Search results for: health data

Authors: Priyanka Patil, Logan Manikam

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Background: The first 1000 days of life are a critical window and can result in adverse health consequences due to inadequate nutrition. South-Asian (SA) communities face significant health disparities, particularly in maternal and child health. Community-based interventions, often employing Participatory-Learning and Action (PLA) approaches, have effectively addressed health inequalities in lower-income nations. The aim of this study was to assess the feasibility of implementing a PLA intervention to improve infant feeding and care practices in SA communities living in London. Methods: Comprehensive analyses were conducted to assess the feasibility/fidelity of this pilot randomized controlled trial. Summary statistics were computed to compare key metrics, including participant consent rates, attendance, retention, intervention support, and perceived effectiveness, against predefined progression rules guiding toward a definitive trial. Secondary outcomes were analyzed, drawing insights from multiple sources, such as The Children’s-Eating-Behaviour Questionnaire (CEBQ), Parental-Feeding-Style Questionnaires (PFSQ), Food-diary, and the Equality-Impact-Assessment (EIA) tool. A video analysis of children's mealtime behavior trends was conducted. Feedback interviews were collected from study participants. Results: Process-outcome measures met predefined progression rules for a definitive trial, which deemed the intervention as feasible and acceptable. The secondary outcomes analysis revealed no significant changes in children's BMI z-scores. This could be attributed to the abbreviated follow-up period of 6 months, reduced from 12 months, due to COVID-19-related delays. CEBQ analysis showed increased food responsiveness, along with decreased emotional over/undereating. A similar trend was observed in PFSQ. The EIA tool found no potential discrimination areas, and video analysis revealed a decrease in force-feeding practices. Participant feedback revealed improved awareness and knowledge sharing. Conclusion: This study demonstrates that a co-adapted PLA intervention is feasible and well-received in optimizing infant-care practices among South-Asian community members in a high-income country. These findings highlight the potential of community-based interventions to enhance health outcomes, promoting health equity.

Keywords: child health, childhood obesity, community-based, infant nutrition

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Authors: Hiranmoyee Das

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Aim. Due to late presentation and delayed diagnosis mortality rate of retinoblastoma is more than 50% in developing counties. So to facilitate the diagnosis, to decrease the disease and treatment burden and to increase the disease survival rate, an attempt was made for early diagnosis of Retinoblastoma by including fundus examination in routine immunization programs. Methods- A unique immunization card is followed in a tertiary health care center where examination of pupillary reflex is made mandatory in each visit of the child for routine immunization. In case of any abnormality, the child is referred to the ophthalmology department. Conclusion- Early detection is the key in the management of retinoblastoma. Every child is brought to the health care system at least five times before the age of 2 years for routine immunization. We should not miss this golden opportunity for early detection of retinoblastoma.

Keywords: retinoblastoma, immunization, unique, early

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Authors: Enoch F. Sam, Kris Brijs, Stijn Daniels, Tom Brijs, Geert Wets

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Notwithstanding the growing body of literature that recognises the importance of personal safety to public transport (PT) users, it remains unclear what PT users consider regarding their safety. In this study, we explore the criteria PT users in Ghana use to assess bus safety. This knowledge will afford a better understanding of PT users’ risk perceptions and assessments which may contribute to theoretical models of PT risk perceptions. We utilised phenomenological research methodology, with data drawn from 61 purposively sampled participants. Data collection (through focus group discussions and in-depth interviews) and analyses were done concurrently to the point of saturation. Our inductive data coding and analyses through the constant comparison and content analytic techniques resulted in 4 code categories (conceptual dimensions), 27 codes (safety items/criteria), and 100 quotations (data segments). Of the number of safety criteria participants use to assess bus safety, vehicle condition, driver’s marital status, and transport operator’s safety records were the most considered. With each criterion, participants rightly demonstrated its respective relevance to bus safety. These findings imply that investment in and maintenance of safer vehicles, and responsible and safety-conscious drivers, and prioritization of passengers’ safety are key-targets for public bus/minibus operators in Ghana.

Keywords: safety evaluations, public bus/minibus, passengers, phenomenology, Ghana

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Authors: Nishant Parashar, Sawan S. Sinha, Balaji Srinivasan

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We perform an investigation of the unclosed terms in the evolution equation of the velocity gradient tensor (VGT) in compressible decaying turbulent flow. Velocity gradients in a compressible turbulent flow field influence several important nonlinear turbulent processes like cascading and intermittency. In an attempt to understand the dynamics of the velocity gradients various researchers have tried to model the unclosed terms in the evolution equation of the VGT. The existing models proposed for these unclosed terms have limited applicability. This is mainly attributable to the complex structure of the higher order gradient terms appearing in the evolution equation of VGT. We investigate these higher order gradients using the data from direct numerical simulation (DNS) of compressible decaying isotropic turbulent flow. The gas kinetic method aided with weighted essentially non-oscillatory scheme (WENO) based flow- reconstruction is employed to generate DNS data. By applying neural-network to the DNS data, we map the structure of the unclosed higher order gradient terms in the evolution of the equation of the VGT with VGT itself. We validate our findings by performing alignment based study of the unclosed higher order gradient terms obtained using the neural network with the strain rate eigenvectors.

