Search results for: healthy urban planning

Authors: Jean Paul Hategekimana, Bampire Claudine, Niyonsenga Nadia, Irakoze Josiane

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Peas, soybeans and rice are crops which are grown in Rwanda and are available in rural and urban local markets and they give contribution in reduction of health problems especially in fighting malnutrition and food insecurity in Rwanda. Several research activities have been conducted on how cereals flour can be mixed with legumes flour for developing baked products which are rich in protein, fiber, minerals as they are found in legumes. However, such activity was not yet well studied in Rwanda. The aim of the present study was to develop bread and biscuit products from peas, soybeans and rice as functional ingredients combined with wheat flour and then analyze the nutritional content and consumer acceptability of new developed products. The malnutrition problem can be reduced by producing bread and biscuits which are rich in protein and are very accessible for every individual. The processing of bread and biscuit were made by taking peas flour, soybeans flour and rice flour mixed with wheat flour and other ingredients then a dough was made followed by baking. For bread, two kind of products were processed, for each product one control and three experimental samples in different three ratios of peas and rice were prepared. These ratios were 95:5, 90:10 and 80:20 for bread from peas and 85:5:10, 80:10:10 and 70:10:20 for bread from peas and rice. For biscuit, two kind of products were also processed, for each product one control sample and three experimental samples in three different ratios were prepared. These ratios are 90:5:5,80:10:10 and 70:10:20 for biscuit from peas and rice and 90:5:5,80:10:10 and 70:10:20 for biscuit from soybean and rice. All samples including the control sample were analyzed for the consumer acceptability (sensory attributes) and nutritional composition. For sensory analysis, bread from of peas and rice flour with wheat flour at ratio 85:5:10 and bread from peas only as functional ingredient with wheat flour at ratio 95:5 and biscuits made from a of soybeans and rice at a ratio 90:5:5 and biscuit made from peas and rice at ratio 90:5:5 were most acceptable compared to control sample and other samples in different ratio. The moisture, protein, fat, fiber and minerals (Sodium and iron.) content were analyzed where bread from peas in all ratios was found to be rich in protein and fiber compare to control sample and biscuit from soybean and rice in all ratios was found to be rich in protein and fiber compare to control sample.

Keywords: bakery products, peas and rice flour, wheat flour, sensory evaluation, proximate composition

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Authors: Molakala Mourya Vardhan Reddy, Kandimala Revanth, Koduru Sumanth, Beena B. M.

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Emergency response and recovery operations are severely hampered by natural catastrophes, especially floods. Understanding post-flood scenarios is essential to disaster management because it facilitates quick evaluation and decision-making. To this end, we introduce FloodNet, a brand-new high-resolution aerial picture collection created especially for comprehending post-flood scenes. A varied collection of excellent aerial photos taken during and after flood occurrences make up FloodNet, which offers comprehensive representations of flooded landscapes, damaged infrastructure, and changed topographies. The dataset provides a thorough resource for training and assessing computer vision models designed to handle the complexity of post-flood scenarios, including a variety of environmental conditions and geographic regions. Pixel-level semantic segmentation masks are used to label the pictures in FloodNet, allowing for a more detailed examination of flood-related characteristics, including debris, water bodies, and damaged structures. Furthermore, temporal and positional metadata improve the dataset's usefulness for longitudinal research and spatiotemporal analysis. For activities like flood extent mapping, damage assessment, and infrastructure recovery projection, we provide baseline standards and evaluation metrics to promote research and development in the field of post-flood scene comprehension. By integrating FloodNet into machine learning pipelines, it will be easier to create reliable algorithms that will help politicians, urban planners, and first responders make choices both before and after floods. The goal of the FloodNet dataset is to support advances in computer vision, remote sensing, and disaster response technologies by providing a useful resource for researchers. FloodNet helps to create creative solutions for boosting communities' resilience in the face of natural catastrophes by tackling the particular problems presented by post-flood situations.

Keywords: image classification, segmentation, computer vision, nature disaster, unmanned arial vehicle(UAV), machine learning.

