Search results for: Aristotelian techniques of communication

Authors: Shuo Li, Yannick Coffinier, Chann Lagadec, Fabrizio Cleri, Katsuhiko Nishiguchi, Akira Fujiwara, Soo Hyeon Kim, Nicolas Clément

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The need for single cell detection and analysis techniques has increased in the past decades because of the heterogeneity of individual living cells, which increases the complexity of the pathogenesis of malignant tumors. In the search for early cancer detection, high-precision medicine and therapy, the technologies most used today for sensitive detection of target analytes and monitoring the variation of these species are mainly including two types. One is based on the identification of molecular differences at the single-cell level, such as flow cytometry, fluorescence-activated cell sorting, next generation proteomics, lipidomic studies, another is based on capturing or detecting single tumor cells from fresh or fixed primary tumors and metastatic tissues, and rare circulating tumors cells (CTCs) from blood or bone marrow, for example, dielectrophoresis technique, microfluidic based microposts chip, electrochemical (EC) approach. Compared to other methods, EC sensors have the merits of easy operation, high sensitivity, and portability. However, despite various demonstrations of low limits of detection (LOD), including aptamer sensors, arrayed EC sensors for detecting single-cell have not been demonstrated. In this work, a new technique based on 20-nm-thick nanopillars array to support cells and keep them at ideal recognition distance for redox-labeled aptamers grafted on the surface. The key advantages of this technology are not only to suppress the false positive signal arising from the pressure exerted by all (including non-target) cells pushing on the aptamers by downward force but also to stabilize the aptamer at the ideal hairpin configuration thanks to a confinement effect. With the first implementation of this technique, a LOD of 13 cells (with5.4 μL of cell suspension) was estimated. In further, the nanosupported cell technology using redox-labeled aptasensors has been pushed forward and fully integrated into a single-cell electrochemical aptasensor array. To reach this goal, the LOD has been reduced by more than one order of magnitude by suppressing parasitic capacitive electrochemical signals by minimizing the sensor area and localizing the cells. Statistical analysis at the single-cell level is demonstrated for the recognition of cancer cells. The future of this technology is discussed, and the potential for scaling over millions of electrodes, thus pushing further integration at sub-cellular level, is highlighted. Despite several demonstrations of electrochemical devices with LOD of 1 cell/mL, the implementation of single-cell bioelectrochemical sensor arrays has remained elusive due to their challenging implementation at a large scale. Here, the introduced nanopillar array technology combined with redox-labeled aptamers targeting epithelial cell adhesion molecule (EpCAM) is perfectly suited for such implementation. Combining nanopillar arrays with microwells determined for single cell trapping directly on the sensor surface, single target cells are successfully detected and analyzed. This first implementation of a single-cell electrochemical aptasensor array based on Brownian-fluctuating redox species opens new opportunities for large-scale implementation and statistical analysis of early cancer diagnosis and cancer therapy in clinical settings.

Keywords: bioelectrochemistry, aptasensors, single-cell, nanopillars

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Authors: R. Ueda

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Today global society is seeking resilient partnership in local organizations and individuals, which realizes multi-stakeholders relationship. Although it is proposed by modern global framework of sustainable development, it is conceivable that such affiliation can be found out in the traditional local community in Japan, and that traditional spirit is tacitly sustaining in modern context of disaster mitigation in society and economy. Then this research is aiming to clarify and analyze implication for the global world by actual case studies. Regional and urban resilience is the ability of multi-stakeholders to cooperate flexibly and to adapt in response to changes in the circumstances caused by disasters, but there are various conflicts affecting coordination of disaster relief measures. These conflicts arise not only from a lack of communication and an insufficient network, but also from the difficulty to jointly draw common context from fragmented information. This is because of the weakness of our modern engineering which focuses on maintenance and restoration of individual systems. Here local ‘circles’ holistically includes local community and interacts periodically. Focusing on examples of resilient organizations and wisdom created in communities, what can be seen throughout history is a virtuous cycle where the information and the knowledge are structured, the context to be adapted becomes clear, and an adaptation at a higher level is made possible, by which the collaboration between organizations is deepened and expanded. And the wisdom of a solid and autonomous disaster prevention formed by the historical community called’ Waju’ – an area surrounded by circle embankment to protect the settlement from flood – lives on in government efforts of the coastal industrial island of today. Industrial company there collaborates to create a circle including common evacuation space, road access improvement and infrastructure recovery. These days, people here adopts new interface technology. Large-scale AR- Augmented Reality for more than hundred people is expressing detailed hazard by tsunami and liquefaction. Common experiences of the major disaster space and circle of mutual discussion are enforcing resilience. Collaboration spirit lies in the center of circle. A consistent key point is a virtuous cycle where the information and the knowledge are structured, the context to be adapted becomes clear, and an adaptation at a higher level is made possible, by which the collaboration between organizations is deepened and expanded. This writer believes that both self-governing human organizations and the societal implementation of technical systems are necessary. Infrastructure should be autonomously instituted by associations of companies and other entities in industrial areas for working closely with local governments. To develop advanced disaster prevention and multi-stakeholder collaboration, partnerships among industry, government, academia and citizens are important.

Keywords: industrial recovery, multi-sakeholders, traditional culture, user experience, Waju

Procedia PDF Downloads 88

Authors: Nicola Colaninno, Eugenio Morello

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The urban environment affects local-to-global climate and, in turn, suffers global warming phenomena, with worrying impacts on human well-being, health, social and economic activities. Physic-morphological features of the built-up space affect urban air temperature, locally, causing the urban environment to be warmer compared to surrounding rural. This occurrence, typically known as the Urban Heat Island (UHI), is normally assessed by means of air temperature from fixed weather stations and/or traverse observations or based on remotely sensed Land Surface Temperatures (LST). The information provided by ground weather stations is key for assessing local air temperature. However, the spatial coverage is normally limited due to low density and uneven distribution of the stations. Although different interpolation techniques such as Inverse Distance Weighting (IDW), Ordinary Kriging (OK), or Multiple Linear Regression (MLR) are used to estimate air temperature from observed points, such an approach may not effectively reflect the real climatic conditions of an interpolated point. Quantifying local UHI for extensive areas based on weather stations’ observations only is not practicable. Alternatively, the use of thermal remote sensing has been widely investigated based on LST. Data from Landsat, ASTER, or MODIS have been extensively used. Indeed, LST has an indirect but significant influence on air temperatures. However, high-resolution near-surface air temperature (NSAT) is currently difficult to retrieve. Here we have experimented Geographically Weighted Regression (GWR) as an effective approach to enable NSAT estimation by accounting for spatial non-stationarity of the phenomenon. The model combines on-site measurements of air temperature, from fixed weather stations and satellite-derived LST. The approach is structured upon two main steps. First, a GWR model has been set to estimate NSAT at low resolution, by combining air temperature from discrete observations retrieved by weather stations (dependent variable) and the LST from satellite observations (predictor). At this step, MODIS data, from Terra satellite, at 1 kilometer of spatial resolution have been employed. Two time periods are considered according to satellite revisit period, i.e. 10:30 am and 9:30 pm. Afterward, the results have been downscaled at 30 meters of spatial resolution by setting a GWR model between the previously retrieved near-surface air temperature (dependent variable), the multispectral information as provided by the Landsat mission, in particular the albedo, and Digital Elevation Model (DEM) from the Shuttle Radar Topography Mission (SRTM), both at 30 meters. Albedo and DEM are now the predictors. The area under investigation is the Metropolitan City of Milan, which covers an area of approximately 1,575 km2 and encompasses a population of over 3 million inhabitants. Both models, low- (1 km) and high-resolution (30 meters), have been validated according to a cross-validation that relies on indicators such as R2, Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). All the employed indicators give evidence of highly efficient models. In addition, an alternative network of weather stations, available for the City of Milano only, has been employed for testing the accuracy of the predicted temperatures, giving and RMSE of 0.6 and 0.7 for daytime and night-time, respectively.

Keywords: urban climate, urban heat island, geographically weighted regression, remote sensing

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Authors: Matthew Arnaouti, Michael Baird, Gabrielle Cahill, Tamara Worlton, Michelle Joseph

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Introduction: Over ten years after the 7.0 magnitude Earthquake struck the capital of Haiti, impacting over three million people and leading to the deaths of over two hundred thousand, the multinational humanitarian response remains the largest disaster relief effort to date. This study critically evaluates the multi-sector and multinational disaster response to the Earthquake, looking at how the lessons learned from this analysis can be applied to future disaster response efforts. We put particular emphasis on assessing the interaction between civilian and military sectors during this humanitarian relief effort, with the hopes of highlighting how concrete guidelines are essential to improve future responses. Methods: An extensive scoping review of the relevant literature was conducted - where library scientists conducted reproducible, verified systematic searches of multiple databases. Grey literature and hand searches were utilised to identify additional unclassified military documents, for inclusion in the study. More than 100 documents were included for data extraction and analysis. Key domains were identified, these included: Humanitarian and Military Response, Communication, Coordination, Resources, Needs Assessment and Pre-Existing Policy. Corresponding information and lessons-learned pertaining to these domains was then extracted - detailing the barriers and facilitators to an effective response. Results: Multiple themes were noted which stratified all identified domains - including the lack of adequate pre-existing policy, as well as extensive ambiguity of actors’ roles. This ambiguity was continually influenced by the complex role the United States military played in the disaster response. At a deeper level, the effects of neo-colonialism and concern about infringements on Haitian sovereignty played a substantial role at all levels: setting the pre-existing conditions and determining the redevelopment efforts that followed. Furthermore, external factors significantly impacted the response, particularly the loss of life within the political and security sectors. This was compounded by the destruction of important infrastructure systems - particularly electricity supplies and telecommunication networks, as well as air and seaport capabilities. Conclusions: This study stands as one of the first and most comprehensive evaluations, systematically analysing the civilian and military response - including their collaborative efforts. This study offers vital information for improving future combined responses and provides a significant opportunity for advancing knowledge in disaster relief efforts - which remains a more pressing issue than ever. The categories and domains formulated serve to highlight interdependent factors that should be applied in future disaster responses, with significant potential to aid the effective performance of humanitarian actors. Further studies will be grounded in these findings, particularly the need for greater inclusion of the Haitian perspective in the literature, through additional qualitative research studies.

