Search results for: mobile health monitoring

Authors: Cindy de Frias, Erum Whyne

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Objectives: The current study examined whether the link between stress and health-related quality of life was buffered by protective factors, namely mindfulness, in a sample of middle-aged and older adults. Method: In this cross-sectional study, 134 healthy, community-dwelling adults (aged 50–85 years) were recruited from Dallas, Texas. The participants were screened for depressive symptoms and severity (using the Patient Health Questionnaire [PHQ-9]). All participants completed measures of self-reported health status (i.e., SF-36v2: mental and physical health composites), life stress (using the Elder’s Life Stress Inventory [ELSI]), and trait mindfulness (i.e., Mindful Attention Awareness Scale). Results: Hierarchical regressions (covarying for age, gender, and education) showed that life stress was inversely related to physical and mental health. Mindfulness was positively related to mental health. The negative effect of life stress on mental health was weakened for those individuals with greater trait mindfulness. Discussion: The results suggest that mindfulness is a powerful, adaptive strategy that may protect middle-aged and older adults from the well-known harmful effects of stress on healthy aging.

Keywords: health, stress, mindfulness, aging

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Authors: Vesna Karapetkovska Hristova, M. Ayaz Ahmad, Julijana Tomovska, Biljana Bogdanova Popov, Blagojce Najdovski

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The average total concentrations of heavy metals; (cadmium [Cd], copper [Cu], nickel [Ni], lead [Pb], and zinc [Zn]) were analyzed in soil and vegetables samples collected from the different region of Macedonia during the years 2010-2012. Basic soil properties such as pH, organic matter and clay content were also included in the study. The average concentrations of Cd, Cu, Ni, Pb, Zn in the A horizon (0-30 cm) of agricultural soils were as follows, respectively: 0.25, 5.3, 6.9, 15.2, 26.3 mg kg-1 of soil. We have found that neural networking model can be considered as a tool for prediction and spatial analysis of the processes controlling the metal transfer within the soil-and vegetables. The predictive ability of such models is well over 80% as compared to 20% for typical regression models. A radial basic function network reflects good predicting accuracy and correlation coefficients between soil properties and metal content in vegetables much better than the back-propagation method. Neural Networking / soft computing can support the decision-making processes at different levels, including agro ecology, to improve crop management based on monitoring data and risk assessment of metal transfer from soils to vegetables.

Keywords: soft computing approach, total concentrations, heavy metals, agricultural soils

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Authors: Yasinta Ratna Esti Wulandari, Vivitri Dewi Prasasty, Adrianus Rio, Cindy Geniola

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Mulberry is a plant that widely cultivated around the world, mostly for silk industry. In recent years, the study showed that the mulberry leaves have an anti-diabetic effect which mostly comes from the compound known as 1-deoxynojirimycin (DNJ). DNJ is a very potent α-glucosidase inhibitor. It will decrease the degradation rate of carbohydrates in digestive tract, leading to slower glucose absorption and reducing the post-prandial glucose level significantly. The mulberry leaves also known as the best source of DNJ. Since then, the DNJ in mulberry leaves had received a considerable attention, because of the increased number of diabetic patients and the raise of people awareness to find a more natural cure for diabetic. The DNJ content in mulberry leaves varied depend on the mulberry species, leaf’s age, and the plant’s growth environment. Few of the mulberry varieties that were cultivated in Indonesiaare Morus alba var. kanva-2, M. alba var. multicaulis, M. bombycis var. lembang, and M. cathayana. The lack of data concerning phytochemicals contained in the Indonesian mulberry leaves are restraining their use in the medicinal field. The aim of this study is to fully utilize the use of mulberry leaves cultivated in Indonesia as a medicinal herb in local, national, or global community, by determining the DNJ and other phytochemical contents in them. This study used eight leaf samples which are the young leaves and mature leaves of both Morus alba var. kanva-2, M. alba var. multicaulis, M. bombycis var. lembang, and M. cathayana. The DNJ content was analyzed using reverse phase high performance liquid chromatography (HPLC). The stationary phase was silica C18 column and the mobile phase was acetonitrile:acetic acid 0.1% 1:1 with elution rate 1 mL/min. Prior to HPLC analysis the samples were derivatized with FMOC to ensure the DNJ detectable by VWD detector at 254 nm. Results showed that the DNJ content in samples are ranging from 2.90-0.07 mg DNJ/ g leaves, with the highest content found in M. cathayana mature leaves (2.90 ± 0.57 mg DNJ/g leaves). All of the mature leaf samples also found to contain higher amount of DNJ from their respective young leaf samples. The phytochemicals in leaf samples was tested using qualitative test. Result showed that all of the eight leaf samples contain alkaloids, phenolics, flavonoids, tannins, and terpenes. The presence of this phytochemicals contribute to the therapeutic effect of mulberry leaves. The pyrolysis-gas chromatography-mass spectrometry (Py-GC-MS) analysis was also performed to the eight samples to quantitatively determine their phytochemicals content. The pyrolysis temperature was set at 400 °C, with capillary column Phase Rtx-5MS 60 × 0.25 mm ID stationary phase and helium gas mobile phase. Few of the terpenes found are known to have anticancer and antimicrobial properties. From all the results, all of four samples of mulberry leaves which are cultivated in Indonesia contain DNJ and various phytochemicals like alkaloids, phenolics, flavonoids, tannins, and terpenes which are beneficial to our health.