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Authors: Zahra Hamidi

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Promoting cycling, as an affordable environmentally friendly mode of transport to replace private car use has been central to sustainable transport policies. Cycling is faster than walking and combined with public transport has the potential to extend the opportunities that people can access. In other words, cycling, besides direct positive health impacts, can improve people mobility and ultimately their quality of life. Transport literature well supports the close relationship between mobility, quality of life, and, well being. At the same time inequity in the distribution of access and mobility has been associated with the key aspects of injustice and social exclusion. The pattern of social exclusion and inequality in access are also often related to population characteristics such as age, gender, income, health, and ethnic background. Therefore, while investing in transport infrastructure it is important to consider the equity of provided access for different population groups. This paper proposes a method to evaluate the equity of cycling in a city from Rawls egalitarian perspective. Since this perspective is concerned with the difference between individuals and social groups, this method combines accessibility measures and Theil index of inequality that allows capturing the inequalities ‘within’ and ‘between’ groups. The paper specifically focuses on two population characteristics as gender and ethnic background. Following Rawls equity principles, this paper measures accessibility by bikes to a selection of urban activities that can be linked to the concept of the social primary goods. Moreover, as growing number of cities around the world have launched bike-sharing systems (BSS) this paper incorporates both private and public bikes networks in the estimation of accessibility levels. Additionally, the typology of bike lanes (separated from or shared with roads), the presence of a bike sharing system in the network, as well as bike facilities (e.g. parking racks) have been included in the developed accessibility measures. Application of this proposed method to a real case study, the city of Malmö, Sweden, shows its effectiveness and efficiency. Although the accessibility levels were estimated only based on gender and ethnic background characteristics of the population, the author suggests that the analysis can be applied to other contexts and further developed using other properties, such as age, income, or health.

Keywords: accessibility, cycling, equity, gender

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Authors: Michelle Eliane Hernández-García, Angélica Lozano

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The traffic accidents study usually contemplates the relation between factors such as the type of vehicle, its operation, and the road infrastructure. Traffic accidents can be explained by different factors, which have a greater or lower relevance. Two zones are studied, a mixed industrial zone and the extended zone of it. The first zone has mainly residential (57%), and industrial (23%) land uses. Trucks are mainly on the roads where industries are located. Four sensors give information about traffic and speed on the main roads. The extended zone (which includes the first zone) has mainly residential (47%) and mixed residential (43%) land use, and just 3% of industrial use. The traffic mix is composed mainly of non-trucks. 39 traffic and speed sensors are located on main roads. The traffic mix in a mixed land use zone, could be related to traffic accidents. To understand this relation, it is required to identify the elements of the traffic mix which are linked to traffic accidents. Models that attempt to explain what factors are related to traffic accidents have faced multiple methodological problems for obtaining robust databases. Poisson regression models are used to explain the accidents. The objective of the Poisson analysis is to estimate a vector to provide an estimate of the natural logarithm of the mean number of accidents per period; this estimate is achieved by standard maximum likelihood procedures. For the estimation of the relation between traffic accidents and the traffic mix, the database is integrated of eight variables, with 17,520 observations and six vectors. In the model, the dependent variable is the occurrence or non-occurrence of accidents, and the vectors that seek to explain it, correspond to the vehicle classes: C1, C2, C3, C4, C5, and C6, respectively, standing for car, microbus, and van, bus, unitary trucks (2 to 6 axles), articulated trucks (3 to 6 axles) and bi-articulated trucks (5 to 9 axles); in addition, there is a vector for the average speed of the traffic mix. A Poisson model is applied, using a logarithmic link function and a Poisson family. For the first zone, the Poisson model shows a positive relation among traffic accidents and C6, average speed, C3, C2, and C1 (in a decreasing order). The analysis of the coefficient shows a high relation with bi-articulated truck and bus (C6 and the C3), indicating an important participation of freight trucks. For the expanded zone, the Poisson model shows a positive relation among traffic accidents and speed average, biarticulated truck (C6), and microbus and vans (C2). The coefficients obtained in both Poisson models shows a higher relation among freight trucks and traffic accidents in the first industrial zone than in the expanded zone.

