Search results for: computerized decision support systems

Authors: Evelyn Bilias-Lolis, Emily Louise Winter

Abstract:

Schools have a responsibility to implement school-wide frameworks that actively prevent, detect, and support all aspects of child development and learning. Such efforts can range from individual or classroom-level supports to school-wide primary prevention practices for the school’s infrastructure or climate. This study assessed the perceptions of educators across a variety of disciplines in Connecticut (i.e., elementary and secondary education, special education, school psychology, and school social work) on the perceived impact of their beliefs, language, and behavior about food and body consciousness on student self-image and school climate. Participants (N=50) completed a short electronic questionnaire measuring perceptions of how their behavior can influence their students’ opinions about themselves, their emerging self-image, and the overall climate of the school community. Secondly, the beliefs that were directly assessed in the first portion of the survey were further measured through the use of applied social vignettes involving students directly or as bystanders. Preliminary findings are intriguing. When asked directly, 100% of the respondents reported that what they say to students directly could influence student opinions about themselves and 98% of participants further agreed that their behavior both to and in front of students could impact a student’s developing self-image. Likewise, 82% of the sample agreed that their personal language and behavior affect the overall climate of a school building. However, when the above beliefs were assessed via applied social vignettes depicting routine social exchanges, results were significantly more widespread (i.e., results were evenly dispersed among levels of agreement and disagreement across participants in all areas). These preliminary findings offer humble but critical implications for informing integrated school wellness frameworks that aim to create body-sensitive school communities. Research indicates that perceptions about body image, attitudes about eating, and the onset of disordered eating practices surface in school-aged years. Schools provide a natural setting for instilling foundations for child wellness as a natural extension of existing school climate reform efforts. These measures do not always need to be expansive or extreme. Rather, educators have a ripe opportunity to become champions for health and wellness through increased self-awareness and subtle shifts in language and behavior. Future psychological research needs to continue to explore this line of inquiry using larger and more varied samples of educators in order to identify needs in teacher training and development that can yield positive and preventative health outcomes for children.

Keywords: body-sensitive schools, integrated school health, school climate reform, teacher awareness

Procedia PDF Downloads 153

Authors: Alexandru-Ion Marinescu

Abstract:

There exist a plethora of methods in the scientific literature which tackle the well-established task of credit score evaluation. In its most abstract form, a credit scoring algorithm takes as input several credit applicant properties, such as age, marital status, employment status, loan duration, etc. and must output a binary response variable (i.e. “GOOD” or “BAD”) stating whether the client is susceptible to payment return delays. Data imbalance is a common occurrence among financial institution databases, with the majority being classified as “GOOD” clients (clients that respect the loan return calendar) alongside a small percentage of “BAD” clients. But it is the “BAD” clients we are interested in since accurately predicting their behavior is crucial in preventing unwanted loss for loan providers. We add to this whole context the constraint that the algorithm must yield an actual, tractable mathematical formula, which is friendlier towards financial analysts. To this end, we have turned to genetic algorithms and genetic programming, aiming to evolve actual mathematical expressions using specially tailored mutation and crossover operators. As far as data representation is concerned, we employ a very flexible mechanism – LINQ expression trees, readily available in the C# programming language, enabling us to construct executable pieces of code at runtime. As the title implies, they model trees, with intermediate nodes being operators (addition, subtraction, multiplication, division) or mathematical functions (sin, cos, abs, round, etc.) and leaf nodes storing either constants or variables. There is a one-to-one correspondence between the client properties and the formula variables. The mutation and crossover operators work on a flattened version of the tree, obtained via a pre-order traversal. A consequence of our chosen technique is that we can identify and discard client properties which do not take part in the final score evaluation, effectively acting as a dimensionality reduction scheme. We compare ourselves with state of the art approaches, such as support vector machines, Bayesian networks, and extreme learning machines, to name a few. The data sets we benchmark against amount to a total of 8, of which we mention the well-known Australian credit and German credit data sets, and the performance indicators are the following: percentage correctly classified, area under curve, partial Gini index, H-measure, Brier score and Kolmogorov-Smirnov statistic, respectively. Finally, we obtain encouraging results, which, although placing us in the lower half of the hierarchy, drive us to further refine the algorithm.

Keywords: expression trees, financial credit scoring, genetic algorithm, genetic programming, symbolic evolution

Procedia PDF Downloads 113

Authors: Md Kamrul Hassan

Abstract:

Adaptation interventions are the common response to manage the vulnerabilities of climate change. The nature of adaptation intervention depends on the degree of vulnerability and the capacity of a society. The coping interventions can take the form of hard adaptation – utilising technologies and capital goods like dykes, embankments, seawalls, and/or soft adaptation – engaging knowledge and information sharing, capacity building, policy and strategy development, and innovation. Hard adaptation is quite capital intensive but provides immediate relief from climate change vulnerabilities. This type of adaptation is not real development, as the investment for the adaptation cannot improve the performance – just maintain the status quo of a social or ecological system, and often lead to maladaptation in the long-term. Maladaptation creates a two-way loss for a society – interventions bring further vulnerability on top of the existing vulnerability and investment for getting rid of the consequence of interventions. Hard adaptation is popular to the vulnerable groups, but it focuses so much on the immediate solution and often ignores the environmental issues and future risks of climate change. On the other hand, soft adaptation is education oriented where vulnerable groups learn how to live with climate change impacts. Soft adaptation interventions build the capacity of vulnerable groups through training, innovation, and support, which might enhance the resilience of a system. In consideration of long-term sustainability, soft adaptation can contribute more to resilience than hard adaptation. Taking a developing society as the study context, this study aims to investigate and understand the effectiveness of the adaptation interventions of the coastal community of Sundarbans mangrove forest in Bangladesh. Applying semi-structured interviews with a range of Sundarbans stakeholders including community residents, tourism demand-supply side stakeholders, and conservation and management agencies (e.g., Government, NGOs and international agencies) and document analysis, this paper reports several key insights regarding climate change adaptation. Firstly, while adaptation interventions may offer a short-term to medium-term solution to climate change vulnerabilities, interventions need to be revised for long-term sustainability. Secondly, soft adaptation offers advantages in terms of resilience in a rapidly changing environment, as it is flexible and dynamic. Thirdly, there is a challenge to communicate to educate vulnerable groups to understand more about the future effects of hard adaptation interventions (and the potential for maladaptation). Fourthly, hard adaptation can be used if the interventions do not degrade the environmental balance and if the investment of interventions does not exceed the economic benefit of the interventions. Overall, the goal of an adaptation intervention should be to enhance the resilience of a social or ecological system so that the system can with stand present vulnerabilities and future risks. In order to be sustainable, adaptation interventions should be designed in such way that those can address vulnerabilities and risks of climate change in a long-term timeframe.

