Kluea school

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Authors: Hsiang-Yu Yuan, Marc Baguelin, Kin O. Kwok, Nimalan Arinaminpathy, Edwin Leeuwen, Steven Riley

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Traditional syndromic surveillance for influenza has substantial public health value in characterizing epidemics. Because the relationship between syndromic incidence and the true infection events can vary from one population to another and from one year to another, recent studies rely on combining serological test results with syndromic data from traditional surveillance into epidemic models to make inference on epidemiological processes of influenza. However, despite the widespread availability of serological data, epidemic models have thus far not explicitly represented antibody titre levels and their correspondence with immunity. Most studies use dichotomized data with a threshold (Typically, a titre of 1:40 was used) to define individuals as likely recently infected and likely immune and further estimate the cumulative incidence. Underestimation of Influenza attack rate could be resulted from the dichotomized data. In order to improve the use of serosurveillance data, here, a refinement of the concept of the stratified immunity within an epidemic model for influenza transmission was proposed, such that all individual antibody titre levels were enumerated explicitly and mapped onto a variable scale of susceptibility in different age groups. Haemagglutination inhibition titres from 523 individuals and 465 individuals during pre- and post-pandemic phase of the 2009 pandemic in Hong Kong were collected. The model was fitted to serological data in age-structured population using Bayesian framework and was able to reproduce key features of the epidemics. The effects of age-specific antibody boosting and protection were explored in greater detail. RB was defined to be the effective reproductive number in the presence of stratified immunity and its temporal dynamics was compared to the traditional epidemic model using use dichotomized seropositivity data. Deviance Information Criterion (DIC) was used to measure the fitness of the model to serological data with different mechanisms of the serological response. The results demonstrated that the differential antibody response with age was present (ΔDIC = -7.0). The age-specific mixing patterns with children specific transmissibility, rather than pre-existing immunity, was most likely to explain the high serological attack rates in children and low serological attack rates in elderly (ΔDIC = -38.5). Our results suggested that the disease dynamics and herd immunity of a population could be described more accurately for influenza when the distribution of immunity was explicitly represented, rather than relying only on the dichotomous states 'susceptible' and 'immune' defined by the threshold titre (1:40) (ΔDIC = -11.5). During the outbreak, RB declined slowly from 1.22[1.16-1.28] in the first four months after 1st May. RB dropped rapidly below to 1 during September and October, which was consistent to the observed epidemic peak time in the late September. One of the most important challenges for infectious disease control is to monitor disease transmissibility in real time with statistics such as the effective reproduction number. Once early estimates of antibody boosting and protection are obtained, disease dynamics can be reconstructed, which are valuable for infectious disease prevention and control.

Keywords: effective reproductive number, epidemic model, influenza epidemic dynamics, stratified immunity

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Authors: Tsega Asresa Mengistu, Getahun Tigistu

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Computer vision is an artificial intelligence subfield that allows computers and systems to retrieve meaning from digital images. It is applied in various fields of study self-driving cars, video surveillance, agriculture, Quality control, Health care, construction, military, and everyday life. Aromatic and medicinal plants are botanical raw materials used in cosmetics, medicines, health foods, and other natural health products for therapeutic and Aromatic culinary purposes. Herbal industries depend on these special plants. These plants and their products not only serve as a valuable source of income for farmers and entrepreneurs, and going to export not only industrial raw materials but also valuable foreign exchange. There is a lack of technologies for the classification and identification of Aromatic and medicinal plants in Ethiopia. The manual identification system of plants is a tedious, time-consuming, labor, and lengthy process. For farmers, industry personnel, academics, and pharmacists, it is still difficult to identify parts and usage of plants before ingredient extraction. In order to solve this problem, the researcher uses a deep learning approach for the efficient identification of aromatic and medicinal plants by using a convolutional neural network. The objective of the proposed study is to identify the aromatic and medicinal plant Parts and usages using computer vision technology. Therefore, this research initiated a model for the automatic classification of aromatic and medicinal plants by exploring computer vision technology. Morphological characteristics are still the most important tools for the identification of plants. Leaves are the most widely used parts of plants besides the root, flower and fruit, latex, and barks. The study was conducted on aromatic and medicinal plants available in the Ethiopian Institute of Agricultural Research center. An experimental research design is proposed for this study. This is conducted in Convolutional neural networks and Transfer learning. The Researcher employs sigmoid Activation as the last layer and Rectifier liner unit in the hidden layers. Finally, the researcher got a classification accuracy of 66.4 in convolutional neural networks and 67.3 in mobile networks, and 64 in the Visual Geometry Group.

Keywords: aromatic and medicinal plants, computer vision, deep convolutional neural network

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Authors: J.P. Henriques, E. R. Neto, G. Almeida, G. Ribeiro, J.V. Coutinho, A.B. Lugli