Keywords: compressible turbulence, neural network, velocity gradient tensor, direct numerical simulation

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Authors: Hafizah Che Hasan, Fateen Nazwa Yusof, Maslina Daud

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Internet of Things (IoT) is a powerful industry system, which end-devices are interconnected and automated, allowing the devices to analyze data and execute actions based on the analysis. The IoT technology leverages the technology of Radio-Frequency Identification (RFID) and Wireless Sensor Network (WSN), including mobile and sensor. These technologies contribute to the evolution of IoT. However, due to more devices are connected each other in the Internet, and data from various sources exchanged between things, confidentiality of the data becomes a major concern. This paper focuses on one of the major challenges in IoT; authentication, in order to preserve data integrity and confidentiality are in place. A few solutions are reviewed based on papers from the last few years. One of the proposed solutions is securing the communication between IoT devices and cloud servers with Elliptic Curve Cryptograhpy (ECC) based mutual authentication protocol. This solution focuses on Hyper Text Transfer Protocol (HTTP) cookies as security parameter.  Next proposed solution is using keyed-hash scheme protocol to enable IoT devices to authenticate each other without the presence of a central control server. Another proposed solution uses Physical Unclonable Function (PUF) based mutual authentication protocol. It emphasizes on tamper resistant and resource-efficient technology, which equals a 3-way handshake security protocol.

Keywords: Internet of Things (IoT), authentication, PUF ECC, keyed-hash scheme protocol

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Authors: Yassir Mohammed

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The study examines the impact of skilled parental migration on left-behind children. It uses the SCOPUS database to evaluate the existing literature from 1972 to 2022 and synthesizes data using the PRISMA framework and bibliometric method of analysis. 49 articles out of 202 papers were involved in the synthesis. International migration, outcome migration, consequence, parental migration, high-skill and left-behind children, and left-behind preschool were all searched. The research found that mental health issues, self-isolation, and physical harm have negative impacts, while sending children to good schools, having good academic records, and better medical care have positive impacts. The study also found that gender gaps increase in some countries while decreasing in others. Further research is needed on child maltreatment, academic performance, subjective well-being, societal effects, behavioral difficulties, and quality of life. The study only included peer-reviewed English publications in the final analysis.

Keywords: parental migration, impact of migration, systematic review, left-behind children

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Authors: Keith T. S. Tung, Frederick K. Ho, Rosa S. Wong, Camilla K. M. Lo, Wilfred H. S. Wong, C. B. Chow, Patrick Ip

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Objectives: Underage drinking is an important public health problem both locally and globally. Conventional prevention/intervention relies on unidirectional knowledge transfer such as mail leaflets or health talks which showed mixed results in changing the target behaviour. Previously, we conducted a school internet-based intervention which was found to be effective in reducing alcohol use among adolescents, yet the underlying mechanisms have not been properly investigated. This study, therefore, examined the mechanisms that explain how the intervention produced a change in alcohol drinking behaviours among Chinese adolescent as observed in our previous clustered randomised controlled trial (RCT) study. Methods: This is a cluster randomised controlled trial with parallel group design. Participating schools were randomised to the Internet intervention or the conventional health education group (control) with a 1:1 allocation ratio. Secondary 1–3 students of the participating schools were enrolled in this study. The Internet intervention was a web-based quiz game competition, in which participating students would answer 1,000 alcohol-related multiple-choice quiz questions. Conventional health education group received a promotional package on equivalent alcohol-related knowledge. The participants’ alcohol-related attitude, knowledge, and perceived behavioural control were self-reported before the intervention (baseline) and one month and three months after the intervention. Results: Our RCT results showed that participants in the Internet group were less likely to drink (risk ratio [RR] 0.79, p < 0.01) as well as in lesser amount (β -0.06, p < 0.05) compared to those in the control group at both post-intervention follow-ups. Within the intervention group, regression analyses showed that high quiz scorer had greater improvement in alcohol-related knowledge (β 0.28, p < 0.01) and attitude (β -0.26, p < 0.01) at 1 month after intervention, which in turn increased their perceived behavioural control against alcohol use (β 0.10 and -0.26, both p < 0.01). Attitude, compared to knowledge, was found to be a stronger contributor to the intervention effect on perceived behavioural control. Conclusions: Our internet-based intervention has demonstrated effectiveness in reducing the risk of underage drinking when compared with conventional health education. Our study results further showed an attitude to be a more important factor than knowledge in changing health-related behaviour. This has an important implication for future prevention/intervention on an underage drinking problem.

Keywords: adolescents, internet-based intervention, randomized controlled trial, underage drinking

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Authors: Rosine Angelique Uwacu

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Poor household sanitation is rife in Uganda, especially in Kampala. This study was carried out with he goal of establishing the main causes and effects of poor household sanitation in Kansanga parish. The study objectively sought to: To identify various ways through which wastes are generated and disposed of in Kansanga parish, identify different hygiene procedures/behaviors of waste handling in Kansanga parish and assess health effects of poor household sanitation and suggest the recommended appropriate measures of addressing cases of lack of hygiene in Kansanga parish. The study used a survey method where cluster sampling was employed. This is because there is no register of population or sufficient information, or geographic distribution of individuals is widely scattered. Data was collected through the use of interviews accompanied by observation and questionnaires. The study involved a sample of 100 households. The study revealed that; some households use wheeled bin collection, skip hire and roll on/off contained others take their wastes to refuse collection vehicles. Surprisingly, majority of the households submitted that they use polythene bags 'Kavera' and at times plastic sacs to dispose of their wastes which are dumped in drainage patterns or dustbins and other illegal dumping site. The study showed that washing hands with small jerrycans after using the toilet was being adopted by most households as there were no or few other alternatives. The study revealed that the common health effects that come as a result of poor household sanitation in Kansanga Parish are diseases outbreaks such as malaria, typhoid and diarrhea. Finally, the study gave a number of recommendations or suggestions on maintaining and achieving an adequate household sanitation in Kansanga Parish such as sensitization of community members by their leaders like Local Counselors could help to improve the situation, establishment of community sanitation days for people to collectively and voluntarily carry out good sanitation practices like digging trenches, burning garbage and proper waste management and disposal. Authorities like Kampala Capital City Authority should distribute dumping containers or allocate dumping sites where people can dispose of their wastes preferably at a minimum cost for proper management.

