Search results for: cellular-based structural health monitoring

Authors: Arwa Alnowaiser, Hala Shoukri

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The ‘FreeAITherapist’ is an artificial intelligence application that uses the power of AI to offer advice and mental health counseling to its users through its chatbot services. The AI therapist is designed to understand users' issues, concerns, and problems and respond appropriately; it provides empathy and guidance and uses evidence-based therapeutic techniques. With its user-friendly platform, it ensures accessibility for individuals in need, regardless of their geographical location. This website was created in direct response to the growing demand for mental health support, aiming to provide a cost-effective and confidential solution. Through promising confidentiality, it considers user privacy and data security. The ‘FreeAITherapist’ strives to bridge the gap in mental health services, offering a reliable resource for individuals seeking guidance and counseling to improve their overall well-being.

Keywords: artificial intelligence, mental health, AI therapist, website, counseling

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Authors: Abram Zoltan

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Over the past hundred years, human activities, particularly the burning of fossil fuels, have released enough carbon dioxide and other greenhouse gases to dissipate additional heat into the lower atmosphere and affect the global climate. Climate change affects many social and environmental determinants of health: clean air, safe drinking water, and adequate food. Our aim is to draw attention to the effects of climate change on the health and health care system. Improving climate awareness and the knowledge related to climate change's health impacts are essential among medical students and practicing medical doctors. Therefore, in their everyday practice, they also need some assistance and up-to-date knowledge of how climate change can endanger human health and deal with these novel health problems. Our activity, based on the cooperation of more universities, aims to develop new curriculum outlines and learning materials on climate change's health impacts for medical schools. Special attention is intended to pay to the possible preventative measures against these impacts. For all of this, the project plans to create new curriculum outlines and learning materials for medical students, elaborate methodological guidelines and create training materials for medical doctors' postgraduate learning programs. The target groups of the project are medical students, educational staff of medical schools and universities, practicing medical doctors with special attention to the general practitioners and family doctors. We had searched various surveys, domestic and international studies about the effects of climate change and statistical estimation of the possible consequences. The health effects of climate change can be measured only approximately by considering only a fraction of the potential health effects and assuming continued economic growth and health progress. We can estimate that climate change is expected to cause about 250,000 more deaths. We conclude that climate change is one of the most serious problems of the 21st century, affecting all populations. In the short- to medium-term, the health effects of climate change will be determined mainly by human vulnerability. In the longer term, the effects depend increasingly on the extent to which transformational action is taken now to reduce emissions. We can contribute to reducing environmental pollution by raising awareness and by educating the population.

Keywords: climate change, health impacts, medical students, education

Procedia PDF Downloads 128

Authors: Ji-Seok Koo, Hee‑Yong Kwon, Hui-Young Yun, Kyung-Hui Wang, Youn-Seo Koo

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This paper presents a forecasting system for PM2.5 levels in Seoul, South Korea, leveraging a combination of chemical transport modeling and ConvLSTM-DNN machine learning technology. Exposure to PM2.5 has known detrimental impacts on public health, making its prediction crucial for establishing preventive measures. Existing forecasting models, like the Community Multiscale Air Quality (CMAQ) and Weather Research and Forecasting (WRF), are hindered by their reliance on uncertain input data, such as anthropogenic emissions and meteorological patterns, as well as certain intrinsic model limitations. The system we've developed specifically addresses these issues by integrating machine learning and using carefully selected input features that account for local and distant sources of PM2.5. In South Korea, the PM2.5 concentration is greatly influenced by both local emissions and long-range transport from China, and our model effectively captures these spatial and temporal dynamics. Our PM2.5 prediction system combines the strengths of advanced hybrid machine learning algorithms, convLSTM and DNN, to improve upon the limitations of the traditional CMAQ model. Data used in the system include forecasted information from CMAQ and WRF models, along with actual PM2.5 concentration and weather variable data from monitoring stations in China and South Korea. The system was implemented specifically for Seoul's PM2.5 forecasting.

Keywords: PM2.5 forecast, machine learning, convLSTM, DNN

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Authors: Ojin Kwon, Yong-Jin Yoon, Liu Xin, Zhang Hongbao

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Wireless Body Area Network (WBAN) is a short-range wireless communication around human body for various applications such as wearable devices, entertainment, military, and especially medical devices. WBAN attracts the attention of continuous health monitoring system including diagnostic procedure, early detection of abnormal conditions, and prevention of emergency situations. Compared to cellular network, WBAN system is more difficult to control inter- and inner-cell interference due to the limited power, limited calculation capability, mobility of patient, and non-cooperation among WBANs. In this paper, we compare the performance of resource allocation scheme based on several Pseudo Orthogonal Codewords (POCs) to mitigate inter-WBAN interference. Previously, the POCs are widely exploited for a protocol sequence and optical orthogonal code. Each POCs have different properties of auto- and cross-correlation and spectral efficiency according to its construction of POCs. To identify different WBANs, several different pseudo orthogonal patterns based on POCs exploits for resource allocation of WBANs. By simulating these pseudo orthogonal resource allocations of WBANs on MATLAB, we obtain the performance of WBANs according to different POCs and can analyze and evaluate the suitability of POCs for the resource allocation in the WBANs system.

Keywords: wireless body area network, body sensor network, resource allocation without feedback, interference mitigation, pseudo orthogonal pattern

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Authors: Abu Afree Andalib, M. Mezbah Uddin, M. Rafiur Rahman, M. Abir Hossain, Rajia Sultana Kamol

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This paper deals with the analysis of flow past the marine turbine blade which is designed by using the blade element theory and momentum theory for the purpose of using in the field of renewable energy. The designed blade is analyzed for various parameters using FSI module of Ansys. Computational Fluid Dynamics is used for the study of fluid flow past the blade and other fluidic phenomena such as lift, drag, pressure differentials, energy dissipation in water. Finite Element Analysis (FEA) module of Ansys was used to analyze the structural parameter such as stress and stress density, localization point, deflection, force propagation. Fine mesh is considered in every case for more accuracy in the result according to computational machine power. The relevance of design, search and optimization with respect to complex fluid flow and structural modeling is considered and analyzed. The relevancy of design and optimization with respect to complex fluid for minimum drag force using Ansys Adjoint Solver module is analyzed as well. The graphical comparison of the above-mentioned parameter using CFD and FEA and subsequently FSI technique is illustrated and found the significant conformity between both the results.