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Industry 4.0, or the Fourth Industrial Revolution, is transforming the relationship between people and machines. In this scenario, some technologies such as Cloud Computing, Internet of Things, Augmented Reality, Artificial Intelligence, Additive Manufacturing, among others, are making industries and devices increasingly intelligent. One of the most powerful technologies of this new revolution is the Digital Twin, which allows the virtualization of a real system or process. In this context, the present paper addresses the linear and nonlinear dynamic study of a didactic level plant using Digital Twin. In the first part of the work, the level plant is identified at a fixed point of operation, BY using the existing method of least squares means. The linearized model is embedded in a Digital Twin using Automation Studio® from Famous Technologies. Finally, in order to validate the usage of the Digital Twin in the linearized study of the plant, the dynamic response of the real system is compared to the Digital Twin. Furthermore, in order to develop the nonlinear model on a Digital Twin, the didactic level plant is identified by using the method proposed by Hammerstein. Different steps are applied to the plant, and from the Hammerstein algorithm, the nonlinear model is obtained for all operating ranges of the plant. As for the linear approach, the nonlinear model is embedded in the Digital Twin, and the dynamic response is compared to the real system in different points of operation. Finally, yet importantly, from the practical results obtained, one can conclude that the usage of Digital Twin to study the dynamic systems is extremely useful in the industrial environment, taking into account that it is possible to develop and tune controllers BY using the virtual model of the real systems.

Keywords: industry 4.0, digital twin, system identification, linear and nonlinear models

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Authors: Burak Oksuzoglu, Savas Yildirim, Ferhat Kutlu

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Opinion mining (OM) is one of the natural language processing (NLP) problems to determine the polarity of opinions, mostly represented on a positive-neutral-negative axis. The data for OM is usually collected from various social media platforms. In an era where social media has considerable control over companies’ futures, it’s worth understanding social media and taking actions accordingly. OM comes to the fore here as the scale of the discussion about companies increases, and it becomes unfeasible to gauge opinion on individual levels. Thus, the companies opt to automize this process by applying machine learning (ML) approaches to their data. For the last two decades, OM or sentiment analysis (SA) has been mainly performed by applying ML classification algorithms such as support vector machines (SVM) and Naïve Bayes to a bag of n-gram representations of textual data. With the advent of deep learning and its apparent success in NLP, traditional methods have become obsolete. Transfer learning paradigm that has been commonly used in computer vision (CV) problems started to shape NLP approaches and language models (LM) lately. This gave a sudden rise to the usage of the pretrained language model (PTM), which contains language representations that are obtained by training it on the large datasets using self-supervised learning objectives. The PTMs are further fine-tuned by a specialized downstream task dataset to produce efficient models for various NLP tasks such as OM, NER (Named-Entity Recognition), Question Answering (QA), and so forth. In this study, the traditional and modern NLP approaches have been evaluated for OM by using a sizable corpus belonging to a large private company containing about 76,000 comments in Turkish: SVM with a bag of n-grams, and two chosen pre-trained models, multilingual universal sentence encoder (MUSE) and bidirectional encoder representations from transformers (BERT). The MUSE model is a multilingual model that supports 16 languages, including Turkish, and it is based on convolutional neural networks. The BERT is a monolingual model in our case and transformers-based neural networks. It uses a masked language model and next sentence prediction tasks that allow the bidirectional training of the transformers. During the training phase of the architecture, pre-processing operations such as morphological parsing, stemming, and spelling correction was not used since the experiments showed that their contribution to the model performance was found insignificant even though Turkish is a highly agglutinative and inflective language. The results show that usage of deep learning methods with pre-trained models and fine-tuning achieve about 11% improvement over SVM for OM. The BERT model achieved around 94% prediction accuracy while the MUSE model achieved around 88% and SVM did around 83%. The MUSE multilingual model shows better results than SVM, but it still performs worse than the monolingual BERT model.

Keywords: BERT, MUSE, opinion mining, pretrained language model, SVM, Turkish

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Authors: Harish Rajak, Swati Singh

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A series of novel pyrimidine based semicarbazone were designed and synthesized on the basis of semicarbazone based pharmacophoric model to satisfy the structural prerequisite crucial for antiepileptic activity. The semicarbazones based pharmacophoric model consists of following four essential binding sites: (i) An aryl hydrophobic binding site with halo substituent; (ii) A hydrogen bonding domain; (iii) An electron donor group and (iv) Another hydrophobic-hydrophilic site controlling the pharmacokinetic features of the anticonvulsant. The aryl semicarbazones has been recognized as a structurally novel class of compounds with remarkable anticonvulsant activity. In the present study, all the test semicarbazones were subjected to molecular docking using Glide v5.8. Some of the compounds were found to interact with ARG192, GLU270 and THR353 residues of 1OHV protein, present in GABA-AT receptor. The chemical structures of the synthesized molecules were characterized by elemental and spectral (IR, 1H NMR, 13C NMR and MS) analysis. The anticonvulsant activities of the compounds were investigated using maximal electroshock seizure (MES) and subcutaneous pentylenetrtrazole (scPTZ) models. The neurotoxicity was evaluated in mice by the rotorod test. The attempts were also made to establish structure-activity relationships among synthesized compounds. The results of the present study confirmed that the pharmacophore model with four binding sites is essential for antiepileptic activity.