Keywords: adaptation, climate change, maladaptation, resilience, Sundarbans, sustainability, vulnerability

Procedia PDF Downloads 190

Authors: Hamed Yaghoubi, Esmaeil Salahi, Fateme Taati

Abstract:

The effective shear and bulk viscosity, as well as dynamic viscosity, describe the rheological properties of the ceramic body during the liquid phase sintering process. The rheological parameters depend on the physical and thermomechanical characteristics of the material such as relative density, temperature, grain size, and diffusion coefficient and activation energy. The main goal of this research is to acquire a comprehensive understanding of the response of an incompressible viscose ceramic material during liquid phase sintering process such as stress-strain relations, sintering and hydrostatic stress, the prediction of anisotropic shrinkage and heterogeneous densification as a function of sintering time by including the simultaneous influence of gravity field, and frictional force. After raw materials analysis, the standard hard porcelain mixture as a ceramic body was designed and prepared. Three different experimental configurations were designed including midpoint deflection, sinter bending, and free sintering samples. The numerical method for the ceramic specimens during the liquid phase sintering process are implemented in the CREEP user subroutine code in ABAQUS. The numerical-experimental procedure shows the anisotropic behavior, the complete difference in spatial displacement through three directions, the incompressibility for ceramic samples during the sintering process. The anisotropic shrinkage factor has been proposed to investigate the shrinkage anisotropy. It has been shown that the shrinkage along the normal axis of casting sample is about 1.5 times larger than that of casting direction, the gravitational force in pyroplastic deformation intensifies the shrinkage anisotropy more than the free sintering sample. The lowest and greatest equivalent creep strain occurs at the intermediate zone and around the central line of the midpoint distorted sample, respectively. In the sinter bending test sample, the equivalent creep strain approaches to the maximum near the contact area with refractory support. The inhomogeneity in Von-Misses, pressure, and principal stress intensifies the relative density non-uniformity in all samples, except in free sintering one. The symmetrical distribution of stress around the center of free sintering sample, cause to hinder the pyroplastic deformations. Densification results confirmed that the effective bulk viscosity was well-defined with relative density values. The stress analysis confirmed that the sintering stress is more than the hydrostatic stress from start to end of sintering time so, from both theoretically and experimentally point of view, the sintering process occurs completely.

Keywords: anisotropic shrinkage, ceramic material, liquid phase sintering process, rheological properties, numerical-experimental procedure

Procedia PDF Downloads 339

Authors: Vania Helena Tonussi Vidal, Ester Eliane Jeunon

Abstract:

This article aims to analyze the change processes of management related bureaucracy and learning organization model. The theoretical framework was based on Beer and Nohria (2001) model, identified as E and O Theory. Based on this theory the empirical research was conducted in connection with six key dimensions: goal, leadership, focus, process, reward systems and consulting. We used a case study of an educational Institution located in Barbacena, Minas Gerais. This traditional center of technical knowledge for long time adopted the bureaucratic way of management. After many changes in a business model, as the creation of graduate and undergraduate courses they decided to make a deep change in management model that is our research focus. The data were collected through semi-structured interviews with director, managers and courses supervisors. The analysis were processed by the procedures of Collective Subject Discourse (CSD) method, develop by Lefèvre & Lefèvre (2000), Results showed the incremental growing of management model toward a learning organization. Many impacts could be seeing. As negative factors we have: people resistance; poor information about the planning and implementation process; old politics inside the new model and so on. Positive impacts are: new procedures in human resources, mainly related to manager skills and empowerment; structure downsizing, open discussions channel; integrated information system. The process is still under construction and now great stimulus is done to managers and employee commitment in the process.

Keywords: bureaucracy, organizational learning, organizational change, E and O theory

Procedia PDF Downloads 431

Authors: Donald Wright

Abstract:

The ultimate goal of this study is to reinvigorate the philosophical underpinnings the study of urbanization with scientific data with the goal of circumventing what seems an inevitable future clash between rural and urban populations. To that end urban infrastructure must be sustainable economically, politically and ecologically over the course of several generations as cities continue to grow with the incorporation of climate refugees. Our research will provide data concerning the projected increase in population over the coming two decades in Morocco, and the population will shift from rural areas to urban centers during that period of time. As a result, urban infrastructure will need to be adapted, developed or built to fit the demand of future internal migrations from rural to urban centers in Morocco. This paper will also examine how past experiences of internally displaced people give insight into the challenges faced by future migrants and, beyond the gathering of data, how people react to internal migration. This study employs four different sets of research tools. First, a large part of this study is archival, which involves compiling the relevant literature on the topic and its complex history. This step also includes gathering data bout migrations in Morocco from public data sources. Once the datasets are collected, the next part of the project involves populating the attribute fields and preprocessing the data to make it understandable and usable by machine learning algorithms. In tandem with the mathematical interpretation of data and projected migrations, this study benefits from a theoretical understanding of the critical apparatus existing around urban development of the 20th and 21st centuries that give us insight into past infrastructure development and the rationale behind it. Once the data is ready to be analyzed, different machine learning algorithms will be experimented (k-clustering, support vector regression, random forest analysis) and the results compared for visualization of the data. The final computational part of this study involves analyzing the data and determining what we can learn from it. This paper helps us to understand future trends of population movements within and between regions of North Africa, which will have an impact on various sectors such as urban development, food distribution and water purification, not to mention the creation of public policy in the countries of this region. One of the strengths of this project is the multi-pronged and cross-disciplinary methodology to the research question, which enables an interchange of knowledge and experiences to facilitate innovative solutions to this complex problem. Multiple and diverse intersecting viewpoints allow an exchange of methodological models that provide fresh and informed interpretations of otherwise objective data.

Keywords: climate change, machine learning, migration, Morocco, urban development

Procedia PDF Downloads 144

Authors: Muhammad Bilal Shaikh

Abstract:

Mineral processing plants play a pivotal role in extracting valuable minerals from raw ores, contributing significantly to various industries. However, the optimization of plant throughput remains a complex challenge, necessitating innovative approaches for increased efficiency and productivity. This research paper investigates the application of Multimodal Artificial Intelligence (MAI) techniques to address this challenge, aiming to improve overall plant throughput in mineral processing operations. The integration of multimodal AI leverages a combination of diverse data sources, including sensor data, images, and textual information, to provide a holistic understanding of the complex processes involved in mineral extraction. The paper explores the synergies between various AI modalities, such as machine learning, computer vision, and natural language processing, to create a comprehensive and adaptive system for optimizing mineral processing plants. The primary focus of the research is on developing advanced predictive models that can accurately forecast various parameters affecting plant throughput. Utilizing historical process data, machine learning algorithms are trained to identify patterns, correlations, and dependencies within the intricate network of mineral processing operations. This enables real-time decision-making and process optimization, ultimately leading to enhanced plant throughput. Incorporating computer vision into the multimodal AI framework allows for the analysis of visual data from sensors and cameras positioned throughout the plant. This visual input aids in monitoring equipment conditions, identifying anomalies, and optimizing the flow of raw materials. The combination of machine learning and computer vision enables the creation of predictive maintenance strategies, reducing downtime and improving the overall reliability of mineral processing plants. Furthermore, the integration of natural language processing facilitates the extraction of valuable insights from unstructured textual data, such as maintenance logs, research papers, and operator reports. By understanding and analyzing this textual information, the multimodal AI system can identify trends, potential bottlenecks, and areas for improvement in plant operations. This comprehensive approach enables a more nuanced understanding of the factors influencing throughput and allows for targeted interventions. The research also explores the challenges associated with implementing multimodal AI in mineral processing plants, including data integration, model interpretability, and scalability. Addressing these challenges is crucial for the successful deployment of AI solutions in real-world industrial settings. To validate the effectiveness of the proposed multimodal AI framework, the research conducts case studies in collaboration with mineral processing plants. The results demonstrate tangible improvements in plant throughput, efficiency, and cost-effectiveness. The paper concludes with insights into the broader implications of implementing multimodal AI in mineral processing and its potential to revolutionize the industry by providing a robust, adaptive, and data-driven approach to optimizing plant operations. In summary, this research contributes to the evolving field of mineral processing by showcasing the transformative potential of multimodal artificial intelligence in enhancing plant throughput. The proposed framework offers a holistic solution that integrates machine learning, computer vision, and natural language processing to address the intricacies of mineral extraction processes, paving the way for a more efficient and sustainable future in the mineral processing industry.

