Search results for: building information modelling

Authors: Ionut Vintu, Stefan Laible, Ruth Schulz

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Agricultural robotics has been developing steadily over recent years, with the goal of reducing and even eliminating pesticides used in crops and to increase productivity by taking over human labor. The majority of crops are arranged in rows. The first step towards autonomous robots, capable of driving in fields and performing crop-handling tasks, is for robots to robustly detect the rows of plants. Recent work done towards autonomous driving between plant rows offers big robotic platforms equipped with various expensive sensors as a solution to this problem. These platforms need to be driven over the rows of plants. This approach lacks flexibility and scalability when it comes to the height of plants or distance between rows. This paper proposes instead an algorithm that makes use of cheaper sensors and has a higher variability. The main application is in tree nurseries. Here, plant height can range from a few centimeters to a few meters. Moreover, trees are often removed, leading to gaps within the plant rows. The core idea is to combine row detection algorithms with graph-based localization methods as they are used in SLAM. Nodes in the graph represent the estimated pose of the robot, and the edges embed constraints between these poses or between the robot and certain landmarks. This setup aims to improve individual plant detection and deal with exception handling, like row gaps, which are falsely detected as an end of rows. Four methods were developed for detecting row structures in the fields, all using a point cloud acquired with a 3D LiDAR as an input. Comparing the field coverage and number of damaged plants, the method that uses a local map around the robot proved to perform the best, with 68% covered rows and 25% damaged plants. This method is further used and combined with a graph-based localization algorithm, which uses the local map features to estimate the robot’s position inside the greater field. Testing the upgraded algorithm in a variety of simulated fields shows that the additional information obtained from localization provides a boost in performance over methods that rely purely on perception to navigate. The final algorithm achieved a row coverage of 80% and an accuracy of 27% damaged plants. Future work would focus on achieving a perfect score of 100% covered rows and 0% damaged plants. The main challenges that the algorithm needs to overcome are fields where the height of the plants is too small for the plants to be detected and fields where it is hard to distinguish between individual plants when they are overlapping. The method was also tested on a real robot in a small field with artificial plants. The tests were performed using a small robot platform equipped with wheel encoders, an IMU and an FX10 3D LiDAR. Over ten runs, the system achieved 100% coverage and 0% damaged plants. The framework built within the scope of this work can be further used to integrate data from additional sensors, with the goal of achieving even better results.

Keywords: 3D LiDAR, agricultural robots, graph-based localization, row detection

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Authors: S. Fares, K. Mellakh, A. Hmouri

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The StorMer project aims to set up a network of researchers to study traditional hydraulic rainwater harvesting systems in the Mediterranean basin, a region suffering from the major impacts of climate change and limited natural water resources. The arid and semi-arid Mediterranean basin has a long history of pioneering water management practices. The region has developed various ancient traditional water management systems, such as cisterns and qanats, to sustainably manage water resources under historical conditions of scarcity. Therefore, the StorMer project brings together Spain, France, Italy, Greece, Jordan and Morocco to explore traditional rainwater harvesting practices and systems in the Mediterranean region and to develop accurate modeling to simulate the performance and sustainability of these technologies under present-day climatic conditions. The ultimate goal of this project was to resuscitate and valorize these practices in the context of contemporary challenges. This project was intended to establish a Mediterranean network to serve as a basis for a more ambitious project. The ultimate objective was to analyze traditional hydraulic systems and create a prototype hydraulic ecosystem using a coupled environmental approach and traditional and ancient know-how, with the aim of reinterpreting them in the light of current techniques. The combination of ‘traditional’ and ‘modern knowledge/techniques’ is expected to lead to proposals for innovative hydraulic systems. The pandemic initially slowed our progress, but in the end it forced us to carry out the fieldwork in Morocco and Saudi Arabia, and so restart the project. With the participation of colleagues from chronologically distant fields (archaeology, sociology), we are now prepared to share our observations and propose the next steps. This interdisciplinary approach should give us a global vision of the project's objectives and challenges. A diachronic approach is needed to tackle the question of the long-term adaptation of societies in a Mediterranean context that has experienced several periods of water stress. The next stage of the StorMer project is the implementation of pilots in non-urbanized regions. These pilots will test the implementation of traditional systems and will be maintained and evaluated in terms of effectiveness, cost and acceptance. Based on these experiences, larger projects will be proposed and could provide information for regional water management policies. One of the most important lessons learned from this project is the highly social nature of managing traditional rainwater harvesting systems. Unlike modern, centralized water infrastructures, these systems often require the involvement of communities, which assume ownership and responsibility for them. This kind of community engagement leads to greater maintenance and, therefore, sustainability of the systems. Knowledge of the socio-cultural characteristics of these communities means that the systems can be adapted to the needs of each location, ensuring greater acceptance and efficiency.

Keywords: oasis, rainfall harvesting, arid regions, Mediterranean

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Authors: Katarina Ott, Velibor Mačkić, Mihaela Bronić, Branko Stanić

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The determinants of national budget transparency have been widely discussed in the literature, while research on determinants of local budget transparency are scarce and empirically inconclusive, particularly in the new, fiscally centralised, EU member states. To fill the gap, we combine two strands of the literature: that concerned with public administration and public finance, shedding light on the economic and financial determinants of local budget transparency, and that on the political economy of transparency (principal agent theory), covering the relationships among politicians and between politicians and voters. Our main hypothesis states that variables describing residents’ capacity have a greater impact on local budget transparency than variables indicating the institutional capacity of local government units (LGUs). Additional subhypotheses test the impact of each variable analysed on local budget transparency. We address the determinants of local budget transparency in Croatia, measured by the number of key local budget documents published on the LGUs’ websites. By using a data set of 128 cities and 428 municipalities over the 2015-2017 period and by applying panel data analysis based on Poisson and negative binomial distribution, we test our main hypothesis and sub-hypotheses empirically. We measure different characteristics of institutional and residents’ capacity for each LGU. Age, education and ideology of the mayor/municipality head, political competition indicators, number of employees, current budget revenues and direct debt per capita have been used as a measure of the institutional capacity of LGU. Residents’ capacity in each LGU has been measured through the numbers of citizens and their average age as well as by average income per capita. The most important determinant of local budget transparency is average residents' income per capita at both city and municipality level. The results are in line with most previous research results in fiscally decentralised countries. In the context of a fiscally centralised country with numerous small LGUs, most of whom have low administrative and fiscal capacity, this has a theoretical rationale in the legitimacy and principal-agent theory (opportunistic motives of the incumbent). The result is robust and significant, but because of the various other results that change between city and municipality levels (e.g. ideology and political competition), there is a need for further research (both on identifying other determinates and/or methods of analysis). Since in Croatia the fiscal capacity of a LGU depends heavily on the income of its residents, units with higher per capita incomes in many cases have also higher budget revenues allowing them to engage more employees and resources. In addition, residents’ incomes might be also positively associated with local budget transparency because of higher citizen demand for such transparency. Residents with higher incomes expect more public services and have more access to and experience in using the Internet, and will thus typically demand more budget information on the LGUs’ websites.

Keywords: budget transparency, count data, Croatia, local government, political economy

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Authors: Motaz Alsolaim

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Nowadays, the challenges of running a start-up can be very complex and are perhaps more difficult than at any other time in the past. Changes in technology, manufacturing innovation, and product development, combined with intense competition and market regulations are factors that have put pressure on classic ways of managing firms, thereby forcing change. As a result, the rate of closure, exit or discontinuation of start-ups and young businesses is very high. Despite the essential role of small firms in an economy, they still tend to face obstacles that exert a negative influence on their performance and rate of survival. In fact, it is not easy to determine with any certainty the reasons why small firms fail. For this reason, failure itself is not clearly defined, and its exact causes are hard to diagnose. In this current study, therefore, the barriers to survival will be covered more broadly, especially personal/entrepreneurial, enterprise and environmental factors with regard to various possible reasons for this failure, in order to determine the best solutions and make appropriate recommendations. Methodology: It could be argued that mixed methods might help to improve entrepreneurship research addressing challenges emphasis in previous studies and to achieve the triangulation. Calls for the combined use of quantitative and qualitative research were also made in the entrepreneurship field since entrepreneurship is a multi-faceted area of research. Therefore, explanatory sequential mixed method was used, using questionnaire online survey for entrepreneurs, followed by semi-structure interview. Collecting over 750 surveys and accepting 296 valid surveys, after that 13 interviews from government official seniors, businessmen successful entrepreneurs, and non-successful entrepreneurs. Findings: The first phase findings ( quantitative) shows the obstacles to survive; starting from the personal/ entrepreneurial factors such as; past work experience, lack of skills and interest, are positive factors, while; gender, age and education level of the owner are negative factors. Internal factors such as lack of marketing research and weak business planning are positive. The environmental factors; in economic perspectives; difficulty to find labors, in socio-cultural perspectives; Social restriction and traditions found to be a negative factors. In other hand, from the political perspective; cost of compliance and insufficient government plans found to be a positive factors for small business failure. From infrastructure perspective; lack of skills labor, high level of bureaucracy and lack of information are positive factors. Conclusion: This paper serves to enrich the understanding of failure factors in MENA region more precisely in SA, by minimizing the probability of failure in small-micro entrepreneurial start-up in SA, in the light of the Saudi government’s Vision 2030 plan.