Keywords: pyrimidine, semicarbazones, anticonvulsant activity, neurotoxicity

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Authors: Ajay Kumar Yadav, Masum Paudel, Ritesh Chaudhary

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Background: Understanding the diagnosis and the treatment plan is very important for the patient which reflects the effectiveness of the patient care as well as counseling. Large groups of patients do not understand their emergency care plan or their discharge instructions. With only a little more than 2/3ʳᵈ of the adult population is literate and poorly distributed health service institutions in Nepal, exploring the current status of patient understanding of their diagnosis and treatment would help identify interventions to improve patient compliance with the provided care and the treatment outcomes. Objectives: This study was conducted to identify and describe the areas of patients’ understanding and confusion regarding emergency care and discharge instructions at the Emergency ward of B. P. Koirala Institute of Health Sciences teaching hospital, Dharan, Nepal. Methods: A cross-sectional study was conducted among 426 patients discharged from the emergency unit of BPKIHS. Cases who are leaving against medical advice absconded cases and those patients who came just for vaccination are excluded from the study. Patients’ understanding of the treatment plan and diagnosis was measured. Results: There were 60% men in this study. More than half of the participants reported not being able to read English. More than 90% of the respondents reported they could not read their prescription at all. While patient could point out their understanding of their diagnosis at discharge, most of them could not tell the names and the dosage of all the drugs prescribed to them at discharge. More than 95% of the patients could not tell the most common side effects of the drugs that they are prescribed. Conclusions: There is a need to further explore the factors influencing the understanding of the patients regarding their treatment plan. Interventions to understand the health literacy needs and ways to improve the health literacy of the patients are needed.

Keywords: discharge instruction, emergency ward, health literacy, treatment plan

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Authors: M. Bouzid, A. Djadi, C. Aribi, A. Irekti, B. Bezzazi, F. Halouene

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The nature of materials structuring our health institutions promote the development of germs. The sustainability of nosocomial infections remains significant (12% and 15%). One of the major factors is the portland cement which is brittle and porous. As part of a national plan to fight nosocomial infections, led by the University Hospital of Blida, we opted for a composite coating, application by multilayer model, composed of epoxy-polyester resin as a binder and calcium carbonate as mineral fillers. The application of composite materials reinforce the wall coating of hospital units and eliminates the hospital infectious areas. The resistance to impact, chemicals, raising temperature and to a biologically active environment gives satisfactory results.

Keywords: nosocomial infection, microbial load, composite materials, portland cement

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Authors: Njoroge Margaret W., Johnson Deborah

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Gender-specific risk factors for common mental disorders that disproportionately affect women include but are not limited to gender-based violence, socioeconomic disadvantage, sociocultural factors and unrelenting responsibility for the care of others. The overall objective of this study was to assess mental health conditions and their risk factors among women in Garissa County, Kenya. The study adopted both quantitative and qualitative research designs. The study participants were 100 adult women and 20 key informants from different sectors in the region. Data was collected using DSM-5 (PCL-5) and Kessler Psychological Distress, interviews schedule and focus group discussions. Analysis of quantitative data was done using univariate analysis, while qualitative data was analyzed using thematic analysis. The results revealed that about 60% of women presented with moderate to severe psychological distress (PD), while 53% presented with PTSD. Additionally, women who have undergone female genital mutilation had higher PTSD and PD scores. They also presented with low self-esteem, depressive symptoms, sex anxiety, avoidance of reminders and intrusive memories of the event, especially those who developed fistula. The risk factors for poor mental health outcomes include lack of awareness/knowledge of mental health, retrogressive cultural practices (child marriage and female genital mutilation), as well as beliefs about the causes of mental disorders. The study also established that people with mental illness are neglected, abused and stigmatized. Preferred treatment approaches include prayers and the use of witch doctors and traditional healers. The study recommends gendered and culturally responsive interventions geared towards increasing community awareness and knowledge on mental health, reducing stigma and improving mental-health-seeking behaviors for women and girls in the region. Supported by the Ministry of Health, the approach should be spearheaded by trained community lay counselors.

Keywords: women, mental health conditions, cultural beliefs/practices, stigma, poverty, psychological distress, PTSD

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Authors: Yaru Meng

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The study contributes to the small but growing literature around computerized approaches to dynamic assessment (C-DA), wherein individual items are accompanied by mediating prompts. Mediation in the current computerized dynamic listening assessment (CDLA) was informed by an attribute-based mediation model (AMM) that identified the underlying L2 listening cognitive abilities and associated descriptors. The AMM served to focus mediation during C-DA on particular cognitive abilities with a goal of specifying areas of learner difficulty. 86 low-intermediate L2 English learners from a university in China completed three listening assessments, with an experimental group receiving the CLDA system and a control group a non-dynamic assessment. As an assessment, the use of the AMM in C-DA generated detailed diagnoses for each learner. In addition, both within- and between-group repeated ANOVA found greater gains at the level of specific attributes among C-DA learners over the course of a 5-week study. Directions for future research are discussed.

Keywords: computerized dynamic assessment, effectiveness, English as foreign language listening, attribute-based mediation model

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Authors: Jonah Kenei, Elisha Opiyo

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Electronic health records, as a repository of patient information, is nowadays the most commonly used technology to record, store and review patient clinical records and perform other clinical tasks. However, the accurate identification and retrieval of relevant information from clinical records is a difficult task due to the unstructured nature of clinical documents, characterized in particular by a lack of clear structure. Therefore, medical practice is facing a challenge thanks to the rapid growth of health information in electronic health records (EHRs), mostly in narrative text form. As a result, it's becoming important to effectively manage the growing amount of data for a single patient. As a result, there is currently a requirement to visualize electronic health records (EHRs) in a way that aids physicians in clinical tasks and medical decision-making. Leveraging text visualization techniques to unstructured clinical narrative texts is a new area of research that aims to provide better information extraction and retrieval to support clinical decision support in scenarios where data generated continues to grow. Clinical datasets in electronic health records (EHR) offer a lot of potential for training accurate statistical models to classify facets of information which can then be used to improve patient care and outcomes. However, in many clinical note datasets, the unstructured nature of clinical texts is a common problem. This paper examines the very issue of getting raw clinical texts and mapping them into meaningful structures that can support healthcare professionals utilizing narrative texts. Our work is the result of a collaborative design process that was aided by empirical data collected through formal usability testing.

