Search results for: care networks

Authors: Emna Abid, Linda Chebbi, Yosra Mabrouk, Amel Labidi, Lamia Mansour

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Werner syndrome (WS) is a rare genetic disorder inherited in an autosomal recessive pattern characterized by accelerated aging. While extensive research has been conducted on its systemic manifestations, the specific dental implications of WS remain poorly understood. The medical history and the oral health status of two patients diagnosed with WS were detailed. Our findings revealed a high prevalence of dental problems in both patients, including periodontitis, xerostomia, and temporomandibular joint disorders. This article aims to investigate the dental challenges faced by individuals with WS as well as the prosthetic options envisaged through two clinical cases contributing to a deeper understanding of the dental implications of WS and to choose the appropriate prosthetic solution in this population. Future research should focus on larger scale studies and clinical trials to validate these proposed strategies.

Keywords: adult progeria, clinical symptoms, oral manifestations, dental care, prosthetic management

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Authors: Thomas D. Collin, Rachel Cunningham, Bruce Jefferson, Raffaella Villa

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Fats, oils and grease (FOG) are by-products of food preparation and cooking processes. FOG enters wastewater systems through a variety of sources such as households, food service establishments, and industrial food facilities. Over time, if no source control is in place, FOG builds up on pipe walls, leading to blockages, and potentially to sewer overflows which are a major risk to the Environment and Human Health. UK water utilities spend millions of pounds annually trying to control FOG. Despite UK legislation specifying that discharge of such material is against the law, it is often complicated for water companies to identify and prosecute offenders. Hence, it leads to uncertainties regarding the attitude to take in terms of FOG management. Research is needed to seize the full potential of implementing current practices. The aim of this research was to undertake a comprehensive study to document the extent of FOG problems in sewer lines and reinforce existing knowledge. Data were collected to develop a model estimating quantities of FOG available for recovery within Thames Water wastewater catchments. Geographical Information System (GIS) software was used in conjunction to integrate data with a geographical component. FOG was responsible for at least 1/3 of sewer blockages in Thames Water waste area. A waste-based approach was developed through an extensive review to estimate the potential for FOG collection and recovery. Three main sources were identified: residential, commercial and industrial. Commercial properties were identified as one of the major FOG producers. The total potential FOG generated was estimated for the 354 wastewater catchments. Additionally, raw and settled sewage were sampled and analysed for FOG (as hexane extractable material) monthly at 20 sewage treatment works (STW) for three years. A good correlation was found with the sampled FOG and population equivalent (PE). On average, a difference of 43.03% was found between the estimated FOG (waste-based approach) and sampled FOG (raw sewage sampling). It was suggested that the approach undertaken could overestimate the FOG available, the sampling could only capture a fraction of FOG arriving at STW, and/or the difference could account for FOG accumulating in sewer lines. Furthermore, it was estimated that on average FOG could contribute up to 12.99% of the primary sludge removed. The model was further used to investigate the relationship between estimated FOG and number of blockages. The higher the FOG potential, the higher the number of FOG-related blockages is. The GIS-based tool was used to identify critical areas (i.e. high FOG potential and high number of FOG blockages). As reported in the literature, FOG was one of the main causes of sewer blockages. By identifying critical areas (i.e. high FOG potential and high number of FOG blockages) the model further explored the potential for source-control in terms of ‘sewer relief’ and waste recovery. Hence, it helped targeting where benefits from implementation of management strategies could be the highest. However, FOG is still likely to persist throughout the networks, and further research is needed to assess downstream impacts (i.e. at STW).

Keywords: fat, FOG, GIS, grease, oil, sewer blockages, sewer networks

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Authors: Antoni Ivanov, Nikolay Dandanov, Nicole Christoff, Vladimir Poulkov

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Spectrum underutilization has made cognitive radio a promising technology both for current and future telecommunications. This is due to the ability to exploit the unused spectrum in the bands dedicated to other wireless communication systems, and thus, increase their occupancy. The essential function, which allows the cognitive radio device to perceive the occupancy of the spectrum, is spectrum sensing. In this paper, the performance of modern adaptations of the four most widely used spectrum sensing techniques namely, energy detection (ED), cyclostationary feature detection (CSFD), matched filter (MF) and eigenvalues-based detection (EBD) is compared. The implementation has been accomplished through the PlutoSDR hardware platform and the GNU Radio software package in very low Signal-to-Noise Ratio (SNR) conditions. The optimal detection performance of the examined methods in a realistic implementation-oriented model is found for the common relevant parameters (number of observed samples, sensing time and required probability of false alarm).