Keywords: civilian and military collaboration, combined response, disaster, disaster response, earthquake, Haiti, humanitarian response

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Authors: Georges F. Hatoum, Thomas H. Temple, Silvio Garcia, Xiaodong Wu

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Soft Tissue Sarcomas (STS) represent a diverse group of malignancies with heterogeneous clinical and pathological features. The treatment of extremity STS aims to achieve optimal local tumor control, improved survival, and preservation of limb function. The National Comprehensive Cancer Network guidelines, based on the cumulated clinical data, recommend radiation therapy (RT) in conjunction with limb-sparing surgery for large, high-grade STS measuring greater than 5 cm in size. Such treatment strategy can offer a cure for patients. However, when recurrence occurs (in nearly half of patients), the prognosis is poor, with a median survival of 12 to 15 months and with only palliative treatment options available. The spatially-fractionated-radiotherapy (SFRT), with a long history of treating bulky tumors as a non-mainstream technique, has gained new attention in recent years due to its unconventional therapeutic effects, such as bystander/abscopal effects. Combining single fraction of GRID, the original form of SFRT, with conventional RT was shown to have marginally increased the rate of pathological necrosis, which has been recognized to have a positive correlation to overall survival. In an effort to consistently increase the pathological necrosis rate over 90%, multiple fractions of Lattice RT (LRT), a newer form of 3D SFRT, interdigitated with the standard RT as neoadjuvant therapy was conducted in a preliminary clinical setting. With favorable results of over 95% of necrosis rate in a small cohort of patients, a Phase I/II clinical study was proposed to exam the safety and feasibility of this new strategy. Herein the design of the clinical study is presented. In this single-arm, two-stage phase I/II clinical trial, the primary objectives are >80% of the patients achieving >90% tumor necrosis and to evaluation the toxicity; the secondary objectives are to evaluate the local control, disease free survival and overall survival (OS), as well as the correlation between clinical response and the relevant biomarkers. The study plans to accrue patients over a span of two years. All patient will be treated with the new neoadjuvant RT regimen, in which one of every five fractions of conventional RT is replaced by a LRT fraction with vertices receiving dose ≥10Gy while keeping the tumor periphery at or close to 2 Gy per fraction. Surgical removal of the tumor is planned to occur 6 to 8 weeks following the completion of radiation therapy. The study will employ a Pocock-style early stopping boundary to ensure patient safety. The patients will be followed and monitored for a period of five years. Despite much effort, the rarity of the disease has resulted in limited novel therapeutic breakthroughs. Although a higher rate of treatment-induced tumor necrosis has been associated with improved OS, with the current techniques, only 20% of patients with large, high-grade tumors achieve a tumor necrosis rate exceeding 50%. If this new neoadjuvant strategy is proven effective, an appreciable improvement in clinical outcome without added toxicity can be anticipated. Due to the rarity of the disease, it is hoped that such study could be orchestrated in a multi-institutional setting.

Keywords: lattice RT, necrosis, SFRT, soft tissue sarcoma

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Authors: Mohanad Elemary, Imose Itua, Rajeswari B. Matam

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Virologists and public health experts have been predicting potential pandemics from coronaviruses for decades. The viruses which caused the SARS and MERS pandemics and the Nipah virus led to many lost lives, but still, the COVID-19 pandemic caused by the SARS-CoV2 virus surprised many scientific communities, experts, and governments with its ease of transmission and its pathogenicity. Governments of various countries reacted by locking down entire populations to their homes to combat the devastation caused by the virus, which led to a loss of livelihood and economic hardship to many individuals and organizations. To revive national economies and support their citizens in resuming their lives, governments focused on the development and use of contact tracing apps as a digital way to track and trace exposure. Google and Apple introduced the Exposure Notification Systems (ENS) framework. Independent organizations and countries also developed different frameworks for contact tracing apps. The efficiency, popularity, and adoption rate of these various apps have been different across countries. In this paper, we present a critical analysis of the different contact tracing apps with respect to their efficiency, adoption rate and general perception, and the governmental strategies and policies, which led to the development of the applications. When it comes to the European countries, each of them followed an individualistic approach to the same problem resulting in different realizations of a similarly functioning application with differing results of use and acceptance. The study conducted an extensive review of existing literature, policies, and reports across multiple disciplines, from which a framework was developed and then validated through interviews with six key stakeholders in the field, including founders and executives in digital health startups and corporates as well as experts from international organizations like The World Health Organization. A framework of best practices and tactics is the result of this research. The framework looks at three main questions regarding the contact tracing apps; how to develop them, how to deploy them, and how to regulate them. The findings are based on the best practices applied by governments across multiple countries, the mistakes they made, and the best practices applied in similar situations in the business world. The findings include multiple strategies when it comes to the development milestone regarding establishing frameworks for cooperation with the private sector and how to design the features and user experience of the app for a transparent, effective, and rapidly adaptable app. For the deployment section, several tactics were discussed regarding communication messages, marketing campaigns, persuasive psychology, and the initial deployment scale strategies. The paper also discusses the data privacy dilemma and how to build for a more sustainable system of health-related data processing and utilization. This is done through principles-based regulations specific for health data to allow for its avail for the public good. This framework offers insights into strategies and tactics that could be implemented as protocols for future public health crises and emergencies whether global or regional.

Keywords: contact tracing apps, COVID-19, digital health applications, exposure notification system

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Authors: I. Stathopoulos, V. Syrgiamiotis, E. Karavasilis, A. Ploussi, I. Nikas, C. Hatzigiorgi, K. Platoni, E. P. Efstathopoulos

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Introduction: Brain and central nervous system (CNS) tumors form the second most common group of cancer in children, accounting for 30% of all childhood cancers. MRI is the key imaging technique used for the visualization and management of pediatric brain tumors. Initial characterization of tumors from MRI scans is usually performed via a radiologist’s visual assessment. However, different brain tumor types do not always demonstrate clear differences in visual appearance. Using only conventional MRI to provide a definite diagnosis could potentially lead to inaccurate results, and so histopathological examination of biopsy samples is currently considered to be the gold standard for obtaining definite diagnoses. Machine learning is defined as the study of computational algorithms that can use, complex or not, mathematical relationships and patterns from empirical and scientific data to make reliable decisions. Concerning the above, machine learning techniques could provide effective and accurate ways to automate and speed up the analysis and diagnosis for medical images. Machine learning applications in radiology are or could potentially be useful in practice for medical image segmentation and registration, computer-aided detection and diagnosis systems for CT, MR or radiography images and functional MR (fMRI) images for brain activity analysis and neurological disease diagnosis. Purpose: The objective of this study is to provide an automated tool, which may assist in the imaging evaluation and classification of brain neoplasms in pediatric patients by determining the glioma type, grade and differentiating between different brain tissue types. Moreover, a future purpose is to present an alternative way of quick and accurate diagnosis in order to save time and resources in the daily medical workflow. Materials and Methods: A cohort, of 80 pediatric patients with a diagnosis of posterior fossa tumor, was used: 20 ependymomas, 20 astrocytomas, 20 medulloblastomas and 20 healthy children. The MR sequences used, for every single patient, were the following: axial T1-weighted (T1), axial T2-weighted (T2), FluidAttenuated Inversion Recovery (FLAIR), axial diffusion weighted images (DWI), axial contrast-enhanced T1-weighted (T1ce). From every sequence only a principal slice was used that manually traced by two expert radiologists. Image acquisition was carried out on a GE HDxt 1.5-T scanner. The images were preprocessed following a number of steps including noise reduction, bias-field correction, thresholding, coregistration of all sequences (T1, T2, T1ce, FLAIR, DWI), skull stripping, and histogram matching. A large number of features for investigation were chosen, which included age, tumor shape characteristics, image intensity characteristics and texture features. After selecting the features for achieving the highest accuracy using the least number of variables, four machine learning classification algorithms were used: k-Nearest Neighbour, Support-Vector Machines, C4.5 Decision Tree and Convolutional Neural Network. The machine learning schemes and the image analysis are implemented in the WEKA platform and MatLab platform respectively. Results-Conclusions: The results and the accuracy of images classification for each type of glioma by the four different algorithms are still on process.