Keywords: freight transport, industrial zone, traffic accidents, traffic mix, trucks

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Authors: Susanne Ferschl, Peter Holzmüller, Elisabeth Wacker

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Ageing populations, advances in medical sciences and digitalization, diversity and social disparities, as well as the increasing need for skilled healthcare professionals, are challenging healthcare systems around the globe. To address these challenges, future healthcare systems need to center on human needs taking into account the living environments that shape individuals’ knowledge of and opportunities to access healthcare. Moreover, health should be considered as a common good and an integral part of securing livelihoods for all people. Therefore, the adoption of a systems approach, as well as inter-disciplinary and inter-sectoral cooperation among healthcare providers, are essential. Additionally, the active engagement of target groups in the planning and design of healthcare structures is indispensable to understand and respect individuals’ health and livelihood needs. We will present the research project b4 – identifying needs | building bridges | developing health care in the social space, which is situated within this reasoning and accompanies the cross-sectoral cooperation project Brückenschlag (building bridges) in a Bavarian district. Brückenschlag seeks to explore effective ways of health care linking university medicine (Maximalversorgung | maximum care) with regional inpatient, outpatient, rehabilitative, and preventive care structures (Regionalversorgung | regional care). To create advantages for both (potential) patients and the involved cooperation partners, project b4 qualitatively assesses needs and motivations among professionals, population groups, and political stakeholders at individual and collective levels. Besides providing an overview of the project structure as well as of regional population and healthcare characteristics, the first results of qualitative interviews conducted with different health experts will be presented. Interviewed experts include managers of participating hospitals, nurses, medical specialists working in the hospital and registered doctors operating in practices in rural areas. At the end of the project life and based on the identified factors relevant to the success -and also for failure- of participatory cooperation in health care, the project aims at informing other districts embarking on similar systems-oriented and human-centered healthcare projects. Individuals’ health care needs in dependence on the social space in which they live will guide the development of recommendations.

Keywords: cross-sectoral collaboration in health care, human-centered health care, regional health care, individual and structural health conditions

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Authors: K. Nikilsha, Lakshmi Manohar, Debayan Chatterjee

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Landscape is a setting that informs the way of life of a set of people, and the repository of intangible values and human meanings that nurture our very existence. Along with the linkage that it forms with our lives, it can be argued that landscape and memory cannot be separated, as landscape is the nucleus of our memories. In this context, this paper studies landscape evolution of a region with unique geographic setting, where the dependency of the inhabitants on its resources, led to the formation of certain peculiar beliefs and taboos that formed the basis of a set of unwritten rules and guidelines which they still follow as a part of their lifestyle. One such example is Kuttanad, a low lying region in Kerala which is a complex mosaic of fragmented agricultural landscape incorporating coastal backwaters, rivers, marshes, paddy fields and water channels. The more the physical involvement with the resources, the more was the inhabitants attachment towards it. This attachment of the inhabitants to the place is very strong because the creation of this land was the result of the toil of the low caste labourers who strived day and night to create Kuttanad, which was reclaimed from water with the help of the finance supplied by their landlords. However, the greatest challenge faced by them is posed by the forces of water in the form of floods. As this land is fed by five rivers, even the slight variation in rainfall in its watershed area can cause a large imbalance in the water level causing the reclaimed land to be inundated. The effects of climate change including increase in rainfall, rise in sea level and change of seasons can act as a catalyst to this damage. Hasty urbanization has led to the conversion of paddy fields to housing plots and coconut/plantain fields giving no regard to the traditional systems which had once respected nature and combated floods and draughts through the various cultural practices and taboos practiced by the people. Thus it is essential to look back at the landscape evolution of Kuttanad and to recognise methods used traditionally in the region to establish a cultural landscape, and to understand how climate change and urbanisation shall pose a challenge to the existing landscape and lifestyle. This research also explores the possibilities of alternative and sustainable approaches for resilient urban development learned from Kuttanad as a case study.

Keywords: ecological conservation, landscape and ecological engineering, landscape evolution, man-made landscapes

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Authors: M. Sulieman, H. Arabiyat, H. Ali, K. Potiszil, I. Abbas, R. English, P. King, I. Brown, P. Drew