Keywords: cognitive radio, dynamic spectrum access, GNU Radio, spectrum sensing

Procedia PDF Downloads 248

Authors: Helen S. Ghali, Haidy S. Ghali, Salma Ibrahim, Ossama Hosny, Hatem S. Elbehairy

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Infrastructure systems are essential assets in any community; accordingly, authorities aim to maximize its life span while minimizing the life cycle cost. This requires studying the asset conditions throughout its operation and forming a cost-efficient maintenance strategy plan. The objective of this study is to develop a highway management system that provides medium-term maintenance plans with the minimum life cycle cost subject to budget constraints. The model is applied to data collected for the highway network in India with the aim to output a 5-year maintenance plan strategy from 2019 till 2023. The main element considered is the surface coarse, either rigid or flexible pavement. The model outputs a 5-year maintenance plan for each segment given the budget constraint while maximizing the new pavement condition rating and minimizing its life cycle cost.

Keywords: infrastructure, asset management, optimization, maintenance plan

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Authors: Faezeh Aghazadeh, Mohammad Javad Sharifi

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The application of neural networks to model a full-scale industrial acetylene hydrogenation in olefin plant has been studied. The operating variables studied are the, input-temperature of the reactor, output-temperature of the reactor, hydrogen ratio of the reactor, [C₂H₂]input, and [C₂H₆]input. The studied operating variables were used as the input to the constructed neural network to predict the [C₂H₆]output at any time as the output or the target. The constructed neural network was found to be highly precise in predicting the quantity of [C₂H₆]output for the new input data, which are kept unaware of the trained neural network showing its applicability to determine the [C₂H₆]output for any operating conditions. The enhancement of [C₂H₆]output as compared with [C₂H₆]input was a consequence of low selective acetylene hydrogenation to ethylene.

Keywords: acetylene hydrogenation, Pd-Ag/Al₂O₃, artificial neural network, modeling, optimal design

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Authors: Rana I. Abdulghani, Amera I. Melhum

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With the abnormal growth of the usage of computers over networks and under the consideration or agreement of most of the computer security experts who said that the goal of building a secure system is never achieved effectively, all these points led to the design of the intrusion detection systems(IDS). This research adopts a comparison between two techniques for network intrusion detection, The first one used the (Particles Swarm Optimization) that fall within the field (Swarm Intelligence). In this Act, the algorithm Enhanced for the purpose of obtaining the minimum error rate by amending the cluster centers when better fitness function is found through the training stages. Results show that this modification gives more efficient exploration of the original algorithm. The second algorithm used a (Back propagation NN) algorithm. Finally a comparison between the results of two methods used were based on (NSL_KDD) data sets for the construction and evaluation of intrusion detection systems. This research is only interested in clustering the two categories (Normal and Abnormal) for the given connection records. Practices experiments result in intrude detection rate (99.183818%) for EPSO and intrude detection rate (69.446416%) for BP neural network.

Keywords: IDS, SI, BP, NSL_KDD, PSO

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Authors: Vaishnavi Shivde, Shrishti Sinha, Trapti Mishra

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Traffic light detection from a moving vehicle is an important technology both for driver safety assistance functions as well as for autonomous driving in the city. This paper proposed a deep-learning-based traffic light recognition method that consists of a pixel-wise image segmentation technique and a fully convolutional network i.e., UNET architecture. This paper has used a method for detecting the position and recognizing the state of the traffic lights in video sequences is presented and evaluated using Traffic Light Dataset which contains masked traffic light image data. The first stage is the detection, which is accomplished through image processing (image segmentation) techniques such as image cropping, color transformation, segmentation of possible traffic lights. The second stage is the recognition, which means identifying the color of the traffic light or knowing the state of traffic light which is achieved by using a Convolutional Neural Network (UNET architecture).

Keywords: traffic light detection, image segmentation, machine learning, classification, convolutional neural networks

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Authors: Krzysztof Malczewski

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Magnetic Resonance Imaging (MRI) reconstruction algorithm using compressed sensing is presented in this paper. It is exhibited that the offered approach improves MR images spatial resolution in circumstances when highly undersampled k-space trajectories are applied. Compressed Sensing (CS) aims at signal and images reconstructing from significantly fewer measurements than were conventionally assumed necessary. Magnetic Resonance Imaging (MRI) is a fundamental medical imaging method struggles with an inherently slow data acquisition process. The use of CS to MRI has the potential for significant scan time reductions, with visible benefits for patients and health care economics. In this study the objective is to combine super-resolution image enhancement algorithm with CS framework benefits to achieve high resolution MR output image. Both methods emphasize on maximizing image sparsity on known sparse transform domain and minimizing fidelity. The presented algorithm considers the cardiac and respiratory movements.