Keywords: image classification, machine learning algorithms, pediatric MRI, pediatric oncology

Procedia PDF Downloads 125

Authors: Beste Ozcan, Valerio Sperati, Laura Romano, Tania Moretta, Simone Scaffaro, Noemi Faedda, Federica Giovannone, Carla Sogos, Vincenzo Guidetti, Gianluca Baldassarre

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+me is an experimental interactive toy with the appearance of a soft, pillow-like, panda. Shape and consistency are designed to arise emotional attachment in young children: a child can wear it around his/her neck and treat it as a companion (i.e. a transitional object). When caressed on paws or head, the panda emits appealing, interesting outputs like colored lights or amusing sounds, thanks to embedded electronics. Such sensory patterns can be modified through a wirelessly connected tablet: by this, an adult caregiver can adapt +me responses to a child's reactions or requests, for example, changing the light hue or the type of sound. The toy control is therefore shared, as it depends on both the child (who handles the panda) and the adult (who manages the tablet and mediates the sensory input-output contingencies). These features make +me a potential tool for therapy with children with Neurodevelopmental Disorders (ND), characterized by impairments in the social area, like Autism Spectrum Disorders (ASD) and Language Disorders (LD): as a proposal, the toy could be used together with a therapist, in rehabilitative play activities aimed at encouraging simple social interactions and reinforcing basic relational and communication skills. +me was tested in two pilot experiments, the first one involving 15 Typically Developed (TD) children aged in 8-34 months, the second one involving 7 children with ASD, and 7 with LD, aged in 30-48 months. In both studies a researcher/caregiver, during a one-to-one, ten-minute activity plays with the panda and encourages the child to do the same. The purpose of both studies was to ascertain the general acceptability of the device as an interesting toy that is an object able to capture the child's attention and to maintain a high motivation to interact with it and with the adult. Behavioral indexes for estimating the interplay between the child, +me and caregiver were rated from the video recording of the experimental sessions. Preliminary results show how -on average- participants from 3 groups exhibit a good engagement: they touch, caress, explore the panda and show enjoyment when they manage to trigger luminous and sound responses. During the experiments, children tend to imitate the caregiver's actions on +me, often looking (and smiling) at him/her. Interesting behavioral differences between TD, ASD, and LD groups are scored: for example, ASD participants produce a fewer number of smiles both to panda and to a caregiver with respect to TD group, while LD scores stand between ASD and TD subjects. These preliminary observations suggest that the interactive toy +me is able to raise and maintain the interest of toddlers and therefore it can be reasonably used as a supporting tool during therapy, to stimulate pivotal social skills as imitation, turn-taking, eye contact, and social smiles. Interestingly, the young age of participants, along with the behavioral differences between groups, seem to suggest a further potential use of the device: a tool for early differential diagnosis (the average age of a child

Keywords: autism spectrum disorders, interactive toy, social interaction, therapy, transitional wearable companion

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Authors: Gloria M. Ntuba-Jua, Afui M. Mih, Eneke E. T. Bechem

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Prunus africana (Hook. F.) Kalkman, commonly known as Pygeum or African cherry belongs to the Rosaceae family. It is a medium to large, evergreen tree with a spreading crown of 10 to 20 m. It is used by the traditional medical practitioners for the treatment of over 45ailments in Cameroon and sub-Sahara Africa. In modern medicine, it is used in the treatment of benign prostrate hyperplasia (BPH), prostate gland hypertrophy (enlarged prostate glands). This is possible because of its ability to produce some secondary metabolites which are believed to have bioactivity against these ailments. The ready international market for the sale of Prunus bark, uncontrolled exploitation, illegal harvesting using inappropriate techniques and poor timing of harvesting have contributed enormously to making the plant endangered. It is known to harbor a large number of endophytic fungi with the potential to produce similar secondary metabolites as the parent plant. Alternative sourcing of medicinal principles through endophytic fungi requires succinct knowledge of the endophytic fungi. This will serve as a conservation measure for Prunus africana by reducing dependence on Prunus bark for such metabolites. This work thus sought to compare the production of some major secondary metabolites produced by P. africana and some of its associated endophytic fungi. The leaves and stem bark of the plant from different provenances were soaked in methanol for 72 hrs to yield the methanolic crude extract. The phytochemical screening of the methanolic crude extracts using different standard procedures revealed the presence of tannins, flavonoids, terpenoids, saponins, phenolics and steroids. Pure cultures of some predominantly isolated endophyte species from the difference Prunus provenances such as Curvularia sp, and Morphospecies P001 were also grown in Potato Dextrose Broth (PDB) for 21 days and later extracted with Methylene dichloride (MDC) solvent after 24hrs to produce crude culture extracts. Qualitative assessment of crude culture extracts showed the presence of tannins, terpenoids, phenolics and steroids particularly β-Sitosterol, (a major bioactive metabolite) as did the plant tissues. Qualitative analysis by thin layer chromatography (TLC) was done to confirm and compare the production of β-Sitosterol (as marker compounds) in the crude extracts of the plant and endophyte. Samples were loaded on TLC silica gel aluminium barked plate (Kieselgel 60 F254, 0.2 mm, Merck) using acetone/hexane, (3.0:7.0) solvent system. They were visualized under an ultra violet lamp (UV254 and UV360). TLC revealed that leaves had a higher concentration of β-sitosterol in terms of band intensity than stem barks from the different provenances. The intensity of β-sitosterol bands in the culture extracts of endophytes was comparable to the plant extracts except for Curvularia sp (very minute) whose band was very faint. The ability of these fungi to make β-sitosterol was confirmed by TLC analysis with the compound having chromatographic properties (retention factor) similar to those of β-sitosterol standard. The ability of these major endophytes to produce secondary metabolites similar to the host has therefore been demonstrated. There is, therefore, the potential of developing the in vitro production system of Prunus secondary metabolites thereby enhancing its conservation.

Keywords: Caneroon, endophytic fungi, Prunus africana, secondary metabolite

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Authors: Saif Al Ghafri, Thomas Hughes, Armand Karimi, Kumarini Seneviratne, Jordan Oakley, Michael Johns, Eric F. May

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Knowledge of the thermophysical properties of complex mixtures at extreme conditions of pressure and temperature have always been essential to the Liquefied Natural Gas (LNG) industry’s evolution because of the tremendous technical challenges present at all stages in the supply chain from production to liquefaction to transport. Each stage is designed using predictions of the mixture’s properties, such as density, viscosity, surface tension, heat capacity and phase behaviour as a function of temperature, pressure, and composition. Unfortunately, currently available models lead to equipment over-designs of 15% or more. To achieve better designs that work more effectively and/or over a wider range of conditions, new fundamental property data are essential, both to resolve discrepancies in our current predictive capabilities and to extend them to the higher-pressure conditions characteristic of many new gas fields. Furthermore, innovative experimental techniques are required to measure different thermophysical properties at high pressures and over a wide range of temperatures, including near the mixture’s critical points where gas and liquid become indistinguishable and most existing predictive fluid property models used breakdown. In this work, we present a wide range of experimental measurements made for different binary and ternary mixtures relevant to LNG processing, with a particular focus on viscosity, surface tension, heat capacity, bubble-points and density. For this purpose, customized and specialized apparatus were designed and validated over the temperature range (200 to 423) K at pressures to 35 MPa. The mixtures studied were (CH4 + C3H8), (CH4 + C3H8 + CO2) and (CH4 + C3H8 + C7H16); in the last of these the heptane contents was up to 10 mol %. Viscosity was measured using a vibrating wire apparatus, while mixture densities were obtained by means of a high-pressure magnetic-suspension densimeter and an isochoric cell apparatus; the latter was also used to determine bubble-points. Surface tensions were measured using the capillary rise method in a visual cell, which also enabled the location of the mixture critical point to be determined from observations of critical opalescence. Mixture heat capacities were measured using a customised high-pressure differential scanning calorimeter (DSC). The combined standard relative uncertainties were less than 0.3% for density, 2% for viscosity, 3% for heat capacity and 3 % for surface tension. The extensive experimental data gathered in this work were compared with a variety of different advanced engineering models frequently used for predicting thermophysical properties of mixtures relevant to LNG processing. In many cases the discrepancies between the predictions of different engineering models for these mixtures was large, and the high quality data allowed erroneous but often widely-used models to be identified. The data enable the development of new or improved models, to be implemented in process simulation software, so that the fluid properties needed for equipment and process design can be predicted reliably. This in turn will enable reduced capital and operational expenditure by the LNG industry. The current work also aided the community of scientists working to advance theoretical descriptions of fluid properties by allowing to identify deficiencies in theoretical descriptions and calculations.

Keywords: LNG, thermophysical, viscosity, density, surface tension, heat capacity, bubble points, models

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Authors: Zachary Blanks, Solomon Sonya

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Poaching presents a serious threat to endangered animal species, environment conservations, and human life. Additionally, some poaching activity has even been linked to supplying funds to support terrorist networks elsewhere around the world. Consequently, agencies dedicated to protecting wildlife habitats have a near intractable task of adequately patrolling an entire area (spanning several thousand kilometers) given limited resources, funds, and personnel at their disposal. Thus, agencies need predictive tools that are both high-performing and easily implementable by the user to help in learning how the significant features (e.g. animal population densities, topography, behavior patterns of the criminals within the area, etc) interact with each other in hopes of abating poaching. This research develops a classification model using machine learning algorithms to aid in forecasting future attacks that is both easy to train and performs well when compared to other models. In this research, we demonstrate how data imputation methods (specifically predictive mean matching, gradient boosting, and random forest multiple imputation) can be applied to analyze data and create significant predictions across a varied data set. Specifically, we apply these methods to improve the accuracy of adopted prediction models (Logistic Regression, Support Vector Machine, etc). Finally, we assess the performance of the model and the accuracy of our data imputation methods by learning on a real-world data set constituting four years of imputed data and testing on one year of non-imputed data. This paper provides three main contributions. First, we extend work done by the Teamcore and CREATE (Center for Risk and Economic Analysis of Terrorism Events) research group at the University of Southern California (USC) working in conjunction with the Department of Homeland Security to apply game theory and machine learning algorithms to develop more efficient ways of reducing poaching. This research introduces ensemble methods (Random Forests and Stochastic Gradient Boosting) and applies it to real-world poaching data gathered from the Ugandan rain forest park rangers. Next, we consider the effect of data imputation on both the performance of various algorithms and the general accuracy of the method itself when applied to a dependent variable where a large number of observations are missing. Third, we provide an alternate approach to predict the probability of observing poaching both by season and by month. The results from this research are very promising. We conclude that by using Stochastic Gradient Boosting to predict observations for non-commercial poaching by season, we are able to produce statistically equivalent results while being orders of magnitude faster in computation time and complexity. Additionally, when predicting potential poaching incidents by individual month vice entire seasons, boosting techniques produce a mean area under the curve increase of approximately 3% relative to previous prediction schedules by entire seasons.