Keywords: blade element theory, computational fluid dynamics, finite element analysis, fluid-structure interaction, momentum theory

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Authors: Elaine Wong Yee-Sing

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Older adults are at high risk of chronic health conditions in Singapore. A closer examination at all facets of their aging process has revealed that they may not be necessary aging well. This demands for an increasing healthcare services brought to their home environment due to limited mobility and in the interest of time management. The home environment is an ideal setting to implement self-directed health promoting activities at their convenience and enable family’s support and motivation. This research protocol aims to explore their healthcare concerns, and creation of age appropriate interventions targeted to improve their chronic disease biomarkers. Convenience sampling of 130 families residing in private housing within five major districts in Singapore will be selected to participate in the health intervention. Statistical Package for Social Science 25 will be used to examine the pre and post screening results of their lipid, glycaemia and anthropometric outcomes. Using focus interviews, data results will be translated and transcribed to investigate on enablers, barriers and improvement on these services. Both qualitative and quantitative research outcomes are crucial to examine the impact of these services for these older adults living in private housing as they are not exposed to government subsidized community health programs. It is hypothesized that provision of relevant yet engaging health programs at their homes may mitigate the rising burden of chronic health conditions and result in successful aging outcomes among older Singaporeans.

Keywords: chronic diseases, health program, older adults, residential homes

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Authors: Kadhim Alabady

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Purpose: Mental health problems affect women and men equally, but some are more common among women. To Provide a baseline of the current picture of major mental health challenges among women in Dubai. which can then be used to measure the impact of interventions or service development. Method: We have used mixed methods evaluation approaches. This was used to increase the validity of findings by using a variety of data collection techniques. We have integrated qualitative and quantitative methods in this piece of work. Conducting the two approaches is to explore issues that might not be highlighted enough through one method. Results: The key findings are: The prevalence of people who suffer from different types of mental disorders remains largely unknown, many women are unwilling to seek professional help because of lack of awareness or the stigma attached to it. -It is estimated there were around 2,928–4,392 mothers in Dubai (2014) suffering from postnatal depression of which 858–1,287, early intervention can be effective. -The system for managing health care for women with mental illness is fragmented and contains gaps and duplications. -It is estimated 1,029 girl aged 13–19 years affected with anorexia nervosa and there would be an estimated 1,029 girl aged 13–19 years affected with anorexia nervosa. Recommendations: -Work is required with primary health care in order to identify women with undiagnosed mental illnesses. Further work is undertaken within primary health care to assess disease registries with the aim of helping GP practices to improve their disease registers. -It is important to conduct local psychiatric morbidity surveys in Dubai to obtain data and assess the prevalence of essential mental health symptoms and conditions that are not routinely collected to get a clear sense of what is needed and to assist decision and policy making in getting a complete picture on what services are required. -Emergency Mental Health Care – there is a need for a crisis response team to respond to emergencies in the community. -Continuum of care – a significant gap in the services for women once they diagnosed with mental disorder.

Keywords: mental health, depression, schizophrenia, women

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Authors: Daniel Walker, Adam Qureshi, David Marchant, Alex Bahrami Balani

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The present study aimed to assess the impact of concussion and physical pain on depression and health-related quality of life. Depressive symptoms were assessed using the Center for Epidemiological Studies' Depression Scale, and scores of health-related quality of life were measured by health-related quality of life short form-12. Data analysis of 67 participants (concussed 32 vs. 35 non-concussed) revealed that (i) 52% were displaying depressive symptoms (concussed 30% vs. non-concussed 22%) (ii) concussion had a significant effect on depressive symptoms when controlling for pain but no effect on the quality of life scores when controlling the same variable (iii) pain had a significant effect on depressive symptoms and quality of life. With this, both concussion and physical pain seem to have a negative impact on mental health; however, individuals may only recognise a reduction in quality of life with increased physical pain, hence a deterioration in mental well-being could be disregarded as a factor of health-related quality of life.

Keywords: depression, quality of life, concussion, physical pain

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Authors: Lakhoua Najeh

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Introduction: In most situations, an industrial system already existing, conditioned by its history, its culture and its context are in difficulty facing the necessity to restructure itself in an organizational and technological environment in perpetual evolution. This is why all operations of restructuring first of all require a diagnosis based on a functional analysis. After a presentation of the functionality of a supervisory system for complex processes, we present the concepts of industrial automation and supervisory control and data acquisition (SCADA). Methods: This global analysis exploits the various available documents on the one hand and takes on the other hand in consideration the various testimonies through investigations, the interviews or the collective workshops; otherwise, it also takes observations through visits as a basis and even of the specific operations. The exploitation of this diagnosis enables us to elaborate the project of restructuring thereafter. Leaving from the system analysis for the restructuring of industrial systems, and after a technical diagnosis based on visits, an analysis of the various technical documents and management as well as on targeted interviews, a focusing retailing the various levels of analysis has been done according a general methodology. Results: The methodology adopted in order to contribute to the restructuring of industrial systems by its participative and systemic character and leaning on a large consultation a lot of human resources that of the documentary resources, various innovating actions has been proposed. These actions appear in the setting of the TQM gait requiring applicable parameter quantification and a treatment valorising some information. The new management environment will enable us to institute an information and communication system possibility of migration toward an ERP system. Conclusion: Technological advancements in process monitoring, control and industrial automation over the past decades have contributed greatly to improve the productivity of virtually all industrial systems throughout the world. This paper tries to identify the principles characteristics of a process monitoring, control and industrial automation in order to provide tools to help in the decision-making process.