Keywords: super-resolution, MRI, compressed sensing, sparse-sense, image enhancement

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Authors: Reisy Tane

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Asthma is the common health problems in adolescents. Self-management is one way to improve health status in adolescent with asthma. Mobile technology has the potential to improve self-management in adolescents with asthma. Objective: the aim of this study to determine the effectiveness of using the mobile technology Asthma Action Plan to improve self management. Method: this study is Systematic review approach using PRISM template. The literature search started on first September 2017 by using electronic data Pro Quest and Google Scholars with keywords ‘Mobile AAP’ and ‘Adolescent Asthma’. Results and Conclusion: M-AAP is effective to improve adolescent self-management with asthma because it is easy to use and provide information appropriately. The improvement of self-management in teenagers will enhance the quality of life of adolescents with asthma. The recommendation of this study is the addition of parental control content in the application appropriate with Family Centered Care (FCC) philosophy on pediatric nursing. In addition, it is expected the development of applications for other chronic diseases such as diabetes mellitus and congestive heart failure.

Keywords: asthma, mobile AAP, adolescent, self-management

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Authors: Yulia Totskaya

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Nowadays, society is in a postindustrial/informational phase of its development. Certain changes have occurred in different parts of society life as a result of the social reality transformations due to the influence of changes in the productive forces. As a result, the personality has received autonomy and independence, as in her or his hands appeared new means of production–information, knowledge, creativity. In such a society, there is a new middle class, which is called meritocratic. It consists of personalities, who are engaged in highly intelligent, creative work; who independently pursue their own well-being and status; who are active in the economic and social spheres. At the forefront there are such qualities as independence, commitment and self-actualization. This modern, intellectual and sovereign personality is no longer in need of care. The role of management has transformed from a paternalistic to the "service", which is aimed at creating the conditions for citizens’ self-realization to meet their needs through the rendering of public services. Such society alterations motivate the need to change the key parameters of social management, which are identified in this article on the basis of the postindustrial society key features.

Keywords: informational society, postindustrial society, postindustrial sociality, public services, social management

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Authors: Jiwan Kumar, Pooja, Sandeep Negi, Anjum Rouf, Amit Kumar, Naveen Lakra

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In modern times where, health issues are increasing day by day, breast cancer is also one of them, which is very crucial and really important to find in the early stages. Doctors can use this model in order to tell their patients whether a cancer is not harmful (benign) or harmful (malignant). We have used the knowledge of machine learning in order to produce the model. we have used algorithms like Logistic Regression, Random forest, support Vector Classifier, Bayesian Network and Radial Basis Function. We tried to use the data of crucial parts and show them the results in pictures in order to make it easier for doctors. By doing this, we're making ML better at finding breast cancer, which can lead to saving more lives and better health care.

Keywords: Bayesian network, radial basis function, ensemble learning, understandable, data making better, random forest, logistic regression, breast cancer

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Authors: Siphesihle Hlongwane