Keywords: Morus, 1-deoxynojirimycin, HPLC, Py-GC-MS

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Authors: Thobela Conco, Sheena Kumari, Chika Nnadozie, Mahmoud Nasr, Thor A. Stenström, Mushal Ali, Arshad Ismail, Faizal Bux

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The discharge of antibiotics and its residues into the wastewater treatment plants (WWTP’s) create a conducive environment for the development of antibiotic resistant pathogens. This presents a risk of potential dissemination of antibiotic resistant pathogens and antibiotic resistance genes into the environment. It is, therefore, necessary to study the level of antibiotic resistance genes (ARG’s) among bacterial pathogens that proliferate in biological wastewater treatment systems. In the current study, metagenomic and meta-transcriptomic sequences of samples collected from the influents, secondary effluents and post chlorinated effluents of three wastewater treatment plants treating domestic and hospital effluents in Durban, South Africa, were analyzed for profiling of ARG’s among bacterial pathogens. Results show that a variety of ARG’s, mostly, aminoglycoside, β-lactamases, tetracycline and sulfonamide resistance genes were harbored by diverse bacterial genera found at different stages of treatment. A significant variation in diversity of pathogen and ARGs between the treatment plant was observed; however, treated final effluent samples from all three plants showed a significant reduction in bacterial pathogens and detected ARG’s. Both pre- and post-chlorinated samples showed the presence of mobile genetic elements (MGE’s), indicating the inefficiency of chlorination to remove of ARG’s integrated with MGE’s. In conclusion, the study showed the wastewater treatment plant efficiently caused the reduction and removal of certain ARG’s, even though the initial focus was the removal of biological nutrients.

Keywords: antibiotic resistance, mobile genetic elements, wastewater, wastewater treatment plants

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Authors: M. Cuevas-González, O. Monserrat, A. Barra, C. Reyes-Carmona, R.M. Mateos, J. P. Galve, R. Sarro, M. Cantalejo, E. Peña, M. Martínez-Corbella, J. A. Luque, J. M. Azañón, A. Millares, M. Béjar, J. A. Navarro, L. Solari

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Geohazard prone areas require continuous monitoring to detect risks, understand the phenomena occurring in those regions and prevent disasters. Satellite interferometry (InSAR) has come to be a trustworthy technique for ground movement detection and monitoring in the last few years. InSAR based techniques allow to process large areas providing high number of displacement measurements at low cost. However, the results provided by such techniques are usually not easy to interpret by non-experienced users hampering its use for decision makers. This work presents a set of tools developed in the framework of different projects (Momit, Safety, U-Geohaz, Riskcoast) and an example of their use in the Granada Coastal area (Spain) is shown. The ADA (Active Displacement Areas) tool have been developed with the aim of easing the management, use and interpretation of InSAR based results. It provides a semi-automatic extraction of the most significant ADAs through the application ADAFinder tool. This tool aims to support the exploitation of the European Ground Motion Service (EU-GMS), which will provide consistent, regular and reliable information regarding natural and anthropogenic ground motion phenomena all over Europe.

Keywords: ground displacements, InSAR, natural hazards, satellite imagery

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Authors: Deniz Sari, Selahattin İncecik, Nesimi Ozkurt

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Surface ozone, which named as one of the most critical pollutants in the 21th century, threats to human health, forest and vegetation. Specifically, in rural areas surface ozone cause significant influences on agricultural productions and trees. In this study, in order to understand to the surface ozone levels in rural areas we focus on the north-western side of Biga Peninsula which covers by the mountainous and forested area. Ozone concentrations were measured for the first time with passive sampling at 10 sites and two online monitoring stations in this rural area from 2013 and 2015. Using with the daytime hourly O3 measurements during light hours (08:00–20:00) exceeding the threshold of 40 ppb over the 3 months (May, June and July) for agricultural crops, and over the six months (April to September) for forest trees AOT40 (Accumulated hourly O3 concentrations Over a Threshold of 40 ppb) cumulative index was calculated. AOT40 is defined by EU Directive 2008/50/EC to evaluate whether ozone pollution is a risk for vegetation, and is calculated by using hourly ozone concentrations from monitoring systems. In the present study, we performed the trajectory analysis by The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to follow the long-range transport sources contributing to the high ozone levels in the region. The ozone episodes observed between 2013 and 2015 were analysed using the HYSPLIT model developed by the NOAA-ARL. In addition, the cluster analysis is used to identify homogeneous groups of air mass transport patterns can be conducted through air trajectory clustering by grouping similar trajectories in terms of air mass movement. Backward trajectories produced for 3 years by HYSPLIT model were assigned to different clusters according to their moving speed and direction using a k-means clustering algorithm. According to cluster analysis results, northerly flows to study area cause to high ozone levels in the region. The results present that the ozone values in the study area are above the critical levels for forest and vegetation based on EU Directive 2008/50/EC.

Keywords: AOT40, Biga Peninsula, HYSPLIT, surface ozone

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Authors: Brighton Chamunorwa

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The current remote sensing of water quality procedures does not provide a step representing physical visualisation of the monitored dam. The application of the remote sensing of water quality techniques may benefit from use of mathematical morphology operators for shape identification. Given an input of dam outline, morphological operators such as the hit or miss transform identifies if the water body is present on input remotely sensed images. This study seeks to determine the accuracy of the hit or miss transform to identify dams monitored by the water resources authorities in South Africa on satellite images. To achieve this objective the study download a Landsat image acquired in winter and tested the capability of the hit or miss transform using shapefile boundaries of dams in the crocodile marico catchment. The results of the experiment show that it is possible to detect most dams on the Landsat image after the adjusting the erosion operator to detect pixel matching a percentage similarity of 80% and above. Successfully implementation of the current study contributes towards optimisation of mathematical morphology image operators. Additionally, the effort helps develop remote sensing of water quality monitoring with improved simulation of the conventional procedures.

Keywords: hit or miss transform, mathematical morphology, remote sensing, water quality monitoring

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Authors: Vahid Bayrami Rad

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In this research, common methods and techniques have been investigated with a focus on intelligent fault finding and monitoring systems in the oil industry. In fact, remote and intelligent control methods are considered a necessity for implementing various operations in the oil industry, but benefiting from the knowledge extracted from countless data generated with the help of data mining algorithms. It is a avoid way to speed up the operational process for monitoring and troubleshooting in today's big oil companies. Therefore, by comparing data mining algorithms and checking the efficiency and structure and how these algorithms respond in different conditions, The proposed (Bayesian) algorithm using data clustering and their analysis and data evaluation using a colored Petri net has provided an applicable and dynamic model from the point of view of reliability and response time. Therefore, by using this method, it is possible to achieve a dynamic and consistent model of the remote control system and prevent the occurrence of leakage in oil pipelines and refineries and reduce costs and human and financial errors. Statistical data The data obtained from the evaluation process shows an increase in reliability, availability and high speed compared to other previous methods in this proposed method.