Keywords: classification, electronic health records, narrative texts, visualization

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Authors: Subham Ghosh, Arnab Nandi

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Background: The proliferation of Wireless Body Area Networks (WBAN) and Internet of Things (IoT) applications demonstrates the potential for continuous monitoring of physical changes in the body. These technologies are vital for health monitoring tasks, such as identifying coughing and breathing activities, which are necessary for disease diagnosis and management. Monitoring activities such as coughing and deep breathing can provide valuable insights into a variety of medical issues. Wearable radio-based antenna sensors, which are lightweight and easy to incorporate into clothing or portable goods, provide continuous monitoring. This mobility gives it a substantial advantage over stationary environmental sensors like as cameras and radar, which are constrained to certain places. Furthermore, using compressive techniques provides benefits such as reduced data transmission speeds and memory needs. These wearable sensors offer more advanced and diverse health monitoring capabilities. Methodology: This study analyzes the feasibility of using a semi-flexible antenna operating at 2.4 GHz (ISM band) and positioned around the neck and near the mouth to identify three activities: coughing, deep breathing, and idleness. Vector network analyzer (VNA) is used to collect time-varying complex reflection coefficient data from perturbed antenna nearfield. The reflection coefficient (S11) conveys nuanced information caused by simultaneous variations in the nearfield radiation of three activities across time. The signatures are sparsely represented with gaussian windowed Gabor spectrograms. The Gabor spectrogram is used as a sparse representation approach, which reassigns the ridges of the spectrogram images to improve their resolution and focus on essential components. The antenna is biocompatible in terms of specific absorption rate (SAR). The sparsely represented Gabor spectrogram pictures are fed into a lightweight deep learning (DL) model for feature extraction and classification. Two antenna locations are investigated in order to determine the most effective localization for three different activities. Findings: Cross-validation techniques were used on data from both locations. Due to the complex form of the recorded S11, separate analyzes and assessments were performed on the magnitude, phase, and their combination. The combination of magnitude and phase fared better than the separate analyses. Various sliding window sizes, ranging from 1 to 5 seconds, were tested to find the best window for activity classification. It was discovered that a neck-mounted design was effective at detecting the three unique behaviors.

Keywords: activity recognition, antenna, deep-learning, time-frequency

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Authors: Festus Adedoyin, Nana Mbeah Otoo, Sofia Meacham

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Hypertension is one of the main health issues in Ghana, where prevalence is higher in rural than in urban areas. This is due to the challenges rural areas have in accessing technology and healthcare services for hypertension control. This study's goal is to create a digital healthcare solution to alleviate this inequality. Through an analysis of current technology and problems, using the ring onion methodology, the study determined the needs for the intervention and evaluated healthcare disparities. An online application with teleconsultation capabilities, reminder mechanisms, and clinical decision support is part of the suggested solution. In outlying areas, mobile clinics in containers with the required equipment will be established. Heuristic evaluation and think-aloud sessions were used to assess the prototype's usability and navigational problems. This study highlights the need to develop digital health interventions to help manage hypertension in rural locations and decrease healthcare disparities. To develop and improve digital healthcare solutions for rural areas worldwide and in Ghana, this study might be used as a tool for future research.

Keywords: digital health, health inequalities, hypertension management, rural areas

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Authors: Zhi-Zhong Chen, Jun-Hao Lu, Jr., Shih-Ying Chueh

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Based on Unified Theory of Acceptance and Use of Technology (UTAUT), the study investigates people’s intention on using smart phones. The study additionally incorporates two new variables: 'self-efficacy' and 'attitude toward using'. Samples are collected by questionnaire survey, in which 240 are valid. After Correlation Analysis, Reliability Test, ANOVA, t-test and Multiple Regression Analysis, the study finds that social impact and self-efficacy have positive effect on use intentions, and the use intentions also have positive effect on use behavior.