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Background: Globally, alcohol consumption, smoking, and the use of illicit drugs kill more than 11.8 million people each year. In sub-Saharan Africa, substance abuse is responsible for more than 6.4% of all deaths recorded and about 4.7% of all Disability Adjusted Life Years (DALYs), with numbers still expected to grow if no drastic measures are taken to curb and address drug use. In a setting where substance use is rife, understanding contextual factors that influence an individual’s perceived eligibility to seek rehabilitation is paramount. Using the candidacy framework, we unpack how situational factors influence an individual’s perceived eligibility for healthcare uptake in adolescents and youth with substance use disorder (SUD). Methods: The candidacy framework is concerned with how people consider their eligibility for accessing a health service. The study collected and analyzed primary qualitative data to answer the research question. Data were collected between January and July 2022 on participants aged between 18 and 35 for drug users and 18 to 60 for family members. Participants include 20 previous and current drug users and 20 family members that experience the effects of addiction. A pre-drafted semi-structured interview guide was administered to a conveniently sampled population supplemented with a referral sampling method. Data were thematically analyzed using the NVivo 12pro software to manage the data. Findings: Our findings show that people with substance use disorders are aware of their drug use habits and acknowledge their candidacy for health services. Candidacy for health services is also acknowledged by those around them, such as family members and peers, and as such, information on the navigation of health services for drug users is shared by those who have attended health services, those affected by drug use, and this includes health service research by family members to identify accessible health services. While participants reported willingness to quit drug use if assistance is provided, the permeability of health care services is hindered by both individual determinations to quit drug use from long-time use and the availability of health services for drug users, such as rehabilitation centers. Our findings also show that drug users are conscious and can articulate their ailments; however, the hunt for the next dose of drugs and long waiting cues for health service acquisition overshadows their claim to health services. Participants reported a mixture of treatments prescribed, with some more gruesome than others prescribed, thus serving as both a facilitator and barrier for health service uptake. Despite some unorthodox forms of treatments prescribed in health care, the majority of those who enter treatment complete the process of treatment, although some are met with setbacks and sometimes relapse after treatment has finished. Conclusion: Drug users are able to ascertain their candidacy for health services; however, individual and environmental characteristics relating to drug use hinder the use of health services. Drug use interventions need to entice health service uptake as a way to improve candidacy for health use.

Keywords: substance use disorder, rehabilitation, drug use, relapse, South Africa, candidacy framework

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Authors: Sabri Sulaiman, Siti Hajar Abu Bakar Ah, Haris Abd Wahab

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Street children is a global phenomenon and declared as a social problem by social researcher and scholars across the world. The insecure street environment exposes street children into various risk factors. One of them is the health and psychological problem. The objective of this study is to assess the health problem and psychological wellbeing of street children in Kuala Lumpur, Malaysia. The cross-sectional study involved 303 street children in Chow Kit, Kuala Lumpur. The study confirmed that the majority (95.7%) of street children who participated in the study have a health problem. The findings also demonstrated that the majority of them have issues related to their psychological wellbeing. The inputs from this study are instrumental for the suggestion of specific intervention to improve the health and psychology wellbeing of street children in Malaysia. Agencies which are responsible for the street children well-being can utilise the inputs to framing and improving the social care programmes for the children.

Keywords: street children, health status, psychology wellbeing, homeless

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Authors: Zhao Gao, Eran Edirisinghe

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The production of an accurate sketch of a suspect based on a verbal description obtained from a witness is an essential task for most criminal investigations. The criminal investigation system employs specifically trained professional artists to manually draw a facial image of the suspect according to the descriptions of an eyewitness for subsequent identification. Within the advancement of Deep Learning, Recurrent Neural Networks (RNN) have shown great promise in Natural Language Processing (NLP) tasks. Additionally, Generative Adversarial Networks (GAN) have also proven to be very effective in image generation. In this study, a trained GAN conditioned on textual features such as keywords automatically encoded from a verbal description of a human face using an RNN is used to generate photo-realistic facial images for criminal investigations. The intention of the proposed system is to map corresponding features into text generated from verbal descriptions. With this, it becomes possible to generate many reasonably accurate alternatives to which the witness can use to hopefully identify a suspect from. This reduces subjectivity in decision making both by the eyewitness and the artist while giving an opportunity for the witness to evaluate and reconsider decisions. Furthermore, the proposed approach benefits law enforcement agencies by reducing the time taken to physically draw each potential sketch, thus increasing response times and mitigating potentially malicious human intervention. With publically available 'CelebFaces Attributes Dataset' (CelebA) and additionally providing verbal description as training data, the proposed architecture is able to effectively produce facial structures from given text. Word Embeddings are learnt by applying the RNN architecture in order to perform semantic parsing, the output of which is fed into the GAN for synthesizing photo-realistic images. Rather than the grid search method, a metaheuristic search based on genetic algorithms is applied to evolve the network with the intent of achieving optimal hyperparameters in a fraction the time of a typical brute force approach. With the exception of the ‘CelebA’ training database, further novel test cases are supplied to the network for evaluation. Witness reports detailing criminals from Interpol or other law enforcement agencies are sampled on the network. Using the descriptions provided, samples are generated and compared with the ground truth images of a criminal in order to calculate the similarities. Two factors are used for performance evaluation: The Structural Similarity Index (SSIM) and the Peak Signal-to-Noise Ratio (PSNR). A high percentile output from this performance matrix should attribute to demonstrating the accuracy, in hope of proving that the proposed approach can be an effective tool for law enforcement agencies. The proposed approach to criminal facial image generation has potential to increase the ratio of criminal cases that can be ultimately resolved using eyewitness information gathering.