Keywords: small business barriers, start-up business, entrepreneurship, Saudi Arabia

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Authors: Xincheng Jiang, Yanyan An, Yaoyao Huang, Wei Ding, Manli Sun, Hong Li, Huaili Zheng

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The residual antibiotics in the environment will pose a threat to the environment and human health. Thus, efficient removal and rapid detection of norfloxacin (NOR) in wastewater is very important. The main sources of NOR pollution are the agricultural, pharmaceutical industry and hospital wastewater. The total consumption of NOR in China can reach 5440 tons per year. It is found that neither animals nor humans can totally absorb and metabolize NOR, resulting in the excretion of NOR into the environment. Therefore, residual NOR has been detected in water bodies. The hazards of NOR in wastewater lie in three aspects: (1) the removal capacity of the wastewater treatment plant for NOR is limited (it is reported that the average removal efficiency of NOR in the wastewater treatment plant is only 68%); (2) NOR entering the environment will lead to the emergence of drug-resistant strains; (3) NOR is toxic to many aquatic species. At present, the removal and detection technologies of NOR are applied separately, which leads to a cumbersome operation process. The development of simultaneous adsorption-flocculation removal and FTIR detection of pollutants has three advantages: (1) Adsorption-flocculation technology promotes the detection technology (the enrichment effect on the material surface improves the detection ability); (2) The integration of adsorption-flocculation technology and detection technology reduces the material cost and makes the operation easier; (3) FTIR detection technology endows the water treatment agent with the ability of molecular recognition and semi-quantitative detection for pollutants. Thus, it is of great significance to develop a smart water treatment material with high removal capacity and detection ability for pollutants. This study explored the feasibility of combining NOR removal method with the semi-quantitative detection method. A magnetic Cu-Ni-S/Ni foam was synthesized by in-situ loading Cu-Ni-S nanostructures on the surface of Ni foam. The novelty of this material is the combination of adsorption-flocculation technology and semi-quantitative detection technology. Batch experiments showed that Cu-Ni-S/Ni foam has a high removal rate of NOR (96.92%), wide pH adaptability (pH=4.0-10.0) and strong ion interference resistance (0.1-100 mmol/L). According to the Langmuir fitting model, the removal capacity can reach 417.4 mg/g at 25 °C, which is much higher than that of other water treatment agents reported in most studies. Characterization analysis indicated that the main removal mechanisms are surface complexation, cation bridging, electrostatic attraction, precipitation and flocculation. Transmission FTIR detection experiments showed that NOR on Cu-Ni-S/Ni foam has easily recognizable FTIR fingerprints; the intensity of characteristic peaks roughly reflects the concentration information to some extent. This semi-quantitative detection method has a wide linear range (5-100 mg/L) and a low limit of detection (4.6 mg/L). These results show that Cu-Ni-S/Ni foam has excellent removal performance and semi-quantitative detection ability of NOR molecules. This paper provides a new idea for designing and preparing multi-functional water treatment materials to achieve simultaneous removal and semi-quantitative detection of organic pollutants in water.

Keywords: adsorption-flocculation, antibiotics detection, Cu-Ni-S/Ni foam, norfloxacin

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Authors: Alexander Guzman Urbina, Atsushi Aoyama

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The sustainability of traditional technologies employed in energy and chemical infrastructure brings a big challenge for our society. Making decisions related with safety of industrial infrastructure, the values of accidental risk are becoming relevant points for discussion. However, the challenge is the reliability of the models employed to get the risk data. Such models usually involve large number of variables and with large amounts of uncertainty. The most efficient techniques to overcome those problems are built using Artificial Intelligence (AI), and more specifically using hybrid systems such as Neuro-Fuzzy algorithms. Therefore, this paper aims to introduce a hybrid algorithm for risk assessment trained using near-miss accident data. As mentioned above the sustainability of traditional technologies related with energy and chemical infrastructure constitutes one of the major challenges that today’s societies and firms are facing. Besides that, the adaptation of those technologies to the effects of the climate change in sensible environments represents a critical concern for safety and risk management. Regarding this issue argue that social consequences of catastrophic risks are increasing rapidly, due mainly to the concentration of people and energy infrastructure in hazard-prone areas, aggravated by the lack of knowledge about the risks. Additional to the social consequences described above, and considering the industrial sector as critical infrastructure due to its large impact to the economy in case of a failure the relevance of industrial safety has become a critical issue for the current society. Then, regarding the safety concern, pipeline operators and regulators have been performing risk assessments in attempts to evaluate accurately probabilities of failure of the infrastructure, and consequences associated with those failures. However, estimating accidental risks in critical infrastructure involves a substantial effort and costs due to number of variables involved, complexity and lack of information. Therefore, this paper aims to introduce a well trained algorithm for risk assessment using deep learning, which could be capable to deal efficiently with the complexity and uncertainty. The advantage point of the deep learning using near-miss accidents data is that it could be employed in risk assessment as an efficient engineering tool to treat the uncertainty of the risk values in complex environments. The basic idea of using a Near-Miss Deep Learning Approach for Neuro-Fuzzy Risk Assessment in Pipelines is focused in the objective of improve the validity of the risk values learning from near-miss accidents and imitating the human expertise scoring risks and setting tolerance levels. In summary, the method of Deep Learning for Neuro-Fuzzy Risk Assessment involves a regression analysis called group method of data handling (GMDH), which consists in the determination of the optimal configuration of the risk assessment model and its parameters employing polynomial theory.

Keywords: deep learning, risk assessment, neuro fuzzy, pipelines

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Authors: Kai Warsoenke, Maik Mackiewicz

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To achieve a high quality of assembled car body structures, tolerancing is used to ensure a geometric accuracy of the single car body parts. There are two main techniques to determine the required tolerances. The first is tolerance analysis which describes the influence of individually tolerated input values on a required target value. Second is tolerance synthesis to determine the location of individual tolerances to achieve a target value. Both techniques are based on classical statistical methods, which assume certain probability distributions. To ensure competitiveness in both saturated and dynamic markets, production processes in vehicle manufacturing must be flexible and efficient. The dimensional specifications selected for the individual body components and the resulting assemblies have a major influence of the quality of the process. For example, in the manufacturing of forming tools as operating equipment or in the higher level of car body assembly. As part of the metrological process monitoring, manufactured individual parts and assemblies are recorded and the measurement results are stored in databases. They serve as information for the temporary adjustment of the production processes and are interpreted by experts in order to derive suitable adjustments measures. In the production of forming tools, this means that time-consuming and costly changes of the tool surface have to be made, while in the body shop, uncertainties that are difficult to control result in cost-intensive rework. The stored measurement results are not used to intelligently design tolerances in future processes or to support temporary decisions based on real-world geometric data. They offer potential to extend the tolerancing methods through data analysis and machine learning models. The purpose of this paper is to examine real-world measurement data from individual car body components, as well as assemblies, in order to develop an approach for using the data in short-term actions and future projects. For this reason, the measurement data will be analyzed descriptively in the first step in order to characterize their behavior and to determine possible correlations. In the following, a database is created that is suitable for developing machine learning models. The objective is to create an intelligent way to determine the position and number of measurement points as well as the local tolerance range. For this a number of different model types are compared and evaluated. The models with the best result are used to optimize equally distributed measuring points on unknown car body part geometries and to assign tolerance ranges to them. The current results of this investigation are still in progress. However, there are areas of the car body parts which behave more sensitively compared to the overall part and indicate that intelligent tolerancing is useful here in order to design and control preceding and succeeding processes more efficiently.

Keywords: automotive production, machine learning, process optimization, smart tolerancing

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Authors: Ignitia Motjolopane

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Small and medium enterprises (SMEs) play an important role in economies by contributing to economic growth and employment. In the fourth industrial revolution, the convergence of technologies and the changing nature of work created pressures on economies globally. Generative artificial intelligence (AI) may support SMEs in exploring, exploiting, and transforming business models to align with their growth aspirations. SMEs' growth aspirations fall into four categories: subsistence, income, growth, and speculative. Subsistence-oriented firms focus on meeting basic financial obligations and show less motivation for business model innovation. SMEs focused on income, growth, and speculation are more likely to pursue business model innovation to support growth strategies. SMEs' strategic goals link to distinct business model innovation paths depending on whether SMEs are starting a new business, pursuing growth, or seeking profitability. Integrating generative artificial intelligence in start-up SME business model innovation enhances value creation, user-oriented innovation, and SMEs' ability to adapt to dynamic changes in the business environment. The existing literature may lack comprehensive frameworks and guidelines for effectively integrating generative AI in start-up reiterative business model innovation paths. This paper examines start-up business model innovation path with generative artificial intelligence. A theoretical approach is used to examine start-up-focused SME reiterative business model innovation path with generative AI. Articulating how generative AI may be used to support SMEs to systematically and cyclically build the business model covering most or all business model components and analyse and test the BM's viability throughout the process. As such, the paper explores generative AI usage in market exploration. Moreover, market exploration poses unique challenges for start-ups compared to established companies due to a lack of extensive customer data, sales history, and market knowledge. Furthermore, the paper examines the use of generative AI in developing and testing viable value propositions and business models. In addition, the paper looks into identifying and selecting partners with generative AI support. Selecting the right partners is crucial for start-ups and may significantly impact success. The paper will examine generative AI usage in choosing the right information technology, funding process, revenue model determination, and stress testing business models. Stress testing business models validate strong and weak points by applying scenarios and evaluating the robustness of individual business model components and the interrelation between components. Thus, the stress testing business model may address these uncertainties, as misalignment between an organisation and its environment has been recognised as the leading cause of company failure. Generative AI may be used to generate business model stress-testing scenarios. The paper is expected to make a theoretical and practical contribution to theory and approaches in crafting a robust business model innovation path with generative artificial intelligence in start-up SMEs.