Keywords: wireless sensors, petroleum equipment troubleshooting, Bayesian algorithm, colored Petri net, rapid miner, data mining-reliability

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Authors: Chelsea Peterson-Salahuddin

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Over the past decade, news outlets have increasingly used social media as a means to create and distribute news content to audiences. Ephemerality, the transitory nature of media, and mobility, media viewing on mobile technologies, are two increasingly salient attributes of social media content; yet little is known about how these features influence news selection practices of news outlets when distributing news via social media. To account for this gap, this study examines the influences of ephemerality and mobility on social media news content on the social media application Snapchat, in order to understand how these qualities of digital media influence and shape news content. Findings from this study suggest that understandings of ephemerality and mobility play a key role in influencing social media news. This paper suggests that as these factors become increasingly salient in our dominant news viewing environments, being able to understand how they manifest themselves in online news reporting practices is critical for both scholars and practitioners of news as they aim to understand what 'newsworthiness' means in the current, digital age. Findings from this study also enhance our current understandings of how the technological affordances of online and digital media platforms play a key role in shaping the kinds being produced and what information is being prioritized and highlighted in our contemporary news media environment. This is especially important in our current era where new mediums and technologies for news dissemination are continuously arising, and reorienting our understandings of what is considered ‘news'. As a key site of mass communication, discourse, and stories highlighted in the news do critical work in defining culture and ideology. Thus, better understanding the contours of news in our contemporary moment is critical in understanding cultural norms and meaning-making.

Keywords: content analysis, ephemerality, mobile communication, social media news

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Authors: Bolin Hua

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In city governance, various data are involved, including city component data, demographic data, housing data and all kinds of business data. These data reflects different aspects of people, events and activities. Data generated from various systems are different in form and data source are different because they may come from different sectors. In order to reflect one or several facets of an event or rule, data from multiple sources need fusion together. Data from different sources using different ways of collection raised several issues which need to be resolved. Problem of data fusion include data update and synchronization, data exchange and sharing, file parsing and entry, duplicate data and its comparison, resource catalogue construction. Governments adopt statistical analysis, time series analysis, extrapolation, monitoring analysis, value mining, scenario prediction in order to achieve pattern discovery, law verification, root cause analysis and public opinion monitoring. The result of Multi-source data fusion is to form a uniform central database, which includes people data, location data, object data, and institution data, business data and space data. We need to use meta data to be referred to and read when application needs to access, manipulate and display the data. A uniform meta data management ensures effectiveness and consistency of data in the process of data exchange, data modeling, data cleansing, data loading, data storing, data analysis, data search and data delivery.

Keywords: multi-source data fusion, urban comprehensive management, information fusion, government data

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Authors: Stefania Fortino, Petr Hradil, Timo Avikainen

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Timber bridges have an excellent environmental performance, are economical, relatively easy to build and can have a long service life. However, the durability of these bridges is the main problem because of their exposure to outdoor climate conditions. The moisture content accumulated in wood for long periods, in combination with certain temperatures, may cause conditions suitable for timber decay. In addition, moisture content variations affect the structural integrity, serviceability and loading capacity of timber bridges. Therefore, the monitoring of the moisture content in wood is important for the durability of the material but also for the whole superstructure. The measurements obtained by the usual sensor-based techniques provide hygro-thermal data only in specific locations of the wood components. In this context, the monitoring can be assisted by numerical modelling to get more information on the hygro-thermal response of the bridges. This work presents a hygro-thermal model based on a multi-phase moisture transport theory to predict the distribution of moisture content, relative humidity and temperature in wood. Below the fibre saturation point, the multi-phase theory simulates three phenomena in cellular wood during moisture transfer, i.e., the diffusion of water vapour in the pores, the sorption of bound water and the diffusion of bound water in the cell walls. In the multi-phase model, the two water phases are separated, and the coupling between them is defined through a sorption rate. Furthermore, an average between the temperature-dependent adsorption and desorption isotherms is used. In previous works by some of the authors, this approach was found very suitable to study the moisture transport in uncoated and coated stress-laminated timber decks. Compared to previous works, the hygro-thermal fluxes on the external surfaces include the influence of the absorbed solar radiation during the time and consequently, the temperatures on the surfaces exposed to the sun are higher. This affects the whole hygro-thermal response of the timber component. The multi-phase model, implemented in a user subroutine of Abaqus FEM code, provides the distribution of the moisture content, the temperature and the relative humidity in a volume of the timber deck. As a case study, the hygro-thermal data in wood are collected from the ongoing monitoring of the stress-laminated timber deck of Tapiola Bridge in Finland, based on integrated humidity-temperature sensors and the numerical results are found in good agreement with the measurements. The proposed model, used to assist the monitoring, can contribute to reducing the maintenance costs of bridges, as well as the cost of instrumentation, and increase safety.

Keywords: moisture content, multi-phase models, solar radiation, timber decks, FEM

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Authors: K. M. G. T. R. Waidyarathna, S. M. Vidanagamachchi

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Public Health System exists in Sri Lanka has a satisfactory complete information flow when compared to other systems in developing countries. The availability of a good health information system contributed immensely to achieve health indices that are in line with the developed countries like US and UK. The health information flow at the moment is completely paper based. In Sri Lanka, the fields like banking, accounting and engineering have incorporated information and communication technology to the same extent that can be observed in any other country. The field of medicine has behind those fields throughout the world mainly due to its complexity, issues like privacy, confidentially and lack of people with knowledge in both fields of Information Technology (IT) and Medicine. Sri Lanka’s situation is much worse and the gap is rapidly increasing with huge IT initiatives by private-public partnerships in all other countries. The major goal of the framework is to support minimizing the spreading diseases. To achieve that a web based framework should be implemented for this application domain with web mapping. The aim of this GIS based public health system is a secure, flexible, easy to maintain environment for creating and maintaining public health records and easy to interact with relevant parties.