Keywords: RNN, GAN, NLP, facial composition, criminal investigation

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Authors: Arindam Chaudhuri

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The research presents epsilon- hierarchical fuzzy twin support vector regression (epsilon-HFTSVR) based on epsilon-fuzzy twin support vector regression (epsilon-FTSVR) and epsilon-twin support vector regression (epsilon-TSVR). Epsilon-FTSVR is achieved by incorporating trapezoidal fuzzy numbers to epsilon-TSVR which takes care of uncertainty existing in forecasting problems. Epsilon-FTSVR determines a pair of epsilon-insensitive proximal functions by solving two related quadratic programming problems. The structural risk minimization principle is implemented by introducing regularization term in primal problems of epsilon-FTSVR. This yields dual stable positive definite problems which improves regression performance. Epsilon-FTSVR is then reformulated as epsilon-HFTSVR consisting of a set of hierarchical layers each containing epsilon-FTSVR. Experimental results on both synthetic and real datasets reveal that epsilon-HFTSVR has remarkable generalization performance with minimum training time.

Keywords: regression, epsilon-TSVR, epsilon-FTSVR, epsilon-HFTSVR

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Authors: I. Ketut Yoga Adityawira, Putu Ayu Novia Viorica, Komang Rahayu Indrawati

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In addition to work and take care of the family, Balinese women also have a role to participate in social activities in Bali. So this will have an impact on the quality of work life of Balinese women. One way to reduce the impact of the fulfillment of the role of Balinese women namely through emotional support. The aim of this research is to find out the effect of emotional support towards the quality of work life on Balinese working women. Data were retrieved by quasi-experimental method with pretest-posttest design. Data were analyzed by Analysis of Variance (ANOVA) through SPSS 17.0 for Windows. The number of subjects in this research is 30 people with the criteria: Balinese Women, aged 27 to 55 years old, have a minimum of two years experience of work and has been married. The analysis showed that there is no effect of emotional support towards the quality of work life on Balinese working women, with information there is no significant of probability value p = 0.304 (p > 0.05).

Keywords: Balinese women, emotional support, quality of work life, working women

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Authors: Khalid Obaed Mahmod, Mesut Cevik

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The term smart city has appeared recently and was accompanied by many definitions and concepts, but as a simplified and clear definition, it can be said that the smart city is a geographical location that has gained efficiency and flexibility in providing public services to citizens through its use of technological and communication technologies, and this is what distinguishes it from other cities. Smart cities connect the various components of the city through the main and sub-networks in addition to a set of applications and thus be able to collect data that is the basis for providing technological solutions to manage resources and provide services. The basis of the work of the smart city is the use of artificial intelligence and the technology of the Internet of Things. The work presents the concept of smart cities, the pillars, standards, and evaluation indicators on which smart cities depend, and the reasons that prompted the world to move towards its establishment. It also provides a simplified hypothetical way to measure the ideal smart city model by defining some indicators and key pillars, simulating them with logic circuits, and testing them to determine if the city can be considered an ideal smart city or not.

Keywords: factors, indicators, logic gates, pillars, smart city

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Authors: Hamid Vahidkia

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The International Health Regulations (IHR), the sole worldwide regulations for managing infectious diseases, have remained largely unchanged since their initial release in 1951. The WHO is currently involved in updating the IHR. This article evaluates WHO's updated IHR draft and suggests enhancements to enhance global health, such as a strong focus on the organization's fundamental public health goals, activities, and crucial services; wide-reaching coverage for various health risks; establishing global monitoring through official and unofficial data networks; setting benchmarks for national public health systems, evaluating results, and ensuring accountability from countries; safeguarding human rights by implementing evidence-based guidelines and just processes; and promoting good governance by embracing fairness, impartiality, and openness. The World Health Organization needs to guarantee that countries follow health regulations and provide ample economic and technical support to less privileged nations. A crucial concern for the global community is how independent nations can collaborate to ensure that global health benefits all individuals, regardless of their economic status.