Keywords: business models, innovation, generative AI, small medium enterprises

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Authors: Katharina Lapin, Debashis Sanyal

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Worldwide urban areas are growing. Urbanization has a great impact on social and economic development and ecosystem services. This global trend of urbanization also has significant impact on habitat and biodiversity. The impact of urbanization on the biodiversity of cities in Europe and North America is well studied, while there is a lack of data from cities in currently fast growing urban areas. Indian cities are expanding. The scientific community and the governmental authorities are facing the ongoing urbanization process as an opportunity for the environment. This case study supports the evaluation of urban biodiversity of the city Raipur in the North-West of India. The aim of this study is to assess the overview of the environmental and ecological implications of urbanization. The collected data and analysis was used to discuss the challenges for the sustainable city development. Vascular plants were chosen as an appropriate indicator for the assessment of local biodiversity changes. On the one hand, the vegetation cover is sensible to anthropogenic influence, and in the other hand, the local species composition is comparable to changes at the regional and national scale, using the plant index of India. Further information of abiotic situation can be gathered with the determination of indicator species. In order to calculate the influence of urbanization on the native plant diversity, the Shannon diversity index H´ was chosen. The Pielou`s pooled quadrate method was used for estimating diversity when a random sample is not expected. It was used to calculate the Pilou´s index of evenness. The estimated species coverage was used for calculating the H´ and J. Pearson correlation was performed to test the relationship between urbanization pattern and plant diversity. Further, a SWOT analysis was used in for analyzing internal and external factors impinging on a decision making process. The city of Raipur (21.25°N 81.63°E) has a population of 1,010,087 inhabitants living in an urban area of 226km², in the district of the Indian state of Chhattisgarh. Within the last decade, the urban area of Raipur increased. The results show that various novel ecosystems exist in the urban area of Raipur. The high amount of native flora is mainly to find at the shore of urban lakes and along the river Karun. These areas of high Biodiversity Index are to protect as urban biodiversity hot spots. The governmental authorities are well informed about the environmental challenges for the sustainable development of the city. Together with the scientific community of the Technical University of Raipur many engineering solutions are discussed for implementation of the future. The case study helped to point out the importance environmental measures that support the ecosystem services of green infrastructure. The fast process of urbanization is difficult to control. Uncontrolled creation of urban housing leads to difficulties in unsustainable use of natural resources. This is the major threat for the urban biodiversity.

Keywords: India, novel ecosystems, plant diversity, urban ecology

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Authors: Innocent Atuhe, Babra Nalwadda, Grace Mulyowa Kitunzi, Annabella Haninka Ejiri

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Background: Atopic Dermatitis (AD) is one of the most prevalent and growing chronic inflammatory skin diseases in African prisons. AD care is limited in African due to lack of information about the disease amongst primary care workers, limited access to dermatologists, lack of proper training of healthcare workers, and shortage of appropriate treatments. We designed and implemented the Prisons Telederma project based on the recommendations of the International Society of Atopic Dermatitis. Our overall goal was to increase access to dermatologist-led care for prisoners with AD through teledermatology in Uganda. We aimed to; i) to increase awareness and understanding of teledermatology among prison health workers; and ii) to improve treatment outcomes of prisoners with atopic dermatitis through increased access to and utilization of consultant dermatologists through teledermatology in Uganda prisons: Approach: We used Store-and-forward Teledermatology (SAF-TD) to increase access to dermatologist-led care for prisoners and prisons staff with AD. We conducted a five days training for prison health workers using an adapted WHO training guide on recognizing neglected tropical diseases through changes on the skin together with an adapted American Academy of Dermatology (AAD) Childhood AD Basic Dermatology Curriculum designed to help trainees develop a clinical approach to the evaluation and initial management of patients with AD. This training was followed by blended e-learning, webinars facilitated by consultant Dermatologists with local knowledge of medication and local practices, apps adjusted for pigmented skin, WhatsApp group discussions, and sharing pigmented skin AD pictures and treatment via zoom meetings. We hired a team of Ugandan Senior Consultant dermatologists to draft an iconographic atlas of the main dermatoses in pigmented African skin and shared this atlas with prison health staff for use as a job aid. We had planned to use MySkinSelfie mobile phone application to take and share skin pictures of prisoners with AD with Consultant Dermatologists, who would review the pictures and prescribe appropriate treatment. Unfortunately, the National Health Service withdrew the app from the market due to technical issues. We monitored and evaluated treatment outcomes using the Patient Oriented Eczema Measure (POEM) tool. We held four advocacy meetings to persuade relevant stakeholders to increase supplies and availability of first-line AD treatments such as emollients in prison health facilities. Results: Draft iconographic atlas of the main dermatoses in pigmented African skin Increased proportion of prison health staff with adequate knowledge of AD and teledermatology from 20% to 80% Increased proportion of prisoners with AD reporting improvement in disease severity (POEM scores) from 25% to 35% in one year. Increased proportion of prisoners with AD seen by consultant dermatologist through teledermatology from 0% to 20% in one year. Increased the availability of AD recommended treatments in prisons health facilities from 5% to 10% in one year

Keywords: teledermatology, prisoners, reaching, un-reachable

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Authors: Stephen Bahooshy

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Co-producing services with the people that access them is considered best practice in the United Kingdom, with the Care Act 2014 arguing that people who access services and their carers should be involved in the design, commissioning and delivery of services. Co-production is a way of working with the community, breaking down barriers of access and providing meaningful opportunity for people to engage. Unfortunately, owing to a number of reported factors such as time constraints, practitioner experience and departmental budget restraints, this process is not always followed. In 2019, in a south London borough, d/Deaf people who access services were engaged in the design, commissioning and delivery of an information and advice service that would support their community to access local government services. To do this, sensory impairment social workers and commissioners collaborated to host a series of engagement events with the d/Deaf community. Interpreters were used to enable communication between the commissioners and d/Deaf participants. Initially, the community’s opinions, ideas and requirements were noted. This was then summarized and fed back to the community to ensure accuracy. Subsequently, a service specification was developed which included performance metrics, inclusive of qualitative and quantitative indicators, such as ‘I statements’, whereby participants respond on an adapted Likert scale how much they agree or disagree with a particular statement in relation to their experience of the service. The service specification was reviewed by a smaller group of d/Deaf residents and social workers, to ensure that it met the community’s requirements. The service was then tendered using the local authority’s e-tender process. Bids were evaluated and scored in two parts; part one was by commissioners and social workers and part two was a presentation by prospective providers to an evaluation panel formed of four d/Deaf residents. The internal evaluation panel formed 75% of the overall score, whilst the d/Deaf resident evaluation panel formed 25% of the overall tender score. Co-producing the evaluation panel with social workers and the d/Deaf community meant that commissioners were able to meet the requirements of this community by developing evaluation questions and tools that were easily understood and use by this community. For example, the wording of questions were reviewed and the scoring mechanism consisted of three faces to reflect the d/Deaf residents’ scores instead of traditional numbering. These faces were a happy face, a neutral face and a sad face. By making simple changes to the commissioning and tender evaluation process, d/Deaf people were able to have meaningful involvement in the design and commissioning process for a service that would benefit their community. Co-produced performance metrics means that it is incumbent on the successful provider to continue to engage with people accessing the service and ensure that the feedback is utilized. d/Deaf residents were grateful to have been involved in this process as this was not an opportunity that they had previously been afforded. In recognition of their time, each d/Deaf resident evaluator received a £40 gift voucher, bringing the total cost of this co-production to £160.

Keywords: co-production, community engagement, deaf and hearing impaired, service design

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Authors: Sigal Portnoy, Jason Friedman, Eitan Raveh

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Introduction: Sensory substitution is possible due to the capacity of our brain to adapt to information transmitted by a synthetic receptor via an alternative sensory system. Practical sensory substitution systems are being developed in order to increase the functionality of individuals with sensory loss, e.g. amputees. For upper limb prosthetic-users the loss of tactile feedback compels them to allocate visual attention to their prosthesis. The effect of adding vibrotactile feedback (VTF) to the applied force has been studied, however its effect on the allocation if visual attention during dual-tasking and the response during misleading visual feedback have not been studied. We hypothesized that VTF will improve the performance and reduce visual attention during dual-task assignments in healthy individuals using a robotic hand and improve the performance in a standardized functional test, despite the presence of misleading visual feedback. Methods: For the dual-task paradigm, twenty healthy subjects were instructed to toggle two keyboard arrow keys with the left hand to retain a moving virtual car on a road on a screen. During the game, instructions for various activities, e.g. mix the sugar in the glass with a spoon, appeared on the screen. The subject performed these tasks with a robotic hand, attached to the right hand. The robotic hand was controlled by the activity of the flexors and extensors of the right wrist, recorded using surface EMG electrodes. Pressure sensors were attached at the tips of the robotic hand and induced VTF using vibrotactile actuators attached to the right arm of the subject. An eye-tracking system tracked to visual attention of the subject during the trials. The trials were repeated twice, with and without the VTF. Additionally, the subjects performed the modified box and blocks, hidden from eyesight, in a motion laboratory. A virtual presentation of a misleading visual feedback was be presented on a screen so that twice during the trial, the virtual block fell while the physical block was still held by the subject. Results: This is an ongoing study, which current results are detailed below. We are continuing these trials with transradial myoelectric prosthesis-users. In the healthy group, the VTF did not reduce the visual attention or improve performance during dual-tasking for the tasks that were typed transfer-to-target, e.g. place the eraser on the shelf. An improvement was observed for other tasks. For example, the average±standard deviation of time to complete the sugar-mixing task was 13.7±17.2s and 19.3±9.1s with and without the VTF, respectively. Also, the number of gaze shifts from the screen to the hand during this task were 15.5±23.7 and 20.0±11.6, with and without the VTF, respectively. The response of the subjects to the misleading visual feedback did not differ between the two conditions, i.e. with and without VTF. Conclusions: Our interim results suggest that the performance of certain activities of daily living may be improved by VTF. The substitution of visual sensory input by tactile feedback might require a long training period so that brain plasticity can occur and allow adaptation to the new condition.