Keywords: ensemble methods, imputation, machine learning, random forests, statistical analysis, stochastic gradient boosting, wildlife protection

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Authors: Ashish Kumar Dwivedi

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Uttar Pradesh is largest part of Indian Federal system encapsulating twenty two million populations and has huge cultural, economic and religious diversity. The newly elected 18 months old state leadership of Uttar Pradesh has envisaged and initiated various proactive strides for the public grievance redressal and inclusive development schemes for all the sections of population from its very day of assumption of the office by Hon’ble Chief Minster Shri Yogi Adtiyanath. These initiatives also include Departmental responses via social media handles as Twitter, Facebook Page, and Web interaction. In the same course, every department of state government has been guided for the correct usage of verified social media handle separately and in co-ordination with other departments. These guidelines included making new WhatsApp groups to connect technocrats and politicians to communicate on common platform. Minister for Department of Infrastructure and Industrial Development, Shri Satish Mahana is a very popular leader and very intuitive statesman, has thousands of followers on social media and his accounts receive almost three hundred individually mentioned notifications from the various parts of Uttar Pradesh. These notifications primarily include problems related to livelihood and grievances concerned to department. To address these communications, a body of five experts has been set who are actively responding on various levels and increase bureaucratic engagements with marginalized sections of society. With reference to above background, this piece of research was conducted to analyze, categorize and derive effective implementation of public policies via social media platforms. This act of responsiveness has brought positive change in the mindset of population for the government, which was missed earlier. Department of Industrial Development in the Government is also inclined to attract investors aiming to become first trillion-dollar economy of India henceforth department also organized two major successful events in last one year. These events were also frame worked on social media platform to update 2.5 million population of state who is actively using social media in many ways. To analyze change scientifically, this study has been conducted and big data has been collected from October 2017 to September 2018 from the departmental social media handles as Twitter, Facebook, and emails. For this data, a statistical study has been conducted to analyze sentiments and expectations, specific and common requirement of communities, nature of grievances and their effective elucidation fitted into government policies. The control sample has also been taken from previous government activities to analyze the change. The statistical study used tools such as correlation study and principal component analysis. Also in this research communication, the modus operandi of grievance redressal, proliferation of government policies, connections to their beneficiaries and quick response procedure will be discussed.

Keywords: correlation study, principal component analysis, bureaucratic engagements, social media

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Authors: Lakshmi Rao Kandukuri, Mamata Deenadayal, Suma Prasad, Bipin Sethi, Srinadh Buragadda, Lalji Singh

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Worldwide; at least 7.6 million children are born annually with severe genetic or congenital malformations and among them 90% of these are born in mid and low-income countries. Precise prevalence data are difficult to collect, especially in developing countries, owing to the great diversity of conditions and also because many cases remain undiagnosed. The genetic and congenital disorder is the second most common cause of infant and childhood mortality and occurs with a prevalence of 25-60 per 1000 births. The higher prevalence of genetic diseases in a particular community may, however, be due to some social or cultural factors. Such factors include the tradition of consanguineous marriage, which results in a higher rate of autosomal recessive conditions including congenital malformations, stillbirths, or mental retardation. Genetic diseases can vary in severity, from being fatal before birth to requiring continuous management; their onset covers all life stages from infancy to old age. Those presenting at birth are particularly burdensome and may cause early death or life-long chronic morbidity. Genetic testing for several genetic diseases identifies changes in chromosomes, genes, or proteins. The results of a genetic test can confirm or rule out a suspected genetic condition or help determine a person's chance of developing or passing on a genetic disorder. Several hundred genetic tests are currently in use and more are being developed. Chromosomal abnormalities are the major cause of human suffering, which are implicated in mental retardation, congenital malformations, dysmorphic features, primary and secondary amenorrhea, reproductive wastage, infertility neoplastic diseases. Cytogenetic evaluation of patients is helpful in the counselling and management of affected individuals and families. We present here especially chromosomal abnormalities which form a major part of genetic disease burden in India. Different programmes on chromosome research and human reproductive genetics primarily relate to infertility since this is a major public health problem in our country, affecting 10-15 percent of couples. Prenatal diagnosis of chromosomal abnormalities in high-risk pregnancies helps in detecting chromosomally abnormal foetuses. Such couples are counselled regarding the continuation of pregnancy. In addition to the basic research, the team is providing chromosome diagnostic services that include conventional and advanced techniques for identifying various genetic defects. Other than routine chromosome diagnosis for infertility, also include patients with short stature, hypogonadism, undescended testis, microcephaly, delayed developmental milestones, familial, and isolated mental retardation, and cerebral palsy. Thus, chromosome diagnostics has found its applicability not only in disease prevention and management but also in guiding the clinicians in certain aspects of treatment. It would be appropriate to affirm that chromosomes are the images of life and they unequivocally mirror the states of human health. The importance of genetic counseling is increasing with the advancement in the field of genetics. The genetic counseling can help families to cope with emotional, psychological, and medical consequences of genetic diseases.

Keywords: India, chromosome abnormalities, genetic disorders, cytogenetic study

Procedia PDF Downloads 282

Authors: Esmael Makarian, Ayub Elyasi, Fatemeh Saberi, Olusegun Stanley Tomomewo

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Rock mechanical investigation is one of the most crucial activities in underground operations, especially in surveys related to hydrocarbon exploration and production, geothermal reservoirs, energy storage, mining, and geotechnics. There is a wide range of traditional methods for driving, collecting, and analyzing rock mechanics data. However, these approaches may not be suitable or work perfectly in some situations, such as fractured zones. Cutting-edge technologies have been provided to solve and optimize the mentioned issues. Internet of Things (IoT), Edge, and Cloud Computing technologies (ECt & CCt, respectively) are among the most widely used and new artificial intelligence methods employed for geomechanical studies. IoT devices act as sensors and cameras for real-time monitoring and mechanical-geological data collection of rocks, such as temperature, movement, pressure, or stress levels. Structural integrity, especially for cap rocks within hydrocarbon systems, and rock mass behavior assessment, to further activities such as enhanced oil recovery (EOR) and underground gas storage (UGS), or to improve safety risk management (SRM) and potential hazards identification (P.H.I), are other benefits from IoT technologies. EC techniques can process, aggregate, and analyze data immediately collected by IoT on a real-time scale, providing detailed insights into the behavior of rocks in various situations (e.g., stress, temperature, and pressure), establishing patterns quickly, and detecting trends. Therefore, this state-of-the-art and useful technology can adopt autonomous systems in rock mechanical surveys, such as drilling and production (in hydrocarbon wells) or excavation (in mining and geotechnics industries). Besides, ECt allows all rock-related operations to be controlled remotely and enables operators to apply changes or make adjustments. It must be mentioned that this feature is very important in environmental goals. More often than not, rock mechanical studies consist of different data, such as laboratory tests, field operations, and indirect information like seismic or well-logging data. CCt provides a useful platform for storing and managing a great deal of volume and different information, which can be very useful in fractured zones. Additionally, CCt supplies powerful tools for predicting, modeling, and simulating rock mechanical information, especially in fractured zones within vast areas. Also, it is a suitable source for sharing extensive information on rock mechanics, such as the direction and size of fractures in a large oil field or mine. The comprehensive review findings demonstrate that digital transformation through integrated IoT, Edge, and Cloud solutions is revolutionizing traditional rock mechanical investigation. These advanced technologies have empowered real-time monitoring, predictive analysis, and data-driven decision-making, culminating in noteworthy enhancements in safety, efficiency, and sustainability. Therefore, by employing IoT, CCt, and ECt, underground operations have experienced a significant boost, allowing for timely and informed actions using real-time data insights. The successful implementation of IoT, CCt, and ECt has led to optimized and safer operations, optimized processes, and environmentally conscious approaches in underground geological endeavors.

Keywords: rock mechanical studies, internet of things, edge computing, cloud computing, underground surveys, geological operations

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Authors: Christine Hough, Eddie Abbott-Halpin, Tariq Mahmood, Jessica Giles

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This paper draws together the findings from two research studies, each undertaken with cohorts of South Asian Muslim respondents located in the North of England between 2017 and 2019. The first study, entitled Faith Family and Crime (FFC), investigated the extent to which a Muslim family’s social and health well-being is affected by a family member’s involvement in the Criminal Justice System (CJS). This study captured a range of data through a detailed questionnaire and structured interviews. The data from the interview transcripts were analysed using open coding and an application of aspects of the grounded theory approach. The findings provide clear evidence that the respondents were neither well-informed nor supported throughout the processes of the CJS, from arrest to post-sentencing. These experiences gave rise to mental and physical stress, potentially unfair sentencing, and a significant breakdown in communication within the respondents’ families. They serve to highlight a particular aspect of complexity in the current needs of those South Asian Muslim families who find themselves involved in the CJS and is closely connected to family structure, culture, and faith. The second study, referred to throughout this paper as #ImamsBritain (that provides the majority of content for this paper), explores how Imams, in their role as community faith leaders, can best address the complex – and changing - needs of South Asian Muslims families, such as those that emerged in the findings from FFC. The changing socio-economic and political climates of the last thirty or so years have brought about significant changes to the lives of Muslim families, and these have created more complex levels of social, cultural, and faith-based needs for families and individuals. As a consequence, Imams now have much greater demands made of them, and so their role has undergone far-reaching changes in response to this. The #ImamsBritain respondents identified a pressing need to develop a wider range of pastoral and counseling skills, which they saw as extending far beyond the traditional role of the Imam as a religious teacher and spiritual guide. The #ImamsBritain project was conducted with a cohort of British Imams in the North of England. Data was collected firstly through a questionnaire that related to the respondents’ training and development needs and then analysed in depth using the Delphi approach. Through Delphi, the data were scrutinized in depth using interpretative content analysis. The findings from this project reflect the respondents’ individual perceptions of the kind of training and development they need to fulfill their role in 21st Century Britain. They also provide a unique framework for constructing a professional guide for Imams in Great Britain. The discussions and critical analyses in this paper draw on the discourses of professionalization and pastoral care and relevant reports and reviews on Imam training in Europe and Canada.