Keywords: IHR, law, health, international, WHO

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Authors: Amira A. Alshowkan, Aleya M. Gamal

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Background: Patient safety is a vital element in providing high quality health care. In psychiatric wards, numerous of physical and emotional factors have been found to affect patient safety. In addition, organization, healthcare provider and patients were identified to be significant factors in patient safety. Aim: This study aims to discover nurses' perception of patient safety in psychiatric wards in Saudi Arabian. Method: Date will be collected through semi-structure face to face interview with nurses who are working at psychiatric wards. Data will be analysed thought the used of thematic analysis. Results: The results of this study will help in understanding the psychiatric nurses' perception of patient safety in Saudi Arabia. Several suggestions will be recommended for formulation of policies and strategies for psychiatric wards. In addition, recommendation to nursing education and training will be tailored in order to improve patient safety culture.

Keywords: patient safety culture, psychiatric, qualitative, Saudi Arabia

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Authors: Luis Andrey Fajardo Fajardo

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We are immersed in complex systems. The human brain, the galaxies, the snowflakes are examples of complex systems. An area of interest in Complex systems is the chaos theory. This revolutionary field of science presents different ways of study than determinism and reductionism. Here is where in junction with the Nonlinear DSP, chaos theory offer valuable techniques that establish a link between time series and complex theory in terms of complex networks, so that, the study of signals can be explored from the graph theory. Recently, some people had purposed a method to transform time series in graphs, but no one had developed a suitable implementation in Python with signals extracted from Chaotic Systems or Complex systems. That’s why the implementation in Python of an existing method to transform one dimensional chaotic signals from time domain to graph domain and some measures that may reveal information not extracted in the time domain is proposed.

Keywords: Python, complex systems, graph theory, dynamical systems

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Authors: Ivashkina Elizaveta

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Despite significant research on the positive effects of houseplants on human life, we know almost nothing about how people perceive plants and their attitudes toward them. The following study seeks to fill this void by applying para-social relationships (PSRs) theory to analyze individuals’ perceptions of houseplants. We reveal how people form and maintain PSRs with indoor plants using 15 semi-structured in-depth interviews with Russian-speaking university students who had a close bond with their indoor plants when the study was conducted. The findings indicate that the process of forming PSRs is influenced by factors such as exposure and homophily. Students develop a sense of companionship with their indoor plants, which contributes to establishing a PSR. Participants reported engaging in various activities, such as regular care, communication, and interaction with their plants. The insights gained from this research have implications for horticultural therapy, environmental psychology, and indoor gardening practices.

Keywords: para-social relationships, plants, people-plant interaction, indoor plants, qualitative research

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Authors: Sandhya Parameswaran, Prajakta Dhuri

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Despite great improvements in health care, the world oral health report states that dental problems still persist, particularly among underprivileged groups in both developing and developed countries. Dental caries and periodontal diseases are identified as the most important oral health problems globally. Acidic foods and beverages can affect natural teeth, and chronic exposure often leads to the development of dental erosion, abrasion, and decay. In recent years, there has been an increased interest toward essential oils. These are secondary metabolites and possess antibacterial, antifungal and antioxidant properties. Essential oils are volatile and chemically unstable in the presence of air, light, moisture and high temperature. Hence many novel methods like a liposomal encapsulation of oils have been introduced to enhance the stability and bioavailability. This research paper focuses on two essential oils, clove and cinnamon oil. Clove oil was obtained from Syzygium aromaticum Linn using clavengers apparatus. It contains eugenol and β caryophyllene. Cinnamon oil, from the barks of Cinnamomum cassia, contains cinnamaldehyde, The objective of the current research was to develop a liposomal carrier system containing clove and cinnamon oil and study their synergistic activity against dental pathogens when formulated as a gel. Methodology: The essential oil were first tested for their antimicrobial activity against dental pathogens, Lactobacillus acidophillus (MTCC No. 10307, MRS broth) and Streptococcus Mutans (MTCC No .890, Brain Heart Infusion agar). The oils were analysed by UV spectroscopy for eugenol and cinnamaldehyde content. Standard eugenol was linear between 5ppm to 25ppm at 282nm and standard cinnamaldehde from 1ppm to 5pmm at 284nm. The concentration of eugenol in clove oil was found to be 62.65 % w/w, and that of cinnamaldehyde was found to be 5.15%s w/w. The oils were then formulated into liposomes. Liposomes were prepared by thin film hydration method using Phospholipid, Cholesterol, and other oils dissolved in a chloroform methanol (3:1) mixture. The organic solvent was evaporated in a rotary evaporator above lipid transition temperature. The film was hydrated with phosphate buffer (pH 5.5).The various batches of liposomes were characterized and compared for their size, loading rate, encapsulation efficiency and morphology. The prepared liposomes when evaluated for entrapment efficiency showed 65% entrapment for clove and 85% for cinnamon oil. They were also tested for their antimicrobial activity against dental pathogens and their synergistic activity studied. Based on the activity and the entrapment efficiency the amount of liposomes required to prepare 1gm of the gel was calculated. The gel was prepared using a simple ointment base and contained 0.56% of cinnamon and clove liposomes. A simultaneous method of analysis for eugenol and cinnamaldehyde.was then developed using HPLC. The prepared gels were then studied for their stability as per ICH guidelines. Conclusion: It was found that liposomes exhibited spherical shaped vesicles and protected the essential oil from degradation. Liposomes, therefore, constitute a suitable system for encapsulation of volatile, unstable essential oil constituents.