Keywords: prosthetics, rehabilitation, sensory substitution, upper limb amputation

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Authors: Sunha Ahn

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Intimate relationships have constructed our embodied experiences and emotional memories, which can become grounded as practical knowledge to some extent and play a critical role in social medicine, particularly, in our well-being and mental health. In South Africa, such relational factors are significant for young women and girls in their emotional development period of time, especially, working as the existence of social and relational pressures over feminine sexual health and choices. This, in turn, brings about the absence/lack of communication in intimate relationships, especially with their parents, which leads to a vicious cycle in sexual health behaviour choices. Drawing upon sociological and socio-anthropological understandings of HIV-related issues, this study provides narrative threads of evidence about South African teenage mothers from early-dating debuted to HIV infection. Their stories consist of a visualised figure in chronicle order, illustrating embodied journeys of sexual health choices surrounding uncommunicative relationships and socially-suppressive environments. Methodologically, this qualitative study explored data from mixed online methods: 1) a case study analysing online comments (N = 12,763) on the South African Springster's website, run by the UK-based NGO, namely, Girl Effect; and 2) In-depth online interviews (N = 21) were conducted with young SA women and girls (16-28 ages) recruited in Cape Town, Pretoria, and Johannesburg, SA. Participants consist of both those living with HIV and without. Ethical approval was gained via the College of Social Sciences Ethical Committee at the University of Glasgow, and informed consent was obtained verbally and in writing from participants in due course. Data were thematically applied to an iteratively developed codebook and analysed. There are three kinds of typical pressures as relational factors for them, including peer pressure, partners or boyfriends, and parents’ reactions. Under the patriarchal and religious-devoted social atmospheres, these relationships work as a source of scaredness among young women and girls who could not talk about their sexual health concerns and rights. Such an inability to communicate with intimate relationships, eventually, emerges as a perpetuated or taken-for-granted social environment in South Africa, insistently leading to an increase in unwanted pregnancies or new HIV infections in young South African women and girls. In this sense, this study reveals the pressing need for open communication between generations with accurate information about HIV/AIDS. This also implies that the sociological feminist praxes in South Africa would help eliminate HIV-related stigma as well as construct open space to reduce gender-based violence and sexually-transmitted infection. Ultimately, this will be a road for supporting sexually healthy decisions and well-being across South African generations.

Keywords: HIV, young women, South Africa, intimate relationships, communication, social medicine

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Authors: Elena Chernyak, Ryan Ceresola

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Intimate partner violence is a serious social problem that affects a million women worldwide and impacts their health and wellbeing. Some risk factors for intimate partner violence against women (e.g., disobeying or arguing with a partner, women’s age, education, and employment) are similar in many countries, both developed and developing. However, one of the principal and most significant contributors to women’s vulnerability to violence perpetrated by their intimate partners is the witnessing of interparental aggression in the family of origin. Witnessing interparental violence may lead to acceptance of intimate partner violence as a normal way to resolve conflicts. Thus, utilization of violence becomes the behavioral model: men who witnessed the parental violence are more likely to employ physical violence against their female partners whereas women who observed their fathers beating their mothers learn to tolerate aggressive behavior and become victims of domestic violence themselves. Taking into consideration the importance of this subject matter, the association between witnessing intimate partner violence in family-of-origin and experience of intimate partner violence in adulthood requires further attention. The objective of this research is to analyze and compare the prevalence of intimate partner violence in ten developing countries in different regions, namely: Mali, Haiti, Jordan, Peru, the Philippines, Pakistan, Cambodia, Egypt, the Dominican Republic and Nigeria. Specifically, this research asks whether witnessing interparental violence in a family of origin is associated with the woman’s experience of intimate partner violence during adulthood and to what extent this factor varies among the countries under investigation. This study contributes to the literature on domestic violence against women, prevalence and experience of intimate partner violence against women in developing countries, and the risk factors, using recently collected, nationally representative population-based data from above-mentioned countries. The data used in this research are derived from the demographic and health surveys conducted in the ten mentioned above countries from 2013-2016. These surveys are cross-sectional, nationally representative surveys of ever-married or cohabitating women of reproductive age and the good source of high quality and comprehensive information about women, their children, partners, and households. To complete this analysis, multivariate logistic regression was run for each of the countries, and the results are presented with odds ratios, in order to highlight the effect of witnessing intimate partner violence controlling for other factors. The results of this study indicated that having witnessed partner violence in a family of origin significantly (by 50-500%) increases the likelihood of experiencing later abuse for respondents in all countries. This finding provides robust support for the intergenerational transmission of violence theory that explains the link between interparental aggression and intimate partner violence in subsequent relationships in adulthood as a result of a learned model of behavior observed in childhood. Furthermore, it was found that some of the control variables (e.g., education, number of children, and wealth) are associated with intimate partner violence in some countries under investigation while are not associated with male partner’s abusive behavior in some other, which may be explained by specific cultural and economic factors.

Keywords: intimate partner violence, domestic violence against women, developing countries, demographic and health surveys, risk factors

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Authors: Meilan Jin, Mary Jane Moran

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This study aims to introduce the framework of culturally responsive home visiting (CRHV) to head start teacher professional sessions in the Southeastern of the US and investigate its influence on the evolving beliefs of teachers about their roles and relationships with families in-home visits. The framework orients teachers to an effective way of taking on the role of learner to listen for spoken and unspoken needs and look for family strengths. In addition, it challenges the deficit model that is grounded on 'cultural deprivation,' and it stresses the value of family cultures and advocates equal, collaborative parent-teacher relationships. The home visit reflection papers and focus group transcriptions of eight teachers have been collected since 2010 throughout a five-year longitudinal collaboration with them. Reflection papers were written by the teachers before and after introducing the CRHV framework, including the details of visit purposes and actions and their plans for later home visits. Particularly, the CRHV framework guided the teachers to listen and look for information about family-living environments; parent-child interactions; child-rearing practices; and parental beliefs, values, and needs. Two focus groups were organized in 2014 by asking the teachers to read their written reflection papers and then discussing their shared beliefs and experiences of home visits in recent years. The average length of the discussions was one hour, and the discussions were audio-recorded and transcribed verbatim. Moreover, the data were analyzed using constant comparative analysis, and the analysis was verified through (a) the uses of multiple data sources, (b) the involvement of multiple researchers, (c) coding checks, and (d) the provisions of the thick descriptions of the findings. The study findings corroborate that the teachers become to reposition themselves as 'knowledge seekers' through reorienting their cynosure toward 'setting stones' to learn, grow, and change rather than framing their home visits. The teachers also continually engage in careful listening, observing, questioning, and dialoguing, and these actions reflect their care toward parents. The value of teamwork with parents is advocated, and the teachers recognize that when parents feel empowered, they are active and committed to doing more for their children, which can further advantage proactive long-term parent-teacher collaborations. The study findings also validate that the framework is influential for educators to provide the experiences of home visiting that is culturally responsive and to share collaborative relationships with caregivers. The long-term impact of the framework further implies that teachers continue to put themselves in the position of evolving, including beliefs and actions, to better work with children and families who are culturally, ethnically, and linguistically different from them. This framework can be applicable to educators and professionals who are looking for avenues to bridge the relationship between home and school and parents and teachers.