Keywords: household sanitation, kansanga parish, Uganda, waste

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Authors: Swati Rajput

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Environmental psychology explains that the person is a social agent that seeks to extract meaning from their built and natural environment to behave in a particular manner. It also shows the attachment or detachment of people to their environment. Assessing environmental psychology of people is imperative for planners and policy makers for urban planning. The paper investigates the environmental psychology of people living in nine districts of Delhi by calculating and assessing their Environmental Emotional Quotient (EEQ). Emotional Quotient deals with the ability to sense, understand, attach and respond according to the power of emotions. An Environmental Emotional Quotient has been formulated based upon the inventory administered to them. The respondents were asked questions related to their view and emotions about the green spaces, water resource conservation, air and environmental quality. An effort has been made to assess the feeling of belongingness among the residents. Their views were assessed on green spaces, reuse, and recycling of resources and their participation level. They were also been assessed upon health awareness level by considering both preventive and curative segments of health care. It was found that only 12 percent of the people is emotionally attached to their surroundings in the city. The emotional attachment reduces as we move away from the house to housing complex to neighbouring areas and rest of the city. In fact, the emotional quotient goes lower to lowest from house to other ends of the city. It falls abruptly after the radius of 1 km from the residence. The result also shows that nearly 54% respondents accept that there is environment pollution in their area. Around 47.8% respondents in the survey consider that diseases occur because of green cover depiction in their area. Major diseases are to airborne diseases like asthma and bronchitis. Seasonal disease prevalent, which specially occurred from last 3-4 years are malaria, dengue and chikengunya. Survey also shows that only 31 % of respondents visit government hospitals while 69% respondents visit private hospitals or small clinics for healthcare services. The paper suggests the need for environmental sensitive policies and need for green insurance in mega cities like Delhi.

Keywords: environmental psychology, environmental emotional quotient, preventive health care and curative health care, sustainable living

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Authors: Angela Maria Fasnacht

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Detection of anomalies due to contaminants’ presence, also known as early detection systems in water treatment plants, has become a critical point that deserves an in-depth study for their improvement and adaptation to current requirements. The design of these systems requires a detailed analysis and processing of the data in real-time, so it is necessary to apply various statistical methods appropriate to the data generated, such as Spearman’s Correlation, Factor Analysis, Cross-Correlation, and k-fold Cross-validation. Statistical analysis and methods allow the evaluation of large data sets to model the behavior of variables; in this sense, statistical treatment or analysis could be considered a vital step to be able to develop advanced models focused on machine learning that allows optimized data management in real-time, applied to early detection systems in water treatment processes. These techniques facilitate the development of new technologies used in advanced sensors. In this work, these methods were applied to identify the possible correlations between the measured parameters and the presence of the glyphosate contaminant in the single-pass system. The interaction between the initial concentration of glyphosate and the location of the sensors on the reading of the reported parameters was studied.

Keywords: glyphosate, emergent contaminants, machine learning, probes, sensors, predictive

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Authors: Fakharuddin Ibrahim, Jamaludin Md. Ali, Ahmad Ramli

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In this paper, we will discuss about the data interpolation by using the rational cubic Ball curve. To generate a curve with a better and satisfactory smoothness, the curve segments must be connected with a certain amount of continuity. The continuity that we will consider is of type G¹ continuity. The conditions considered are known as the G¹ Hermite condition. A simple application of the proposed method is to generate an Arabic font satisfying the required continuity.

Keywords: data interpolation, rational ball curve, hermite condition, continuity

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Authors: Babak Nematshahrbabaki, Fallahi Arezoo

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Objective: The aim of this study was to describe teenagers’ decisions to undergo orthodontic treatment through a qualitative study. Materials and methods: Twenty-three patients (12 girls), aged 12–18 years, at a dental clinic in Sanandaj the western part of Iran participated. Face-to-face and semi-structured interviews and two focus group discussions were held to gather data. Data analyzed by the grounded theory method. Results: ‘Decision-making’ was the core category. During the data analysis four main themes were developed: ‘being like everyone else’, ‘being diagnosed’, ‘maintaining the mouth’ and ‘cultural-social and environmental factors’. Conclusions: cultural- social and environmental factors have crucial role in decision-making to undergo orthodontic treatment. The teenagers were not fully conscious of these external influences. They thought their decision to undergo orthodontic treatment is independent while it is related to cultural- social and environmental factors.

Keywords: decision-making, qualitative study, teenager, orthodontic treatment

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Authors: Robert Caulk

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A generalized framework for adaptive machine learning deployments in algorithmic trading is introduced, tested, and released as open-source code. The presented software aims to test the hypothesis that recent data contains enough information to form a probabilistically favorable short-term price prediction. Further, the framework contains various adaptive machine learning techniques that are geared toward generating profit during strong trends and minimizing losses during trend changes. Results demonstrate that this adaptive machine learning approach is capable of capturing trends and generating profit. The presentation also discusses the importance of defining the parameter space associated with the dynamic training data-set and using the parameter space to identify and remove outliers from prediction data points. Meanwhile, the generalized architecture enables common users to exploit the powerful machinery while focusing on high-level feature engineering and model testing. The presentation also highlights common strengths and weaknesses associated with the presented technique and presents a broad range of well-tested starting points for feature set construction, target setting, and statistical methods for enforcing risk management and maintaining probabilistically favorable entry and exit points. The presentation also describes the end-to-end data processing tools associated with FreqAI, including automatic data fetching, data aggregation, feature engineering, safe and robust data pre-processing, outlier detection, custom machine learning and statistical tools, data post-processing, and adaptive training backtest emulation, and deployment of adaptive training in live environments. Finally, the generalized user interface is also discussed in the presentation. Feature engineering is simplified so that users can seed their feature sets with common indicator libraries (e.g. TA-lib, pandas-ta). The user also feeds data expansion parameters to fill out a large feature set for the model, which can contain as many as 10,000+ features. The presentation describes the various object-oriented programming techniques employed to make FreqAI agnostic to third-party libraries and external data sources. In other words, the back-end is constructed in such a way that users can leverage a broad range of common regression libraries (Catboost, LightGBM, Sklearn, etc) as well as common Neural Network libraries (TensorFlow, PyTorch) without worrying about the logistical complexities associated with data handling and API interactions. The presentation finishes by drawing conclusions about the most important parameters associated with a live deployment of the adaptive learning framework and provides the road map for future development in FreqAI.