Keywords: automation, supervision, SCADA, TQM

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Authors: Tya M. Arthur

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Purpose: BIPOC (Black, Indigenous, and People of Color) adolescents face racism and discrimination at a young age. These early experiences have short- and long-term impacts on their health and overall well-being. The purpose of this study was to determine the relationships between perceived racial discrimination at school and health risk behaviors and experiences of BIPOC adolescents. Methods: Data from the 2021 Adolescent Behaviors and Experiences Survey (ABES) were analyzed. All demographic data were summarized using frequencies and chi-squared tests. A univariate and multivariate logistic regression model was used to test the relationship between perceived racial discrimination and selected health risk factors. All analyses were conducted using STATA SE 18. Results: A total of 42.2% of the BIPOC adolescents in the study indicated being treated unfairly at school due to their race. The majority of those who reported being discriminated against were Black/African American or Multiple Race-Hispanic. Asian adolescents were almost 5 times more likely to face racial discrimination at school compared to their American Indian/Alaska Native counterparts (OR = 4.86, 95% CI [2.69-8.77], p < 0.001). Other risk predictors of racial discrimination included being female (OR = 1.38, 95% CI [1.13-1.68], p = 0.002) and feeling disconnected at school (OR = 1.76, 95% CI [1.30-2.38], p < 0.001). After adjustment for health risk behaviors and experiences, BIPOC adolescents were still more likely to face racial discrimination with even higher odds. Conclusions: The results of this study highlight the depth of racial discrimination faced by BIPOC adolescents at school. Greater attention should be placed on racial discrimination as a social determinant of health and a public health crisis.

Keywords: racial discrimination, adolescents, heath risk factors, BIPOC

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Authors: Mona G. Alharbi

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A new family of methionine-sulfoxide reductase (Msr) was recently discovered and was named free methionine sulfoxide reductase (fRMsr). This family includes enzymes with a reductase activity toward the free R isomer of a methionine sulfoxide substrate. The fRMsrs have a GAF domain topology, a domain, which was previously identified as having in some cases a cyclic nucleotide phosphodiesterase activity. The classification of fRMsrs as GAF domains revealed a new function can be added to the GAF domain family. Interestingly the four members identified in the fRMsr family share the GAF domain structure and the presence of three conserved cysteines in the active site with free R methionine sulfoxide substrate specificity. This thesis presents the crystal structures of reduced, free Met-SO substrate-bound and MES-bound forms of a new fRMsr from Burkholderia pseudomallei (BPSL2418). BPSL2418 was cloned, overexpressed and purified to enable protein crystallization. The crystallization trials for reduced, Met-SO-bound and MES-bound forms of BPSL2418 were prepared and reasonable crystals of each form were produced. The crystal structures of BPSL2418MES, BPSL2418Met-SO and BPSL2418Reduced were solved at 1.18, 1.4 and 2.0Å, respectively by molecular replacement. The BPSL2418MES crystal belongs to space group P 21 21 21 while BPSL2418Met-SO and BPSL2418Reduced crystals belong to space group P 1 21 1. All three forms share the GAF domain structure of six antiparallel β-strands and four α-helices with connecting loops. The antiparallel β-strands (β1, β2, β5 and β6) are located in the center of the BPSL2418 structure flanked on one side by a three α-helices (α1, α2 and α4) and on the other side by a (loop1, β3, loop2, α3, β4 loop4) unit where loop4 forms a capping flap and covers the active site. The structural comparison of the three forms of BPSL2418 indicates that the catalytically important cysteine is CYS109, where the resolving cysteine is CYS75, which forms a disulfide bond with CYS109. They also suggest that the third conserved cysteine in the active site, CYS85, which is located in α3, is a non-essential cysteine for the catalytic function but it may play a role in the binding of the substrate. The structural comparison of the three forms reveals that conformational changes appear in the active site particularly involving loop4 and CYS109 during catalysis. The 3D structure of BPSL2418 shows strong structure similarity to fRMsrs enzymes, which further suggests that BPSL2418 acts as a free Met-R-SO reductase and shares the catalytic mechanism of fRMsr family.

Keywords: Burkholderia pseudomallei, GAF domain protein, methionine sulfoxide reductase, protein crystallization

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Authors: Yun-Tsuen Chen, Shih-Ting Huang, Pi-Fen Cheng, Yu-Ting Su, Joffrey Hsu, Hui-Zhu Chen

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Acute intestinal obstruction is one of the differentials of acute abdomen and requires timely alleviation of intestinal distention and abdominal pain to avoid perforation, intra-abdominal infection, and peritonitis. Investigation to identify the cause of obstruction will direct treatment planning and allow for more effective management. In this study, we present a 71-year-old female presenting with symptoms of acute intestinal obstruction for five days. After extensive history taking, physical exam, medical imaging, and pathology, the patient was diagnosed with colon cancer with lung metastasis and acute intestinal obstruction. The patient was placed on nil per os status with intravenous fluid support, intravenous antibiotics, and a decompression nasogastric tube was placed. The patient received decompression with colostomy creation surgery. After assessing the patient’s clinical condition and tumor staging, a multidisciplinary healthcare team created an individualized treatment plan, which included plans to prepare the patient for home self-care and maintain good mental health with regular monitoring in the clinic setting. This case demonstrates the importance of early diagnosis, effective treatment, and a multidisciplinary approach to the management of acute intestinal obstruction secondary to colon cancer.

Keywords: acute intestinal obstruction, colostomy surgery, metastatic colon cancer, multidisciplinary healthcare team

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Authors: Joyce Chieh Hsin Lo

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In the forthcoming paper, we aim to comprehensively investigate the relation between floor movement and the health condition. We embark on an extensive exploration of the innovative Movement Flow system, a contemporary paradigm that is reshaping the landscape of physical fitness and well-being. Our primary aim is to dissect the profound potential of this groundbreaking approach, not only as a means to enhance our physical fitness but also as a transformative tool for nurturing mental health. Within the scope of this comprehensive analysis, we will delve into the multifaceted aspects of Movement Flow, highlighting its versatility and adaptability to various individuals' needs and objectives.