Keywords: DHIS2, GIS, public health, Sri Lanka

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Authors: Arjun Goutham, Chaitanya Sridhar, Sunita Maheshwari, Robin Uthappa, Prasanna Gopinath

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In alignment with the growth in the sporting industry, a number of people playing and competing in sports are growing exponentially across the globe. However, the number of sports psychology experts are not growing at a similar rate, especially in the Asian and more so, Indian context. Hence, the access to actionable mental training solutions specific to individual athletes is limited. Also, the time constraint an athlete faces due to their intense training schedule makes one-on-one sessions difficult. One of the means to bridge that gap is through technology. Technology makes individualization possible. It allows for easy access to specific-qualitative content/information and provides a medium to place individualized assessments, analysis, solutions directly into an athlete's hands. This enables mental training awareness, education, and real-time actionable solutions possible for athletes in-spite of the limitation of available sports psychology experts in their region. Furthermore, many athletes are hesitant to seek support due to the stigma of appearing weak. Such individuals would prefer a more discreet way. Athletes who have strong mental performance tend to produce better results. The mobile application helps to equip athletes with assessing and developing their mental strategies directed towards improving performance on an ongoing basis. When an athlete understands their strengths and limitations in their mental application, they can focus specifically on applying the strategies that work and improve on zones of limitation. With reports, coaches get to understand the unique inner workings of an athlete and can utilize the data & analysis to coach them with better precision and use coaching styles & communication that suits better. Systematically capturing data and supporting athletes(with individual-specific solutions) or teams with assessment, planning, instructional content, actionable tools & strategies, reviewing mental performance and the achievement of objectives & goals facilitate for a consistent mental skills development at all levels of sporting stages of an athlete's career. The mobile application will help athletes recognize and align with their stable attributes such as their personalities, learning & execution modalities, challenges & requirements of their sport, etc and help develop dynamic attributes like states, beliefs, motivation levels, focus etc. with practice and training. It will provide measurable analysis on a regular basis and help them stay aligned to their objectives & goals. The solutions are based on researched areas of influence on sporting performance individually or in teams.

Keywords: athletes, mental training, mobile application, performance, sports

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Authors: Jeong-Min Son, Jeong-Hee Eum, Jin-Kyu Min, Uk-Je Sung, Ju-Eun Kim

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While various environmental problems are severe due to climate change, especially in cities where population and development are concentrated, urban thermal environment problems such as heat waves and tropical nights are particularly worsening. Accordingly, the Korean government provides basic data related to the urban thermal environment to support each local government in effectively establishing policies to cope with heat waves. However, the basic data related to the thermal environment provided by the government has limitations in establishing a regional thermal adaptation plan with a minimum unit of cities, counties, and districts. In addition, the urban heat environment perceived by people differs in each region and space. Therefore, it is necessary to prepare practical measures that can be used to establish regional-based policies for heat wave adaptation by identifying people’s heat perception in the entire city. This study aims to develop a mobile phone application (APP) to gather people’s thermal sensation information and create Korea’s first thermal map based on this information. In addition, through this APP, citizens directly propose thermal adaptation policies, and urban planners and policymakers accept citizens' opinions, so this study provides a tool to solve local thermal environment problems. To achieve this purpose, first, the composition and contents of the app were discussed by examining various existing apps and cases for citizen participation and collection of heat information. In addition, factors affecting human thermal comfort, such as spatial, meteorological, and demographic factors, were investigated to construct the APP system. Based on these results, the basic version of the APP was developed. Second, the living lab methodology was adopted to gather people’s heat perception using the developed app to conduct overall evaluation and feedback of people on the APP. The people participating in the living lab were selected as those living in Daegu Metropolitan City, which is located in South Korea and annually records high temperatures. The user interface was improved through the living lab to make the app easier to use and the thermal map was modified. This study expects to establish high-resolution thermal maps for effective policies and measures and to solve local thermal environmental problems using the APP. The collected information can be used to evaluate spatial, meteorological, and demographic characteristics that affect the perceived heat of citizens. In addition, it is expected that the research can be expanded by gathering thermal information perceived by citizens of foreign cities as well as other cities in South Korea through the APP developed in this study.

Keywords: mobile application, living lab, thermal map, climate change adaptation

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Authors: Mitsuo Yoshida

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A significant mercury contamination of soil/sediment was unveiled by an environmental monitoring program in a wetland along La Plata River, west to Montevideo City, Uruguay. The mercury contamination was caused by industrial wastewater discharged from a chlor-alkali plant using a mercury-cell process. The contamination level is above 60 mg/kg in soil/sediment. Most of mercury (Hg) in the environment is inorganic, but some fractions are converted by bacteria to methylmercury (MeHg), a toxic organic compound. MeHg biologically accumulates through a food-chain and become serious public health risk. In order to clarify the contaminated part for countermeasure operation, an intervention value of mercury contamination of sediment/soil was defined as 15 mg/kg (total Hg) by the authority. According to the intervention value, mercury contaminated area in the La Plata site is approximately 48,280 m² and estimated total volume of contaminated sediments/soils was around 18,750 m³. The countermeasures to contaminated zone were proposed in two stages; (i) mitigation of risks for public health and (ii) site remediation. The first stage is an installation of fens and net around the contamination zone, for mitigating risks of exposure, inhalation, and intake. The food chain among wetland-river ecosystem was also interrupted by the installation of net and fens. The state of mercury contamination in La Plata site and plan of countermeasure was disclosed to local people and the public, and consensus on setting off-limit area was successfully achieved. Mass media also contribute to share the information on the contamination site. The cost for countermeasures was borne by the industry under the polluter-pay-principle.