Keywords: multimodal AI, computer vision, NLP, mineral processing, mining

Procedia PDF Downloads 64

Authors: Felicite Ann Fairer-Wessels

Abstract:

There has always been a disparity between mining and tourism mainly due to the socio-economic and environmental impacts of mines on both the adjacent resident communities and the areas taken up by the mining operation. Although heritage mining tourism has been actively and successfully pursued and developed in the UK, largely Wales, and Scandinavian countries, the debate whether active mining and tourism can have a mutually beneficial relationship remains imminent. This pilot study explores the relationship between the ‘to be developed’ future Nokeng Mine and its adjacent community, the rural community of Moloto, will be investigated in terms of whether sustainable tourism and livelihood activities can potentially be developed with the support of the mine. Concepts such as social entrepreneur, corporate social responsibility, sustainable development and triple bottom line are discussed. Within the South African context as a mineral rich developing country, the government has a statutory obligation to empower disenfranchised communities through social and labour plans and policies. All South African mines must preside over a Social and Labour Plan according to the Mineral and Petroleum Resources Development Act, No 28 of 2002. The ‘social’ component refers to the ‘social upliftment’ of communities within or adjacent to any mine; whereas the ‘labour’ component refers to the mine workers sourced from the specific community. A qualitative methodology is followed using the case study as research instrument for the Nokeng Mine and Moloto community with interviews and focus group discussions. The target population comprised of the Moloto Tribal Council members (8 in-depth interviews), the Moloto community members (17: focus groups); and the Nokeng Mine representatives (4 in-depth interviews). In this pilot study two disparate ‘worlds’ are potentially linked: on the one hand, the mine as social entrepreneur that is searching for feasible and sustainable ideas; and on the other hand, the community adjacent to the mine, with potentially sustainable tourism entrepreneurs that can tap into the resources of the mine should their ideas be feasible to build their businesses. Being an exploratory study the findings are limited but indicate that the possible success of tourism and sustainable livelihood activities lies in the fact that both the Mine and Community are keen to work together – the mine in terms of obtaining labour and profit; and the community in terms of improved and sustainable social and economic conditions; with both parties realizing the importance to mitigate negative environmental impacts. In conclusion, a relationship of trust is imperative between a mine and a community before a long term liaison is possible. However whether tourism is a viable solution for the community to engage in is debatable. The community could initially rather pursue the sustainable livelihoods approach and focus on life-supporting activities such as building, gardening, etc. that once established could feed into possible sustainable tourism activities.

Keywords: community development, mining tourism, sustainability, South Africa

Procedia PDF Downloads 292

Authors: Mohammad Idrees Yusofzai, Hirobata Yasuhiro, Matsuo Kojiro

Abstract:

Kabul is the capital of Afghanistan. It is the focal point of educational, industrial, etc. of Afghanistan. Additionally, the population of Kabul has grown recently and will increase because of return of refugees and shifting of people from other province to Kabul city. However, this increase in population, the issues of urban congestion and other related problems of urban transportation in Kabul city arises. One of the problems is public transport (large buses) service and needs to be modified and enhanced especially large bus routes that are operating in each zone of the 22 zone of Kabul City. To achieve the above mentioned goal of improving public transport, Spatial Accessibility Analysis is one of the important attributes to assess the effectiveness of transportation system and urban transport policy of a city, because accessibility indicator as an alternative tool to support public policy that aims the reinforcement of sustainable urban space. The case study of this research compares the present model (present bus route) and the modified model of public transport. Furthermore, present model, the bus routes in most of the zones are active, however, with having low frequency and unpublished schedule, and accessibility result is analyzed in four cases, based on the variables of accessibility. Whereas in modified model all zones in Kabul is taken into consideration with having specified origin and high frequency. Indeed the number of frequencies is kept high; however, this number is based on the number of buses Millie Bus Enterprise Authority (MBEA) owns. The same approach of cases is applied in modified model to figure out the best accessibility for the modified model. Indeed, the modified model is having a positive impact in congestion level in Kabul city. Besides, analyses of person trip and trip distribution have been also analyzed because how people move in the study area by each mode of transportation. So, the general aims of this research are to assess the present movement of people, identify zones in need of public transport and assess equity level of accessibility in Kabul city. The framework of methodology used in this research is based on gravity analysis model of accessibility; besides, generalized cost (time) of travel and travel mode is calculated. The main data come from person trip survey, socio-economic characteristics, demographic data by Japan International Cooperation Agency, 2008, study of Kabul city and also from the previous researches on travel pattern and the remaining data regarding present bus line and routes have been from MBEA. In conclusion, this research explores zones where public transport accessibility level is high and where it is low. It was found that both models the downtown area or central zones of Kabul city is having high level accessibility. Besides, the present model is the most unfavorable compared with the modified model based on the accessibility analysis.

Keywords: accessibility, bus generalized cost, gravity model, public transportation network

Procedia PDF Downloads 190

Authors: Nazari Maryam, Gorji Saman

Abstract:

For most competitions, athletes usually engage in a process called rapid weight loss (RWL) and subsequent rapid weight gain (RWG) in the days preceding the event. Besides the perfection of performance, weight regulation mediates a self-image of being “a real athlete” which is mentally important as a part of the pre-competition preparation. This feeling enhances the focus and commitment of the athlete. There is a large body of evidence that weight loss, particularly in combat sports, results in several health benefits. However, intentional weight loss beyond normal levels might have unknown negative special effects on the immune system. As the results show, a high prevalence (50%) of RWL is happening among combat athletes. It seems that energy deprivation and intense exercise to reach RWL results in altered blood cell distribution through modification of body composition that, in turn, changes B and T-Lymphocyte and/or CD4 T-Helper response. Moreover, it may diminish IgG antibody levels and modulate IgG glycosylation after this course. On the other hand, some studies show suppression of signaling and regulation of IgE antibody and chemokine production are responsible for immunodeficiency following a period of low-energy availability. Some researchers hypothesize that severe glutamine depletion, which occurs during exercise and calorie restriction, is responsible for this immune system weakness. However, supplementation by this amino acid is not prescribed yet. Therefore, weight loss is achieved not only through chronic strategies (body fat losses) but also through acute manipulations prior to competition should be supervised by a sports nutritionist to minimize side effects on the immune system and other body systems.