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Introduction: The incidence of breast ductal Carcinoma in Situ (DCIS) has been increasing; it currently represents up 20-25% of all breast carcinomas. Some aspects of DCIS management are still controversial, mainly due to the heterogeneity of its clinical presentation and of its biological and pathological characteristics. In DCIS, histological diagnosis obtained preoperatively, carries the risk of sampling error if the presence of invasive cancer is subsequently diagnosed. The mammographic extent over than 4–5 cm and the presence of architectural distortion, focal asymmetric density or mass on mammography are proven important risk factors of preoperative histological under staging. Intracystic papillary cancer (IPC) is a rare form of breast carcinoma. Despite being previously compared to DCIS it has been shown to present histologically with invasion of the basement membrane and even metastasis. SLNB – Carries the risk of associated comorbidity that should be considered when planning surgery for DCIS and IPC. Objectives: The aim of this Audit was to better define a ‘high risk’ group of patients with pre-op diagnosis of non-invasive cancer undergoing breast conserving surgery, who would benefit from sentinel node biopsy. Method: Retrospective data collection of all patients with ductal carcinoma in situ over 5 years. 636 patients identified, and after exclusion criteria applied: 394 patients were included. High risk defined as: Extensive micro-calcification >40mm OR any mass forming DCIS. IPC: Winpath search from for the term ‘papillary carcinoma’ in any breast specimen for 5 years duration;.29 patients were included in this group. Results: DCIS: 188 deemed high risk due to >40mm calcification or a mass forming (radiological or palpable) 61% of those had a mastectomy and 32% BCS. Overall, in that high-risk group - the number with invasive disease was 38%. Of those high-risk DCIS pts 85% had a SLN - 80% at the time of surgery and 5% at a second operation. For the BCS patients - 42% had SLN at time of surgery and 13% (8 patients) at a second operation. 15 (7.9%) pts in the high-risk group had a positive SLNB, 11 having a mastectomy and 4 having BCS. IPC: The provisional diagnosis of encysted papillary carcinoma is upgraded to an invasive carcinoma on final histology in around a third of cases. This has may have implications when deciding whether to offer sentinel node removal at the time of therapeutic surgery. Conclusions: We have defined a ‘high risk’ group of pts with pre-op diagnosis of non-invasive cancer undergoing BCS, who would benefit from SLNB at the time of the surgery. In patients with high-risk features; the risk of invasive disease is up to 40% but the risk of nodal involvement is approximately 8%. The risk of morbidity from SLN is up to about 5% especially the risk of lymphedema.

Keywords: breast ductal carcinoma in Situ (DCIS), intracystic papillary carcinoma (IPC), sentinel node biopsy (SLNB), high-risk, non-invasive, cancer disease

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Authors: Pin-Ling Yin, Dung-Ying Lin

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Satellites play an important role in our daily lives, from monitoring the Earth's environment and providing real-time disaster imagery to predicting extreme weather events. As technology advances and demands increase, the tasks undertaken by satellites have become increasingly complex, with more stringent resource management requirements. A common challenge in satellite mission scheduling is the limited availability of resources, including onboard memory, ground station accessibility, and satellite power. In this context, efficiently scheduling and managing the increasingly complex satellite missions under constrained resources has become a critical issue that needs to be addressed. The core of Satellite Onboard Activity Planning (SOAP) lies in optimizing the scheduling of the received tasks, arranging them on a timeline to form an executable onboard mission plan. This study aims to develop an optimization model that considers the various constraints involved in satellite mission scheduling, such as the non-overlapping execution periods for certain types of tasks, the requirement that tasks must fall within the contact range of specified types of ground stations during their execution, onboard memory capacity limits, and the collaborative constraints between different types of tasks. Specifically, this research constructs a mixed-integer programming mathematical model and solves it with a commercial optimization package. Simultaneously, as the problem size increases, the problem becomes more difficult to solve. Therefore, in this study, a heuristic algorithm has been developed to address the challenges of using commercial optimization package as the scale increases. The goal is to effectively plan satellite missions, maximizing the total number of executable tasks while considering task priorities and ensuring that tasks can be completed as early as possible without violating feasibility constraints. To verify the feasibility and effectiveness of the algorithm, test instances of various sizes were generated, and the results were validated through feedback from on-site users and compared against solutions obtained from a commercial optimization package. Numerical results show that the algorithm performs well under various scenarios, consistently meeting user requirements. The satellite mission scheduling algorithm proposed in this study can be flexibly extended to different types of satellite mission demands, achieving optimal resource allocation and enhancing the efficiency and effectiveness of satellite mission execution.