Keywords: chlor-alkali plant, mercury contamination, polluter pay principle, Uruguay, wetland

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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: Mohammad K. Abedin, Mohammad Shahjahan, Zeenat Sultana, Tawfique Jahan, Jesmin Akter

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To strengthen social and behavior change communication (SBCC) capacity of Ministry of Health and Family Welfare (MoHFW) of the Government of Bangladesh, BCCP/BKMI developed two eLearning courses providing opportunities for professional development of SBCC Program Managers who have no access to training or refreshers training. The two eLearning courses – Message and Material Development (MMD) and Monitoring and Evaluation (MandE) of SBCC programs – went online in September 2015, where all users could register their participation so results could be monitored. Methodology: To assess the uses of these courses a randomly selected sample was collected to run a pre and post-test analyses and a phone survey were conducted. Systematic random sampling was used to select a sample of 75 MandE and 25 MMD course participants from a sampling frame of 179 and 51 respectively. Results: As of September 2016, more than 179 learners have completed the MandE course, and 49 learners have completed the MMD course. The users of these courses are program managers, university faculty members, and students. Encouraging results were revealed from the analysis of pre and post-test scores and a phone survey three months after course completion. Test scores suggested a substantial increase in knowledge. The pre-test scores findings suggested that about 19% learners scored high on the MandE. The post-test scores finding indicated a high score (92%) of the sample across 4 modules of MandE. For MMD course in pre-test scoring, 30% of the learners scored high, and 100% scored high at the post-test. It was found that all the learners in the phone survey have discussed the courses. Most of the sharing occurred with colleagues and friends, usually through face to face (70%) interaction. The learners reported that they did recommend the two courses to concerned people. About 67% MandE and 76% MMD learners stated that the concepts that they had to learn during the course were put into practice in their work settings. The respondents for both MandE and MMD courses have provided a valuable set of suggestions that would further strengthen the courses. Conclusions: The study showed that the initiative offered ample opportunities to build capacity in various ways in which the eLearning courses were used. It also highlighted the importance of scaling up these efforts to further strengthen the outcomes.

Keywords: e-learning course, message & material development, monitoring & evaluation, social and behavior change communication

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Authors: Rudy Bahouth, Farouk Benmeddour, Emmanuel Moulin, Jamal Assaad

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Guided ultrasonic waves are used in Non-Destructive Testing (NDT) and Structural Health Monitoring (SHM) for inspection and damage detection. Recently, wireless data transmission using ultrasonic waves in solid metallic channels has gained popularity in some industrial applications such as nuclear, aerospace and smart vehicles. The idea is to find a good substitute for electromagnetic waves since they are highly attenuated near metallic components due to Faraday shielding. The proposed solution is to use ultrasonic guided waves such as Lamb waves as an information carrier due to their capability of propagation for long distances. In addition to this, valuable information about the health of the structure could be extracted simultaneously. In this work, the reliable frequency bandwidth for communication is extracted experimentally from dispersion curves at first. Then, an experimental platform for wireless communication using Lamb waves is described and built. After this, coherent demodulation algorithm used in telecommunications is tested for Amplitude Shift Keying, On-Off Keying and Binary Phase Shift Keying modulation techniques. Signal processing parameters such as threshold choice, number of cycles per bit and Bit Rate are optimized. Experimental results are compared based on the average Bit Error Rate. Results have shown high sensitivity to threshold selection for Amplitude Shift Keying and On-Off Keying techniques resulting a Bit Rate decrease. Binary Phase Shift Keying technique shows the highest stability and data rate between all tested modulation techniques.

Keywords: lamb waves communication, wireless communication, coherent demodulation, bit error rate

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Authors: Farhan Ali

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Use of wastewater for growing vegetables has become a common practice around big cities. Wastewater contains organic material and inorganic elements essential for plant growth but also contain heavy metals, which may be lethal for animals and humans if their concentration increases than permissible limit. To monitor this situation, a survey was conducted to ascertain the addition of heavy metals into agricultural fields through wastewater irrigation and their translocation in to the edible parts of the vegetables. The study highlighted that there is a large accumulation of heavy metals in the soil, which is irrigated with industrial wastewater Laden and people consume vegetables grown in soil irrigated with sewage water to absorb a large amount of these metals. This accumulation of heavy metals in food cause possible health risks for the consumer. Regular monitoring of the levels of pathogens and heavy metals from the waste water drain which effluent are used for growing vegetables and other foodstuffs is essential to monitor excessive accumulation of these metals in the food chain.

Keywords: pathogens, wastewater, concentration, effluent

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Authors: Pedro P. Drumond, Priscilla M. Moura, Marcia M. L. P. Coelho

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The purpose of On-site Stormwater Detention (OSD) system is to promote the detention of addition stormwater runoff caused by impervious areas, in order to maintain the peak flow the same as the pre-urbanization condition. In recent decades, these systems have been built in many cities around the world. However, its real efficiency continues to be unknown due to the lack of research, especially with regard to monitoring its real performance. Thus, this study aims to compare the water level monitoring data of an OSD built in Belo Horizonte/Brazil with the results of theoretical methods simulations, usually adopted in OSD design. There were made two theoretical simulations, one using the Rational Method and Modified Puls method and another using the Soil Conservation Service (SCS) method and Modified Puls method. The monitoring data were obtained with a water level sensor, installed inside the reservoir and connected to a data logger. The comparison of OSD performance was made for 48 rainfall events recorded from April/2015 to March/2017. The comparison of maximum water levels in the OSD showed that the results of the simulations with Rational/Puls and SCS/Puls methods were, on average 33% and 73%, respectively, lower than those monitored. The Rational/Puls results were significantly higher than the SCS/Puls results, only in the events with greater frequency. In the events with average recurrence interval of 5, 10 and 200 years, the maximum water heights were similar in both simulations. Also, the results showed that the duration of rainfall events was close to the duration of monitored hydrograph. The rising time and recession time of the hydrographs calculated with the Rational Method represented better the monitored hydrograph than SCS Method. The comparison indicates that the real discharge coefficient value could be higher than 0.61, adopted in Puls simulations. New researches evaluating OSD real performance should be developed. In order to verify the peak flow damping efficiency and the value of the discharge coefficient is necessary to monitor the inflow and outflow of an OSD, in addition to monitor the water level inside it.