Keywords: athletes, immune system, rapid weight loss, weight loss strategies

Procedia PDF Downloads 114

Authors: Audrius Dedele, Aukse Miskinyte

Abstract:

Air pollution is a major problem, especially in large cities, causing a variety of environmental issues and a risk to human health effects. In order to observe air quality, to reduce and control air pollution in the city, municipalities are responsible for the creation of air quality management plans, air quality monitoring and emission inventories. Atmospheric dispersion modelling systems, along with monitoring, are powerful tools, which can be used not only for air quality management, but for the assessment of human exposure to air pollution. These models are widely used in epidemiological studies, which try to determine the associations between exposure to air pollution and the adverse health effects. The purpose of this study was to determine the concentration of particulate matter smaller than 10 μm (PM10) in different districts of Kaunas city during winter season. ADMS-Urban dispersion model was used for the simulation of PM10 pollution. The inputs of the model were the characteristics of stationary, traffic and domestic sources, emission data, meteorology and background concentrations were entered in the model. To assess the modelled concentrations of PM10 in Kaunas districts, geographic information system (GIS) was used. More detailed analysis was made using Spatial Analyst tools. The modelling results showed that the average concentration of PM10 during winter season in Kaunas city was 24.8 µg/m3. The highest PM10 levels were determined in Zaliakalnis and Aleksotas districts with are the highest number of individual residential properties, 32.0±5.2 and 28.7±8.2 µg/m3, respectively. The lowest pollution of PM10 was modelled in Petrasiunai district (18.4 µg/m3), which is characterized as commercial and industrial neighbourhood.

Keywords: air pollution, dispersion model, GIS, Particulate matter

Procedia PDF Downloads 264

Authors: Madalina Postaru, Alexandra Tucaliuc, Dan Cascaval, Anca Irina Galaction

Abstract:

Ergosterol (ergosta-5,7,22-trien-3β-ol) is the precursor of vitamin D2 (ergocalciferol), known as provitamin D2 as it is converted under UV radiation to this vitamin. The natural sources of ergosterol are mainly the yeasts (Saccharomyces sp., Candida sp.), but it can be also found in fungus (Claviceps sp.) or plants (orchids). As ergosterol is mainly accumulated in yeast cell membranes, especially in free form in the plasma-membrane, and the chemical synthesis of ergosterol does not represent an efficient method for its production, this study aimed to analyze the influence of aeration efficiency on ergosterol production by S. cerevisiae in batch and fed-batch fermentations, by considering different levels of mixing intensity, aeration rate, and n-dodecane concentration. Our previous studies on ergosterol production by S. cerevisiae in batch and fed-batch fermentation systems indicated that the addition of n-dodecane led to the increase of almost 50% of this sterol concentration, the highest productivity being reached for the fed-batch process. The experiments were carried out in a laboratory stirred bioreactor, provided with computer-controlled and recorded parameters. In batch fermentation system, the study indicated that the oxygen mass transfer coefficient, kLa, is amplified for about 3 times by increasing the volumetric concentration of n-dodecane from 0 to 15%. Moreover, the increase of dissolved oxygen concentration by adding n-dodecane leads to the diminution for 3.5 times of the produced alcohol amount. In fed-batch fermentation process, the positive influence of hydrocarbon on oxygen transfer rate is amplified mainly at its higher concentration level, as the result of the increased yeasts cells amount. Thus, by varying n-dodecane concentration from 0 to 15% vol., the kLa value increase becomes more important than for the batch fermentation, being of 4 times

Keywords: ergosterol, yeast fermentation, n-dodecane, oxygen-vector

Procedia PDF Downloads 114

Authors: Theresa K., Shanmugasundaram R., Kennedy J. S.

Abstract:

Nutrient supplements are indispensable for raising crops and to reap determining productivity. The nutrient imbalance between replenishment and crop uptake is attempted through the input of inorganic fertilizers. Excessive dumping of inorganic nutrients in soil cause stagnant and decline in yield. Imbalanced N-P-K ratio in the soil exacerbates and agitates the soil ecosystems. The study evaluated the fertilization practices of conventional (CFs), organic and Integrated Nutrient Management system (INM) on soil quality using key indicators and soil quality indices. Twelve rice farming fields of which, ten fields were having conventional cultivation practices, one field each was organic farming based and INM based cultivated under monocropping sequence in the Thondamuthur block of Coimbatore district were fixed and properties viz., physical, chemical and biological were studied for four cropping seasons to determine soil quality index (SQI). SQI was computed for conventional, organic and INM fields. Comparing conventional farming (CF) with organic and INM, CF was recorded with a lower soil quality index. While in organic and INM fields, the higher SQI value of 0.99 and 0.88 respectively were registered. CF₄ received with a super-optimal dose of N (250%) showed a lesser SQI value (0.573) as well as the yield (3.20 t ha⁻¹) and the CF6 which received 125 % N recorded the highest SQI (0.715) and yield (6.20 t ha⁻¹). Likewise, most of the CFs received higher N beyond the level of 125 % except CF₃ and CF₉, which recorded lower yields. CFs which received super-optimal P in the order of CF₆&CF₇>CF₁&CF₁₀ recorded lesser yields except for CF₆. Super-optimal K application also recorded lesser yield in CF₄, CF₇ and CF₉.

Keywords: rice cropping system, soil quality indicators, imbalanced fertilization, yield

Procedia PDF Downloads 154

Authors: Naseer M. A.

Abstract:

Buildings are major consumers of energy in both their construction and operation. They account for 40% of World’s energy use. It is estimated that 40-60% of this goes for conditioning the indoor environment. In India, like many other countries, the residential buildings have a major share (more than 50%) in the building sector. Of these, single-family units take a mammoth share. The single-family dwelling units in the urban and fringe areas are built in two stories to minimize the building foot print on small land parcels. And quite often, the bedrooms are located in the first floors. The modern buildings are provided with reinforced concrete (RC) roofs that absorb heat throughout the day and radiate the heat into the interiors during the night. The rooms that are occupied in the night, like bedrooms, are having their indoors uncomfortable. This has resulted in the use of active systems like air-conditioners and air coolers, thereby increasing the energy use. An investigation conducted by monitoring the thermal comfort condition in the residential building with RC roofs have proved that the indoors are really uncomfortable in the night hours. A sustainable solution to improve the thermal performance of the RC roofs was developed by an experimental study by continuously monitoring the thermal comfort parameters during summer (the period that is most uncomfortable in temperate climate). The study conducted in the southern peninsular India, prove that retrofitting of existing residential building can give a sustainable solution in abating the ever increasing energy demand especially when it is a fact that these residential buildings that are built for a normal life span of 40 years would continue to consume the energy for the rest of its useful life.