Keywords: culturally responsive home visit, early childhood education, parent–teacher collaboration, teacher professional development

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Authors: Tiptunya Duangsri, Panwilai Chomchid, Natchanok Jansawang

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This research study was to investigate of education decisions must be made which a part of it should be passed on to future generations as obligatory for all members of a chemistry class for students who will prepare themselves for a special position. The descriptions of instructional design were provided and the recent criticisms are discussed. This research study to an outline of an integrative framework for the description of information and the instructional design model give structure to negotiate a semblance of conscious understanding. The aims of this study are to describe the instructional design model for comparisons between students’ genders of their effects on STEM educational learning achievement motives to their science attitudes and logical thinking abilities with a sample size of 18 students at the 11th grade level with the cluster random sampling technique in Mahawichanukul School were designed. The chemistry learning environment was administered with the STEM education method. To build up the 5-instrument lesson instructional plan issues were instructed innovations, the 30-item Logical Thinking Test (LTT) on 5 scales, namely; Inference, Recognition of Assumptions, Deduction, Interpretation and Evaluation scales was used. Students’ responses of their perceptions with the Test Of Chemistry-Related Attitude (TOCRA) were assessed of their attitude in science toward chemistry. The validity from Index Objective Congruence value (IOC) checked by five expert specialist educator in two chemistry classroom targets in STEM education, the E1/E2 process were equaled evidence of 84.05/81.42 which results based on criteria are higher than of 80/80 standard level with the IOC from the expert educators. Comparisons between students’ learning achievement motives with STEM educational model on stoichiometry issue in chemistry classes with different genders were differentiated at evidence level of .05, significantly. Associations between students’ learning achievement motives on their posttest outcomes and logical thinking abilities, the predictive efficiency (R2) values indicate that 69% and 70% of the variances in different male and female student groups of their logical thinking abilities. The predictive efficiency (R2) values indicate that 73%; and 74% of the variances in different male and female student groups of their science attitudes toward chemistry were associated. Statistically significant on students’ perceptions of their chemistry learning classroom environment and their science attitude toward chemistry when using the MCI and TOCRA, the predictive efficiency (R2) values indicated that 72% and 74% of the variances in different male and female student groups of their chemistry classroom climate, consequently. Suggestions that supporting chemistry or science teachers from science, technology, engineering and mathematics (STEM) in addressing complex teaching and learning issues related instructional design to develop, teach, and assess traditional are important strategies with a focus on STEM education instructional method.

Keywords: development, the instructional design model, students learning achievement motives, science attitudes with STEM educational model, stoichiometry issue, chemistry classes, genders

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Authors: Oleg Reva, Ilya Korotetskiy, Marina Lankina, Murat Kulmanov, Aleksandr Ilin

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Molecular docking approaches are widely used for design of new antibiotics and modeling of antibacterial activities of numerous ligands which bind specifically to active centers of indispensable enzymes and/or key signaling proteins of pathogens. Widespread drug resistance among pathogenic microorganisms calls for development of new antibiotics specifically targeting important metabolic and information pathways. A generally recognized problem is that almost all molecular targets have been identified already and it is getting more and more difficult to design innovative antibacterial compounds to combat the drug resistance. A promising way to overcome the drug resistance problem is an induction of reversion of drug resistance by supplementary medicines to improve the efficacy of the conventional antibiotics. In contrast to well established computer-based drug design, modeling of drug resistance reversion still is in its infancy. In this work, we proposed an approach to identification of compensatory genetic variants reducing the fitness cost associated with the acquisition of drug resistance by pathogenic bacteria. The approach was based on an analysis of the population genetic of Mycobacterium tuberculosis and on results of experimental modeling of the drug resistance reversion induced by a new anti-tuberculosis drug FS-1. The latter drug is an iodine-containing nanomolecular complex that passed clinical trials and was admitted as a new medicine against MDR-TB in Kazakhstan. Isolates of M. tuberculosis obtained on different stages of the clinical trials and also from laboratory animals infected with MDR-TB strain were characterized by antibiotic resistance, and their genomes were sequenced by the paired-end Illumina HiSeq 2000 technology. A steady increase in sensitivity to conventional anti-tuberculosis antibiotics in series of isolated treated with FS-1 was registered despite the fact that the canonical drug resistance mutations identified in the genomes of these isolates remained intact. It was hypothesized that the drug resistance phenotype in M. tuberculosis requires an adjustment of activities of many genes to compensate the fitness cost of the drug resistance mutations. FS-1 cased an aggravation of the fitness cost and removal of the drug-resistant variants of M. tuberculosis from the population. This process caused a significant increase in genetic heterogeneity of the Mtb population that was not observed in the positive and negative controls (infected laboratory animals left untreated and treated solely with the antibiotics). A large-scale search for linkage disequilibrium associations between the drug resistance mutations and genetic variants in other genomic loci allowed identification of target proteins, which could be influenced by supplementary drugs to increase the fitness cost of the drug resistance and deprive the drug-resistant bacterial variants of their competitiveness in the population. The approach will be used to improve the efficacy of FS-1 and also for computer-based design of new drugs to combat drug-resistant infections.

Keywords: complete genome sequencing, computational modeling, drug resistance reversion, Mycobacterium tuberculosis

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Authors: Sara Rejeb, Catherine Duveau, Tabea Rebafka

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To monitor the production process of turbofan aircraft engines, multiple measurements of various geometrical parameters are systematically recorded on manufactured parts. Engine parts are subject to extremely high standards as they can impact the performance of the engine. Therefore, it is essential to analyze these databases to better understand the influence of the different parameters on the engine's performance. Self-organizing maps are unsupervised neural networks which achieve two tasks simultaneously: they visualize high-dimensional data by projection onto a 2-dimensional map and provide clustering of the data. This technique has become very popular for data exploration since it provides easily interpretable results and a meaningful global view of the data. As such, self-organizing maps are usually applied to aircraft engine condition monitoring. As databases in this field are huge and complex, they naturally contain multiple missing entries for various reasons. The classical Kohonen algorithm to compute self-organizing maps is conceived for complete data only. A naive approach to deal with partially observed data consists in deleting items or variables with missing entries. However, this requires a sufficient number of complete individuals to be fairly representative of the population; otherwise, deletion leads to a considerable loss of information. Moreover, deletion can also induce bias in the analysis results. Alternatively, one can first apply a common imputation method to create a complete dataset and then apply the Kohonen algorithm. However, the choice of the imputation method may have a strong impact on the resulting self-organizing map. Our approach is to address simultaneously the two problems of computing a self-organizing map and imputing missing values, as these tasks are not independent. In this work, we propose an extension of self-organizing maps for partially observed data, referred to as missSOM. First, we introduce a criterion to be optimized, that aims at defining simultaneously the best self-organizing map and the best imputations for the missing entries. As such, missSOM is also an imputation method for missing values. To minimize the criterion, we propose an iterative algorithm that alternates the learning of a self-organizing map and the imputation of missing values. Moreover, we develop an accelerated version of the algorithm by entwining the iterations of the Kohonen algorithm with the updates of the imputed values. This method is efficiently implemented in R and will soon be released on CRAN. Compared to the standard Kohonen algorithm, it does not come with any additional cost in terms of computing time. Numerical experiments illustrate that missSOM performs well in terms of both clustering and imputation compared to the state of the art. In particular, it turns out that missSOM is robust to the missingness mechanism, which is in contrast to many imputation methods that are appropriate for only a single mechanism. This is an important property of missSOM as, in practice, the missingness mechanism is often unknown. An application to measurements on one type of part is also provided and shows the practical interest of missSOM.

Keywords: imputation method of missing data, partially observed data, robustness to missingness mechanism, self-organizing maps

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Authors: Marita Pigłowska, Beata Kurc, Maciej Galiński

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The application of carbon materials in the branches of the electrochemical industry shows an increasing tendency each year due to the many interesting properties they possess. These are, among others, a well-developed specific surface, porosity, high sorption capacity, good adsorption properties, low bulk density, electrical conductivity and chemical resistance. All these properties allow for their effective use, among others in supercapacitors, which can store electric charges of the order of 100 F due to carbon electrodes constituting the capacitor plates. Coals (including expanded graphite, carbon black, graphite carbon fibers, activated carbon) are commonly used in electrochemical methods of removing oil derivatives from water after tanker disasters, e.g. phenols and their derivatives by their electrochemical anodic oxidation. Phenol can occupy practically the entire surface of carbon material and leave the water clean of hydrophobic impurities. Regeneration of such electrodes is also not complicated, it is carried out by electrochemical methods consisting in unblocking the pores and reducing resistances, and thus their reactivation for subsequent adsorption processes. Graphite is commonly used as an anode material in lithium-ion cells, while due to the limited capacity it offers (372 mAh g-1), new solutions are sought that meet both capacitive, efficiency and economic criteria. Increasingly, biodegradable materials, green materials, biomass, waste (including agricultural waste) are used in order to reuse them and reduce greenhouse effects and, above all, to meet the biodegradability criterion necessary for the production of lithium-ion cells as chemical power sources. The most common of these materials are cellulose, starch, wheat, rice, and corn waste, e.g. from agricultural, paper and pharmaceutical production. Such products are subjected to appropriate treatments depending on the desired application (including chemical, thermal, electrochemical). Starch is a biodegradable polysaccharide that consists of polymeric units such as amylose and amylopectin that build an ordered (linear) and amorphous (branched) structure of the polymer. Carbon is also used as a catalyst. Elemental carbon has become available in many nano-structured forms representing the hybridization combinations found in the primary carbon allotropes, and the materials can be enriched with a large number of surface functional groups. There are many examples of catalytic applications of coal in the literature, but the development of this field has been hampered by the lack of a conceptual approach combining structure and function and a lack of understanding of material synthesis. In the context of catalytic applications, the integrity of carbon environmental management properties and parameters such as metal conductivity range and bond sequence management should be characterized. Such data, along with surface and textured information, can form the basis for the provision of network support services.