Keywords: machine learning, market trend detection, open-source, adaptive learning, parameter space exploration

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Authors: C. J. Rossouw, T. I. van Niekerk

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The global manufacturing industry is utilizing the internet and cloud-based services to further explore the anatomy and optimize manufacturing processes in support of the movement into the Fourth Industrial Revolution (4IR). The 4IR from a third world and African perspective is hindered by the fact that many manufacturing systems that were developed in the third industrial revolution are not inherently equipped to utilize the internet and services of the 4IR, hindering the progression of third world manufacturing industries into the 4IR. This research focuses on the development of a non-invasive and cost-effective cyber-physical IoT system that will exploit a machine’s vibration to expose semantic characteristics in the manufacturing process and utilize these results through a real-time cloud-based machine condition monitoring system with the intention to optimize the system. A microcontroller-based IoT sensor was designed to acquire a machine’s mechanical vibration data, process it in real-time, and transmit it to a cloud-based platform via Wi-Fi and the internet. Time-frequency Fourier analysis was applied to the vibration data to form an image representation of the machine’s behaviour. This data was used to train a Convolutional Neural Network (CNN) to learn semantic characteristics in the machine’s behaviour and relate them to a state of operation. The same data was also used to train a Convolutional Autoencoder (CAE) to detect anomalies in the data. Real-time edge-based artificial intelligence was achieved by deploying the CNN and CAE on the sensor to analyse the vibration. A cloud platform was deployed to visualize the vibration data and the results of the CNN and CAE in real-time. The cyber-physical IoT system was deployed on a semi-automated metal granulation machine with a set of trained machine learning models. Using a single sensor, the system was able to accurately visualize three states of the machine’s operation in real-time. The system was also able to detect a variance in the material being granulated. The research demonstrates how non-IoT manufacturing systems can be equipped with edge-based artificial intelligence to establish a remote machine condition monitoring system.

Keywords: IoT, cyber-physical systems, artificial intelligence, manufacturing, vibration analytics, continuous machine condition monitoring

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Authors: Hye-Kyung Kang

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Social justice is a central principle of the social work profession and education. However, scholars have long questioned the profession’s commitment to putting social justice values into practice. Clinical social work has been particularly criticized for its lack of attention to social justice and for failing to address the concerns of the oppressed. One prominent criticism of clinical social work is that it often relies on individual intervention and fails to take on system-level changes or advocacy. This concern evokes the historical macro-micro tension of the social work profession where micro (e.g., mental health counseling) and macro (e.g., policy advocacy) practices are conceptualized as separate domains, creating a false binary for social workers. One contributor to this false binary seems to be that most clinical practice models do not prepare social work students and practitioners to make a clear link between clinical practice and social justice. This paper presents a model of clinical social work practice that clearly recognizes the essential and necessary connection between social justice, advocacy, and clinical practice throughout the clinical process: engagement, assessment, intervention, and evaluation. Contemporary relational theories, critical social work frameworks, and anti-oppressive practice approaches are integrated to build a clinical social work practice model that addresses the urgent need for mental health practice that not only helps and heals the person but also challenges societal oppressions and aims to change them. The application of the model is presented through case vignettes.

Keywords: social justice, clinical social work, clinical social work model, integrative model

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Authors: Dejana Bouillet, Vlatka Domović

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Both policymakers and researchers recognize that participating in early childhood education and care (ECEC) is useful for all children, especially for those who are exposed to the high risk of social exclusion. Social exclusion of children is understood as a multidimensional construct including economic, social, cultural, health, and other aspects of disadvantage and deprivation, which individually or combined can have an unfavorable effect on the current life and development of a child, as well as on the child’s development and on disadvantaged life chances in adult life. ECEC institutions should be able to promote educational approaches that portray developmental, cultural, language, and other diversity amongst children. However, little is known about the ways in which Croatian ECEC institutions recognize and respect the diversity of children and their families and how they respond to their educational needs. That is why this paper is dedicated to the analysis of the capacities of ECEC professionals to respond to the demands of educational needs of this very diverse group of children and their families. The results obtained in the frame of the project “Models of response to educational needs of children at risk of social exclusion in ECEC institutions,” funded by the Croatian Science Foundation, will be presented. The research methodology arises from explanations of educational processes and risks of social exclusion as a complex and heterogeneous phenomenon. The preliminary results of the qualitative data analysis of educational practices regarding capacities to identify and appropriately respond to the requirements of children at risk of social exclusion will be presented. The data have been collected by interviewing educational staff in 10 Croatian ECEC institutions (n = 10). The questions in the interviews were related to various aspects of inclusive institutional policy, culture, and practices. According to the analysis, it is possible to conclude that Croatian ECEC professionals are still faced with great challenges in the process of implementation of inclusive policies, culture, and practices. There are several baselines of this conclusion. The interviewed educational professionals are not familiar enough with the whole complexity and diversity of needs of children at risk of social exclusion, and the ECEC institutions do not have enough resources to provide all interventions that these children and their families need.