Keywords: energy efficiency, thermal comfort, retrofitting, residential buildings

Procedia PDF Downloads 247

Authors: Nadish Anand, Richard D. Gould

Abstract:

A simplistic model is introduced for determining the thermal characteristics of a Low-rise Residential (LRR) building and then predicts the energy usage by its Heating Ventilation & Air Conditioning (HVAC) system according to changes in weather conditions which are reflected in the Ambient Temperature (Outside Air Temperature). The LRR buildings are treated as a simple lump for solving the heat transfer problem and the model is derived using the lumped capacitance model of transient conduction heat transfer from bodies. Since most contemporary HVAC systems have a thermostat control which will have an offset temperature and user defined set point temperatures which define when the HVAC system will switch on and off. The aim is to predict without any error the Body Temperature (i.e. the Inside Air Temperature) which will estimate the switching on and off of the HVAC system. To validate the mathematical model derived from lumped capacitance we have used EnergyPlus simulation engine, which simulates Buildings with considerable accuracy. We have predicted through the low order model the Inside Air Temperature of a single house kept in three different climate zones (Detroit, Raleigh & Austin) and different orientations for summer and winter seasons. The prediction error from the model for the same day as that of model parameter calculation has showed an error of < 10% in winter for almost all the orientations and climate zones. Whereas the prediction error is only <10% for all the orientations in the summer season for climate zone at higher latitudes (Raleigh & Detroit). Possible factors responsible for the large variations are also noted in the work, paving way for future research.

Keywords: building energy, energy consumption, energy+, HVAC, low order model, lumped capacitance

Procedia PDF Downloads 264

Authors: Farhad Salek, Shahaboddin Resalati

Abstract:

The production of electric vehicles (EVs) featuring lithium-ion battery technology has substantially escalated over the past decade, demonstrating a steady and persistent upward trajectory. The imminent retirement of electric vehicle (EV) batteries after approximately eight years underscores the critical need for their redirection towards recycling, a task complicated by the current inadequacy of recycling infrastructures globally. A potential solution for such concerns involves extending the operational lifespan of electric vehicle (EV) batteries through their utilization in stationary energy storage systems during secondary applications. Such adoptions, however, require addressing the safety concerns associated with batteries’ knee points and thermal runaways. This paper develops an accurate mathematical model representative of the second-life battery packs from a cell-to-pack scale using an equivalent circuit model (ECM) methodology. Neural network algorithms are employed to forecast the degradation parameters based on the EV batteries' aging history to develop a degradation model. The degradation model is integrated with the ECM to reflect the impacts of the cycle aging mechanism on battery parameters during operation. The developed model is tested under real-life load profiles to evaluate the life span of the batteries in various operating conditions. The methodology and the algorithms introduced in this paper can be considered the basis for Battery Management System (BMS) design and techno-economic analysis of such technologies.

Keywords: second life battery, electric vehicles, degradation, neural network

Procedia PDF Downloads 59

Authors: Huijie Wang, Bin Zhang

Abstract:

In China, the middle reaches of the Yangtze River are well-developed, boasting a wealth of different types of watershed landscape. In this regard, landscape character assessment (LCA) can serve as a basis for protection, management and planning of trans-regional watershed landscape types. For this study, we chose the middle reaches of the Yangtze River in Wuhan metropolitan area as our study site, wherein the water system consists of rich variety in landscape types. We analyzed trans-regional data to cluster and identify types of landscape characteristics at two levels. 55 basins were analyzed as variables with topography, land cover and river system features in order to identify the watershed landscape character types. For watershed landscape, drainage density and degree of curvature were specified as special variables to directly reflect the regional differences of river system features. Then, we used the principal component analysis (PCA) method and hierarchical clustering algorithm based on the geographic information system (GIS) and statistical products and services solution (SPSS) to obtain results for clusters of watershed landscape which were divided into 8 characteristic groups. These groups highlighted watershed landscape characteristics of different river systems as well as key landscape characteristics that can serve as a basis for targeted protection of watershed landscape characteristics, thus helping to rationally develop multi-value landscape resources and promote coordinated development of trans-regions.

Keywords: GIS, hierarchical clustering, landscape character, landscape typology, principal component analysis, watershed

Procedia PDF Downloads 223

Authors: Mrinalini Amritkar, Disha Patil, Swapna Kulkarni, Sukratu Barve, Suresh Gosavi

Abstract:

Micro-mixers play an important role in the lab-on-a-chip applications and micro total analysis systems to acquire the correct level of mixing for any given process. The mixing process can be classified as active or passive according to the use of external energy. Literature of microfluidics reports that most of the work is done on the models of steady laminar flow; however, the study of unsteady laminar flow is an active area of research at present. There are wide applications of this, out of which, we consider nanoparticle synthesis in micro-mixers. In this work, we have developed a model for unsteady flow to study the mixing performance of a passive micro mixer for reactants used for such synthesis. The model is developed in Finite Volume Method (FVM)-based software, OpenFOAM. The model is tested by carrying out the simulations at Re of 0.5. Mixing performance of the micro-mixer is investigated using simulated concentration values of mixed species across the width of the micro-mixer and calculating the variance across a line profile. Experimental validation is done by passing dyes through a Y shape micro-mixer fabricated using polydimethylsiloxane (PDMS) polymer and comparing variances with the simulated ones. Gold nanoparticles are later synthesized through the micro-mixer and collected at two different times leading to significantly different size distributions. These times match with the time scales over which reactant concentrations vary as obtained from simulations. Our simulations could thus be used to create design aids for passive micro-mixers used in nanoparticle synthesis.

Keywords: Lab-on-chip, LOC, micro-mixer, OpenFOAM, PDMS

Procedia PDF Downloads 155

Authors: M. H. Pazandeh, M. Doudi, S. Barahimi, L. Rahimzadeh Torabi

Abstract:

The use of antibiotics is essential in reducing the occurrence of adverse effects and inhibiting the emergence of antibiotic resistance in microbial populations. The necessity for a novel methodology concerning local administration of antibiotics has arisen, with particular focus on dealing with localized infections prompted by bacterial colonization of medical devices or implant materials. Bioactive glasses (BG) are extensively employed in the field of regenerative medicine, encompassing a diverse range of materials utilized for drug delivery systems. In the present investigation, various drug carriers for imipenem and tetracycline, namely single systems BG/SnO2, BG/NiO with varying proportions of metal oxide, and nanocomposite BG/SnO2/NiO, were synthesized through the sol-gel technique. The antibacterial efficacy of the synthesized samples was assessed through the utilization of the disk diffusion method with the aim of neutralizing Staphylococcus aureus as the bacterial model. The current study involved the examination of the bioactivity of two samples, namely BG10SnO2/10NiO and BG20SnO2, which were chosen based on their heightened bacterial inactivation properties. This evaluation entailed the employment of two techniques: the measurement of the pH of simulated body fluid (SBF) solution and the analysis of the sample tablets through X-ray diffraction (XRD), scanning electron microscopy (SEM), and Fourier transform infrared (FTIR) spectroscopy. The sample tablets were submerged in SBF for varying durations of 7, 14, and 28 days. The bioactivity of the composite bioactive glass sample was assessed through characterization of alterations in its surface morphology, structure, and chemical composition. This evaluation was performed using scanning electron microscopy (SEM), Fourier-transform infrared (FTIR) spectroscopy, and X-ray diffraction spectroscopy. Subsequently, the sample was immersed in simulated liquids to simulate its behavior in biological environments. The specific body fat percentage (SBF) was assessed over a 28-day period. The confirmation of the formation of a hydroxyapatite surface layer serves as a distinct indicator of bioactivity. The infusion of antibiotics into the composite bioactive glass specimen was done separately, and then the release kinetics of tetracycline and imipenem were tested in simulated body fluid (SBF). Antimicrobial effectiveness against various bacterial strains have been proven in numerous instances using both melt and sol-gel techniques to create multiple bioactive glass compositions. An elevated concentration of calcium ions within a solution has been observed to cause an increase in the pH level. In aqueous suspensions, bioactive glass particles manifest a significant antimicrobial impact. The composite bioactive glass specimen exhibits a gradual and uninterrupted release, which is highly desirable for a drug delivery system over a span of 72 hours. The reduction in absorption, which signals the loss of a portion of the antibiotic during the loading process from the initial phosphate-buffered saline solution, indicates the successful bonding of the two antibiotics to the surfaces of the bioactive glass samples. The sample denoted as BG/10SnO2/10NiO exhibits a higher loading of particles compared to the sample designated as BG/20SnO2 in the context of bioactive glass. The enriched sample demonstrates a heightened bactericidal impact on the bacteria under investigation while concurrently preserving its antibacterial characteristics. Tailored bioactive glass that incorporates hydroxyapatite, with a regulated and efficient release of drugs targeting bacterial infections, holds promise as a potential framework for bone implant scaffolds following rigorous clinical evaluation, thereby establishing potential future biomedical uses. During the modification process, the introduction of metal oxides into bioactive glass resulted in improved antibacterial characteristics, particularly in the composite bioactive glass sample that displayed the highest level of efficiency.