Keywords: prehab, floor movement, proprioception, movement flow

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Authors: Jiwon Lee, Yeong-Ju Go, Jong-Soo Choi

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Drones were first developed for military use and were used in World War 1. But recently drones have been used in a variety of fields. Several companies actively utilize drone technology to strengthen their services, and in agriculture, drones are used for crop monitoring and sowing. Other people use drones for hobby activities such as photography. However, as the range of use of drones expands rapidly, problems caused by drones such as improperly flying, privacy and terrorism are also increasing. As the need for monitoring and tracking of drones increases, researches are progressing accordingly. The drone detection system estimates the position of the drone using the physical phenomena that occur when the drones fly. The drone detection system measures being developed utilize many approaches, such as radar, infrared camera, and acoustic detection systems. Among the various drone detection system, the acoustic detection system is advantageous in that the microphone array system is small, inexpensive, and easy to operate than other systems. In this paper, the acoustic signal is acquired by using minimum microphone when drone is flying, and direction of drone is estimated. When estimating the Direction of Arrival(DOA), there is a method of calculating the DOA based on the Time Difference of Arrival(TDOA) and a method of calculating the DOA based on the beamforming. The TDOA technique requires less number of microphones than the beamforming technique, but is weak in noisy environments and can only estimate the DOA of a single source. The beamforming technique requires more microphones than the TDOA technique. However, it is strong against the noisy environment and it is possible to simultaneously estimate the DOA of several drones. When estimating the DOA using acoustic signals emitted from the drone, it is impossible to measure the position of the drone, and only the direction can be estimated. To overcome this problem, in this work we show how to estimate the position of drones by arranging multiple microphone arrays. The microphone array used in the experiments was four tetrahedral microphones. We simulated the performance of each DOA algorithm and demonstrated the simulation results through experiments.

Keywords: acoustic sensing, direction of arrival, drone detection, microphone array

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Authors: Arlett A. Rosado-Torres, Ismael Marino-Tapia

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Changes in benthic cover of coral dominated systems to macroalgae dominance are widely studied worldwide. Watershed pollutants are potentially as important as overfishing causing phase shift. In certain regions of the world most of the continental inputs are through submarine groundwater discharges (SGD), which can play a significant ecological role because the concentration of its nutrients is usually greater that the one found in surface seawater. These stressors have adversely affected coral reefs, particularly in the Caribbean. Measurements of benthic cover (with video tracing, through a Go Pro camera), reef roughness (acoustic estimates with an Acoustic Doppler Current Velocity profiler and a differential GPS), thermohaline conditions (conductivity-temperature-depth (CTD) instrument) and nutrient measurements were taken in different sites in the reef lagoon of Puerto Morelos, Q. Roo, Mexico including those with influence of SGD and without it. The results suggest a link between SGD, macroalgae cover and structural complexity. Punctual water samples and data series from a CTD Diver confirm the presence of the SGD. On the site where the SGD is, the macroalgae cover is larger than in the other sites. To establish a causal link between this phase shift and SGD, the DELFT 3D hydrodynamic model (FLOW and WAVE modules) was performed under different environmental conditions and discharge magnitudes. The model was validated using measurements of oceanographic instruments anchored in the lagoon and forereef. The SGD is consistently favoring macroalgae populations and affecting structural complexity of the reef.

Keywords: hydrodynamic model, macroalgae, nutrients, phase shift

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Authors: Mohd Tahseen Islam Talukder, Sheikh Adnan Enam, Latifa Akter Lithi, Soebur Rahman

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Composite structures have made significant advances in construction applications during the last few decades. Composite structures are composed of structural steel shapes and reinforced concrete combined with shear connectors, which benefit each material's unique properties. Significant research has been conducted on different types of connectors’ behavior and shear capacity. Moreover, the AISC 360-16 “Specification for Steel Structural Buildings” consists of a formula for channel shear connectors' shear capacity. This research compares the behavior of C type and L type shear connectors using Finite Element Analysis. Experimental results from published literature are used to validate the finite element models. The 3-D Finite Element Model (FEM) was built using ABAQUS 2017 to investigate non-linear capabilities and the ultimate load-carrying potential of the connectors using push-out tests. The changes in connector dimensions were analyzed using this non-linear model in parametric investigations. The parametric study shows that by increasing the length of the shear connector by 10 mm, its shear strength increases by 21%. Shear capacity increased by 13% as the height was increased by 10 mm. The thickness of the specimen was raised by 1 mm, resulting in a 2% increase in shear capacity. However, the shear capacity of channel connectors was reduced by 21% due to an increase of thickness by 2 mm.

Keywords: finite element method, channel shear connector, angle shear connector, ABAQUS, composite structure, shear connector, parametric study, ultimate shear capacity, push-out test

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Authors: Marwa Mamdouh Shaban, Nagat Saied Habib, Shireen Ezz El-Din Taha, Eman Mahmoud Seif El-Naser

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Background: Dental nurses and dentists were constantly exposed to a number of specific work related health risk factors which develop and intensify with years. Awareness regarding these work-related health risk factors and implementation of preventive health care measures could provide a safe work environment for all dental nurses and dentists. Aim of the study: to assess the work-related health risk factors among dental nurses and dentists and preventive health care measures applied among dental nurses and dentists. Research design: A descriptive design was utilized. Sample: Convenience sample of 50 dental nurses and 150 dentists were included in the current study. Setting: This study was conducted at the dental clinics at faculty of oral and dental medicine, Al-Kasr Al Ainy Hospital. Tools of data collection: Three tools were developed, tested for clarity, and feasibility: a-Socio-demographic data sheet, b-Work-related health risk factors questionnaire, and c-structured observational checklist. Results: The most common work risk factors prevailing among dental nurses were emotional exhaustion (82%), low back pain (76%) and latex allergy (62%) and the most common work risk factors prevailing among dentists were percutaneous exposure incident (100%), emotional exhaustion (100%) and low back pain (93.3%). Also, statistically significant negative correlation (r=-0.274, at p = 0.045) between the incidence of chemical health risk factors and application of chemical preventive measures among dental nurses. A statistically significant negative correlation (r=-0.177, at p = 0.030) between the incidences of mechanical health risk factors among dentists and application of mechanical preventive measures. Conclusion: The studied dental nurses and dentists exposed to many work related health risk factors as latex allergy, percutaneous exposure incidents, low back pain and emotional exhaustion related to inappropriate application of preventive health care measures. Recommendation: Raise awareness of dental nurses and dentists about work-related health risk factors, design and implement health education program for preventive health care measures.