Keywords: [1] Ajzen & Fishbein (1975), “Belief, attitude, intention and behavior: An introduction to theory and research”, Reading MA: Addison-Wesley. [2] Bandura (1977) Self-efficacy: toward a unifying theory of behavioural change. Psychological Review , 84, 191–215. [3] Bandura( 1986) A. Bandura, Social foundations of though and action, Prentice-Hall. Englewood Cliffs. [4] Ching-Hui Huang (2005). The effect of Regular Exercise on Elderly Optimism: The Self-efficacy and Theory of Reasoned Action Perspectives.(Master's dissertation, National Taiwan Sport University, 2005).National Digital Library of Theses and Dissertations in Taiwan。 [5] Chun-Mo Wu (2007).The Effects of Perceived Risk and Service Quality on Purchase Intention - an Example of Taipei City Long-Term Care Facilities. (Master's dissertation, Ming Chuan University, 2007).National Digital Library of Theses and Dissertations in Taiwan. [6] Compeau, D.R., and Higgins, C.A., (1995) “Application of social cognitive theory to training for computer skills.”, Information Systems Research, 6(2), pp.118-143. [7] computer-self-efficacy and mediators of the efficacy-performance relationship. International Journal of Human-Computer Studies, 62, 737-758. [8] Davis et al(1989), “User acceptance of computer technology: A comparison of two theoretical models ”, Management Science, 35(8), p.982-1003. [9] Davis et al(1989), “User acceptance of computer technology:A comparison of two theoretical models ”, Management Science, 35(8), p.982-1003. [10] Davis, F.D. (1989). Perceived Usefulness, Perceived Ease of Use and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319-340。 [11] Davis. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319–340. doi:10.2307/249008 [12] Johnson, R. D. (2005). An empirical investigation of sources of application-specific [13] Mei-yin Hsu (2010).The Study on Attitude and Satisfaction of Electronic Documents System for Administrators of Elementary Schools in Changhua County.(Master's dissertation , Feng Chia University, 2010).National Digital Library of Theses and Dissertations in Taiwan. [14] Ming-Chun Hsieh (2010). Research on Parents’ Attitudes Toward Electronic Toys： The case of Taichung City.(Master's dissertation, Chaoyang University of Technology，2010).National Digital Library of Theses and Dissertations in Taiwan. [15] Moon and Kim（2001）. Extending the TAM for a World-Wide-Web context, Information and Management, v.38 n.4, p.217-230. [16] Shang-Yi Hu (2010).The Impacts of Knowledge Management on Customer Relationship Management – Enterprise Characteristicsand Corporate Governance as a Moderator.(Master's dissertation, Leader University, 2010)。National Digital Library of Theses and Dissertations in Taiwan. [17] Sheng-Yi Hung (2013, September10).Worldwide sale of smartphones to hit one billion IDC：Android dominate the market. ETtoday. Retrieved data form the available protocol:2013/10/3. [18] Thompson, R.L., Higgins, C.A., and Howell, J.M.(1991), “Personal Computing: Toward a Conceptual Model of Utilization”, MIS Quarterly(15:1), pp. 125-143. [19] Venkatesh, V., M.G. Morris, G.B. Davis, and F. D. Davis (2003), “User acceptance of information technology: Toward a unified view, ” MIS Quarterly, 27, No. 3, pp.425-478. [20] Vijayasarathy, L. R. (2004), Predicting Consumer Intentions to Use On-Line Shopping： The Case for an Augmented Technology Acceptance Model, Information and Management, Vol.41, No.6, pp.747-762. [21] Wikipedia - smartphone (http://zh.wikipedia.org/zh-tw/%E6%99%BA%E8%83%BD%E6%89%8B%E6%9C%BA)。 [22] Wu-Minsan (2008).The impacts of self-efficacy, social support on work adjustment with hearing impaired. (Master's dissertation, Southern Taiwan University of Science and Technology, 2008).National Digital Library of Theses and Dissertations in Taiwan. [23] Yu-min Lin (2006). The Influence of Business Employee’s MSN Self-efficacy On Instant Messaging Usage Behavior and Communicaiton Satisfaction.(Master's dissertation, National Taiwan University of Science and Technology, 2006).National Digital Library of Theses and Dissertations in Taiwan.

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Authors: F. Jiménez, R. Jódar, M. Martín, G. Sánchez, G. Sciavicco

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Abstract—Attribute or feature selection is one of the basic strategies to improve the performances of data classification tasks, and, at the same time, to reduce the complexity of classifiers, and it is a particularly fundamental one when the number of attributes is relatively high. Its application to unsupervised classification is restricted to a limited number of experiments in the literature. Evolutionary computation has already proven itself to be a very effective choice to consistently reduce the number of attributes towards a better classification rate and a simpler semantic interpretation of the inferred classifiers. We present a feature selection wrapper model composed by a multi-objective evolutionary algorithm, the clustering method Expectation-Maximization (EM), and the classifier C4.5 for the unsupervised classification of data extracted from a psychological test named BASC-II (Behavior Assessment System for Children - II ed.) with two objectives: Maximizing the likelihood of the clustering model and maximizing the accuracy of the obtained classifier. We present a methodology to integrate feature selection for unsupervised classification, model evaluation, decision making (to choose the most satisfactory model according to a a posteriori process in a multi-objective context), and testing. We compare the performance of the classifier obtained by the multi-objective evolutionary algorithms ENORA and NSGA-II, and the best solution is then validated by the psychologists that collected the data.

Keywords: evolutionary computation, feature selection, classification, clustering

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Authors: Haseen Siddiqui, Sanjay M. Mahajani