Keywords: criminal justice system, faith and culture, Imams, Muslim community leadership, professionalization, South Asian family structure

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Authors: Satya Narayan

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India, a rapidly growing economy with a burgeoning population, grapples with the dual challenge of meeting rising energy demands and reducing its carbon footprint. Geothermal energy, an often overlooked and underutilized renewable source, holds immense potential for addressing this challenge. Geothermal resources offer a valuable, consistent, and sustainable energy source, and may significantly contribute to India's energy. This paper discusses the importance of geothermal exploration in India, emphasizing its role in achieving sustainable energy production while mitigating environmental impacts. It also delves into the methodology employed to assess geothermal resource feasibility, including geophysical surveys and borehole drilling. The results and discussion sections highlight promising geothermal sites across India, illuminating the nation's vast geothermal potential. It detects potential geothermal reservoirs, characterizes subsurface structures, maps temperature gradients, monitors fluid flow, and estimates key reservoir parameters. Globally, geothermal energy falls into high and low enthalpy categories, with India mainly having low enthalpy resources, especially in hot springs. The northwestern Himalayan region boasts high-temperature geothermal resources due to geological factors. Promising sites, like Puga Valley, Chhumthang, and others, feature hot springs suitable for various applications. The Son-Narmada-Tapti lineament intersects regions rich in geological history, contributing to geothermal resources. Southern India, including the Godavari Valley, has thermal springs suitable for power generation. The Andaman-Nicobar region, linked to subduction and volcanic activity, holds high-temperature geothermal potential. Geophysical surveys, utilizing gravity, magnetic, seismic, magnetotelluric, and electrical resistivity techniques, offer vital information on subsurface conditions essential for detecting, evaluating, and exploiting geothermal resources. The gravity and magnetic methods map the depth of the mantle boundary (high-temperature) and later accurately determine the Curie depth. Electrical methods indicate the presence of subsurface fluids. Seismic surveys create detailed sub-surface images, revealing faults and fractures and establishing possible connections to aquifers. Borehole drilling is crucial for assessing geothermal parameters at different depths. Detailed geochemical analysis and geophysical surveys in Dholera, Gujarat, reveal untapped geothermal potential in India, aligning with renewable energy goals. In conclusion, geophysical surveys and borehole drilling play a pivotal role in economically viable geothermal site selection and feasibility assessments. With ongoing exploration and innovative technology, these surveys effectively minimize drilling risks, optimize borehole placement, aid in environmental impact evaluations, and facilitate remote resource exploration. Their cost-effectiveness informs decisions regarding geothermal resource location and extent, ultimately promoting sustainable energy and reducing India's reliance on conventional fossil fuels.

Keywords: geothermal resources, geophysical methods, exploration, exploitation

Procedia PDF Downloads 47

Authors: U.K. Sarkar, G. Karnatak, P. Mishal, Lianthuamluaia, S. Kumari, S.K. Das, B.K. Das

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Inland open water fisheries provide food, income, livelihood and nutritional security to millions of fishers across the globe. However, the open water ecosystem and fisheries are threatened due to climate change and anthropogenic pressures, which are more visible in the recent six decades, making the resources vulnerable. Understanding the interaction between meteorological parameters and inland fisheries is imperative to develop mitigation and adaptation strategies. As per IPCC 5th assessment report, the earth is warming at a faster rate in recent decades. Global mean surface temperature (GMST) for the decade 2006–2015 (0.87°C) was 6 times higher than the average over the 1850–1900 period. The direct and indirect impacts of climatic parameters on the ecology of fisheries ecosystem have a great bearing on fisheries due to alterations in fish physiology. The impact of meteorological factors on ecosystem health and fish food organisms brings about changes in fish diversity, assemblage, reproduction and natural recruitment. India’s average temperature has risen by around 0.7°C during 1901–2018. The studies show that the mean air temperature in the Ganga basin has increased in the range of 0.20 - 0.47 °C and annual rainfall decreased in the range of 257-580 mm during the last three decades. The studies clearly indicate visible impacts of climatic and environmental factors on inland open water fisheries. Besides, a significant reduction in-depth and area (37.20–57.68% reduction), diversity of natural indigenous fish fauna (ranging from 22.85 to 54%) in wetlands and progression of trophic state from mesotrophic to eutrophic were recorded. In this communication, different applications of biometeorology in inland fisheries management with special reference to the assessment of ecosystem and species vulnerability to climatic variability and change have been discussed. Further, the paper discusses the impact of climate anomaly and extreme climatic events on inland fisheries and emphasizes novel modeling approaches for understanding the impact of climatic and environmental factors on reproductive phenology for identification of climate-sensitive/resilient fish species for the adoption of climate-smart fisheries in the future. Adaptation and mitigation strategies to enhance fish production and the role of culture-based fisheries and enclosure culture in converting sequestered carbon into blue carbon have also been discussed. In general, the type and direction of influence of meteorological parameters on fish biology in open water fisheries ecosystems are not adequately understood. The optimum range of meteorological parameters for sustaining inland open water fisheries is yet to be established. Therefore, the application of biometeorology in inland fisheries offers ample scope for understanding the dynamics in changing climate, which would help to develop a database on such least, addressed research frontier area. This would further help to project fisheries scenarios in changing climate regimes and develop adaptation and mitigation strategies to cope up with adverse meteorological factors to sustain fisheries and to conserve aquatic ecosystem and biodiversity.

Keywords: biometeorology, inland fisheries, aquatic ecosystem, modeling, India

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Authors: Marina Gold, Yves Jackson, David Parrat

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The high predominance of Latin American migrants in Geneva from countries where Chagas disease is endemic (Bolivia, Brazil, Argentina, Colombia) is increasing the incidence of chronic Chagas-related problems, especially cardiovascular complications. The precarious migratory status of what are mostly undocumented migrants complicates access to health and affects patients’ and doctors’ health perceptions regarding screening, treatment and monitoring of Chagas-related health concerns. This project results from a 3 year collaboration between the Geneva University Hospital and the NGO Mundo Sano to understand the following questions: 1) how do Latin American migrants perceive their health? 2) What do they understand from Chagas disease? 3) Are patients’ and doctors’ health perceptions similar or do they have competing agendas? This paper aims to present the results of a long-term study that interrogates health perceptions among Latin American migrants in Geneva. The first phase consisted in completing surveys at three community screening events (2016, 2017. 2018), and the results of these surveys reveal the subordination of the importance of health to that of having met economic family obligation. That is, health is important only when it becomes an impediment to economic gain. The contradictory result emerged that people are aware of the importance of health prevention in order to ensure long-term health, but they do not always have agency over their life-style habits (healthy food, regular exercise, emotional stability). The second phase of the research collected open-ended interviews with selected participants, in order to explore in more detail how Latin American migrants deal with Chagas in a different socio-political and economic context to that of endemic countries. These interviews (5 in total) reveal mixed methods of managing health: social networks, access to health care transnationally (in Geneva, Spain and back in their home country), and different valuations of health problems in each situation. The third phase consisted in observations of doctor-patient consultations and further extended interviews with patients to determine doctor/patient health perceptions around Chagas disease. This phase is ongoing, but it has yielded preliminarily observations regarding the expectations that patients’ have of doctors, and the understanding of doctors’ to patients’ complex situations. Positive and complementary health perceptions include patients’ feeling that doctors in Geneva are more understanding, more knowledgeable and less racist than those in their home country, who do not provide detailed information about Chagas or its treatment and discriminate against them for being indigenous or from poor rural areas, enabling a better communication between doctors and patients. Possible conflicting health perceptions include patients addressing their health concerns more holistically and encountering the specialist’s limitations to only treating one health concern, given time limitations and lack of competition with their colleagues (the general practitioner that referred the patient, for example). The implications of this study extend the case of Chagas disease in Geneva and is relevant for all chronic concerns and migratory contexts of precarity.

Keywords: chagas disease, health perceptions, Latin American Migrants, non-endemic countries

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Authors: Marco Frieslaar, Bing Chu, Eric Rogers

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Stroke is a devastating illness that is the second biggest cause of death in the world (after heart disease). Where it does not kill, it leaves survivors with debilitating sensory and physical impairments that not only seriously harm their quality of life, but also cause a high incidence of severe depression. It is widely accepted that early intervention is essential for recovery, but current rehabilitation techniques largely favor hospital-based therapies which have restricted access, expensive and specialist equipment and tend to side-step the emotional challenges. In addition, there is insufficient funding available to provide the long-term assistance that is required. As a consequence, recovery rates are poor. The relatively unexplored solution is to develop therapies that can be harnessed in the home and are formulated from technologies that already exist in everyday life. This would empower individuals to take control of their own improvement and provide choice in terms of when and where they feel best able to undertake their own healing. This research seeks to identify how effective post-stroke, rehabilitation therapy can be applied to upper limb mobility, within the physical context of a home rather than a hospital. This is being achieved through the design and construction of an automation scheme, based on iterative learning control and the Riener muscle model, that has the ability to adapt to the user and react to their level of fatigue and provide tangible physical recovery. It utilizes a SMART Phone and laptop to construct an iterative learning control (ILC) system, that monitors upper arm movement in three dimensions, as a series of exercises are undertaken. The equipment generates functional electrical stimulation to assist in muscle activation and thus improve directional accuracy. In addition, it monitors speed, accuracy, areas of motion weakness and similar parameters to create a performance index that can be compared over time and extrapolated to establish an independent and objective assessment scheme, plus an approximate estimation of predicted final outcome. To further extend its assessment capabilities, nerve conduction velocity readings are taken by the software, between the shoulder and hand muscles. This is utilized to measure the speed of response of neuron signal transfer along the arm and over time, an online indication of regeneration levels can be obtained. This will prove whether or not sufficient training intensity is being achieved even before perceivable movement dexterity is observed. The device also provides the option to connect to other users, via the internet, so that the patient can avoid feelings of isolation and can undertake movement exercises together with others in a similar position. This should create benefits not only for the encouragement of rehabilitation participation, but also an emotional support network potential. It is intended that this approach will extend the availability of stroke recovery options, enable ease of access at a low cost, reduce susceptibility to depression and through these endeavors, enhance the overall recovery success rate.