Keywords: antibacterial, bioactive glasses, implant infections, multi drug resistant

Procedia PDF Downloads 94

Authors: Ritika Chaturvedi

Abstract:

Introduction: Sexual objectification, characterized by the reduction of an individual to a mere object of sexual desire, remains a pervasive societal issue with profound repercussions on individual well-being. Such experiences, often rooted in systemic and cultural norms, have long-lasting implications for mental and emotional health. This study aims to explore the intricate relationship between experiences of sexual objectification and insidious trauma, further investigating the potential moderating effects of overexcitabilities as proposed by Dabrowski's theory of positive disintegration. Methodology: The research involved a comprehensive cohort of 204 women, spanning ages from 18 to 65 years. Participants were tasked with completing self-administered questionnaires designed to capture their experiences with sexual objectification. Additionally, the questionnaire assessed symptoms indicative of insidious trauma and explored overexcitabilities across five distinct domains: emotional, intellectual, psychomotor, sensory, and imaginational. Employing advanced statistical techniques, including multiple regression and moderation analysis, the study sought to decipher the intricate interplay among these variables. Findings: The study's results revealed a compelling positive correlation between experiences of sexual objectification and the onset of symptoms indicative of insidious trauma. This correlation underscores the profound and detrimental effects of sexual objectification on an individual's psychological well-being. Interestingly, the moderation analyses introduced a nuanced understanding, highlighting the differential roles of various overexcitabilities. Specifically, emotional, intellectual, and sensual overexcitabilities were found to exacerbate trauma symptomatology. In contrast, psychomotor overexcitability emerged as a protective factor, demonstrating a mitigating influence on the relationship between sexual objectification and trauma. Implications: The study's findings hold significant implications for a diverse array of stakeholders, encompassing mental health practitioners, educators, policymakers, and advocacy groups. The identified moderating effects of overexcitabilities emphasize the need for tailored interventions that consider individual differences in coping and resilience mechanisms. By recognizing the pivotal role of overexcitabilities in modulating the traumatic consequences of sexual objectification, this research advocates for the development of more nuanced and targeted support frameworks. Moreover, the study underscores the importance of continued research endeavors to unravel the intricate mechanisms and dynamics underpinning these relationships. Such endeavors are crucial for fostering the evolution of informed, evidence-based interventions and strategies aimed at mitigating the adverse effects of sexual objectification and promoting holistic well-being.

Keywords: sexual objectification, insidious trauma, emotional overexcitability, intellectual overexcitability, sensual overexcitability, psychomotor overexcitability, imaginational overexcitability

Procedia PDF Downloads 44

Authors: Serge Tshibangu, Turgay Celik, Zenzo Ncube

Abstract:

Road crashes kill nearly over a million people every year, and leave millions more injured or permanently disabled. Various annual reports reveal that the percentage of fatal crashes due to fatigue/driver falling asleep comes directly after the percentage of fatal crashes due to intoxicated drivers. This percentage is higher than the combined percentage of fatal crashes due to illegal/Un-Safe U-turn and illegal/Un-Safe reversing. Although a relatively small percentage of police reports on road accidents highlights drowsiness and fatigue, the importance of these factors is greater than we might think, hidden by the undercounting of their events. Some scenarios show that these factors are significant in accidents with killed and injured people. Thus the need for an automatic drivers fatigue detection system in order to considerably reduce the number of accidents owing to fatigue.This research approaches the drivers fatigue detection problem in an innovative way by combining cues collected from both temporal analysis of drivers’ faces and environment. Monotony in driving environment is inter-related with visual symptoms of fatigue on drivers’ faces to achieve fatigue detection. Optical and infrared (IR) sensors are used to analyse the monotony in driving environment and to detect the visual symptoms of fatigue on human face. Internal cues from drivers faces and external cues from environment are combined together using machine learning algorithms to automatically detect fatigue.

Keywords: intelligent transportation systems, bayesian networks, yawning computing, machine learning algorithms

Procedia PDF Downloads 453

Authors: Marina Kapsali, John S. Anagnostopoulos

Abstract:

Greek islands’ interconnection (IC) with larger power systems, such as the mainland grid, is a crucial issue that has attracted a lot of interest; however, the recent economic recession that the country undergoes together with the highly capital intensive nature of this kind of projects have stalled or sifted the development of many of those on a more long-term basis. On the other hand, most of Greek islands are still heavily dependent on the lengthy and costly supply chain of oil imports whilst the majority of them exhibit excellent potential for wind energy (WE) applications. In this respect, the main purpose of the present work is to investigate −through a parametric study which varies both in wind farm (WF) and submarine IC capacities− the impact of large-scale WE development on the IC of the third in size island of Greece (Lesbos) with the mainland system. The energy and economic performance of the system is simulated over a 25-year evaluation period assuming two possible scenarios, i.e. S(a): without the contribution of the local Thermal Power Plant (TPP) and S(b): the TPP is maintained to ensure electrification of the island. The economic feasibility of the two options is investigated in terms of determining their Levelized Cost of Energy (LCOE) including also a sensitivity analysis on the worst/reference/best Cases. According to the results, Lesbos island IC presents considerable economic interest for covering part of island’s future electrification needs with WE having a vital role in this challenging venture.