Keywords: children at risk of social exclusion, ECEC professionals, inclusive policies, culture and practices, quallitative analysis

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Authors: N. W. Paul, S. Michl

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In our globalized world we need to appreciate the fact that questions of health and justice need to be addressed on a global scale, too. The way in which diverse governmental and non-governmental initiatives are trying to answer the need for humanitarian medical aid has long since been a visible result of globalized responsibility. While the intention of humanitarian medical aids seems to be evident, the allocation of resources has become more and more an ethical and societal challenge. With a rising number and growing dimension of humanitarian catastrophes around the globe the search for ethically justifiable ways to decide who might benefit from limited resources has become a pressing question. Rooted in theories of justice (Rawls) and concepts of social welfare (Sen) we developed and implemented a model for an ethically sound distribution of a limited annual budget for humanitarian care in one of the largest medical universities of Germany. Based on our long lasting experience with civil casualties of war (Afghanistan) and civil war (Libya) as well as with under- and uninsured and/or stateless patients we are now facing the on-going refugee crisis as our most recent challenge in terms of global health and justice. Against this background, the paper strives to a) explain key issues of humanitarian medical aid in the 21st century, b) explore the problem of rationing from an ethical point of view, c) suggest a tool for the rational allocation of scarce resources in humanitarian medical aid, d) present actual cases of humanitarian care that have been managed with our toolbox, and e) discuss the international applicability of our model beyond local contexts.

Keywords: humanitarian care, medical ethics, allocation, rationing

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Authors: Sajida Saqira, Anthony Chariton, Grant C. Hose

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The Anthropocene has seen dramatic environmental changes which are affecting every ecosystem on earth. Freshwater ecosystems are particularly vulnerable as they are at risk from the many activities that go on and contaminants that are released in catchments. They are thus subject to many stressors simultaneously. Freshwater ecosystems respond to stress at all levels of biological organization, from subcellular to community structure and ecosystem functioning. The aim of this study was to examine the resistance and resilience of freshwater ecosystems to multiple stressors. Here we explored the individual and combined effects of copper as a chemical stressor and common carp (Cyprinus carpio) as a biological stressor on the health, functioning, and recovery of outdoor experimental pond ecosystems in a long-term, controlled, factorial experiment. Primary productivity, decomposition, and water and sediment quality were analysed at regular intervals for one year to understand the health and functioning of the ecosystems. Changes to benthic biota were quantified using DNA-based and traditional microscopy-based counts of invertebrates. Carp were added to the ponds to copper contaminated sediments (with controls) to explore the combined effects of copper and carp and removed after six months to explore the resilience and recovery of the system. The outcomes of this study will advance our understanding of the impacts of multiple stressors on freshwater ecosystems, and the resilience of these systems to copper and C. carpio, which are both globally significant stressors in freshwater systems.

Keywords: carp, copper, ecosystem health, freshwater ecosystem, multiple stressors

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Authors: Kaleeswari R. K., Seevagan L .

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Soil quality in an agroecosystem is influenced by the cropping system, water and soil fertility management. A valid soil quality index would help to assess the soil and crop management practices for desired productivity and soil health. The soil quality indices also provide an early indication of soil degradation and needy remedial and rehabilitation measures. Imbalanced fertilization and inadequate organic carbon dynamics deteriorate soil quality in an intensive cropping system. The rice soil ecosystem is different from other arable systems since rice is grown under submergence, which requires a different set of key soil attributes for enhancing soil quality and productivity. Assessment of the soil quality index involves indicator selection, indicator scoring and comprehensive score into one index. The most appropriate indicator to evaluate soil quality can be selected by establishing the minimum data set, which can be screened by linear and multiple regression factor analysis and score function. This investigation was carried out in intensive rice cultivating regions (having >1.0 lakh hectares) of Tamil Nadu viz., Thanjavur, Thiruvarur, Nagapattinam, Villupuram, Thiruvannamalai, Cuddalore and Ramanathapuram districts. In each district, intensive rice growing block was identified. In each block, two sampling grids (10 x 10 sq.km) were used with a sampling depth of 10 – 15 cm. Using GIS coordinates, and soil sampling was carried out at various locations in the study area. The number of soil sampling points were 41, 28, 28, 32, 37, 29 and 29 in Thanjavur, Thiruvarur, Nagapattinam, Cuddalore, Villupuram, Thiruvannamalai and Ramanathapuram districts, respectively. Principal Component Analysis is a data reduction tool to select some of the potential indicators. Principal Component is a linear combination of different variables that represents the maximum variance of the dataset. Principal Component that has eigenvalues equal or higher than 1.0 was taken as the minimum data set. Principal Component Analysis was used to select the representative soil quality indicators in rice soils based on factor loading values and contribution percent values. Variables having significant differences within the production system were used for the preparation of the minimum data set. Each Principal Component explained a certain amount of variation (%) in the total dataset. This percentage provided the weight for variables. The final Principal Component Analysis based soil quality equation is SQI = ∑ i=1 (W ᵢ x S ᵢ); where S- score for the subscripted variable; W-weighing factor derived from PCA. Higher index scores meant better soil quality. Soil respiration, Soil available Nitrogen and Potentially Mineralizable Nitrogen were assessed as soil quality indicators in rice soil of the Cauvery Delta zone covering Thanjavur, Thiruvavur and Nagapattinam districts. Soil available phosphorus could be used as a soil quality indicator of rice soils in the Cuddalore district. In rain-fed rice ecosystems of coastal sandy soil, DTPA – Zn could be used as an effective soil quality indicator. Among the soil parameters selected from Principal Component Analysis, Microbial Biomass Nitrogen could be used quality indicator for rice soils of the Villupuram district. Cauvery Delta zone has better SQI as compared with other intensive rice growing zone of Tamil Nadu.