Keywords: mixed-integer programming, meta-heuristics, optimization, resource management, satellite mission scheduling

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Authors: Josué Alfredo Tomas Machaca Fajardo, Jhon Elvis Chahua Janampa, Pedro Rau Lavado

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A flood vulnerability index was developed for the Piura River watershed in northern Peru using Principal Component Analysis (PCA) to assess flood risk. The official methodology to assess risk from natural hazards in Peru was introduced in 1980 and proved effective for aiding complex decision-making. This method relies in part on decision-makers defining subjective correlations between variables to identify high-risk areas. While risk identification and ensuing response activities benefit from a qualitative understanding of influences, this method does not take advantage of the advent of national and international data collection efforts, which can supplement our understanding of risk. Furthermore, this method does not take advantage of broadly applied statistical methods such as PCA, which highlight central indicators of vulnerability. Nowadays, information processing is much faster and allows for more objective decision-making tools, such as PCA. The approach presented here develops a tool to improve the current flood risk assessment in the Peruvian basin. Hence, the spatial analysis of the census and other datasets provides a better understanding of the current land occupation and a basin-wide distribution of services and human populations, a necessary step toward ultimately reducing flood risk in Peru. PCA allows the simplification of a large number of variables into a few factors regarding social, economic, physical and environmental dimensions of vulnerability. There is a correlation between the location of people and the water availability mainly found in rivers. For this reason, a comprehensive vision of the population location around the river basin is necessary to establish flood prevention policies. The grouping of 5x5 km gridded areas allows the spatial analysis of flood risk rather than assessing political divisions of the territory. The index was applied to the Peruvian region of Piura, where several flood events occurred in recent past years, being one of the most affected regions during the ENSO events in Peru. The analysis evidenced inequalities for the access to basic services, such as water, electricity, internet and sewage, between rural and urban areas.

Keywords: assess risk, flood risk, indicators of vulnerability, principal component analysis

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Authors: Manal M. Kame, Zeinab A. Demerdash, Hanan G. El-Baz, Salwa M. Hassan, Faten M. Salah, Wafaa Mansour, Olfat Hammam

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Cord blood (CB) derived Unrestricted Somatic Stem Cells (USSCs) with their multipotentiality hold great promise in liver regeneration. This work aims at evaluation of the therapeutic potentiality of USSCs in two experimental models of chronic liver injury induced either by S. mansoni infection in balb/c mice or CCL4 injection in hamsters. Isolation, propagation, and characterization of USSCs from CB samples were performed. USSCs were induced to differentiate into osteoblasts, adipocytes and hepatocyte-like cells. Cells of the third passage were transplanted in two models of liver fibrosis: (1) Twenty hamsters were induced to liver fibrosis by repeated i. p. injection of 100 μl CCl4 /hamster for 8 weeks. This model was designed as; 10 hamsters with liver fibrosis and treated with i.h. injection of 3x106 USSCs (USSCs transplanted group), 10 hamsters with liver fibrosis (pathological control group), and 10 hamsters with healthy livers (normal control group). (2) Murine chronics S.mansoni model: twenty mice were induced to liver fibrosis with S. mansoni ceracariae (60 cercariae/ mouse) using the tail immersion method and left for 12 weeks. This model was designed as; 10 mice with liver fibrosis were transplanted with i. v. injection of 1×106 USCCs (USSCs transplanted group). Other 2 groups were designed as in hamsters model. Animals were sacrificed 12 weeks after USSCs transplantation, and their liver sections were examined for detection of human hepatocyte-like cells by immunohistochemistry staining. Moreover, liver sections were examined for fibrosis level, and fibrotic indices were calculated. Sera of sacrificed animals were tested for liver functions. CB USSCs, with fibroblast-like morphology, expressed high levels of CD44, CD90, CD73 and CD105 and were negative for CD34, CD45, and HLA-DR. USSCs showed high expression of transcripts for Oct4 and Sox2 and were in vitro differentiated into osteoblasts, adipocytes. In both animal models, in vitro induced hepatocyte-like cells were confirmed by cytoplasmic expression of glycogen, alpha-fetoprotein, and cytokeratin18. Livers of USSCs transplanted group showed engraftment with human hepatocyte-like cells as proved by cytoplasmic expression of human alpha-fetoprotein, cytokeratin18, and OV6. In addition, livers of this group showed less fibrosis than the pathological control group. Liver functions in the form of serum AST & ALT level and serum total bilirubin level were significantly lowered in USSCs transplanted group than pathological control group (p < 0.001). Moreover, the fibrotic index was significantly lower (p< 0.001) in USSCs transplanted group than pathological control group. In addition liver sections, of i. v. injection of 1×106 USCCs of mice, stained with either H&E or sirius red showed diminished granuloma size and a relative decrease in hepatic fibrosis. Our experimental liver fibrosis models transplanted with CB-USSCs showed liver engraftment with human hepatocyte-like cells as well as signs of liver regeneration in the form of improvement in liver function assays and fibrosis level. These data provide hope that human CB- derived USSCs are introduced as multipotent stem cells with great potentiality in regenerative medicine & strengthens the concept of cellular therapy for the treatment of liver fibrosis.