Keywords: best management practices, on-site stormwater detention, source control, urban drainage

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Authors: Mohammed-Hareef Asunramu, Sana Hashemi, Raja Ohri, Luc Worthington, Nadia Zaman, Junkai Zhu

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Background: The 2012 Health and Social Care Act committed to a ‘parity of esteem between mental and physical health services. Although this investment, aimed to both increase the quality of services and ensure the retention of mental health staff, questions remained regarding its ability to prevent mental health problems. One possible solution is a focus on the social determinants of health which have been shown to impact mental health. Aim: To examine the relationship between the index of multiple deprivations (IMD) and the prevalence of common mental health disorders (CMD) for CCGs in NHS England between 2019 and 2020. Design and setting: Cross-sectional analysis of 189 CCGs in NHS England. Methods: A multivariate linear regression model was utilized with CMD as outcome variable and IMD, age and ethnicity as explanatory variables. Datasets were obtained from Public Health England and the latest UK Census. Results: CCG IMD was found to have a significantly positive relationship with CMD. For every 1-point increase in IMD, CMD increases by 0.25%. Ethnicity had a significantly positive relationship with CMD. For every 1% increase in the population that identifies as BME, there is a 0.03% increase in CMD. Age had a significantly negative relationship with CMD. For every 1% increase in the population aged 60+, there is a 0.11% decrease in CMD. Conclusion: This study demonstrates that addressing mental health issues may require a multi-pronged approach. Beyond budget increases, it is essential to prioritize health equity, with careful considerations towards ethnic minorities and different age brackets.

Keywords: deprivation, health inequality, mental health, social determinants

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Authors: Maatouk Mohamed, Nouira Mariem

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Background and aims: Healthcare-associated infections (HAI) represent a major public health problem worldwide. They represent one of the most serious adverse events in health care. The objectives of our study were to estimate the prevalence of HAI at the Charles Nicolle Hospital (CNH) and to identify the main associated factors as well as to estimate the frequency of antibiotic use. Methods: It was a cross sectional study at the CNH with a unique passage per department (OctoberDecember 2018). All patients present at the wards for more than 48 hours were included. All patients from outpatient consultations, emergency and dialysis departments were not included. The site definitions of infections proposed by the Centers for Disease Control and Prevention (CDC) were used. Only clinically and/or microbiologically confirmed active HAIs were included. Results: A total of 318 patients were included with a mean age of 52 years and a sex ratio (Female/Male) of 1.05. A total of 41 patients had one or more active HAIs, corresponding to a prevalence of 13.1% (95% CI: 9.3%-16.9%). The most frequent sites infections were urinary tract infections and pneumonia. Multivariate analysis among adult patients (>=18 years) (n=261), revealed that infection on admission (p=0.01), alcoholism (p=0.01), high blood pressure (p=0.008), having at least one invasive device inserted (p=0.004), and history of recent surgery (p=0.03), increased significantly the risk of HAIs. More than 1 of 3 patients (35.4%) were under antibiotics on the day of the survey, of which more than half (57.4%) were under 2 or more types of antibiotics. Conclusion: The prevalence of HAIs and antibiotic prescriptions at the CNH were considerably high. An infection prevention and control committee, as well as the development of an Antibiotic stewardship program with continuous monitoring using repeated prevalence surveys must be implemented to limit the frequency of these infections effectively.

Keywords: tumors, oesophagectomy, esophagogastric junction, systematic review

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Authors: Maria M. Calheiros, Carla Silva, Eunice Magalhães

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Professionals working in child protection services (CPS) need to have common and clear criteria to identify cases of maltreatment and to differentiate levels of severity in order to determine when CPS intervention is required, its nature and urgency, and, in most countries, the service that will be in charge of the case (community or specialized CPS). Actually, decision-making process is complex in CPS, and, for that reason, such criteria are particularly important for who significantly contribute to that decision-making in child maltreatment cases. The main objective of this presentation is to describe the Maltreatment Severity Assessment Questionnaire (MSQ), specifically designed to be used by professionals in the CPS, which adopts a multidimensional approach and uses a scale of severity within subtypes. Specifically, we aim to provide evidence of validity and reliability of this tool, in order to improve the quality and validity of assessment processes and, consequently, the decision making in CPS. The total sample was composed of 1000 children and/or adolescents (51.1% boys), aged between 0 and 18 years old (M = 9.47; DP = 4.51). All the participants were referred to official institutions of the children and youth protective system. Children and adolescents maltreatment (abuse, neglect experiences and sexual abuse) were assessed with 21 items of the Maltreatment Severity Questionnaire (MSQ), by professionals of CPS. Each item (sub-type) was composed of four descriptors of increasing severity. Professionals rated the level of severity, using a 4-point scale (1= minimally severe; 2= moderately severe; 3= highly severe; 4= extremely severe). The construct validity of the Maltreatment Severity Questionnaire was assessed with a holdout method, performing an Exploratory Factor Analysis (EFA) followed by a Confirmatory Factor Analysis (CFA). The final solution comprised 18 items organized in three factors 47.3% of variance explained. ‘Physical neglect’ (eight items) was defined by parental omissions concerning the insurance and monitoring of the child’s physical well-being and health, namely in terms of clothing, hygiene, housing conditions and contextual environmental security. ‘Physical and Psychological Abuse’ (four items) described abusive physical and psychological actions, namely, coercive/punitive disciplinary methods, physically violent methods or verbal interactions that offend and denigrate the child, with the potential to disrupt psychological attributes (e.g., self-esteem). ‘Psychological neglect’ (six items) involved omissions related to children emotional development, mental health monitoring, school attendance, development needs, as well as inappropriate relationship patterns with attachment figures. Results indicated a good reliability of all the factors. The assessment of child maltreatment cases with MSQ could have a set of practical and research implications: a) It is a valid and reliable multidimensional instrument to measure child maltreatment, b) It is an instrument integrating the co-occurrence of various types of maltreatment and a within-subtypes scale of severity; c) Specifically designed for professionals, it may assist them in decision-making processes; d) More than using case file reports to evaluate maltreatment experiences, researchers could guide more appropriately their research about determinants and consequences of maltreatment.