Keywords: work-related risk factors, preventive measures, nurses, dentists

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Authors: Yiqi Zhu, Jean Francois Trani, Rameez Ulhassan

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Extreme weather phenomena increased by 46% between 2007 and 2017 and have become more intense with the rise in global average temperatures. This increased intensity of climate variations often induces humanitarian crises and particularly affects vulnerable populations in low- and middle-income countries (LMICs). Expectant and lactating mothers are among the most vulnerable groups. Pakistan ranks 10th among the most affected countries by climate disasters. In 2022, monsoon floods submerged a third of the country, causing the loss of 1,500 lives. Approximately 650,000 expectant and lactating mothers faced systematic stress from climatic disasters. Our study used participatory methods to investigate the systematic impact of climatic disasters on maternal health. In March 2023, we conducted six Group Model Building (GMB) workshops with healthcare workers, fathers, and mothers separately in two of the most affected areas in Pakistan. This study was approved by the Islamic Relief Research Review Board. GMB workshops consist of three sessions. In the first session, participants discussed the factors that impact maternal health. After identifying the factors, they discussed the connections among them and explored the system structures that collectively impact maternal health. Based on the discussion, a causal loop diagram (CLD) was created. Finally, participants discussed action ideas that could improve the system to enhance maternal health. Based on our discussions and the causal loop diagram, we identified interconnected factors at the family, community, and policy levels. Mothers and children are directly impacted by three interrelated factors: food insecurity, unstable housing, and lack of income. These factors create a reinforcing cycle that negatively affects both mothers and newborns. After the flood, many mothers were unable to produce sufficient breastmilk due to their health status. Without breastmilk and sufficient food for complementary feeding, babies tend to get sick in damp and unhygienic environments resulting from temporary or unstable housing. When parents take care of sick children, they miss out on income-generating opportunities. At the community level, the lack of access to clean water and sanitation (WASH) and maternal healthcare further worsens the situation. Structural failures such as a lack of safety nets and programs associated with flood preparedness make families increasingly vulnerable with each disaster. Several families reported that they had not fully recovered from a flood that occurred ten years ago, and this latest disaster destroyed their lives again. Although over twenty non-profit organizations are working in these villages, few of them provide sustainable support. Therefore, participants called for systemic changes in response to the increasing frequency of climate disasters. The study reveals the systematic vulnerabilities of mothers and children after climatic disasters. The most vulnerable populations are often affected the most by climate change. Collaborative efforts are required to improve water and forest management, strengthen public infrastructure, increase access to WASH, and gradually build climate-resilient communities. Governments, non-governmental organizations, and the community should work together to develop and implement effective strategies to prevent, mitigate, and adapt to climate change and its impacts.

Keywords: climatic disasters, maternal health, Pakistan, systematic impact, flood, disaster relief.

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Authors: Nina Kaufmans

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Traditional therapies, utilizing spoken narratives as a primary source of intervention, are proven to be limited in effectively treating post traumatic stress disorder. Following the effects of the global pandemic of COVID-19, an increasing number of mental health consumers are beginning to experience somatically-based distress in addition to existing mental health symptoms. Moreover, the aftermath of the rapid increase in demand for mental health services has caused significant burnout in mental health professionals. This paper explores the ramifications of recent changes and challenges in the mental health demands and subsequent response and its consequences for mental health workers. We will begin by investigating the neurobiological mechanisms involved in traumatic experiences, then discuss the premises for "bottom-up" or somatically oriented psychotherapy approaches, and finally offer clinical skills and interventions for clients diagnosed with post traumatic stress disorder. In addition, we will discuss how somatically-based psychotherapy interventions implemented in sessions may decrease burnout and improve the well-being of clinicians. We will discuss how the integration of somatically-based interventions into counseling would increase the effectiveness of mental health recovery and sustain remission while simultaneously providing opportunities for self-care for mental health professionals.

Keywords: somatic psychotherapy interventions, trauma counseling, preventing and treating burnout, adults with PTSD, bottom-up skills, the effectiveness of trauma treatment

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Authors: Valentin Nickolai, Florian Pfeffel, Christian Louis Kühner