Keywords: carbon materials, catalysis, BET, capacitors, lithium ion cell

Procedia PDF Downloads 174

Authors: Sardorbek Numonov, Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Dongeun Choi, Byung-Woo Hong

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The detection of curvilinear structures often plays an important role in the analysis of images. In particular, it is considered as a crucial step for the diagnosis of chronic respiratory diseases to localize the fissures in chest CT imagery where the lung is divided into five lobes by the fissures that are characterized by linear features in appearance. However, the characteristic linear features for the fissures are often shown to be subtle due to the high intensity variability, pathological deformation or image noise involved in the imaging procedure, which leads to the uncertainty in the quantification of anatomical or functional properties of the lung. Thus, it is desired to enhance the linear features present in the chest CT images so that the distinctiveness in the delineation of the lobe is improved. We propose a recursive diffusion process that prefers coherent features based on the analysis of structure tensor in an anisotropic manner. The local image features associated with certain scales and directions can be characterized by the eigenanalysis of the structure tensor that is often regularized via isotropic diffusion filters. However, the isotropic diffusion filters involved in the computation of the structure tensor generally blur geometrically significant structure of the features leading to the degradation of the characteristic power in the feature space. Thus, it is required to take into consideration of local structure of the feature in scale and direction when computing the structure tensor. We apply an anisotropic diffusion in consideration of scale and direction of the features in the computation of the structure tensor that subsequently provides the geometrical structure of the features by its eigenanalysis that determines the shape of the anisotropic diffusion kernel. The recursive application of the anisotropic diffusion with the kernel the shape of which is derived from the structure tensor leading to the anisotropic scale-space where the geometrical features are preserved via the eigenanalysis of the structure tensor computed from the diffused image. The recursive interaction between the anisotropic diffusion based on the geometry-driven kernels and the computation of the structure tensor that determines the shape of the diffusion kernels yields a scale-space where geometrical properties of the image structure are effectively characterized. We apply our recursive anisotropic diffusion algorithm to the detection of curvilinear structure in the chest CT imagery where the fissures present curvilinear features and define the boundary of lobes. It is shown that our algorithm yields precise detection of the fissures while overcoming the subtlety in defining the characteristic linear features. The quantitative evaluation demonstrates the robustness and effectiveness of the proposed algorithm for the detection of fissures in the chest CT in terms of the false positive and the true positive measures. The receiver operating characteristic curves indicate the potential of our algorithm as a segmentation tool in the clinical environment. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: anisotropic diffusion, chest CT imagery, chronic respiratory disease, curvilinear structure, fissure detection, structure tensor

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Authors: Supriya Majumder, Pabitra Banik

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Fates of Arsenic (As) on the soil-plant environment belong to the critical emerging issue, which in turn to appraises the threatening implications of a human health risk — assessing the dynamics of As in soil solid components are likely to impose its potential availability towards plant uptake. In the present context, we introduced an improved Sequential Extraction Procedure (SEP) questioning to identify solid-phase speciation of As in paddy soil under variable soil environmental conditions during two consecutive seasons of rice cultivation practices. We coupled gradients of water management practices with the addition of fertilizer amendments to assess the changes in a partition of As through a field experimental study during monsoon and post-monsoon season using two rice cultivars. Water management regimes were varied based on the methods of cultivation of rice by Conventional (waterlogged) vis-a-vis System of Rice Intensification-SRI (saturated). Fertilizer amendment through the nutrient treatment of absolute control, NPK-RD, NPK-RD + Calcium silicate, NPK-RD + Ferrous sulfate, Farmyard manure (FYM), FYM + Calcium silicate, FYM + Ferrous sulfate, Vermicompost (VC), VC + Calcium silicate, VC + Ferrous sulfate were selected to construct the study. After harvest, soil samples were sequentially extracted to estimate partition of As among the different fractions such as: exchangeable (F1), specifically sorbed (F2), As bound to amorphous Fe oxides (F3), crystalline Fe oxides (F4), organic matter (F5) and residual phase (F6). Results showed that the major proportions of As were found in F3, F4 and F6, whereas F1 exhibited the lowest proportion of total soil As. Among the nutrient treatment mediated changes on As fractions, the application of organic manure and ferrous sulfate were significantly found to restrict the release of As from exchangeable phase. Meanwhile, conventional practice produced much higher release of As from F1 as compared to SRI, which may substantially increase the environmental risk. In contrast, SRI practice was found to retain a significantly higher proportion of As in F2, F3, and F4 phase resulting restricted mobilization of As. This was critically reflected towards rice grain As bioavailability where the reduction in grain As concentration of 33% and 55% in SRI concerning conventional treatment (p <0.05) during monsoon and post-monsoon season respectively. Also, prediction assay for rice grain As bioavailability based on the linear regression model was performed. Results demonstrated that rice grain As concentration was positively correlated with As concentration in F1 and negatively correlated with F2, F3, and F4 with a satisfactory level of variation being explained (p <0.001). Finally, we conclude that F1, F2, F3 and F4 are the major soil. As fractions critically may govern the potential availability of As in soil and suggest that rice cultivation with the SRI treatment is particularly at less risk of As availability in soil. Such exhaustive information may be useful for adopting certain management practices for rice grown in contaminated soil concerning to the environmental issues in particular.

Keywords: arsenic, fractionation, paddy soil, potential availability

Procedia PDF Downloads 125

Authors: B. Garfolo, L. Kelpsh, R. Roak, R. Kuck

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Often, student ratings of instructors play a significant role in the career path of an instructor in higher education. So then, how does a student view the effectiveness of instructor teaching? This question has been address by literally thousands of studies found in the literature. Yet, why does this question still persist? A literature review reveals that while it is true that student evaluations of instructors can be biased, there is still a considerable amount of work that needs to be done in understanding why. As student evaluations of instructors can be used in a variety of settings (formative or summative) it is critical to understand the nature of the bias. The authors believe that not only is some bias possible in student evaluations, it should be expected for the simple reason that a student evaluation is a human activity and as such, relies upon perception and interpersonal judgment. As such, student ratings are affected by the same factors that can potentially affect any rater’s judgment, such as stereotypes based on gender, culture, race, etc. Previous study findings suggest that student evaluations of teacher effectiveness differ between male and female raters. However, even though studies have shown that instructor gender does play an important role in influencing student ratings, the exact nature and extent of that role remains the subject of debate. Researchers, in their attempt to define good teaching, have looked for differences in student evaluations based on a variety of characteristics such as course type, class size, ability level of the student and grading practices in addition to instructor and student characteristics (gender, age, etc.) with inconsistent results. If a student evaluation represents more than an instructor’s teaching ability, for example, a physical characteristic such as gender, then this information must be taken into account if the evaluation is to have meaning with respect to instructor assessment. While the authors concede that it is difficult or nearly impossible to separate gender from student perception of teaching practices in person, it is, however, possible to shield an instructor’s gender identity with respect to an online teaching experience. The online teaching modality presents itself as a unique opportunity to experiment directly with gender identity. The analysis of the differences of online behavior of individuals when they perceive that they are interacting with a male or female could provide a wealth of data on how gender influences student perceptions of teaching effectiveness. Given the importance of the role student ratings play in hiring, retention, promotion, tenure, and salary deliberations in academic careers, this question warrants further attention as it is important to be aware of possible bias in student evaluations if they are to be used at all with respect to any academic considerations. For experimental purposes, the author’s constructed and online class where each instructors operate under two different gender identities. In this study, each instructor taught multiple sections of the same class using both a male identity and a female identity. The study examined student evaluations of teaching based on certain student and instructor characteristics in order to determine if and where male and female students might differ in their ratings of instructors based on instructor gender. Additionally, the authors examined if there are differences between undergraduate and graduate students' ratings with respect to the experimental criteria.

Keywords: gender bias, ethics, student evaluations, student perceptions, online instruction

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Authors: Leonardo Parra, Manuel Chacón-Fuentes, Andrés Quiroz

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One of the most important factors in beef and dairy production in the world as well as also in Chile, is related to the correct choice of cultivars or mixtures of forage grasses and legumes to ensure high yields and quality of grassland. However, a great problem is the persistence of the grasses as a result of the action of different hypogeous as epigean pests. The complex insect pests associated with grassland include white grubs (Hylamorpha elegans, Phytoloema herrmanni), blackworm (Dalaca pallens) and Argentine stem weevil (Listronotus bonariensis). In Chile, the principal strategy utilized for controlling this pest is chemical control, through the use of synthetic insecticides, however, underground feeding habits of larval and flight activity of adults makes this uneconomic method. Furthermore, due to problems including environmental degradation, development of resistance and chemical residues, there is a worldwide interest in the use of alternative environmentally friendly pest control methods. In this sense, in recent years there has been an increasing interest in determining the role of endophyte fungi in controlling epigean and hypogeous pest. Endophytes from ryegrass (Lolium perenne), establish a biotrophic relationship with the host, defined as mutualistic symbiosis. The plant-fungi association produces a “cocktail of alkaloids” where peramine is the main toxic substance present in endophyte of ryegrass and responsible for damage reduction of L. bonariensis. In the last decade, few studies have been developed on the effectiveness of new ryegrass cultivars carriers of endophyte in controlling insect pests. Therefore, the aim of this research is to provide knowledge concerning to evaluate the alkaloid content, such as peramine and Lolitrem B, present in new experimental lines of ryegrass and feasible to be used in grasslands of southern Chile. For this, during 2016, ryegrass plants of six experimental lines and two commercial cultivars sown at the Instituto de Investigaciones Agropecuarias Carrillanca (Vilcún, Chile) were collected and subjected to a process of chemical extraction to identify and quantify the presence of peramine and lolitrem B by the technique of liquid chromatography of high resolution (HPLC). The results indicated that the experimental lines EL-1 and EL-3 had high content of peramine (0.25 and 0.43 ppm, respectively) than with lolitrem B (0.061 and 0.19 ppm, respectively). Furthermore, the higher contents of lolitrem B were detected in the EL-4 and commercial cultivar Alto (positive control) with 0.08 and 0.17 ppm, respectively. Peramine and lolitrem B were not detected in the cultivar Jumbo (negative control). These results suggest that EL-3 would have potential as future cultivate because it has high content of peramine, alkaloid responsible for controlling insect pest. However, their current role on the complex insects attacking ryegrass grasslands should be evaluated. The information obtained in this research could be used to improve control strategies against hypogeous and epigean pests of grassland in southern Chile and also to reduce the use of synthetic pesticides.