Keywords: home-based therapy, iterative learning control, Riener muscle model, SMART phone, stroke rehabilitation

Procedia PDF Downloads 241

Authors: Satam Alotibi, Osama A. Hussein, Aziz H. Al-Shaibani, Nawaf A. Al-Aqeel, Abdellah Kaiba, Fatehia S. Alhakami, Mohammed Alyami, Talal F. Qahtan

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The demand for sustainable and efficient energy conversion using solar energy has grown rapidly in recent years. In this pursuit, solar-to-chemical conversion has emerged as a promising approach, with oxygen vacancies-rich tungsten trioxide (WO₃) playing a crucial role. This study presents a method for synthesizing oxygen vacancies-rich WO3, resulting in a significant enhancement of its photocatalytic activity, representing a significant step towards sustainable energy solutions. Experimental results underscore the importance of oxygen vacancies in modifying the properties of WO₃. These vacancies introduce additional energy states within the material, leading to a reduction in the bandgap, increased light absorption, and acting as electron traps, thereby reducing emissions. Our focus lies in developing oxygen vacancies-rich WO₃, which demonstrates unparalleled potential for improved photocatalytic applications. The effectiveness of oxygen vacancies-rich WO₃ in solar-to-chemical conversion was showcased through rigorous assessments of its photocatalytic degradation performance. Sunlight irradiation was employed to evaluate the material's effectiveness in degrading organic pollutants in wastewater. The results unequivocally demonstrate the superior photocatalytic performance of oxygen vacancies-rich WO₃ compared to conventional WO₃ nanomaterials, establishing its efficacy in sustainable and efficient energy conversion. Furthermore, the synthesized material is utilized to fabricate films, which are subsequently employed in immobilized WO₃ and oxygen vacancies-rich WO₃ reactors for water purification under natural sunlight irradiation. This application offers a sustainable and efficient solution for water treatment, harnessing solar energy for effective decontamination. In addition to investigating the photocatalytic capabilities, we extensively analyze the structural and chemical properties of the synthesized material. The synthesis process involves in situ thermal reduction of WO₃ nano-powder in a nitrogen environment, meticulously monitored using thermogravimetric analysis (TGA) to ensure precise control over the synthesis of oxygen vacancies-rich WO₃. Comprehensive characterization techniques such as UV-Vis spectroscopy, X-ray photoelectron spectroscopy (XPS), FTIR, Raman spectroscopy, scanning electron microscopy (SEM), transmission electron microscopy (TEM), and selected area electron diffraction (SAED) provide deep insights into the material's optical properties, chemical composition, elemental states, structure, surface properties, and crystalline structure. This study represents a significant advancement in sustainable energy conversion through solar-to-chemical processes and water purification. By harnessing the unique properties of oxygen vacancies-rich WO₃, we not only enhance our understanding of energy conversion mechanisms but also pave the way for the development of highly efficient and environmentally friendly photocatalytic materials. The application of this material in water purification demonstrates its versatility and potential to address critical environmental challenges. These findings bring us closer to a sustainable energy future and cleaner water resources, laying a solid foundation for a more sustainable planet.

Keywords: sustainable energy conversion, solar-to-chemical conversion, oxygen vacancies-rich tungsten trioxide (WO₃), photocatalytic activity enhancement, water purification

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Authors: Mamert Mbonimpa, Ousseynou Kanteye, Élysée Tshibangu Ngabu, Rachid Amrou, Abdelkabir Maqsoud, Tikou Belem

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The management of mine wastes (waste rocks and tailings) containing sulphide minerals such as pyrite and pyrrhotite represents the main environmental challenge for the mining industry. Indeed, acid mine drainage (AMD) can be generated when these wastes are exposed to water and air. AMD is characterized by low pH and high concentrations of heavy metals, which are toxic to plants, animals, and humans. It affects the quality of the ecosystem through water and soil pollution. Different techniques involving soil materials can be used to control AMD generation, including impermeable covers (compacted clays) and oxygen barriers. The latter group includes covers with capillary barrier effects (CCBE), a multilayered cover that include the moisture retention layer playing the role of an oxygen barrier. Once AMD is produced at a mine site, it must be treated so that the final effluent at the mine site complies with regulations and can be discharged into the environment. Active neutralization with lime is one of the treatment methods used. This treatment produces sludge that is usually stored in sedimentation ponds. Other sludge management alternatives have been examined in recent years, including sludge co-disposal with tailings or waste rocks, disposal in underground mine excavations, and storage in technical landfill sites. Considering the ability of AMD neutralization sludge to maintain an alkaline to neutral pH for decades or even centuries, due to the excess alkalinity induced by residual lime within the sludge, valorization of sludge in specific applications could be an interesting management option. If done efficiently, the reuse of sludge could free up storage ponds and thus reduce the environmental impact. It should be noted that mixtures of sludge and soils could potentially constitute usable materials in CCBE for the rehabilitation of acid-generating mine sites, while sludge alone is not suitable for this purpose. The high sludge water content (up to 300%), even after sedimentation, can, however, constitute a geotechnical challenge. Adding lime to the mixtures can reduce the water content and improve the geotechnical properties. The objective of this paper is to investigate the impact of the sludge content (30, 40 and 50%) in sand-sludge mixtures (SSM) on their hydrogeotechnical properties (compaction, shrinkage behaviour, saturated hydraulic conductivity, and water retention curve). The impact of lime addition (dosages from 2% to 6%) on the moisture content, dry density after compaction and saturated hydraulic conductivity of SSM was also investigated. Results showed that sludge adding to sand significantly improves the saturated hydraulic conductivity and water retention capacity, but the shrinkage increased with sludge content. The dry density after compaction of lime-treated SSM increases with the lime dosage but remains lower than the optimal dry density of the untreated mixtures. The saturated hydraulic conductivity of lime-treated SSM after 24 hours of cure decreases by 3 orders of magnitude. Considering the hydrogeotechnical properties obtained with these mixtures, it would be possible to design CCBE whose moisture retention layer is made of SSM. Physical laboratory models confirmed the performance of such CCBE.

Keywords: mine waste, AMD neutralization sludge, sand-sludge mixture, hydrogeotechnical properties, mine site reclamation, CCBE

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Authors: Hakimeh Masoudigavgani

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Since manufacturing firms deplete non-renewable resources and pollute air, soil, and water in greatly unsustainable manner, industrial activities or production of products are considered to be a key contributor to adverse environmental impacts. Hence, management strategies and approaches that involve an effective supply chain decision process in a manufacturing sector could be extremely significant to the application of environmental initiatives. Green manufacturing (GM) is one of these strategies which minimises negative effects on the environment through reducing greenhouse gas emissions, waste, and the consumption of energy and natural resources. This paper aims to explore what greening methods and mechanisms could be applied in the manufacturing supply chain and what are the outcomes of adopting these methods in terms of abating environmental burdens? The study is an interpretive research with an exploratory approach, using thematic analysis by coding text, breaking down and grouping the content of collected literature into various themes and categories. It is found that green supply chain could be attained through execution of some pre-production strategies including green building, eco-design, and green procurement as well as a number of in-production and post-production strategies involving green manufacturing and green logistics. To achieve an effective GM, the pre-production strategies are suggested to be employed. This paper defines GM as (1) the analysis of the ecological impacts generated by practices, products, production processes, and operational functions, and (2) the implementation of greening methods to reduce damaging influences of them on the natural environment. Analysis means assessing, monitoring, and auditing of practices in order to measure and pinpoint their harmful impacts. Moreover, greening methods involved within GM (arranged in order from the least to the most level of environmental compliance and techniques) consist of: •product stewardship (e.g. less use of toxic, non-renewable, and hazardous materials in the manufacture of the product; and stewardship of the environmental problems with regard to the product in all production, use, and end-of-life stages); •process stewardship (e.g. controlling carbon emission, energy and resources usage, transportation method, and disposal; reengineering polluting processes; recycling waste materials generated in production); •lean and clean production practices (e.g. elimination of waste, materials replacement, materials reduction, resource-efficient consumption, energy-efficient usage, emission reduction, managerial assessment, waste re-use); •use of eco-industrial parks (e.g. a shared warehouse, shared logistics management system, energy co-generation plant, effluent treatment). However, the focus of this paper is only on methods related to the in-production phase and needs further research on both pre-production and post-production environmental innovations. The outlined methods in this investigation may possibly be taken into account by policy/decision makers. Additionally, the proposed future research direction and identified gaps can be filled by scholars and researchers. The paper compares and contrasts a variety of viewpoints and enhances the body of knowledge by building a definition for GM through synthesising literature and categorising the strategic concept of greening methods, drivers, barriers, and successful implementing tactics.