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In many industrialized nations, the demand for skilled workers rises, causing the current market for employees to be more candidate-driven than employer-driven. Therefore, losing highly skilled and experienced employees due to early or partial retirement negatively impacts firms. Therefore, finding new ways to incentivize older employees (Silver Workers) to stay longer with the company and in their job can be crucial for the success of a firm. This study analyzes how working remotely can be a valid incentive for experienced Silver Workers to stay in their job and instead work from home with more flexible working hours. An online survey with n = 684 respondents, who are employed in the service sector, has been conducted based on 13 constructs that influence job satisfaction. These have been further categorized into three groups “classic influencing factors,” “influencing factors changed by remote working,” and new remote working influencing factors,” and were analyzed using structural equation modeling (SEM). Here, Cronbach’s alpha of the individual constructs was shown to be suitable. Furthermore, the construct validity of the constructs was confirmed by face validity, content validity, convergent validity (AVE > 0.5: CR > 0.7), and discriminant validity. Additionally, confirmatory factor analysis (CFA) confirmed the model fit for the investigated sample (CMIN/DF: 2.567; CFI: 0.927; RMSEA: 0.048). It was shown in the SEM-analysis that the influencing factor on job satisfaction, “identification with the work,” is the most significant with β = 0.540, followed by “Appreciation” (β = 0.151), “Compensation” (β = 0.124), “Work-Life-Balance” (β = 0.116), and “Communication and Exchange of Information” (β = 0.105). While the significance of each factor can vary depending on the work model, the SEM-analysis also shows that the identification with the work is the most significant factor in all three work models mentioned above and, in the case of the traditional office work model, it is the only significant influencing factor. The study shows that employees between the ages of 56 and 65 years have the highest job satisfaction when working entirely from home or remotely. Furthermore, their job satisfaction score of 5.4 on a scale from 1 (very dissatisfied) to 7 (very satisfied) is the highest amongst all age groups in any of the three work models. Due to the significantly higher job satisfaction, it can be argued that giving Silver Workers the offer to work from home or remotely can incentivize them not to opt for early retirement or partial retirement but to stay in their job full-time Furthermore, these findings can indicate that employees in the Silver Worker age are much more inclined to leave their job for early retirement if they have to entirely work in the office.

Keywords: home office, remote work instead of early or partial retirement, silver worker, structural equation modeling

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Authors: Umamaheswari Shanmugam, Silvia Ronchi, Radu Vornicu

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Software, artificial intelligence, and machine learning can improve healthcare through innovative and advanced technologies that are able to use the large amount and variety of data generated during healthcare services every day. As we read the news, over 500 machine learning or other artificial intelligence medical devices have now received FDA clearance or approval, the first ones even preceding the year 2000. One of the big advantages of these new technologies is the ability to get experience and knowledge from real-world use and to continuously improve their performance. Healthcare systems and institutions can have a great benefit because the use of advanced technologies improves the same time efficiency and efficacy of healthcare. Software-defined as a medical device, is stand-alone software that is intended to be used for patients for one or more of these specific medical intended uses: - diagnosis, prevention, monitoring, prediction, prognosis, treatment or alleviation of a disease, any other health conditions, replacing or modifying any part of a physiological or pathological process–manage the received information from in vitro specimens derived from the human samples (body) and without principal main action of its principal intended use by pharmacological, immunological or metabolic definition. Software qualified as medical devices must comply with the general safety and performance requirements applicable to medical devices. These requirements are necessary to ensure high performance and quality and also to protect patients’ safety. The evolution and the continuous improvement of software used in healthcare must take into consideration the increase in regulatory requirements, which are becoming more complex in each market. The gap between these advanced technologies and the new regulations is the biggest challenge for medical device manufacturers. Regulatory requirements can be considered a market barrier, as they can delay or obstacle the device approval, but they are necessary to ensure performance, quality, and safety, and at the same time, they can be a business opportunity if the manufacturer is able to define in advance the appropriate regulatory strategy. The abstract will provide an overview of the current regulatory framework, the evolution of the international requirements, and the standards applicable to medical device software in the potential market all over the world.

Keywords: artificial intelligence, machine learning, SaMD, regulatory, clinical evaluation, classification, international requirements, MDR, 510k, PMA, IMDRF, cyber security, health care systems.

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Authors: Ofelia Loani Elvir Lazo, Roya Yumul, Sevan Komshian, Ruby Wang, Jun Tang

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Background: Monitoring the anti-nociceptive drug effect is useful because a sudden and strong nociceptive stimulus may result in untoward autonomic responses and muscular reflex movements. Monitoring the anti-nociceptive effects of perioperative medications has long been desiredas a way to provide anesthesiologists information regarding a patient’s level of antinociception and preclude any untoward autonomic responses and reflexive muscular movements from painful stimuli intraoperatively.To this end, electroencephalogram (EEG) based tools includingBIS and qCON were designed to provide information about the depth of sedation whileqNOXwas produced to informon the degree of antinociception.The goal of this study was to compare the reliability of qCON/qNOX to BIS asspecific indicators of response to nociceptive stimulation. Methods: Sixty-two patients undergoing general anesthesia with LMA were included in this study. Institutional Review Board(IRB) approval was obtained, and informed consent was acquired prior to patient enrollment. Inclusion criteria included American Society of Anesthesiologists (ASA) class I-III, 18 to 80 years of age, and either gender. Exclusion criteria included the inability to consent. Withdrawal criteria included conversion to endotracheal tube and EEG malfunction. BIS and qCON/qNOX electrodes were simultaneously placed o62n all patientsprior to induction of anesthesia and were monitored throughout the case, along with other perioperative data, including patient response to noxious stimuli. All intraoperative decisions were made by the primary anesthesiologist without influence from qCON/qNOX. Student’s t-distribution, prediction probability (PK), and ANOVA were used to statistically compare the relative ability to detect nociceptive stimuli for each index. Twenty patients were included for the preliminary analysis. Results: A comparison of overall intraoperative BIS, qCON and qNOX indices demonstrated no significant difference between the three measures (N=62, p> 0.05). Meanwhile, index values for qNOX (62±18) were significantly higher than those for BIS (46±14) and qCON (54±19) immediately preceding patient responses to nociceptive stimulation in a preliminary analysis (N=20, * p= 0.0408). Notably, certain hemodynamic measurements demonstrated a significant increase in response to painful stimuli (MAP increased from74±13 mm Hg at baseline to 84± 18 mm Hg during noxious stimuli [p= 0.032] and HR from 76±12 BPM at baseline to 80±13BPM during noxious stimuli[p=0.078] respectively). Conclusion: In this observational study, BIS and qCON/qNOX provided comparable information on patients’ level of sedation throughout the course of an anesthetic. Meanwhile, increases in qNOX values demonstrated a superior correlation to an imminent response to stimulation relative to all other indices.