Keywords: electricity generation cost, levelized cost of energy, mainland grid, wind energy rejection

Procedia PDF Downloads 211

Authors: Swapnil Kumar Singh

Abstract:

Gamma-ray bursts (GRB's), short and intense pulses of low-energy γ rays, have fascinated astronomers and astrophysicists since their unexpected discovery in the late sixties. GRB'sare accompanied by long-lasting afterglows, and they are associated with core-collapse supernovae. The detection of delayed emission in X-ray, optical, and radio wavelength, or "afterglow," following a γ-ray burst can be described as the emission of a relativistic shell decelerating upon collision with the interstellar medium. While it is fair to say that there is strong diversity amongst the afterglow population, probably reflecting diversity in the energy, luminosity, shock efficiency, baryon loading, progenitor properties, circumstellar medium, and more, the afterglows of GRBs do appear more similar than the bursts themselves, and it is possible to identify common features within afterglows that lead to some canonical expectations. After an initial flash of gamma rays, a longer-lived "afterglow" is usually emitted at longer wavelengths (X-ray, ultraviolet, optical, infrared, microwave, and radio). It is a slowly fading emission at longer wavelengths created by collisions between the burst ejecta and interstellar gas. In X-ray wavelengths, the GRB afterglow fades quickly at first, then transitions to a less-steep drop-off (it does other stuff after that, but we'll ignore that for now). During these early phases, the X-ray afterglow has a spectrum that looks like a power law: flux F∝ E^β, where E is energy and beta is some number called the spectral index. This kind of spectrum is characteristic of synchrotron emission, which is produced when charged particles spiral around magnetic field lines at close to the speed of light. In addition to the outgoing forward shock that ploughs into the interstellar medium, there is also a so-called reverse shock, which propagates backward through the ejecta. In many ways," reverse" shock can be misleading; this shock is still moving outward from the restframe of the star at relativistic velocity but is ploughing backward through the ejecta in their frame and is slowing the expansion. This reverse shock can be dynamically important, as it can carry comparable energy to the forward shock. The early phases of the GRB afterglow still provide a good description even if the GRB is highly collimated since the individual emitting regions of the outflow are not in causal contact at large angles and so behave as though they are expanding isotropically. The majority of afterglows, at times typically observed, fall in the slow cooling regime, and the cooling break lies between the optical and the X-ray. Numerous observations support this broad picture for afterglows in the spectral energy distribution of the afterglow of the very bright GRB. The bluer light (optical and X-ray) appears to follow a typical synchrotron forward shock expectation (note that the apparent features in the X-ray and optical spectrum are due to the presence of dust within the host galaxy). We need more research in GRB and Particle Physics in order to unfold the mysteries of afterglow.

Keywords: GRB, synchrotron, X-ray, isotropic energy

Procedia PDF Downloads 87

Authors: Joleen L. H. Lee, K. F. Yen, Janette W. P. Ng, D. Woon, Mandy M. Y. Lau, Ivan M. H. Woo, S. N. Goh

Abstract:

Case assignment systems are created to meet a need for equity in work distribution and better match between medical social workers' (MSWs) competencies and patients' problems. However, there is no known study that has explored how MSWs in Singapore assign cases to achieve equity in work distribution. Focus group discussions were conducted with MSWs from public hospitals to understand their perception on equitable workload and case allocation. Three approaches to case allocation were found. First is the point system where points are allocated to cases based on a checklist of presenting issues identified most of the time by non-MSWs. Intensity of case is taken into consideration, but allocation of points is often subject to variation in appreciation of roles of MSWs by the source of referral. Second is the round robin system, where all MSWs are allocated cases based on a roster. This approach resulted in perceived equity due to element of luck, but it does not match case complexity with competencies of MSWs. Third approach is unit-based allocation, where MSWs are assigned to attend to cases from specific unit. This approach helps facilitate specialization among MSWs but may result in MSWs having difficulty providing transdisciplinary care due to narrow set of knowledge and skills. Trade-offs resulted across existing approaches for case allocation by MSWs. Conversations are needed among Singapore MSWs to decide on a case allocation system that comes with trade-offs that are acceptable for patients and other key stakeholders of the care delivery system.

Keywords: case allocation, equity, medical social worker, work distribution

Procedia PDF Downloads 122

Authors: Alexander Otchere Fianko, Clement Yeboah, Evans Oteng

Abstract:

Prior research concludes that Green Procurement Practices positively drive Organisational Performance. Nonetheless, the nexus and conditions under which Green Procurement Practices contribute to a Firm’s Performance are less understood. The purpose of this quantitative relational study was to examine the relationship between Green Procurement Practices and 500 Firms’ Performances in Ghana. The researchers further seek to draw insights from the resource-based view to conceptualize Green Procurement Practices and Environmental Commitment as resource capabilities to enhance Firm Performance. The researchers used insights from the contingent resource-based view to examine Green Leadership Orientation conditions under which Green Procurement Practices contribute to Firm Performance through Environmental Commitment Capabilities. The study’s conceptual framework was tested on primary data from some firms in the Ghanaian market. PROCESS Macro was used to test the study’s hypotheses. Beyond that, Environmental Commitment Capabilities mediated the association between Green Procurement Practices and the Firm’s Performance. The study further seeks to find out whether Green Leadership Orientation positively moderates the indirect relationship between Green Procurement Practices and Firm Performance through Environmental Commitment Capabilities. While conventional wisdom suggests that improved Green Procurement Practices help improve a Firm’s Performance, this study tested this presumed relationship between Green Procurement Practices and Firm Performance and provides theoretical arguments and empirical evidence to justify how Environmental Commitment Capabilities uniquely and in synergy with Green Leadership Orientation transform this relationship. The study results indicated a positive correlation between Green Procurement Practices and Firm Performance. This result suggests that firms that prioritize environmental sustainability and demonstrate a strong commitment to environmentally responsible practices tend to experience better overall performance. This includes financial gains, operational efficiency, enhanced reputation, and improved relationships with stakeholders. The study's findings inform policy formulation in Ghana related to environmental regulations, incentives, and support mechanisms. Policymakers can use the insights to design policies that encourage and reward firms for their Green Procurement Practices, thereby fostering a more sustainable and environmentally responsible business environment. The findings from such research can influence the design and development of educational programs in Ghana, specifically in fields related to sustainability, environmental management, and corporate social responsibility (CSR). Institutions may consider integrating environmental and sustainability topics into their business and management courses to create awareness and promote responsible practices among future business professionals. Also, the study results can also promote the adoption of environmental accounting practices in Ghana. By recognizing and measuring the environmental impacts and costs associated with business activities, firms can better understand the financial implications of their Green Procurement Practices and develop strategies for improved performance.

Keywords: environmental commitment, firm’s performance, green procurement practice, green leadership orientation

Procedia PDF Downloads 76

Authors: Vasanth C. Shunmugasamy, Bilal Mansoor

Abstract:

Magnesium alloys are increasingly being considered for structural systems across different industrial sectors, including precision components of biomedical devices, owing to their high specific strength, stiffness and biodegradability. However, Mg alloys exhibit a high corrosion rate that restricts their application as a biomaterial. For safe use as biomaterial, it is essential to control their corrosion rates. Mg alloy corrosion is influenced by several factors, such as grain size, precipitates and texture. In Mg alloys, microgalvanic coupling between the α-Mg matrix and secondary precipitates can exist, which results in an increased corrosion rate. The present research addresses this challenge by engineering the microstructure of a biodegradable Mg–Zn–RE–Zr alloy by friction stir processing (FSP), a severe plastic deformation process. The FSP-processed Mg alloys showed improved corrosion resistance and mechanical properties. FSPed Mg alloy showed refined grains, a strong basal texture and broken and uniformly distributed secondary precipitates in the stir zone. Mg, alloy base material, exposed to In vitro corrosion medium showed micro galvanic coupling between precipitate and matrix, resulting in the unstable passive layer. However, FS processed alloy showed uniform corrosion owing to stable surface film formation. The stable surface film is attributed to refined grains, preferred texture and distribution of precipitates. The research results show promising potential for Mg alloy to be developed as a biomaterial.