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Various important reactions in chemical and metallurgical industries fall in the category of gas-solid reactions. These reactions can be categorized as catalytic and non-catalytic gas-solid reactions. In gas-solid reaction systems, heat and mass transfer limitations put an appreciable influence on the rate of the reaction. The consequences can be unavoidable for overlooking such effects while collecting the reaction rate data for the design of the reactor. Pyrolysis reaction comes in this category that involves the production of gases due to the interaction of heat and solid substance. Pyrolysis is also an important step in the gasification process and therefore, the gasification reactivity majorly influenced by the pyrolysis process that produces the char, as a feed for the gasification process. Therefore, in the present study, a non-isothermal transient 1-D model is developed for a single biomass pellet to investigate the effect of heat and mass transfer limitations on the rate of pyrolysis reaction. The obtained set of partial differential equations are firstly discretized using the concept of ‘method of lines’ to obtain a set of ordinary differential equation with respect to time. These equations are solved, then, using MATLAB ode solver ode15s. The model is capable of incorporating structural changes, porosity variation, variation in various thermal properties and various pellet shapes. The model is used to analyze the effectiveness factor for different values of Lewis number and heat of reaction (G factor). Lewis number includes the effect of thermal conductivity of the solid pellet. Higher the Lewis number, the higher will be the thermal conductivity of the solid. The effectiveness factor was found to be decreasing with decreasing Lewis number due to the fact that smaller Lewis numbers retard the rate of heat transfer inside the pellet owing to a lower rate of pyrolysis reaction. G factor includes the effect of the heat of reaction. Since the pyrolysis reaction is endothermic in nature, the G factor takes negative values. The more the negative value higher will be endothermic nature of the pyrolysis reaction. The effectiveness factor was found to be decreasing with more negative values of the G factor. This behavior can be attributed to the fact that more negative value of G factor would result in more energy consumption by the reaction owing to a larger temperature gradient inside the pellet. Further, the analytical expressions are also derived for gas and solid concentrations and effectiveness factor for two limiting cases of the general model developed. The two limiting cases of the model are categorized as the homogeneous model and unreacted shrinking core model.

Keywords: effectiveness factor, G-factor, homogeneous model, lewis number, non-catalytic, shrinking core model

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Authors: Halkiopoulos Constantinos, Koutsopoulou Ioanna, Gkintoni Evgenia, Antonopoulou Hera

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Immunization appears to be an essential part of health care service in times of pandemics such as covid-19 and aims not only to protect the health of the population but also the health and sustainability of the economies of the countries affected. It is reported that more than 3.44 billion doses have been administered so far, which accounts for 45 doses for 100 people. Vaccination programs in various countries have been promoted and accepted by people differently and therefore they proceeded in different ways and speed; most countries directing them towards people with vulnerable chronic or recent health statuses. Large scale restriction measures or lockdown, personal protection measures such as masks and gloves and a decrease in leisure and sports activities were also implemented around the world as part of the protection health strategies against the covid-19 pandemic. This research aims to present an analysis based on variations on people’s attitudes towards vaccination based on demographic, social and epidemiological characteristics, and health status on the one hand and perception of health, health satisfaction, pain, and quality of life on the other hand. 1500 Greek e-consumers participated in the research, mainly through social media who took part in an online-based survey voluntarily. The questionnaires included demographic, social and medical characteristics of the participants, and questions asking people’s willingness to be vaccinated and their opinion on whether there should be a vaccine against covid-19. Other stressor factors were also reported in the questionnaires and participants’ loss of someone close due to covid-19, or staying at home quarantine due to being infected from covid-19. WHOQUOL-BREF and GLOBAL PSYCHOTRAUMA SCREEN- GPS were used with kind permission from WHO and from the International Society for Traumatic Stress Studies in this study. Attitudes towards vaccination varied significantly related to aging, level of education, health status and consumer behavior. Health professionals’ attitudes also varied in relation to age, level of education, profession, health status and consumer needs. Vaccines have been the most common technological aid of human civilization so far in the fight against viruses. The results of this study can be used for health managers and digital marketers of pharmaceutical companies and also other staff involved in vaccination programs and for designing health policy immunization strategies during pandemics in order to achieve positive attitudes towards vaccination and larger populations being vaccinated in shorter periods of time after the break out of pandemic. Health staff needs to be trained, aided and supervised to go through with vaccination programs and to be protected through vaccination programs themselves. Feedback in each country’s vaccination program, short backs, deficiencies and delays should be addressed and worked out.

Keywords: consumer behavior, cognitive models, vaccination policy, pandemic, Covid-19, Greece

Procedia PDF Downloads 185

Authors: Sreejith Jayachandran, Mojtaba Ghods, Morteza Mohammadzaheri

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The modern busy world is running behind new embedded technologies based on computers and software; meanwhile, some people forget to do their health condition and regular medical check-ups. Some of them postpone medical check-ups due to a lack of time and convenience, while others skip these regular evaluations and medical examinations due to huge medical bills and hospital expenses. Engineers and medical experts have come together to give birth to a new device in the telemonitoring system capable of monitoring, checking, and evaluating the health status of the human body remotely through the internet for the needs of all kinds of people. The remote health monitoring device is a microcontroller-based embedded unit. Various types of sensors in this device are connected to the human body, and with the help of an Arduino UNO board, the required analogue data is collected from the sensors. The microcontroller on the Arduino board processes the analogue data collected in this way into digital data and transfers that information to the cloud, and stores it there, and the processed digital data is instantly displayed through the LCD attached to the machine. By accessing the cloud storage with a username and password, the concerned person’s health care teams/doctors and other health staff can collect this data for the assessment and follow-up of that patient. Besides that, the family members/guardians can use and evaluate this data for awareness of the patient's current health status. Moreover, the system is connected to a Global Positioning System (GPS) module. In emergencies, the concerned team can position the patient or the person with this device. The setup continuously evaluates and transfers the data to the cloud, and also the user can prefix a normal value range for the evaluation. For example, the blood pressure normal value is universally prefixed between 80/120 mmHg. Similarly, the RHMS is also allowed to fix the range of values referred to as normal coefficients. This IoT-based miniature system (11×10×10) cm³ with a low weight of 500 gr only consumes 10 mW. This smart monitoring system is manufactured with 100 GBP, which can be used not only for health systems, it can be used for numerous other uses including aerospace and transportation sections.