Keywords: green manufacturing (GM), product stewardship, process stewardship, clean production, eco-industrial parks (EIPs)

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Authors: Igor Peraza Curiel, Suzanne Strum

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Today, when many foreign architects are receiving commissions in the United Arab Emirates, it is essential to analyze how their designs are influenced by the region's culture, environment, and building traditions. This study examines the approach to siting, geometry, construction methods, and material choices in two private homes for a family in Dubai, a project being constructed on adjacent sites by the acclaimed Spanish team of RCR Architects. Their third project in Dubai, the houses mark a turning point in their design approach to the desert. The Pritzker Prize-winning architects of RCR gained renown for building works deeply responsive to the history, landscape, and customs of their hometown in a volcanic area of the Catalonia region of Spain. Key formative projects and their entry to practice in UAE will be analyzed according to the concepts of place identity, the poetics of construction, and material imagination. The poetics of construction, a theoretical position with a long practical tradition, was revived by the British critic Kenneth Frampton. The idea of architecture as a constructional craft is related to the concepts of material imagination and place identity--phenomenological concerns with the creative engagement with local matter and topography that are at the very essence of RCR's way of designing, detailing, and making. Our study situates RCR within the challenges of building in the region, where western forms and means have largely replaced the ingenious responsiveness of indigenous architecture to the climate and material scarcity. The dwellings, iterations of the same steel and concrete vaulting system, highlight the conceptual framework of RCR's design approach to offer a study in contemporary critical regionalism. The Kama House evokes Bedouin tents, while the Alwah House takes the form of desert dunes in response to the temporality of the winds. Metal mesh screens designed to capture the shifting sands will complete the forms. The original research draws on interviews with the architects and unique documentation provided by them and collected by the authors during on-site visits. By examining the two houses in-depth, this paper foregrounds a series of timely questions: 1) What is the impact of the local climatic, cultural, and material conditions on their project in the UAE? 2) How does this work further their experiences in the region? 3) How has RCR adapted their construction techniques as their work expands beyond familiar settings? The investigation seeks to understand how the design methodology developed for more than 20 years and enmeshed in the regional milieu of their hometown can transform as the architects encounter unique characteristics and values in the Middle East. By focusing on the contemporary interpretation of Arabic geometry and elements, the houses reveal the role of geometry, tectonics, and material specificity in the realization from conceptual sketches to built form. In emphasizing the importance of regional responsiveness, the dynamics of international construction practice, and detailing this study highlights essential issues for professionals and students looking to practice in an increasingly global market.

Keywords: material imagination, regional responsiveness, place identity, poetics of construction

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Authors: Jose Neri, Fabrice Canto, Alastair Magnaldo, Laurent Guillerme, Vincent Dugas

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A miniaturized and automated approach for the volumetric titration of free nitric acid in U(VI) solutions is presented. Free acidity measurement refers to the acidity quantification in solutions containing hydrolysable heavy metal ions such as U(VI), U(IV) or Pu(IV) without taking into account the acidity contribution from the hydrolysis of such metal ions. It is, in fact, an operation having an essential role for the control of the nuclear fuel recycling process. The main objective behind the technical optimization of the actual ‘beaker’ method was to reduce the amount of radioactive substance to be handled by the laboratory personnel, to ease the instrumentation adjustability within a glove-box environment and to allow a high-throughput analysis for conducting more cost-effective operations. The measurement technique is based on the concept of the Taylor-Aris dispersion in order to create inside of a 200 μm x 5cm circular cylindrical micro-channel a linear concentration gradient in less than a second. The proposed analytical methodology relies on the actinide complexation using pH 5.6 sodium oxalate solution and subsequent alkalimetric titration of nitric acid with sodium hydroxide. The titration process is followed with a CCD camera for fluorescence detection; the neutralization boundary can be visualized in a detection range of 500nm- 600nm thanks to the addition of a pH sensitive fluorophore. The operating principle of the developed device allows the active generation of linear concentration gradients using a single cylindrical micro channel. This feature simplifies the fabrication and ease of use of the micro device, as it does not need a complex micro channel network or passive mixers to generate the chemical gradient. Moreover, since the linear gradient is determined by the liquid reagents input pressure, its generation can be fully achieved in faster intervals than one second, being a more timely-efficient gradient generation process compared to other source-sink passive diffusion devices. The resulting linear gradient generator device was therefore adapted to perform for the first time, a volumetric titration on a chip where the amount of reagents used is fixed to the total volume of the micro channel, avoiding an important waste generation like in other flow-based titration techniques. The associated analytical method is automated and its linearity has been proven for the free acidity determination of U(VI) samples containing up to 0.5M of actinide ion and nitric acid in a concentration range of 0.5M to 3M. In addition to automation, the developed analytical methodology and technique greatly improves the standard off-line oxalate complexation and alkalimetric titration method by reducing a thousand fold the required sample volume, forty times the nuclear waste per analysis as well as the analysis time by eight-fold. The developed device represents, therefore, a great step towards an easy-to-handle nuclear-related application, which in the short term could be used to improve laboratory safety as much as to reduce the environmental impact of the radioanalytical chain.

Keywords: free acidity, lab-on-a-chip, linear concentration gradient, Taylor-Aris dispersion, volumetric titration

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Authors: Varinder Kaur Gambhir, Neema Gupta, Sonal Tickoo Chaudhuri

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Bengaluru, a rapidly growing metropolis in India, with a population of 12.5 million citizens, generates 5,757 metric tonnes of solid waste per day. Despite their invaluable contribution to waste management, society and the economy, waste pickers face significant stigma, suspicion and contempt and are left with a sense of shame about their work. In this context, BBC Media Action was funded by the H&M Foundation to develop a 3-year multi-phase social media campaign to shift perceptions of waste picking and informal waste pickers amongst the Bengaluru population. Research has been used to inform project strategy and adaptation, at all stages. Formative research to inform campaign strategy used mixed methods– 14 focused group discussions followed by 406 online surveys – to explore people’s knowledge of, and attitudes towards waste pickers, and identify potential barriers and motivators to changing perceptions. Use of qualitative techniques like metaphor maps (using bank of pictures rather than direct questions to understand mindsets) helped establish the invisibility of informal waste pickers, and the quantitative research enabled audience segmentation based on attitudes towards informal waste pickers. To pretest the campaign idea, eight I-GDs (individual interaction followed by group discussions) were conducted to allow interviewees to first freely express their feelings individually, before discussing in a group. Robert Plucthik’s ‘wheel of emotions’ was used to understand audience’s emotional response to the content. A robust monitoring and evaluation is being conducted (baseline and first phase of monitoring already completed) using a rotating longitudinal panel of 1,800 social media users (exposed and unexposed to the campaign), recruited face to face and representative of the social media universe of Bengaluru city. In addition, qualitative in-depth interviews are being conducted after each phase to better understand change drivers. The research methodology and ethical protocols for impact evaluation have been independently reviewed by an Institutional Review Board. Formative research revealed that while waste on the streets is visible and is of concern to the public, informal waste pickers are virtually ‘invisible’, for most people in Bengaluru Pretesting research revealed that the creative outputs evoked emotions like acceptance and gratitude towards waste-pickers, suggesting that the content had the potential to encourage attitudinal change. After the first phase of campaign, social media analytics show that #Invaluables content reached at least 2.6 million unique people (21% of the Bengaluru population) through Facebook and Instagram. Further, impact monitoring results show significant improvements in spontaneous awareness of different segments of informal waste pickers ( such as sorters at scrap shops or dry waste collection centres -from 10% at baseline to 16% amongst exposed and no change amongst unexposed), recognition that informal waste pickers help the environment (71% at baseline to 77% among exposed and no change among unexposed) and greater discussion about informal waste pickers among those exposed (60%) as against not exposed (49%). Using the insights from this research, the planned social media intervention is designed to increase the visibility of and appreciation for the work of waste pickers in Bengaluru, supporting a more inclusive society.

Keywords: awareness, discussion, discrimination, informal waste pickers, invisibility, social media campaign, waste management

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Authors: Ding Liangxiao

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The technological advancements in Micro-Electro-Mechanical Systems (MEMS) have significantly contributed to the development of new, flexible capacitive pressure sensors,which are pivotal in transforming wearable and medical device technologies. This study employs the sophisticated simulation tools available in COMSOL Multiphysics® to develop and analyze a MEMS-based sensor with a tri-layered design. This sensor comprises top and bottom electrodes made from gold (Au), noted for their excellent conductivity, a middle dielectric layer made from a composite of Silver Nanowires (AgNWs) embedded in Thermoplastic Polyurethane (TPU), and a flexible, durable substrate of Polydimethylsiloxane (PDMS). This research was directed towards understanding how changes in the physical characteristics of the AgNWs/TPU dielectric layer—specifically, its thickness and surface area—impact the sensor's operational efficacy. We assessed several key electrical properties: capacitance, electric potential, and membrane displacement under varied pressure conditions. These investigations are crucial for enhancing the sensor's sensitivity and ensuring its adaptability across diverse applications, including health monitoring systems and dynamic user interface technologies. To ensure the reliability of our simulations, we applied the Effective Medium Theory to calculate the dielectric constant of the AgNWs/TPU composite accurately. This approach is essential for predicting how the composite material will perform under different environmental and operational stresses, thus facilitating the optimization of the sensor design for enhanced performance and longevity. Moreover, we explored the potential benefits of innovative three-dimensional structures for the dielectric layer compared to traditional flat designs. Our hypothesis was that 3D configurations might improve the stress distribution and optimize the electrical field interactions within the sensor, thereby boosting its sensitivity and accuracy. Our simulation protocol includes comprehensive performance testing under simulated environmental conditions, such as temperature fluctuations and mechanical pressures, which mirror the actual operational conditions. These tests are crucial for assessing the sensor's robustness and its ability to function reliably over extended periods, ensuring high reliability and accuracy in complex real-world environments. In our current research, although a full dynamic simulation analysis of the three-dimensional structures has not yet been conducted, preliminary explorations through three-dimensional modeling have indicated the potential for mechanical and electrical performance improvements over traditional planar designs. These initial observations emphasize the potential advantages and importance of incorporating advanced three-dimensional modeling techniques in the development of Micro-Electro-Mechanical Systems (MEMS)sensors, offering new directions for the design and functional optimization of future sensors. Overall, this study not only highlights the powerful capabilities of COMSOL Multiphysics® for modeling sophisticated electronic devices but also underscores the potential of innovative MEMS technology in advancing the development of more effective, reliable, and adaptable sensor solutions for a broad spectrum of technological applications.