Keywords: biomaterials, severe plastic deformation, magnesium alloys, corrosion

Procedia PDF Downloads 36

Authors: Kim Toyer, Belinda Thompson, Louise Koelmeyer

Abstract:

Lymphoedema is a chronic condition caused by dysfunction of the lymphatic system, which limits the drainage of fluid and tissue waste from the interstitial space of the affected body part. The normal physiological changes in pregnancy cause an increased load on a normal lymphatic system which can result in a transient lymphatic overload (oedema). The interaction between lymphoedema and pregnancy oedema is unclear. Women with pre-existing lymphoedema require accurate information and additional strategies to manage their lymphoedema during pregnancy. Currently, no resources are available to guide women or their healthcare providers with accurate advice and additional management strategies for coping with lymphoedema during pregnancy until they have recovered postnatally. This study explored the experiences of Australian women with pre-existing lymphoedema during recent pregnancy and the early postnatal period to determine how their usual lymphoedema management strategies were adapted and what were their additional or unmet needs. Interactions with their obstetric care providers, the hospital maternity services, and usual lymphoedema therapy services were detailed. Participants were sourced from several Australian lymphoedema community groups, including therapist networks. Opportunistic sampling is appropriate to explore this topic in a small target population as lymphoedema in women of childbearing age is uncommon, with prevalence data unavailable. Inclusion criteria were aged over 18 years, diagnosed with primary or secondary lymphoedema of the arm or leg, pregnant within the preceding ten years (since 2012), and had their pregnancy and postnatal care in Australia. Exclusion criteria were a diagnosis of lipedema and if unable to read or understand a reasonable level of English. A mixed-method qualitative design was used in two phases. This involved an online survey (REDCap platform) of the participants followed by online semi-structured interviews or focus groups to provide the transcript data for inductive thematic analysis to gain an in-depth understanding of issues raised. Women with well-managed pre-existing lymphoedema coped well with the additional oedema load of pregnancy; however, those with limited access to quality conservative care prior to pregnancy were found to be significantly impacted by pregnancy, including many reporting deterioration of their chronic lymphoedema. Misinformation and a lack of support increased fear and apprehension in planning and enjoying their pregnancy experience. Collaboration between maternity and lymphoedema therapy services did not happen despite study participants suggesting it. Helpful resources and unmet needs were identified in the recent Australian context to inform further research and the development of resources to assist women with lymphoedema who are considering or are pregnant and their supporters, including health care providers.

Keywords: lymphoedema, management strategies, pregnancy, qualitative

Procedia PDF Downloads 80

Authors: Omar Farshad Jeelani, Makaire Njie, Viktoriia M. Korzhuk

Abstract:

Recently, the application of AI-powered algorithms in healthcare continues to flourish. Particularly, access to healthcare information, including patient health history, diagnostic data, and PII (Personally Identifiable Information) is paramount in the delivery of efficient patient outcomes. However, as the exchange of healthcare information between patients and healthcare providers through AI-powered solutions increases, protecting a person’s information and their privacy has become even more important. Arguably, the increased adoption of healthcare AI has resulted in a significant concentration on the security risks and protection measures to the security and privacy of healthcare data, leading to escalated analyses and enforcement. Since these challenges are brought by the use of AI-based healthcare solutions to manage healthcare data, AI-based data protection measures are used to resolve the underlying problems. Consequently, this project proposes AI-powered safeguards and policies/laws to protect the privacy of healthcare data. The project presents the best-in-school techniques used to preserve the data privacy of AI-powered healthcare applications. Popular privacy-protecting methods like Federated learning, cryptographic techniques, differential privacy methods, and hybrid methods are discussed together with potential cyber threats, data security concerns, and prospects. Also, the project discusses some of the relevant data security acts/laws that govern the collection, storage, and processing of healthcare data to guarantee owners’ privacy is preserved. This inquiry discusses various gaps and uncertainties associated with healthcare AI data collection procedures and identifies potential correction/mitigation measures.

Keywords: data privacy, artificial intelligence (AI), healthcare AI, data sharing, healthcare organizations (HCOs)

Procedia PDF Downloads 87

Authors: Hilal Ahmad Punoo

Abstract:

Conjugated linoleic acid (CLA) is a mixture of positional and geometric isomers of octadecadienoic acid with two conjugated double bonds. Of more than a dozen isomers of CLA found naturally in dairy and meat products from ruminants, c-9, t-11 and t-10, c-12 are the two isomers with known physiological importance, including anticarcinogenic, antidiabetic, antilipogenic, and antiatherosclerotic effects. Conjugated linoleic acids (CLA) may influence the onset and severity of several chronic diseases, including various cancers, atherosclerosis, obesity, bone density loss, and diabetes. These findings are of special interest to the agriculture community, because dietary sources of CLA are almost exclusively beef and dairy products. Thus, a better understanding of the specific isomers and mechanisms responsible for these positive effects of CLA on human health would be both prudent and economically beneficial. To date, research related to the advantages of CLA consumption on human health has been conducted using experimental laboratory animals and cell culture systems. These data consistently show that relatively low levels of CLA can influence risk of cancer. Further, very recent investigations suggest that the predominate CLA isoform (cis-9, trans-11 CLA or rumenic acid) found in beef and milk fat possesses anticarcinogenic effects but does not alter body composition; the trans-10, cis-12 CLA has been shown to inhibit lipogenesis. Clearly, further work, especially using human subjects, will be required to characterize the potential benefits of CLA consumption on human health. Moreover, we suggest that foods naturally containing high amounts of CLA (e.g., beef and dairy products) be considered as meeting the definition of functional foods.

Keywords: conjugated linoleic acid, potential health benefits, fats, animals, humans

Procedia PDF Downloads 303

Authors: Dibakar Chakrabarty, Mebada Suiting

Abstract:

Rapid urbanization coupled with changes in land use pattern results in increasing peak discharge and shortening of catchment time of concentration. The consequence is floods, which often inundate roads and inhabited areas of cities and towns. Management of storm water resulting from rainfall has, therefore, become an important issue for the municipal bodies. Proper management of storm water obviously includes adequate design of storm water drainage networks. The design of storm water network is a costly exercise. Least cost design of storm water networks assumes significance, particularly when the fund available is limited. Optimal design of a storm water system is a difficult task as it involves the design of various components, like, open or closed conduits, storage units, pumps etc. In this paper, a methodology for least cost design of storm water drainage systems is proposed. The methodology proposed in this study consists of coupling a storm water simulator with an optimization method. The simulator used in this study is EPA’s storm water management model (SWMM), which is linked with Genetic Algorithm (GA) optimization method. The model proposed here is a mixed integer nonlinear optimization formulation, which takes care of minimizing the sectional areas of the open conduits of storm water networks, while satisfactorily conveying the runoff resulting from rainfall to the network outlet. Performance evaluations of the developed model show that the proposed method can be used for cost effective design of open conduit based storm water networks.

Keywords: genetic algorithm (GA), optimal design, simulation-optimization, storm water network, SWMM

Procedia PDF Downloads 245