Keywords: embedded technology, telemonitoring system, microcontroller, Arduino UNO, cloud storage, global positioning system, remote health monitoring system, alert system

Procedia PDF Downloads 90

Authors: Mimi My Tse

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The prevalence of chronic non-cancer pain is high among community-dwelling older adults. Pain affects physical and psychosocial abilities. Older adults tend to be less mobile and have a high tendency to fall risk. In addition, older adults with pain are depressed, anxious, and not too willing to join social activities. This will make them feel very lonely and social isolation. Instead of giving pain management education and programs to older adults/clients, both older adults and their caregivers, it is sad to find that the majority of existing services are given to older adults only. Given the importance of family members in increasing compliance with health-promoting programs, we proposed to offer pain management programs to both older adults with his/her caregiver as a “dyad.” We used the Health Promotion Model and implemented a dyadic pain management program (DPM). The DPM is an 8-week group-based program. The DPM comprises 4 weeks of center-based, face-to-face activities and 4 weeks of digital-based activities delivered via a WhatsApp group. There were 30 dyads (15 in the experimental group with DPM and 15 in the control group with pain education pamphlets). Upon the completion of DPM, pain intensity and pain interference were significantly lower in the intervention group as compared to the control group. At the same time, physical function showed significant improvement and lower depression scores in the intervention group. In conclusion, the study highlights the potential benefits of involving caregivers in the management of chronic pain for older adults. This approach should be widely promoted in managing chronic pain situations for community-dwelling older adults and their caregivers.

Keywords: pain, older adults, dyadic approach, education

Procedia PDF Downloads 78

Authors: Harish Rajak, Preeti Patel

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HDAC inhibitors can reactivate gene expression and inhibit the growth and survival of cancer cells. The 3D-QSAR and Pharmacophore modeling studies were performed to identify important pharmacophoric features and correlate 3D-chemical structure with biological activity. The pharmacophore hypotheses were developed using e-pharmacophore script and phase module. Pharmacophore hypothesis represents the 3D arrangement of molecular features necessary for activity. A series of 55 compounds with well-assigned HDAC inhibitory activity was used for 3D-QSAR model development. Best 3D-QSAR model, which is a five PLS factor model with good statistics and predictive ability, acquired Q2 (0.7293), R2 (0.9811) and standard deviation (0.0952). Molecular docking were performed using Histone Deacetylase protein (PDB ID: 1t69) and prepared series of hydroxamic acid based HDAC inhibitors. Docking study of compound 43 show significant binding interactions Ser 276 and oxygen atom of dioxine cap region, Gly 151 and amino group and Asp 267 with carboxyl group of CONHOH, which are essential for anticancer activity. On docking, most of the compounds exhibited better glide score values between -8 to -10.5. We have established structure activity correlation using docking, energetic based pharmacophore modelling, pharmacophore and atom based 3D QSAR model. The results of these studies were further used for the design and testing of new HDAC analogs.

Keywords: Docking, e-pharmacophore, HDACIs, QSAR, Suberoylanilidehydroxamic acid.

Procedia PDF Downloads 301

Authors: Carla Nardelli, Jérome Holtzmann, Céline Baeyens, Catherine Bortolon

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Background. Emotion regulation (ER) is a process associated with difficulties in mental health. Given its transdiagnostic features, its improvement could facilitate the recovery of various psychological issues. A limit of current studies is the lack of knowledge regarding whether available interventionsimprove ER flexibility (i.e., the ability to implement ER strategies in line with contextual demands), even though this capacity has been associated with better mental health and well-being. Therefore, the aim of the study is to test the efficacy of a 9-weeks ER group program (the Affect Regulation Training-ART), using the most appropriate measures (i.e., experience sampling method) in a student population. Plus, the goal of the study is to explore the potential mediative role of ER flexibility on mental health improvement. Method. This Randomized Controlled Trial will comparethe ER program group to an active control group (a relaxation program) in 100 participants. To test the mediative role of ER flexibility on mental health, daily measures will be used before, during, and after the interventions to evaluate the extent to which participants are flexible in their ER. Expected outcomes. Using multilevel analyses, we expect an improvement in anxious-depressive symptomatology for both groups. However, we expect the ART group to improve specifically on ER flexibility ability and the last to be a mediative variable on mental health. Conclusion. This study will enhance knowledge on interventions for students and the impact of interventions on ER flexibility. Also, this research will improve knowledge on ecological measures for assessing the effect of interventions. Overall, this project represents new opportunities to improve ER skills to improve mental health in undergraduate students.

Keywords: emotion regulation flexibility, experience sampling method, psychological intervention, emotion regulation skills

Procedia PDF Downloads 136

Authors: Anan Jarab, Riham Almrayat, Salam Alqudah, Maher Khdour, Tareq Mukattash, Sharell Pinto