Keywords: soil quality index, soil attributes, soil mapping, and rice soil

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Authors: Nasir Ashraf, Sajid Rahid Ahmad, Adeel Ahmad

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Pakistan is a major tea consumer country and ranked as the third largest importer of tea worldwide. Out of all beverage consumed in Pakistan, tea is the one with most demand for which tea import is inevitable. Being an agrarian country, Pakistan should cultivate its own tea and save the millions of dollars cost from tea import. So the need is to identify the most suitable areas with favorable weather condition and suitable soils where tea can be planted. This research is conducted over District Mansehra and District Abbottabad in Khyber Pakhtoonkhwah Province of Pakistan where the most favorable conditions for tea cultivation already exist and National Tea Research Institute has done successful experiments to cultivate high quality tea. High tech approach is adopted to meet the objectives of this research by using the remotely sensed data i.e. Aster DEM, Landsat8 Imagery. The Remote Sensing data was processed in Erdas Imagine, Envi and further analyzed in ESRI ArcGIS spatial analyst for final results and representation of result data in map layouts. Integration of remote sensing data with GIS provided the perfect suitability analysis. The results showed that out of all study area, 13.4% area is highly suitable while 33.44% area is suitable for tea plantation. The result of this research is an impressive GIS based outcome and structured format of data for the agriculture planners and Tea growers. Identification of suitable tea growing areas by using remotely sensed data and GIS techniques is a pressing need for the country. Analysis of this research lets the planners to address variety of action plans in an economical and scientific manner which can lead tea production in Pakistan to meet demand. This geomatics based model and approach may be used to identify more areas for tea cultivation to meet our demand which we can reduce by planting our own tea, and our country can be independent in tea production.

Keywords: agrarian country, GIS, geoinformatics, suitability analysis, remote sensing

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Authors: Dosun Shin, Assegid Kidane, Pavan Turaga

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According to the National Institute of Health, living a sedentary lifestyle leads to a number of health issues, including increased risk of cardiovascular dis-ease, type 2 diabetes, obesity, and certain types of cancers. This project brings together experts in multiple disciplines to bring product design, sensor design, algorithms, and health intervention studies to develop a product and system that helps reduce the amount of time sitting at the workplace. This paper illustrates ongoing improvements to prototypes the research team developed in initial research; including working prototypes with a software application, which were developed and demonstrated for users. Additional modifications were made to improve functionality, aesthetics, and ease of use, which will be discussed in this paper. Extending on the foundations created in the initial phase, our approach sought to further improve the product by conducting additional human factor research, studying deficiencies in competitive products, testing various materials/forms, developing working prototypes, and obtaining feedback from additional potential users. The solution consisted of an aesthetically pleasing seat cover cushion that easily attaches to common office chairs found in most workplaces, ensuring a wide variety of people can use the product. The product discreetly contains sensors that track when the user sits on their chair, sending information to a phone app that triggers reminders for users to stand up and move around after sitting for a set amount of time. This paper also presents the analyzed typical office aesthetics and selected materials, colors, and forms that complimented the working environment. Comfort and ease of use remained a high priority as the design team sought to provide a product and system that integrated into the workplace. As the research team continues to test, improve, and implement this solution for the sedentary workplace, the team seeks to create a viable product that acts as an impetus for a more active workday and lifestyle, further decreasing the proliferation of chronic disease and health issues for sedentary working people. This paper illustrates in detail the processes of engineering, product design, methodology, and testing results.

Keywords: anti-sedentary work behavior, new product development, sensor design, health intervention studies

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Authors: Julaine Allan, Katarzyna Olcon, Padmini Pai, Lynne Keevers, Mim Fox, Maria Mackay, Ruth Everingham, Sue Cutmore, Chris Degeling, Kristine Falzon, Summer Finlay

Abstract:

Effective local responses to community needs are grounded in contextual knowledge and built on existing resources. The SEED Wellbeing Program was created in 2020 in response to cumulative disasters, bushfires, floods and COVID experienced by healthcare staff in the Illawarra Shoalhaven Local Health District, NSW, Australia. SEED used a participatory action methodology to bring healthcare staff teams together to engage in restorative activities in the workplace. Guided by Practice Theory, this study identified the practices that supported the recovery of healthcare staff.

Keywords: mental health and wellbeing, workplace wellness, healthcare providers, natural disasters, COVID-19, burnout, occupational trauma

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Authors: Hai Zeng, Yisheng Li, Jincheng Huang, Chenghui Huang, Ying Zhang

Abstract:

Children are strong; the country strong, the development of children Basketball is a strategic advantage. Common forms of basketball equipment has been difficult to meet the needs of young children teaching the game of basketball, basketball development for 3-6 years old children in the form of appropriate teaching aids is a breakthrough basketball game teaching children bottlenecks, improve teaching critical path pleasure, but also the development of early childhood basketball a necessary requirement. In this study, literature, questionnaires, focus group interviews, comparative analysis, for domestic and foreign use of 12 kinds of basketball teaching aids (cloud computing MINI basketball, adjustable basketball MINI, MINI basketball court, shooting assist paw print ball, dribble goggles, dribbling machine, machine cartoon shooting, rebounding machine, against the mat, elastic belt, ladder, fitness ball), from fun and improve early childhood shooting technique, dribbling technology, as well as offensive and defensive rebounding against technology conduct research on conversion technology. The results show that by using appropriate forms of teaching children basketball aids, can effectively improve children's fun basketball game, targeted to improve a technology, different types of aids from different perspectives enrich the connotation of children basketball game. Recommended for children of color psychology, cartoon and environmentally friendly material production aids, and increase research efforts basketball aids children, encourage children to sports teachers aids applications.