Keywords: antinociception, bispectral index (BIS), general anesthesia, laryngeal mask airway, qCON/qNOX

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Authors: W. Rowan, Y. O’Connor, L. Lynch, C. Heavin

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Situation Awareness can offer the potential for conscious dynamic reflection. In an era of online health data sharing, it is becoming increasingly important that users of health social networks (HSNs) have the information necessary to make informed decisions as part of the registration process and in the provision of eConsent. This research aims to leverage an adapted Situation Awareness (SA) model to explore users’ decision making processes in the provision of eConsent. A HSN platform was used to investigate these behaviours. A mixed methods approach was taken. This involved the observation of registration behaviours followed by a questionnaire and focus group/s. Early results suggest that users are apt to automatically accept eConsent, and only later consider the long-term implications of sharing their personal health information. Further steps are required to continue developing knowledge and understanding of this important eConsent process. The next step in this research will be to develop a set of guidelines for the improved presentation of eConsent on the HSN platform.

Keywords: eConsent, health social network, mixed methods, situation awareness

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Authors: Alok Madan, Ashok Gupta, Arshad K. Hashmi

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Non-linear dynamic time history analysis is considered as the most advanced and comprehensive analytical method for evaluating the seismic response and performance of multi-degree-of-freedom building structures under the influence of earthquake ground motions. However, effective and accurate application of the method requires the implementation of advanced hysteretic constitutive models of the various structural components including masonry infill panels. Sophisticated computational research tools that incorporate realistic hysteresis models for non-linear dynamic time-history analysis are not popular among the professional engineers as they are not only difficult to access but also complex and time-consuming to use. And, commercial computer programs for structural analysis and design that are acceptable to practicing engineers do not generally integrate advanced hysteretic models which can accurately simulate the hysteresis behavior of structural elements with a realistic representation of strength degradation, stiffness deterioration, energy dissipation and ‘pinching’ under cyclic load reversals in the inelastic range of behavior. In this scenario, push-over or non-linear static analysis methods have gained significant popularity, as they can be employed to assess the seismic performance of building structures while avoiding the complexities and difficulties associated with non-linear dynamic time-history analysis. “Push-over” or non-linear static analysis offers a practical and efficient alternative to non-linear dynamic time-history analysis for rationally evaluating the seismic demands. The present paper is based on the analytical investigation of the effect of distribution of masonry infill panels over the elevation of planar masonry infilled reinforced concrete (R/C) frames on the seismic demands using the capacity spectrum procedures implementing nonlinear static analysis (pushover analysis) in conjunction with the response spectrum concept. An important objective of the present study is to numerically evaluate the adequacy of the capacity spectrum method using pushover analysis for performance based design of masonry infilled R/C frames for near-field earthquake ground motions.

Keywords: nonlinear analysis, capacity spectrum method, response spectrum, seismic demand, near-field earthquakes

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Authors: Maad Kamal Al-Anni

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This study is about an algorithmic dependence of Artificial Neural Network on Multilayer Perceptron (MPL) pertaining to the classification and clustering presentations for Mobile Adhoc Network vulnerabilities. Moreover, mobile ad hoc network (MANET) is ubiquitous intelligent internetworking devices in which it has the ability to detect their environment using an autonomous system of mobile nodes that are connected via wireless links. Security affairs are the most important subject in MANET due to the easy penetrative scenarios occurred in such an auto configuration network. One of the powerful techniques used for inspecting the network packets is Intrusion Detection System (IDS); in this article, we are going to show the effectiveness of artificial neural networks used as a machine learning along with stochastic approach (information gain) to classify the malicious behaviors in simulated network with respect to different IDS techniques. The monitoring agent is responsible for detection inference engine, the audit data is collected from collecting agent by simulating the node attack and contrasted outputs with normal behaviors of the framework, whenever. In the event that there is any deviation from the ordinary behaviors then the monitoring agent is considered this event as an attack , in this article we are going to demonstrate the  signature-based IDS approach in a MANET by implementing the back propagation algorithm over ensemble-based Traffic Table (TT), thus the signature of malicious behaviors or undesirable activities are often significantly prognosticated and efficiently figured out, by increasing the parametric set-up of Back propagation algorithm during the experimental results which empirically shown its effectiveness  for the ratio of detection index up to 98.6 percentage. Consequently it is proved in empirical results in this article, the performance matrices are also being included in this article with Xgraph screen show by different through puts like Packet Delivery Ratio (PDR), Through Put(TP), and Average Delay(AD).

Keywords: Intrusion Detection System (IDS), Mobile Adhoc Networks (MANET), Back Propagation Algorithm (BPA), Neural Networks (NN)

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Authors: Bishoy Abouelsoud Saad Amin

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This paper examines the use of computer and its related health hazard among computer users in South-Western zone of Nigeria. Two hundred and eighteen (218) computer users constituted the population used to evaluate association between posture, extensive computer use and related health hazard. The instruments for the study are a questionnaire on demographics, lifestyle, body features and work ability index while mean rating, standard deviation and t test were used for data analysis. Identified health related hazard include damages to the eyesight, bad posture, arthritis, musculoskeletal disorders, headache, stress and so on. The results showed that factors such as work demand, posture, closeness to computer screen and excessive working hours on computers constitute health hazards in both old and young computer users of various gender. It is therefore recommended that total number of hours spent with computer should be monitored and controlled.