Keywords: assessment, maltreatment, children and youth, decision-making

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Authors: Xiaobo Liu, Rakesh Mishra, Yun Zhang

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Continuous monitoring of forest canopy height with large coverage is essential for obtaining forest carbon stocks and emissions, quantifying biomass estimation, analyzing vegetation coverage, and determining biodiversity. LiDAR can be used to collect accurate woody vegetation structure such as canopy height. However, LiDAR’s coverage is usually limited because of its high cost and limited maneuverability, which constrains its use for dynamic and large area forest canopy monitoring. On the other hand, optical satellite images, like Sentinel-2, have the ability to cover large forest areas with a high repeat rate, but they do not have height information. Hence, exploring the solution of integrating LiDAR data and Sentinel-2 images to enlarge the coverage of forest canopy height prediction and increase the prediction repeat rate has been an active research topic in the environmental remote sensing community. In this study, we explore the potential of training a Random Forest Regression (RFR) model and a Convolutional Neural Network (CNN) model, respectively, to develop two predictive models for predicting and validating the forest canopy height of the Acadia Forest in New Brunswick, Canada, with a 10m ground sampling distance (GSD), for the year 2018 and 2021. Two 10m airborne LiDAR-derived canopy height models, one for 2018 and one for 2021, are used as ground truth to train and validate the RFR and CNN predictive models. To evaluate the prediction performance of the trained RFR and CNN models, two new predicted canopy height maps (CHMs), one for 2018 and one for 2021, are generated using the trained RFR and CNN models and 10m Sentinel-2 images of 2018 and 2021, respectively. The two 10m predicted CHMs from Sentinel-2 images are then compared with the two 10m airborne LiDAR-derived canopy height models for accuracy assessment. The validation results show that the mean absolute error (MAE) for year 2018 of the RFR model is 2.93m, CNN model is 1.71m; while the MAE for year 2021 of the RFR model is 3.35m, and the CNN model is 3.78m. These demonstrate the feasibility of using the RFR and CNN models developed in this research for predicting large-coverage forest canopy height at 10m spatial resolution and a high revisit rate.

Keywords: remote sensing, forest canopy height, LiDAR, Sentinel-2, artificial intelligence, random forest regression, convolutional neural network

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Authors: Jinsiang Shaw, Sheng-Xiang Xu

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This paper presents the development of an autonomous automated guided vehicle (AGV) with a robot arm attached on top of it within the framework of robot operation system (ROS). ROS can provide libraries and tools, including hardware abstraction, device drivers, libraries, visualizers, message-passing, package management, etc. For this reason, this AGV can provide automatic navigation and parts transportation and pick-and-place task using robot arm for typical industrial production line use. More specifically, this AGV will be controlled by an on-board host computer running ROS software. Command signals for vehicle and robot arm control and measurement signals from various sensors are transferred to respective microcontrollers. Users can operate the AGV remotely through the TCP / IP protocol and perform SLAM (Simultaneous Localization and Mapping). An RGBD camera and LIDAR sensors are installed on the AGV, using these data to perceive the environment. For SLAM, Gmapping is used to construct the environment map by Rao-Blackwellized particle filter; and AMCL method (Adaptive Monte Carlo localization) is employed for mobile robot localization. In addition, current AGV position and orientation can be visualized by ROS toolkit. As for robot navigation and obstacle avoidance, A* for global path planning and dynamic window approach for local planning are implemented. The developed ROS AGV with a robot arm on it has been experimented in the university factory. A 2-D and 3-D map of the factory were successfully constructed by the SLAM method. Base on this map, robot navigation through the factory with and without dynamic obstacles are shown to perform well. Finally, pick-and-place of parts using robot arm and ensuing delivery in the factory by the mobile robot are also accomplished.

Keywords: automated guided vehicle, navigation, robot operation system, Simultaneous Localization and Mapping

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Authors: Swati Naruka

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"Looking after one’s mind is as important as looking after one’s body". As part of one’s overall health, mental and emotional health or well being is a necessary condition to enable one to manage one’s life successfully. Mental health is the capacity of an individual to form harmonious adjustments to one’s social and physical environments. Universities and colleges are dealing with substantial challenges posed by the changing mental health needs of today’s college students. It is important for administrators, faculty, and staff to understand the profound impact that mental health problems can have on all aspects of campus life, and to treat mental health issues as an institutional responsibility and priority. Counselling centres can respond effectively to the current challenges if they have the support and commitment of the administration; and if they take steps to balance the demand for services with existing resources by reviewing priorities, establishing appropriate limits, employing innovative strategies, and practicing good self-care to minimize stress and burnout. The need for counselling centres has never been greater. They will continue to play an important role in supporting the mission of higher education institutions by providing counselling for students who are experiencing problems and assisting them in achieving their educational and personal goals.