Keywords: cinnamon oil, clove oil, dental caries, liposomes

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Authors: C. Surmei

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Autism Spectrum Disorder (ASD) is a complex developmental disorder that can affect an individual’s (but is not limited to) cognitive development, emotional development, language acquisition and the capability to relate to others. Ecological Systems Theory is a sociocultural theory that focuses on environmental systems with which an individual interacts. The SCERTS Model is an educational approach and multidisciplinary framework that addresses the challenges confronted by individuals on the autism spectrum and other developmental disabilities. To aid the understanding of ASD and educational philosophies for families, educators, and the global community alike, a Comparative Analysis was undertaken to examine key variables (the child, society, education, nurture/care, relationships, communication). The results indicated that the Ecological Systems Theory and the SCERTS Model were comparable in focus, motivation, and application, attaining to a viable and notable relationship between both theories. This paper unpacks two child development philosophies and their relationship to each other.

Keywords: autism spectrum disorder, ecological systems theory, education, SCERTS model

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Authors: A. Anitha, M. Aishwariya

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The realization of truly ubiquitous wireless sensor networks (WSN) demands Ultra-low power wireless communication capability. Because the radio transceiver in a wireless sensor node consumes more power when compared to the computation part it is necessary to reduce the power consumption. Hence, a low power transceiver is designed and implemented in a 120 nm CMOS technology for wireless sensor nodes. The power consumption of the transceiver is reduced still by maintaining the sensitivity. The transceiver designed combines the blocks including differential oscillator, mixer, envelope detector, power amplifiers, and LNA. RF signal modulation and demodulation is carried by On-Off keying method at 2.4 GHz which is said as ISM band. The transmitter demonstrates an output power of 2.075 mW while consuming a supply voltage of range 1.2 V-5.0 V. Here the comparison of LNA and power amplifier is done to obtain an amplifier which produces a high gain of 1.608 dB at receiver which is suitable to produce a desired sensitivity. The multistage RF amplifier is used to improve the gain at the receiver side. The power dissipation of the circuit is in the range of 0.183-0.323 mW. The receiver achieves a sensitivity of about -95 dBm with data rate of 1 Mbps.

Keywords: CMOS, envelope detector, ISM band, LNA, low power electronics, PA, wireless transceiver

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Authors: K. P. Farsana

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Each and every community has its own way of understanding on health and illness; it varies from culture to culture. According to the Mappila Muslims of Malappuram, the state of pain, distress, and misery is understood as an affliction to their health. They believe that most of the afflictions are due to the Jinn/ Shaitanic Possession. So they prefer religious healers than the other systems of medicine for their treatments. Thangals are the endogamous community in Kerala, of Yemeni heritage who claim direct descent from the Prophet Mohammed’s family. Because of their sacrosanct status, many Thangals works as religious healers in Northern Kerala. Using the case of one Thangal healer as the illustration of the many religious healers in Kerala who engage in the healing practices, it is intended, in this paper to illustrate the patterns of afflictions among Mappila Muslims of Malappuram. Based on the analysis of this Thangal’s healing practice in the local context of Northern Kerala, the researcher further discusses the modes of treatment which they are providing to care seekers.

Keywords: affliction, religious healing, faith, Mappila Muslims, Jinn/Shaitanic possession

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Authors: Saul A. Torres Z., Eduardo Liceaga C., Alfredo Arias M.