Keywords: HPLC, Lolitrem B, peramine, pest

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Authors: Beverly Black

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Background: Adolescent dating abuse (ADA) is widespread throughout the world and negatively impacts many adolescents. ADA is associated with lower self-esteem, poorer school performance, lower employment opportunities, higher rates of depression, absenteeism from school, substance abuse, bullying, smoking, suicide, pregnancy, eating disorders, and risky sexual behaviors, and experiencing domestic violence later in life. ADA prevention is sometimes addressed through school programming; yet, parental responses to ADA can also be an important vehicle for its prevention. In this exploratory study, the author examined how mothers, including abused mothers, responded to scenarios of ADA involving their children. Methods: Six focus groups were conducted between December, 2013 and June, 2014 with mothers (n=31) in the southern part of the United States. Three of the focus groups were comprised of mothers (n=17) who had been abused by their partners. Mothers were recruited from local community family agencies. Participants were provided a series of four scenarios about ADA and they were asked to explain how they would respond. Focus groups lasted approximately 45 minutes. All participants were given a gift card to a major retailer as a ‘thank you’. Using QSR-N10, two researchers’ analyzed the focus group data first using open and axial coding techniques to find overarching themes. Researchers triangulated the coded data to ensure accurate interpretations of the participants’ messages and used the scenario questions to structure the coded results. Results: Almost 30% of 699 comments coded as mothers’ recommendations for responding to ADA focused on the importance of providing advice to their children. Advice included breaking up, going to police, ignoring or avoiding the abusive partner, and setting boundaries in relationships. About 22% of comments focused on the need for educating teens about healthy and unhealthy relationships and seeking additional information. About 13% of the comments reflected the view that parents should confront abuser and/or abusers’ parents, and less than 2% noted the need to take their child to counseling. Mothers who had been abused offered similar responses as parents who had not experienced abuse. However, their responses were more likely to focus on sharing their own experience exercising caution in their responses, as they knew from their own experiences that authoritarian responses were ineffective. Over half of the comments indicated that parents would react stronger, quicker, and angrier if a girl was being abused by a boy than vice versa; parents expressed greater fear for their daughters than their sons involved in ADA. Conclusions. Results suggest that mothers have ideas about how to respond to ADA. Mothers who have been abused draw from their experiences and are aware that responding in an authoritarian manner may not be helpful. Because parental influence on teens is critical in their development, it is important for all parents to respond to ADA in a helpful manner to break the cycle of violence. Understanding responses to ADA can inform prevention programming to work with parents in responding to ADA.

Keywords: abused mothers' responses to dating abuse, adolescent dating abuse, mothers' responses to dating abuse, teen dating violence

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Authors: Jone Ibarruri, Mikel Manso, Marta Cebrián

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A high amount of food is lost or discarded in the World every year. In addition, in the last decades, an increasing demand of new alternative and sustainable sources of proteins and other valuable compounds is being observed in the food and feeding sectors and, therefore, the use of food by-products as nutrients for these purposes sounds very interesting from the environmental and economical point of view. However, the direct use of discarded fruit and vegetables that present, in general, a low protein content is not interesting as feeding ingredient except if they are used as a source of fiber for ruminants. Especially in the case of aquaculture, several alternatives to the use of fish meal and other vegetable protein sources have been extensively explored due to the scarcity of fish stocks and the unsustainability of fishing for these purposes. Fish mortality is also of great concern in this sector as this problem highly reduces their economic feasibility. So, the development of new functional and natural ingredients that could reduce the need for vaccination is also of great interest. In this work, several fermentation tests were developed at lab scale using a selected mixture of fruit and vegetable discards from a wholesale market located in the Basque Country to increase their protein content and also to produce some bioactive extracts that could be used as additives in aquaculture. Fruit and vegetable mixtures (60/40 ww) were centrifugated for humidity reduction and crushed to 2-5 mm particle size. Samples were inoculated with a selected Rhizopus oryzae strain and fermented for 7 days in controlled conditions (humidity between 65 and 75% and 28ºC) in Petri plates (120 mm) by triplicate. Obtained results indicated that the final fermented product presented a twofold protein content (from 13 to 28% d.w). Fermented product was further processed to determine their possible functionality as a feed additive. Extraction tests were carried out to obtain an ethanolic extract (60:40 ethanol: water, v.v) and remaining biomass that also could present applications in food or feed sectors. The extract presented a polyphenol content of about 27 mg GAE/gr d.w with antioxidant activity of 8.4 mg TEAC/g d.w. Remining biomass is mainly composed of fiber (51%), protein (24%) and fat (10%). Extracts also presented antibacterial activity according to the results obtained in Agar Diffusion and to the Minimum Inhibitory Concentration (MIC) tests determined against several food and fish pathogen strains. In vitro, digestibility was also assessed to obtain preliminary information about the expected effect of extraction procedure on fermented product digestibility. First results indicated that remaining biomass after extraction doesn´t seem to improve digestibility in comparison to the initial fermented product. These preliminary results show that fermented fruit and vegetables can be a useful source of functional ingredients for aquaculture applications and a substitute of other protein sources in the feeding sector. Further validation will be also carried out through “in vivo” tests with trout and bass.

Keywords: fungal solid state fermentation, protein increase, functional extracts, feed ingredients

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Authors: Jovana Grahovac, Ivana Pajcin, Natasa Lukic, Jelena Dodic, Aleksandar Jokic

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To obtain purified biomass to be used in the plant pathogen biocontrol or as soil biofertilizer, it is necessary to eliminate residual broth components at the end of the fermentation process. The main drawback of membrane separation techniques is permeate flux decline due to the membrane fouling. Fouling mitigation measures increase the pressure drop along membrane channel due to the increased resistance to flow of the feed suspension, thus increasing the hydraulic power drop. At the same time, these measures lead to an increase in the permeate flux due to the reduced resistance of the filtration cake on the membrane surface. Because of these opposing effects, the energy efficiency of fouling mitigation measures is limited, and the justification of its application is provided by information on a reducing specific energy consumption compared to a case without any measures employed. In this study, the influence of static mixer (Kenics) and air-sparging (two-phase flow) on reduction of specific energy consumption (ER) was investigated. Cultivation Bacillus velezensis was carried out in the 3-L bioreactor (Biostat® Aplus) containing 2 L working volume with two parallel Rushton turbines and without internal baffles. Cultivation was carried out at 28 °C on at 150 rpm with an aeration rate of 0.75 vvm during 96 h. The experiments were carried out in a conventional cross-flow microfiltration unit. During experiments, permeate and retentate were recycled back to the broth vessel to simulate continuous process. The single channel ceramic membrane (TAMI Deutschland) used had a nominal pore size 200 nm with the length of 250 mm and an inner/external diameter of 6/10 mm. The useful membrane channel surface was 4.33×10⁻³ m². Air sparging was brought by the pressurized air connected by a three-way valve to the feed tube by a simple T-connector without diffusor. The different approaches to flux improvement are compared in terms of energy consumption. Reduction of specific energy consumption compared to microfiltration without fouling mitigation is around 49% and 63%, for use of two-phase flow and a static mixer, respectively. In the case of a combination of these two fouling mitigation methods, ER is 60%, i.e., slightly lower compared to the use of turbulence promoter alone. The reason for this result can be found in the fact that flux increase is more affected by the presence of a Kenics static mixer while sparging results in an increase of energy used during microfiltration. By comparing combined method with turbulence promoter flux enhancement method ER is negative (-7%) which can be explained by increased power consumption for air flow with moderate contribution to the flux increase. Another confirmation for this fact can be found by comparing energy consumption values for combined method with energy consumption in the case of two-phase flow. In this instance energy reduction (ER) is 22% that demonstrates that turbulence promoter is more efficient compared to two phase flow. Antimicrobial activity of Bacillus velezensis biomass against phytopathogenic isolates Xanthomonas campestris was preserved under different fouling reduction methods.