Keywords: mental health, well being, India, college students

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Authors: James Skon, Irina Beshentseva, Michelle Polak

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Wifi solutions come in two major classes. Small Office/Home Office (SOHO) WiFi, characterized by inexpensive WiFi routers, with one or two service set identifiers (SSIDs), and a single shared passphrase. These access points provide no significant user management or monitoring, and no aggregation of monitoring and control for multiple routers. The other solution class is managed enterprise WiFi solutions, which involve expensive Access Points (APs), along with (also costly) local or cloud based management components. These solutions typically provide portal based login, per user virtual local area networks (VLANs), and sophisticated monitoring and control across a large group of APs. The cost for deploying and managing such managed enterprise solutions is typically about 10 fold that of inexpensive consumer APs. Low revenue organizations, such as schools, non-profits, non-government organizations (NGO's), small businesses, and even homes cannot easily afford quality enterprise WiFi solutions, though they may need to provide quality WiFi access to their population. Using available lower cost Wifi solutions can significantly reduce their ability to provide reliable, secure network access. This project explored and created a new approach for providing secured managed enterprise WiFi based on low cost hardware combined with both new and existing (but modified) open source software. The solution provides a cloud based management interface which allows organizations to aggregate the configuration and management of small, medium and large WiFi solutions. It utilizes a novel approach for user management, giving each user a unique passphrase. It provides unlimited SSID's across an unlimited number of WiFI zones, and the ability to place each user (and all their devices) on their own VLAN. With proper configuration it can even provide user local services. It also allows for users' usage and quality of service to be monitored, and for users to be added, enabled, and disabled at will. As inferred above, the ultimate goal is to free organizations with limited resources from the expense of a commercial enterprise WiFi, while providing them with most of the qualities of such a more expensive managed solution at a fraction of the cost.

Keywords: wifi, enterprise, cloud, managed

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Authors: ByoungJoon Yu, Junkyeong Kim, Seunghee Park

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The tensile force estimation PS tendons is in great demand on monitoring the structural health condition of PSC girder bridges. Measuring the tensile force of the PS tendons inside the PSC girder using conventional methods is hard due to its location. In this paper, an embedded EM sensor based tensile force estimation of PS tendon was carried out by measuring the permeability of the PS tendons in PSC girder. The permeability is changed due to the induced tensile force by the magneto-elastic effect and the effect then lead to the gradient change of the B-H curve. An experiment was performed to obtain the signals from the EM sensor using three down-scaled PSC girder models. The permeability of PS tendons was proportionally decreased according to the increase of the tensile forces. To verify the experiment results, a simulation of tensile force estimation will be conducted in further study. Consequently, it is expected that both the experiment results and the simulation results increase the accuracy of the tensile force estimation, and then it could be one of the solutions for evaluating the performance of PSC girder.

Keywords: tensile force estimation, embedded EM sensor, PSC girder, EM sensor simulation, cross section loss

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Authors: Ming Ma, Rui Li

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In the highly urbanized district, green open space is playing an important role in human’s health and wellbeing as a physical, aesthetic and natural environment resources. The aim of this paper is to close this gap through providing a comprehensive, qualitative meta-analysis of existing studies related to this issue. A systematic scoping of current quantitative research is conducted which mostly focused on cross-sectional survey and experimental studies. Health benefits from contact with green open space could be categorized into physical health, psychological health and social wellbeing. Mechanism for the health related to green open space could be clearly identified with the regard to natural restoration, physical activities and social capital. These results indicate a multiple pathways framework between the health benefits and mechanism. In order to support design and planning, the most evident relationship was picked up that people could psychologically benefit from green open space through outdoors physical activities. Additionally, three design and planning strategies are put forward. Various and multi-level contacts with green open space would be considered as an explanation of the pathway results and tie to bridge the health to design and planning. There is a need to carry out long-term research emphasizing on causal relationship between health and green open space through excluding cofounding factors such as self-selection.

Keywords: urban green open space, planning and design, health benefit, mechanism, pathway framework

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Authors: Asma Omri, Iheb Sifaoui, Sofiane Sayahi, Hichem Besbes

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Future vehicle systems demand advanced capabilities, notably in-cabin life detection and driver monitoring systems, with a particular emphasis on drowsiness detection. To meet these requirements, several techniques employ artificial intelligence methods based on real-time vital sign measurements. In parallel, Frequency-Modulated Continuous-Wave (FMCW) radar technology has garnered considerable attention in the domains of healthcare and biomedical engineering for non-invasive vital sign monitoring. FMCW radar offers a multitude of advantages, including its non-intrusive nature, continuous monitoring capacity, and its ability to penetrate through clothing. In this paper, we propose a system utilizing the AWR6843AOP radar from Texas Instruments (TI) to extract precise vital sign information. The radar allows us to estimate Ballistocardiogram (BCG) signals, which capture the mechanical movements of the body, particularly the ballistic forces generated by heartbeats and respiration. These signals are rich sources of information about the cardiac cycle, rendering them suitable for heart rate estimation. The process begins with real-time subject positioning, followed by clutter removal, computation of Doppler phase differences, and the use of various filtering methods to accurately capture subtle physiological movements. To address the challenges associated with FMCW radar-based vital sign monitoring, including motion artifacts due to subjects' movement or radar micro-vibrations, Long Short-Term Memory (LSTM) networks are implemented. LSTM's adaptability to different heart rate patterns and ability to handle real-time data make it suitable for continuous monitoring applications. Several crucial steps were taken, including feature extraction (involving amplitude, time intervals, and signal morphology), sequence modeling, heart rate estimation through the analysis of detected cardiac cycles and their temporal relationships, and performance evaluation using metrics such as Root Mean Square Error (RMSE) and correlation with reference heart rate measurements. For dataset construction and LSTM training, a comprehensive data collection system was established, integrating the AWR6843AOP radar, a Heart Rate Belt, and a smart watch for ground truth measurements. Rigorous synchronization of these devices ensured data accuracy. Twenty participants engaged in various scenarios, encompassing indoor and real-world conditions within a moving vehicle equipped with the radar system. Static and dynamic subject’s conditions were considered. The heart rate estimation through LSTM outperforms traditional signal processing techniques that rely on filtering, Fast Fourier Transform (FFT), and thresholding. It delivers an average accuracy of approximately 91% with an RMSE of 1.01 beat per minute (bpm). In conclusion, this paper underscores the promising potential of FMCW radar technology integrated with artificial intelligence algorithms in the context of automotive applications. This innovation not only enhances road safety but also paves the way for its integration into the automotive ecosystem to improve driver well-being and overall vehicular safety.

Keywords: ballistocardiogram, FMCW Radar, vital sign monitoring, LSTM

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