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Background: The prevalence of diabetes in Jordan is among the highest in the world, making it a particularly alarming health problem there. It has been indicated that poor adherence to the prescribed therapy lead to poor glycemic control and enhance the development of diabetes complications and unnecessary hospitalization. Purpose: To explore factors associated with medication non-adherence in patients with type 2 diabetes in Jordan. Materials and Methods: Variables including socio-demographics, disease and therapy factors, diabetes knowledge, and health-related quality of life in addition to adherence assessment were collected for 171 patients with type 2 diabetes using custom-designed and validated questionnaires. Logistic regression was performed to develop a model with variables that best predicted medication non-adherence in patients with type 2 diabetes in Jordan. Results: The majority of the patients (72.5%) were non-adherent. Patients were found four times less likely to adhere to their medications with each unit increase in the number of prescribed medications (OR = 0.244, CI = 0.08-0.63) and nine times less likely to adhere to their medications with each unit increase in the frequency of administration of diabetic medication (OR = 0.111, CI = 0.04-2.01). Patients in the present study were also approximately three times less likely (OR = 0.362, CI = 0.24-0.87) to adhere to their medications if they reported having concerns about side effects and twice more likely to adhere to medications (OR = 0.493, CI = 0.08-1.16) if they had one or more micro-vascular complication. Conclusion: The current study revealed low adherence rate to the prescribed therapy among Jordanians with type 2 diabetes. Simplifying dosage regimen, selecting treatments with lower side effects along with an emphasis on diabetes complications should be taken into account when developing care plans for patients with type 2 diabetes.

Keywords: type 2 diabetes, adherence, glycemic control, clinical pharmacist, Jordan

Procedia PDF Downloads 438

Authors: Abdolmoghset Banikamal

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This study looks at the issue of human needs from Islamic perspectives. The key objective of the study is to contribute in regulating the persuasion of needs. It argues that all needs are not necessarily genuine, rather a significant part of them are delusive. To distinguish genuine needs from delusive ones, the study suggests looking at the purpose of the persuasion of that particular need as a key criterion. In doing so, the paper comes with a model namely Orbit of Needs. The orbit has four circles. The central one is a necessity, followed by comfort, beautification, and exhibition. According to the model, all those needs that fall into one of the first three circles in terms of purpose are genuine, while any need which falls into the fourth circle is delusive.

Keywords: desire, human need, Islam, orbit of needs

Procedia PDF Downloads 284

Authors: hadi kargar, bahador shabani

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In this article, 16 cylinder motor combustion CFD modeling with a diameter of 165 mm and 195 mm along the way to help the FIRE software to optimize its function to work. A three-dimensional model of the processes that formed inside the cylinder made that involves mixing the fuel and air, ignition and spraying. In this three-dimensional model, all chemical species, density of air fuel spraying and spray with full profile intended to detailed results from mixing the fuel and air, igniting the ignition advance, spray, and mixed media in different times and get fit by moving the piston. Optimal selection of the model for the shape of the piston and spraying fuel specifications (including the management of spraying, the number of azhneh hole, start time of spraying and spraying angle) to achieve the best fuel consumption and minimal pollution. The spray hole 6 and 7 in three different configurations with five spraying and gives the best geometry and various performances in the simulation. 6 hole spray angle, finally spraying 72.5 degrees and two forms of spraying a better performance in comparison with other items of their own.

Keywords: spray, FIRE, CFD, optimize, diesel engine

Procedia PDF Downloads 419

Authors: Ruoyu Mao

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Exploring the relationship between urban green development and regional integration level is of great significance for realising regional high quality and sustainable development. Based on the Tapio decoupling model and the theoretical framework of urban green development and regional integration, this paper builds an analysis system, makes a quantitative analysis of urban green development and regional integration level in a certain period, and discusses the relationship between the two. It also takes China's Yangtze River Delta urban agglomeration as an example to study the degree of decoupling, the type of decoupling, and the trend of the evolution of the spatio-temporal pattern of decoupling between the level of urban green development and the level of regional integration in the period of 2014-2021, with the aim of providing a useful reference for the future development of the region.

Keywords: regional integration, urban green development, Tapio decoupling model, Yangtze River Delta urban agglomeration

Procedia PDF Downloads 43

Authors: A. T. Kuda, J. J. Dayya, A. Jimoh

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This paper investigates the fault detection and Isolation technique of measurement data sets from a three tank system using analytical model-based temporal redundancy which is based on residual generation using parity equations/space approach. It further briefly outlines other approaches of model-based residual generation. The basic idea of parity space residual generation in temporal redundancy is dynamic relationship between sensor outputs and actuator inputs (input-output model). These residuals where then used to detect whether or not the system is faulty and indicate the location of the fault when it is faulty. The method obtains good results by detecting and isolating faults from the considered data sets measurements generated from the system.

Keywords: fault detection, fault isolation, disturbing influences, system failure, parity equation/relation, structured parity equations

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Authors: J. Junk, M. Eickermann

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The Small Hive Beetle, Aethina tumida (Coleoptera: Nitidulidae) is a parasite for honey bee colonies, Apis mellifera, and was recently introduced to the European continent, accidentally. Based on the literature, a model was developed by using regional meteorological variables (daily values of minimum, maximum and mean air temperature as well as mean soil temperature at 50 mm depth) to calculate the time-point of hive invasion by A. tumida in springtime, the development duration of pupae as well as the number of generations of A. tumida per year. Luxembourg was used as a test region for our model for 2005 to 2013. The model output indicates a successful surviving of the Small Hive Beetle in Luxembourg with two up to three generations per year. Additionally, based on our meteorological data sets a first migration of SHB to apiaries can be expected from mid of March up to April. Our approach can be transferred easily to other countries to estimate the risk potential for a successful introduction and spreading of A. tumida in Western Europe.

Keywords: Aethina tumida, air temperature, larval development, soil temperature

Procedia PDF Downloads 116