Keywords: computer game, metaphor, middle school students, virtual environments computer auditing, risk, measures to prevent, information management computer-related health hazard, musculoskeletal disorders, computer usage, work ability index

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Authors: Folasade R. Sulaiman

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Pupils’ health and nutrition are basically important to their schooling. The preponderance of avoidable deaths among children in Africa (WHO, 2000) may not be unconnected with the nutritional and health education status of families and communities that have their children as school clients. This study adopted a descriptive survey design focusing on the assessment of the level of nutritional and health education of families and community members in the rural riverine areas of Ogun State. Two research questions were raised. The Nutritional and Health Education of Families and Communities Inventory (NHEFCI) was used to collect data from 250 rural child-bearing aged women, and 0.73 test-retest reliability coefficient was established to determine the strength of the instrument. Data collected were analysed using descriptive statistics of frequency counts, percentages and mean in accordance with research questions raised in the study. The findings revealed amongst others: that 65% of the respondents had low level of nutritional and health education among the families and community members; while 72% had low level of awareness of the possible influence of nutritional and health education on the learning outcomes of the children. Based on the findings, it was recommended among others that government should intensify efforts on sensitization, mass literacy campaign etc.; also improve upon the already existing School Feeding Programme in Nigerian primary schools to provide at least one balanced diet for children while in school; community health workers, social workers, Non-Governmental Organizations (NGO) should collaborate with international Organizations like UNICEF, UNESCO, WHO etc. to organize sensitization programmes for members of the rural riverine communities on the importance of meeting the health and nutritional needs of their children in order to attain their educational potentials.

Keywords: nutritional and health education, learning capacities, school-age children, universal basic education, rural riverine areas

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Authors: Damilohun D. Ayoyo, Anthony Mpiani, Temitope B. Oriola

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The debate on women’s roles in insurgencies and terrorist organizations continues to garner scholarly attention. While some scholars view women insurgents and terrorists as perpetrators, others have argued that they are non-agents and victims. This paper de/reconstructs the notion of ‘women as perpetrators’ of terrorism. Drawing on the narratives of rescued female Boko Haram operatives, and Boko Haram’s tactics for recruiting and deploying women and girls, the paper advances three main arguments. First, the growing social construction of women as perpetrators of terrorism – particularly radical Islamic terrorism – downplays the socio-cultural and structural processes leading to women’s involvement with terrorist organizations. Second, women agency in Boko Haram activities is better understood when grounded in the cultural and structural contexts of Northern Nigeria, Boko Haram’s construction of ‘female,’ and the experiences of female Boko Haram operatives. Third, the mechanisms through which female Boko Haram operatives are recruited and deployed make them more of non-agents and victims than perpetrators of terrorism. The paper draws on the agency-structure approach and argues that the gendered power asymmetries embedded in the cultures and structures of Northern Nigeria –the base of Boko Haram– contribute to the nature and dynamics of women’s involvement in the insurgency. Although the paper does not negate the agency of women in terrorism, it aligns with the studies that consider women insurgents as more victims than perpetrators of terror.

Keywords: Boko Haram, female agency, Northern Nigeria, patriarchy, perpetrator of terror, radical Islamic terrorism, sharia, victim of terror, women insurgents

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Authors: Lorho Mary Maheo, Arundhati Maibam Devi

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Background: Maternal and child health (MCH) cares are the health services provided to mothers and children. It includes the health promotion, preventive, curative and rehabilitation health care for mothers and children. Materials and method: The present study sample comprises of 208 women within the age range 15-69 years from two remote villages of Tamenglong District in Manipur. They were randomly chosen for assessing their health as well as the child’s health adopting an interview schedule method. Results: The findings of the study revealed that majority (80%) of the women have their first conception in their first year of married life. A decadal change has been observed with regard to the last pregnancy i.e., antenatal check-up, place of delivery as well as the service provider. However, irrespective of age of the women, home delivery is still preferred though very few are locally trained. Pre- and post-delivery resting period vary depending on the busy schedule of the agricultural works as the population under study is basically agriculturist. Postnatal care remains to be traditional as they are strongly associated with cultural beliefs and practices that continue to prevail in the studied community. Breast feeding practices such as colostrums given, initiation of breastfeeding, weaning was all taken into account.  Immunization of children has not reached the expected target owing to a variety of reasons. Maternal health care also includes use of birth control measures. The health status of women would invariably improve if family planning is meaningfully adopted. Only 10.1% of the women adopted the modern birth control implying its deep-rooted value attached to the children. Based on the self-assessment report on their health treatment a good number of the respondents resorted to self-medication even to the extent of buying allopathic medicine without a doctor’s prescription. One important finding from the study is the importance attributed to the traditional health care system which is easily affordable and accessible to the villagers. Conclusion: The overall condition of maternal and child care is way behind till now as no adequate/proper health services are available.

Keywords: antenatal, breastfeeding, child health, maternal, Tamenglong District

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Authors: Suriya

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Rapid socio-economic development and urbanization have led to an increasingly serious air pollution problem in Ulaanbaatar (UB), the capital of Mongolia. PM₂.₅ pollution has become the most pressing aspect of UB air pollution. Therefore, monitoring and predicting PM₂.₅ concentration in UB is of great significance for the health of the local people and environmental management. As of yet, very few studies have used models to predict PM₂.₅ concentrations in UB. Using data from 0:00 on June 1, 2018, to 23:00 on April 30, 2020, we proposed two deep learning models based on Bayesian-optimized LSTM (Bayes-LSTM) and CNN-LSTM. We utilized hourly observed data, including Himawari8 (H8) aerosol optical depth (AOD), meteorology, and PM₂.₅ concentration, as input for the prediction of PM₂.₅ concentrations. The correlation strengths between meteorology, AOD, and PM₂.₅ were analyzed using the gray correlation analysis method; the comparison of the performance improvement of the model by using the AOD input value was tested, and the performance of these models was evaluated using mean absolute error (MAE) and root mean square error (RMSE). The prediction accuracies of Bayes-LSTM and CNN-LSTM deep learning models were both improved when AOD was included as an input parameter. Improvement of the prediction accuracy of the CNN-LSTM model was particularly enhanced in the non-heating season; in the heating season, the prediction accuracy of the Bayes-LSTM model slightly improved, while the prediction accuracy of the CNN-LSTM model slightly decreased. We propose two novel deep learning models for PM₂.₅ concentration prediction in UB, Bayes-LSTM, and CNN-LSTM deep learning models. Pioneering the use of AOD data from H8 and demonstrating the inclusion of AOD input data improves the performance of our two proposed deep learning models.

Keywords: deep learning, AOD, PM2.5, prediction, Ulaanbaatar

Procedia PDF Downloads 49