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Agriculture in the world falls within the main sources of economic and global needs, so care of crop is extremely important for owners and workers; one of the major causes of loss of product is the pest infection of different types of organisms. We seek to develop a UAV for agricultural spraying at a maximum altitude of 5000 meters above sea level, with a payload of 100 liters of fumigant. For the developing the aerodynamic design of the aircraft is using computational tools such as the "Vortex Lattice Athena" software, "MATLAB"," ANSYS FLUENT"," XFoil " package among others. Also methods are being used structured programming, exhaustive analysis of optimization methods and search. The results have a very low margin of error, and the multi- objective problems can be helpful for future developments. The program has 10 functions developed in MATLAB, these functions are related to each other to enable the development of design, and all these functions are controlled by the principal code "Master.m".

Keywords: aerodynamics design, optimization, algorithm genetic, multi-objective problem, stability, vortex

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Authors: Etaf Alkhlaifat

Abstract:

This study drew conceptually on Communication Accommodation Theory to describe and analyze conversations between doctors and patients to examine the extent to which patients’ level of literacy represents one of the linguistic obstacles that may adversely influence the quality of healthcare services in Jordan. A thematic qualitative approach was employed to interpret the phenomena under study, which required direct observation and interviews with doctors (n=6) and patients (n=15) in natural Jordanian medical settings. This generated a comprehensive corpus of audio and videotaped data, which revealed that most doctors expressed dissatisfaction with patients’ ability to express themselves and comprehend them as a result of a lack of medical awareness and limited health education. The significance of this study rests on its detailed investigation of the impact of health literacy on patients’ health outcomes and while providing unique insights into how low health literacy could contribute to misunderstanding and potential ill-health.

Keywords: doctor-patient communication, health literacy, medical knowledge, communication accommodation theory, qualitative research

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Authors: Soha A. Bahanshal, Byung G. Kim

Abstract:

Identification of patients at high risk for hospital readmission is of crucial importance for quality health care and cost reduction. Predicting hospital readmissions among diabetic patients has been of great interest to many researchers and health decision makers. We build a prediction model to predict hospital readmission for diabetic patients within 30 days of discharge. The core of the prediction model is a modified k Nearest Neighbor called Hybrid Fuzzy Weighted k Nearest Neighbor algorithm. The prediction is performed on a patient dataset which consists of more than 70,000 patients with 50 attributes. We applied data preprocessing using different techniques in order to handle data imbalance and to fuzzify the data to suit the prediction algorithm. The model so far achieved classification accuracy of 80% compared to other models that only use k Nearest Neighbor.

Keywords: machine learning, prediction, classification, hybrid fuzzy weighted k-nearest neighbor, diabetic hospital readmission

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Authors: Ruth Mandujano Lopez

Abstract:

During the second half of the 19th century, in the transition from sail to steam navigation, the transpacific space underwent major transformation. This paper examines the role that the steamship companies between Mexico, the rest of North America and Asia played in that process. Based on primary sources found in Mexico, California, London and Hong Kong, it argues that these companies actively participated in the redefining of the Pacific space as they opened new routes, transported thousands of people and had an impact on regional geopolitics. In order to prove this, the text will present the cases of a handful of companies that emerged between 1867 and 1910 and of some of their passengers. By looking at the way the Mexican ports incorporated to the transpacific steam maritime network, this work contributes to have a better understanding of the role that Latin American ports have played in the formation of a global order. From a theoretical point of view, it proposes the conceptualization of space in the form of transnational networks as a point of departure to conceive a history that is truly global.

Keywords: mexico, steamships, transpacific, maritime companies

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Authors: Neelam Singha

Abstract:

The present work intends to analyze the system dynamics of Hashimoto’s thyroiditis with the assistance of fractional calculus. Hashimoto’s thyroiditis or chronic lymphocytic thyroiditis is an autoimmune disorder in which the immune system attacks the thyroid gland, which gradually results in interrupting the normal thyroid operation. Consequently, the feedback control of the system gets disrupted due to thyroid follicle cell lysis. And, the patient perceives life-threatening clinical conditions like goiter, hyperactivity, euthyroidism, hyperthyroidism, etc. In this work, we aim to obtain the approximate solution to the posed fractional-order problem describing Hashimoto’s thyroiditis. We employ the Adomian decomposition method to solve the system of fractional-order differential equations, and the solutions obtained shall be useful to provide information about the effect of medical care. The numerical technique is executed in an organized manner to furnish the associated details of the progression of the disease and to visualize it graphically with suitable plots.

Keywords: adomian decomposition method, fractional derivatives, Hashimoto's thyroiditis, mathematical modeling

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