Keywords: health and physical education field of curriculum outline, health fitness, sports and health curriculum reform, Taiwan, twelve years basic education

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Authors: Rômulo Eustáquio Martins de Souza, Paulo Alexandre Rodrigues de Vasconcelos Figueiredo

Abstract:

In recent years, there has been a surge in interest in applying artificial intelligence techniques, particularly machine learning algorithms. Machine learning is a data-analysis technique that automates the creation of analytical models, making it especially useful for designing complex situations. As a result, this technology aids in reducing human intervention while producing accurate results. This methodology is also extensively used in aerospace engineering since this is a field that encompasses several high-complexity operations, such as rocket propulsion. Rocket propulsion is a high-risk operation in which engine failure could result in the loss of life. As a result, it is critical to use computational methods capable of precisely representing the spacecraft's analytical model to guarantee its security and operation. Thus, this paper describes the use of machine learning algorithms for rocket propulsion to aid the realization that this technique is an efficient way to deal with challenging and restrictive aerospace engineering activities. The paper focuses on three machine-learning-aided rocket propulsion applications: set-point control of an expander-bleed rocket engine, supersonic retro-propulsion of a small-scale rocket, and leak detection and isolation on rocket engine data. This paper describes the data-driven methods used for each implementation in depth and presents the obtained results.

Keywords: data analysis, modeling, machine learning, aerospace, rocket propulsion

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Authors: Soo Hong Da, Ng Zheng Yao, Burra Venkata Durga Kumar

Abstract:

The Healthcare sector is a business that consists of providing medical services, manufacturing medical equipment and drugs as well as providing medical insurance to the public. Most of the time, the data stored in the healthcare database is to be related to patient’s information which is required to be accurate when it is accessed by authorized stakeholders. In distributed systems, one important issue is concurrency in the system as it ensures the shared resources to be synchronized and remains consistent through multiple read and write operations by multiple clients. The problems of concurrency in the healthcare sector are who gets the access and how the shared data is synchronized and remains consistent when there are two or more stakeholders attempting to the shared data simultaneously. In this paper, a framework that is beneficial to distributed healthcare sector concurrent environment is proposed. In the proposed framework, four different level nodes of the database, which are national center, regional center, referral center, and local center are explained. Moreover, the frame synchronization is not symmetrical. There are two synchronization techniques, which are complete and partial synchronization operation are explained. Furthermore, when there are multiple clients accessed at the same time, synchronization types are also discussed with cases at different levels and priorities to ensure data is synchronized throughout the processes.

Keywords: resources, healthcare, concurrency, synchronization, stakeholders, database

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Authors: Gumashta Raghvendra, Gumashta Jyotsna

Abstract:

Aim and Objective of Study : The use of Horrock’s Apparatus by health care worker requires onsite mathematical calculations for estimation of ‘volume of water’ and ‘amount of bleaching powder’ necessary as per the serial number of first cup showing blue coloration after adding freshly prepared starch-iodide indicator solution. In view of the difficulties of two simultaneous calculations required to be done, the use of Horrock’s Apparatus is not routinely done by health care workers because it is impractical and inconvenient Material and Methods: Arbitrary use of bleaching powder in wells results in hyper-chlorination or hypo-chlorination of well defying the purpose of adequate chlorination or non-usage of well water due to hyper-chlorination. Keeping this in mind two nomograms have been developed, one to assess the volume of well using depth and diameter of well and the other to know the quantity of bleaching powder to b added using the number of the cup of Horrock’s apparatus which shows the colour indication. Result & Conclusion: Out of thus developed two self-speaking interlinked easy charts, first chart will facilitate bypassing requirement of formulae ‘πr2h’ for water volume (ready reckoner table with depth of water shown on ‘X’ axis and ‘diameter of well’ on ‘Y’ axis) and second chart will facilitate bypassing requirement formulae ‘2ab/455’ (where ‘a’ is for ‘serial number of cup’ and ‘b’ is for ‘water volume’, while ready reckoner table showing ‘water volume’ shown on ‘X’ axis and ‘serial number of cup’ on ‘Y’ axis). The use of these two charts will help health care worker to immediately known, by referring the two charts, about the exact requirement of bleaching powder. Thus, developed ready reckoner charts will be easy and convenient to use for ensuring prevention of water-borne diseases occurring due to hypo-chlorination, especially in rural India and other developing countries.

Keywords: apparatus, bleaching, chlorination, Horrock’s, nomogram

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Authors: M. G. R. S. Perera, B. S. Weerakoon, L. P. G. Sherminie, M. L. Jayatilake, R. D. Jayasinghe, W. Huang

Abstract:

The aim of this study was to measure and evaluate the Longitudinal Relaxation Times (T1) in bone marrow of an Acute Myeloid Leukaemia (AML) patient in order to explore the potential for a prognostic biomarker using Magnetic Resonance Imaging (MRI) which will be a non-invasive prognostic approach to AML. MR image data were collected in the DICOM format and MATLAB Simulink software was used in the image processing and data analysis. For quantitative MRI data analysis, Region of Interests (ROI) on multiple image slices were drawn encompassing vertebral bodies of L3, L4, and L5. T1 was evaluated using the T1 maps obtained. The estimated bone marrow mean value of T1 was 790.1 (ms) at 3T. However, the reported T1 value of healthy subjects is significantly (946.0 ms) higher than the present finding. This suggests that the T1 for bone marrow can be considered as a potential prognostic biomarker for AML patients.

Keywords: acute myeloid leukaemia, longitudinal relaxation time, magnetic resonance imaging, prognostic biomarker.