Keywords: MEMS, flexible sensors, COMSOL Multiphysics, AgNWs/TPU, PDMS, 3D modeling, sensor durability

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Authors: Monika Jurkeviciute, Amia Enam, Johanna Torres Bonilla, Henrik Eriksson

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Introduction: Many evaluations of eHealth interventions conclude that the evidence for improved clinical outcomes is limited, especially when the intervention is short, such as one year. Often, evaluation design does not address the feasibility of achieving clinical outcomes. Evaluations are designed to reflect upon clinical goals of intervention without utilizing the opportunity to illuminate effects on organizations and cost. A comprehensive design of evaluation can better support decision-making regarding the effectiveness and potential transferability of eHealth. Hence, the purpose of this paper is to present a feasible and comprehensive design of evaluation for eHealth intervention, including the design process in different contexts. Methodology: The situation of limited feasibility of clinical outcomes was foreseen in the European Union funded project called “DECI” (“Digital Environment for Cognitive Inclusion”) that is run under the “Horizon 2020” program with an aim to define and test a digital environment platform within corresponding care models that help elderly people live independently. A complex intervention of eHealth implementation into elaborate care models in four different countries was planned for one year. To design the evaluation, a participative approach was undertaken using Pettigrew’s lens of change and transformations, including context, process, and content. Through a series of workshops, observations, interviews, and document analysis, as well as a review of scientific literature, a comprehensive design of evaluation was created. Findings: The findings indicate that in order to get evidence on clinical outcomes, eHealth interventions should last longer than one year. The content of the comprehensive evaluation design includes a collection of qualitative and quantitative methods for data gathering which illuminates non-medical aspects. Furthermore, it contains communication arrangements to discuss the results and continuously improve the evaluation design, as well as procedures for monitoring and improving the data collection during the intervention. The process of the comprehensive evaluation design consists of four stages: (1) analysis of a current state in different contexts, including measurement systems, expectations and profiles of stakeholders, organizational ambitions to change due to eHealth integration, and the organizational capacity to collect data for evaluation; (2) workshop with project partners to discuss the as-is situation in relation to the project goals; (3) development of general and customized sets of relevant performance measures, questionnaires and interview questions; (4) setting up procedures and monitoring systems for the interventions. Lastly, strategies are presented on how challenges can be handled during the design process of evaluation in four different countries. The evaluation design needs to consider contextual factors such as project limitations, and differences between pilot sites in terms of eHealth solutions, patient groups, care models, national and organizational cultures and settings. This implies a need for the flexible approach to evaluation design to enable judgment over the effectiveness and potential for adoption and transferability of eHealth. In summary, this paper provides learning opportunities for future evaluation designs of eHealth interventions in different national and organizational settings.

Keywords: ehealth, elderly, evaluation, intervention, multi-cultural

Procedia PDF Downloads 293

Authors: Jonathan Kissi, Baozhen Dai, Wisdom W. K. Pomegbe, Abdul-Basit Kassim

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Protecting patient’s digital information is a growing concern for healthcare institutions as people nowadays perpetually live their lives through telemedicine services. These telemedicine services have been confronted with several determinants that hinder their successful implementations, especially in developing countries. Identifying such determinants that influence the acceptance of telemedicine services is also a problem for healthcare professionals. Despite the tremendous increase in telemedicine services, its adoption, and use has been quite slow in some healthcare settings. Generally, it is accepted in today’s globalizing world that the success of telemedicine services relies on users’ satisfaction. Satisfying health professionals and patients are one of the crucial objectives of telemedicine success. This study seeks to investigate the determinants that influence health professionals’ intention to utilize telemedicine services in clinical activities in a sub-Saharan African country in West Africa (Ghana). A hybridized model comprising of health adoption models, including technology acceptance theory, diffusion of innovation theory, and protection of motivation theory, were used to investigate these quandaries. The study was carried out in four government health institutions that apply and regulate telemedicine services in their clinical activities. A structured questionnaire was developed and used for data collection. Purposive and convenience sampling methods were used in the selection of healthcare professionals from different medical fields for the study. The collected data were analyzed based on structural equation modeling (SEM) approach. All selected constructs showed a significant relationship with health professional’s behavioral intention in the direction expected from prior literature including perceived usefulness, perceived ease of use, management strategies, financial sustainability, communication channels, patients security threat, patients privacy risk, self efficacy, actual service use, user satisfaction, and telemedicine services systems securities threat. Surprisingly, user characteristics and response efficacy of health professionals were not significant in the hybridized model. The findings and insights from this research show that health professionals are pragmatic when making choices for technology applications and also their willingness to use telemedicine services. They are, however, anxious about its threats and coping appraisals. The identified significant constructs in the study may help to increase efficiency, quality of services, quality patient care delivery, and satisfactory user satisfaction among healthcare professionals. The implantation and effective utilization of telemedicine services in the selected hospitals will aid as a strategy to eradicate hardships in healthcare services delivery. The service will help attain universal health access coverage to all populace. This study contributes to empirical knowledge by identifying the vital factors influencing health professionals’ behavioral intentions to adopt telemedicine services. The study will also help stakeholders of healthcare to formulate better policies towards telemedicine service usage.

Keywords: telemedicine service, perceived usefulness, perceived ease of use, management strategies, security threats

Procedia PDF Downloads 112

Authors: Nancy A. Delich, Stephen D. Roberts

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This case study explores using self-efficacy theory in counseling deaf and hard of hearing students in one California school district. Self-efficacy is described as the confidence a student has for performing a set of skills required to succeed at a specific task. When students need to learn a skill, self-efficacy can be a major factor in influencing behavioral change. Self-efficacy is domain specific, meaning that students can have high confidence in their abilities to accomplish a task in one domain, while at the same time having low confidence in their abilities to accomplish another task in a different domain. The communication isolation experienced by deaf and hard of hearing children and adolescents can negatively impact their belief about their ability to navigate life challenges. There is a need to address issues that impact deaf and hard of hearing students’ social-emotional development. Failure to address these needs may result in depression, suicidal ideation, and anxiety among other mental health concerns. Self-efficacy training can be used to address these socio-emotional developmental issues with this population. Four sources of experiences are applied during an intervention: (a) enactive mastery experience, (b) vicarious experience, (c) verbal persuasion, and (d) physiological and affective states. This case study describes the use of self-efficacy training with a coed group of 12 deaf and hard of hearing high school students who experienced bullying at school. Beginning with enactive mastery experience, the counselor introduced the topic of bullying to the group. The counselor educated the students about the different types of bullying while teaching them the terminology, signs and their meanings. The most effective way to increase self-efficacy is through extensive practice. To better understand these concepts, the students practiced through role-playing with the goal of developing self-advocacy skills. Vicarious experience is the perception that students have about their capabilities. Viewing other students advocating for themselves, cognitively rehearsing what actions they will and will not take, and teaching each other how to stand up against bullying can strengthen their belief in successfully overcoming bullying. The third source of self-efficacy beliefs is verbal persuasion. It occurs when others express belief in the capabilities of the student. Didactic training and pedagogic materials on bullying were employed as part of the group counseling sessions. The fourth source of self-efficacy appraisals is physiological and affective states. Students expect positive emotions to be associated with successful skilled performance. When students practice new skills, the counselor can apply several strategies to enhance self-efficacy while reducing and controlling emotional and physical states. The intervention plan incorporated all four sources of self-efficacy training during several interactive group sessions regarding bullying. There was an increased understanding around the issues of bullying, resulting in the students’ belief of their ability to perform protective behaviors and deter future occurrences. The outcome of the intervention plan resulted in a reduction of reported bullying incidents. In conclusion, self-efficacy training can be an effective counseling and teaching strategy in addressing and enhancing the social-emotional functioning with deaf and hard of hearing adolescents.

Keywords: counseling, self-efficacy, bullying, social-emotional development, mental health, deaf and hard of hearing students

Procedia PDF Downloads 327

Authors: Yan Zhang

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Predictive maintenance is a technique to predict when an in-service machine will fail so that maintenance can be planned in advance. Analytics-driven predictive maintenance is gaining increasing attention in many industries such as manufacturing, utilities, aerospace, etc., along with the emerging demand of Internet of Things (IoT) applications and the maturity of technologies that support Big Data storage and processing. This study aims to build an end-to-end analytics solution that includes both real-time machine condition monitoring and machine learning based predictive analytics capabilities. The goal is to showcase a general predictive maintenance solution architecture, which suggests how the data generated from field machines can be collected, transmitted, stored, and analyzed. We use a publicly available aircraft engine run-to-failure dataset to illustrate the streaming analytics component and the batch failure prediction component. We outline the contributions of this study from four aspects. First, we compare the predictive maintenance problems from the view of the traditional reliability centered maintenance field, and from the view of the IoT applications. When evolving to the IoT era, predictive maintenance has shifted its focus from ensuring reliable machine operations to improve production/maintenance efficiency via any maintenance related tasks. It covers a variety of topics, including but not limited to: failure prediction, fault forecasting, failure detection and diagnosis, and recommendation of maintenance actions after failure. Second, we review the state-of-art technologies that enable a machine/device to transmit data all the way through the Cloud for storage and advanced analytics. These technologies vary drastically mainly based on the power source and functionality of the devices. For example, a consumer machine such as an elevator uses completely different data transmission protocols comparing to the sensor units in an environmental sensor network. The former may transfer data into the Cloud via WiFi directly. The latter usually uses radio communication inherent the network, and the data is stored in a staging data node before it can be transmitted into the Cloud when necessary. Third, we illustrate show to formulate a machine learning problem to predict machine fault/failures. By showing a step-by-step process of data labeling, feature engineering, model construction and evaluation, we share following experiences: (1) what are the specific data quality issues that have crucial impact on predictive maintenance use cases; (2) how to train and evaluate a model when training data contains inter-dependent records. Four, we review the tools available to build such a data pipeline that digests the data and produce insights. We show the tools we use including data injection, streaming data processing, machine learning model training, and the tool that coordinates/schedules different jobs. In addition, we show the visualization tool that creates rich data visualizations for both real-time insights and prediction results. To conclude, there are two key takeaways from this study. (1) It summarizes the landscape and challenges of predictive maintenance applications. (2) It takes an example in aerospace with publicly available data to illustrate each component in the proposed data pipeline and showcases how the solution can be deployed as a live demo.

Keywords: Internet of Things, machine learning, predictive maintenance, streaming data

Procedia PDF Downloads 359