Keywords: Bacillus velezensis, microfiltration, static mixer, two-phase flow

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Authors: O. J. Akinsola, Yinan Zheng, Rose Anorlu, F. T. Ogunsola, Lifang Hou, Robert Leo-Murphy

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Cervical Cancer (CC) is the 2nd most common cancer among women living in low and middle-income countries, with no associated symptoms during formative periods. With the advancement and innovative medical research, there are numerous preventive measures being utilized, but the incidence of cervical cancer cannot be truncated with the application of only screening tests. The mortality associated with this invasive cervical cancer can be nipped in the bud through the important role of early-stage detection. This study research selected an array of different top features selection techniques which was aimed at developing a model that could validly diagnose the risk factors of cervical cancer. A retrospective clinic-based cohort study was conducted on 178 HIV-associated cervical cancer patients in Lagos University teaching Hospital, Nigeria (U54 data repository) in April 2022. The outcome measure was the automated prediction of the HIV-associated cervical cancer cases, while the predictor variables include: demographic information, reproductive history, birth control, sexual history, cervical cancer screening history for invasive cervical cancer. The proposed technique was assessed with R and Python programming software to produce the model by utilizing the classification algorithms for the detection and diagnosis of cervical cancer disease. Four machine learning classification algorithms used are: the machine learning model was split into training and testing dataset into ratio 80:20. The numerical features were also standardized while hyperparameter tuning was carried out on the machine learning to train and test the data. Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), and K-Nearest Neighbor (KNN). Some fitting features were selected for the detection and diagnosis of cervical cancer diseases from selected characteristics in the dataset using the contribution of various selection methods for the classification cervical cancer into healthy or diseased status. The mean age of patients was 49.7±12.1 years, mean age at pregnancy was 23.3±5.5 years, mean age at first sexual experience was 19.4±3.2 years, while the mean BMI was 27.1±5.6 kg/m2. A larger percentage of the patients are Married (62.9%), while most of them have at least two sexual partners (72.5%). Age of patients (OR=1.065, p<0.001**), marital status (OR=0.375, p=0.011**), number of pregnancy live-births (OR=1.317, p=0.007**), and use of birth control pills (OR=0.291, p=0.015**) were found to be significantly associated with HIV-associated cervical cancer. On top ten 10 features (variables) considered in the analysis, RF claims the overall model performance, which include: accuracy of (72.0%), the precision of (84.6%), a recall of (84.6%) and F1-score of (74.0%) while LR has: an accuracy of (74.0%), precision of (70.0%), recall of (70.0%) and F1-score of (70.0%). The RF model identified 10 features predictive of developing cervical cancer. The age of patients was considered as the most important risk factor, followed by the number of pregnancy livebirths, marital status, and use of birth control pills, The study shows that data mining techniques could be used to identify women living with HIV at high risk of developing cervical cancer in Nigeria and other sub-Saharan African countries.

Keywords: associated cervical cancer, data mining, random forest, logistic regression

Procedia PDF Downloads 84

Authors: Zahide Tepeli Temiz, Itir Tari Comert

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Attachment patterns based on early emotional interactions between infant and primary caregiver continue to be influential in adult life, in terms of mental health and behaviors of individuals. Several studies reveal that infant-caregiver relationships have impressed the affect regulation, coping with stressful and negative situations, general satisfaction of life, and self image in adulthood, besides the attachment styles. The present study aims to examine the relationships between university students’ attachment style and their self-esteem, alexithymic features, satisfaction of life, and level of resilience. In line with this aim, the hypothesis of the prediction of attachment styles (anxious and avoidant) over life satisfaction, self-esteem, alexithymia, and psychological resilience was tested. Additionally, in this study Structural Equational Modeling was conducted to investigate the mediational role of self-esteem in the relationship between attachment styles and alexithymia, life satisfaction, and resilience. This model was examined with path analysis. The sample of the research consists of 425 university students who take education from several region of Turkey. The participants who sign the informed consent completed the Demographic Information Form, Experiences in Close Relationships-Revised, Rosenberg Self-Esteem Scale, The Satisfaction with Life Scale, Toronto Alexithymia Scale, and Resilience Scale for Adults. According to results, anxious, and avoidant dimensions of insecure attachment predicted the self-esteem score and alexithymia in positive direction. On the other hand, these dimensions of attachment predicted life satisfaction in negative direction. The results of linear regression analysis indicated that anxious and avoidant attachment styles didn’t predict the resilience. This result doesn’t support the theory and research indicating the relationship between attachment style and psychological resilience. The results of path analysis revealed the mediational role self esteem in the relation between anxious, and avoidant attachment styles and life satisfaction. In addition, SEM analysis indicated the indirect effect of attachment styles over alexithymia and resilience besides their direct effect. These findings support the hypothesis of this research relation to mediating role of self-esteem. Attachment theorists suggest that early attachment experiences, including supportive and responsive family interactions, have an effect on resilience to harmful situations in adult life, ability to identify, describe, and regulate emotions and also general satisfaction with life. Several studies examining the relationship between attachment styles and life satisfaction, alexithymia, and psychological resilience draw attention to mediational role of self-esteem. Results of this study support the theory of attachment patterns with the mediation of self-image influence the emotional, cognitive, and behavioral regulation of person throughout the adulthood. Therefore, it is thought that any intervention intended for recovery in attachment relationship will increase the self-esteem, life satisfaction, and resilience level, on the one side, decrease the alexithymic features, on the other side.

Keywords: alexithymia, anxious attachment, avoidant attachment, life satisfaction, path analysis, resilience, self-esteem, structural equation

Procedia PDF Downloads 196

Authors: Mbonigaba Swale

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Malaria is an infection or disease caused by parasites (Plasmodium Falciparum — causes severe Malaria, plasmodium Vivax, Plasmodium Ovale, and Plasmodium Malariae), transmitted by bites of infected anopheles (female) mosquitoes to humans. These vectors comprise of two types in Africa, particularly in Uganda, i.e. anopheles fenestus and Anopheles gambaie (‘example Anopheles arabiensis,,); feeds on man inside the house mainly at dusk, mid-night and dawn and rests indoors and makes them effective transmitters (vectors) of the disease. People in both urban and rural areas have consistently become prone to repetitive attacks of malaria, causing a lot of deaths and significantly increasing the poverty levels of the rural poor. Malaria is a national problem; it causes a lot of maternal pre-natal and antenatal disorders, anemia in pregnant mothers, low birth weights for the newly born, convulsions and epilepsy among the infants. Cumulatively, it kills about one million children every year in sub-Saharan Africa. It has been estimated to account for 25-35% of all outpatient visits, 20-45% of acute hospital admissions and 15-35% of hospital deaths. Uganda is the leading victim country, for which Rakai and Masaka districts are the most affected. So, it is not clear whether these abhorrent situations and episodes of recurrences and failure to cure from the disease are a result of poor diagnosis, prescription and dosing, treatment habits and compliance of the patients to the drugs or the ethical domain of the stake holders in relation to the main stream methodology of malaria management. The research is aimed at offering an alternative approach to manage and deal absolutely with problem by using a knowledge based software model of Artificial Intelligence (Al) that is capable of performing common-sense and cognitive reasoning so as to take decisions like the human brain would do to provide instantaneous expert solutions so as to avoid speculative simulation of the problem during differential diagnosis in the most accurate and literal inferential aspect. This system will assist physicians in many kinds of medical diagnosis, prescribing treatments and doses, and in monitoring patient responses, basing on the body weight and age group of the patient, it will be able to provide instantaneous and timely information options, alternative ways and approaches to influence decision making during case analysis. The computerized system approach, a new model in Uganda termed as “Software Aided Treatment” (SAT) will try to change the moral and ethical approach and influence conduct so as to improve the skills, experience and values (social and ethical) in the administration and management of the disease and drugs (combination therapy and generics) by both the patient and the health worker.

Keywords: knowledge based software, management, treatment, diagnosis

Procedia PDF Downloads 57

Authors: E. A. Krasikov

Abstract:

As the service life of an operating nuclear power plant (NPP) increases, the potential misunderstanding of the degradation of aging components must receive more attention. Integrity assurance analysis contributes to the effective maintenance of adequate plant safety margins. In essence, the reactor pressure vessel (RPV) is the key structural component determining the NPP lifetime. Environmentally induced cracking in the stainless steel corrosion-preventing cladding of RPV’s has been recognized to be one of the technical problems in the maintenance and development of light-water reactors. Extensive cracking leading to failure of the cladding was found after 13000 net hours of operation in JPDR (Japan Power Demonstration Reactor). Some of the cracks have reached the base metal and further penetrated into the RPV in the form of localized corrosion. Failures of reactor internal components in both boiling water reactors and pressurized water reactors have increased after the accumulation of relatively high neutron fluences (5´1020 cm–2, E>0,5MeV). Therefore, in the case of cladding failure, the problem arises of hydrogen (as a corrosion product) embrittlement of irradiated RPV steel because of exposure to the coolant. At present when notable progress in plasma physics has been obtained practical energy utilization from fusion reactors (FR) is determined by the state of material science problems. The last includes not only the routine problems of nuclear engineering but also a number of entirely new problems connected with extreme conditions of materials operation – irradiation environment, hydrogenation, thermocycling, etc. Limiting data suggest that the combined effect of these factors is more severe than any one of them alone. To clarify the possible influence of the in-service synergistic phenomena on the FR structural materials properties we have studied hydrogen-irradiated steel interaction including alternating hydrogenation and heat treatment (annealing). Available information indicates that the life of the first wall could be expanded by means of periodic in-place annealing. The effects of neutron fluence and irradiation temperature on steel/hydrogen interactions (adsorption, desorption, diffusion, mechanical properties at different loading velocities, post-irradiation annealing) were studied. Experiments clearly reveal that the higher the neutron fluence and the lower the irradiation temperature, the more hydrogen-radiation defects occur, with corresponding effects on the steel mechanical properties. Hydrogen accumulation analyses and thermal desorption investigations were performed to prove the evidence of hydrogen trapping at irradiation defects. Extremely high susceptibility to hydrogen embrittlement was observed with specimens which had been irradiated at relatively low temperature. However, the susceptibility decreases with increasing irradiation temperature. To evaluate methods for the RPV’s residual lifetime evaluation and prediction, more work should be done on the irradiated metal–hydrogen interaction in order to monitor more reliably the status of irradiated materials.

Keywords: hydrogen, radiation, stability, structural steel

Procedia PDF Downloads 270