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Authors: Antonia Egli, Theo Lynn, Pierangelo Rosati, Gary Sinclair

Abstract:

The World Health Organization (WHO) defines vaccine hesitancy as the postponement or complete denial of vaccines and estimates a direct linkage to approximately 1.5 million avoidable deaths annually. This figure is not immune to public health developments, as has become evident since the global spread of COVID-19 from Wuhan, China in early 2020. Since then, the proliferation of influential, but oftentimes inaccurate, outdated, incomplete, or false vaccine-related information on social media has impacted hesitancy levels to a degree described by the WHO as an infodemic. The COVID-19 pandemic and related vaccine hesitancy levels have in 2022 resulted in the largest drop in childhood vaccinations of the 21st century, while the prevalence of online stigma towards vaccine hesitant consumers continues to grow. Simultaneously, a second disease has risen to global importance: Monkeypox is an infection originating from west and central Africa and, due to racially motivated online hate, was in August 2022 set to be renamed by the WHO. To better understand public reactions towards two viral infections that became global threats to public health no two years apart, this research examines user replies to threads published by the WHO on Twitter. Replies to two Tweets from the @WHO account declaring COVID-19 and Monkeypox as ‘public health emergencies of international concern’ on January 30, 2020, and July 23, 2022, are gathered using the Twitter application programming interface and user mention timeline endpoint. Research methodology is unique in its analysis of stigmatizing, racist, and hateful content shared on social media within the vaccine discourse over the course of two disease outbreaks. Three distinct analyses are conducted to provide insight into (i) the most prevalent topics and sub-topics among user reactions, (ii) changes in sentiment towards the spread of the two diseases, and (iii) the presence of stigma, racism, and online hate. Findings indicate an increase in hesitancy to accept further vaccines and social distancing measures, the presence of stigmatizing content aimed primarily at anti-vaccine cohorts and racially motivated abusive messages, and a prevalent fatigue towards disease-related news overall. This research provides value to non-profit organizations or government agencies associated with vaccines and vaccination programs in emphasizing the need for public health communication fitted to consumers' vaccine sentiments, levels of health information literacy, and degrees of trust towards public health institutions. Considering the importance of addressing fears among the vaccine hesitant, findings also illustrate the risk of alienation through stigmatization, lead future research in probing the relatively underexamined field of online, vaccine-related stigma, and discuss the potential effects of stigma towards vaccine hesitant Twitter users in their decisions to vaccinate.

Keywords: social marketing, social media, public health communication, vaccines

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Authors: Li Kewen, Su Zhaoxin, Wang Xingmou, Zhu Jian Bing

Abstract:

Conventional reservoir prediction methods ar not sufficient to explore the implicit relation between seismic attributes, and thus data utilization is low. In order to improve the predictive classification accuracy of reservoir lithology, this paper proposes a deep learning lithology prediction method based on ResNet (Residual Neural Network) and SENet (Squeeze-and-Excitation Neural Network). The neural network model is built and trained by using seismic attribute data and lithology data of Shengli oilfield, and the nonlinear mapping relationship between seismic attribute and lithology marker is established. The experimental results show that this method can significantly improve the classification effect of reservoir lithology, and the classification accuracy is close to 70%. This study can effectively predict the lithology of undrilled area and provide support for exploration and development.

Keywords: convolutional neural network, lithology, prediction of reservoir, seismic attributes

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Authors: Maznieda Mahjom, Rohaida Ismail, Masita Arip, Mohd Shaiful Azlan, Nor’Ashikin Othman, Hafizah Abdullah, nor Zahrin Hasran, Joshita Jothimanickam, Syaqilah Shawaluddin, Nadia Mohamad, Raheel Nazakat, Tuan Mohd Amin, Mizanurfakhri Ghazali, Rosmanajihah Mat Lazim

Abstract:

COVID-19 outbreak is particularly detrimental to the mental health of everyone as well as leaving a long devastating crisis in the healthcare sector. Daily increment of COVID-19 cases and close contact, necessitating the testing of a large number of samples, thus increasing the workload and burden to laboratory personnel. This study aims to determine the prevalence of personal-, work- and client-related burnout as well as to measure the concentration of salivary cortisol among laboratory personnel in the main laboratories in Klang Valley, Malaysia. This cross-sectional study was conducted in late 2021 and recruited a total of 404 respondents from three laboratories in Klang Valley, Malaysia. The level of burnout was assessed using Copenhagen Burnout Inventory (CBI) comprising three sub-dimensions of personal-, work- and client-related burnout. The cut-off score of 50% and above indicated possible burnout. Meanwhile, salivary cortisol was measured using a competitive enzyme immunoassay kit (Salimetrics, State College, PA, USA). Normal levels of salivary cortisol concentration in adults are within 0.094 to 1.551 μg/dl (morning) and can be none detected to 0.359 μg/dl (evening). The prevalence of personal-, work- and client-related burnout among laboratory personnel were 36.1%, 17.8% and 7.2% respectively. Meanwhile, the abnormal morning and evening cortisol concentration recorded were 29.5% and 21.8% excluding 6.9%-7.4% missing data. While the IgA level is normal for most of the respondents, which recorded at 95.53%. Laboratory personnel were at risk of suffering burnout during the COVID-19 pandemic. Thus, mental health programs need to be addressed at the department and hospital level by regularly screening healthcare workers and designing an intervention program. It is also vital to improve the coping skills of laboratory personnel by increasing the awareness of good coping skill techniques. The training must be in an innovative way to ensure that the lab personnel can internalise the technique and practise it in real life.

Keywords: burnout, COVID-19, laborotary personnel, salivary cortisol

Procedia PDF Downloads 76