Keywords: cord blood, liver fibrosis, stem cells, transplantation

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Authors: Soheila Sadeghi

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In the dynamic landscape of project management, scope changes are an inevitable reality that can significantly impact project performance. These changes, whether initiated by stakeholders, external factors, or internal project dynamics, can lead to cost overruns and schedule delays. Accurately predicting the consequences of these changes is crucial for effective project control and informed decision-making. This study aims to develop predictive models to estimate the impact of scope changes on project cost and schedule using machine learning techniques. The research utilizes a comprehensive dataset containing detailed information on project tasks, including the Work Breakdown Structure (WBS), task type, productivity rate, estimated cost, actual cost, duration, task dependencies, scope change magnitude, and scope change timing. Multiple machine learning models are developed and evaluated to predict the impact of scope changes on project cost and schedule. These models include Linear Regression, Decision Tree, Ridge Regression, Random Forest, Gradient Boosting, and XGBoost. The dataset is split into training and testing sets, and the models are trained using the preprocessed data. Cross-validation techniques are employed to assess the robustness and generalization ability of the models. The performance of the models is evaluated using metrics such as Mean Squared Error (MSE) and R-squared. Residual plots are generated to assess the goodness of fit and identify any patterns or outliers. Hyperparameter tuning is performed to optimize the XGBoost model and improve its predictive accuracy. The feature importance analysis reveals the relative significance of different project attributes in predicting the impact on cost and schedule. Key factors such as productivity rate, scope change magnitude, task dependencies, estimated cost, actual cost, duration, and specific WBS elements are identified as influential predictors. The study highlights the importance of considering both cost and schedule implications when managing scope changes. The developed predictive models provide project managers with a data-driven tool to proactively assess the potential impact of scope changes on project cost and schedule. By leveraging these insights, project managers can make informed decisions, optimize resource allocation, and develop effective mitigation strategies. The findings of this research contribute to improved project planning, risk management, and overall project success.

Keywords: cost impact, machine learning, predictive modeling, schedule impact, scope changes

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Authors: Jalil ur Rehman, Ramesh C. Tailor, Muhammad Isa Khan, Jahnzeeb Ashraf, Muhammad Afzal, Geofferry S. Ibbott

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Purpose: The purpose of this analysis was to investigate dose distribution of different techniques (3D-CRT, IMRT and VMAT) of head and neck cancer using 3-dimensional dosimeter called PRESAGETM Dosimeter. Materials and Methods: Computer tomography (CT) scans of radiological physics center (RPC) head and neck anthropomorphic phantom with both RPC standard insert and PRESAGETM insert were acquired separated with Philipp’s CT scanner and both CT scans were exported via DICOM to the Pinnacle version 9.4 treatment planning system (TPS). Each plan was delivered twice to the RPC phantom first containing the RPC standard insert having TLD and film dosimeters and then again containing the Presage insert having 3-D dosimeter (PRESAGETM) by using a Varian True Beam linear accelerator. After irradiation, the standard insert including point dose measurements (TLD) and planar Gafchromic® EBT film measurement were read using RPC standard procedure. The 3D dose distribution from PRESAGETM was read out with the Duke Midsized optical scanner dedicated to RPC (DMOS-RPC). Dose volume histogram (DVH), mean and maximal doses for organs at risk were calculated and compared among each head and neck technique. The prescription dose was same for all head and neck radiotherapy techniques which was 6.60 Gy/friction. Beam profile comparison and gamma analysis were used to quantify agreements among film measurement, PRESAGETM measurement and calculated dose distribution. Quality assurances of all plans were performed by using ArcCHECK method. Results: VMAT delivered the lowest mean and maximum doses to organ at risk (spinal cord, parotid) than IMRT and 3DCRT. Such dose distribution was verified by absolute dose distribution using thermoluminescent dosimeter (TLD) system. The central axial, sagittal and coronal planes were evaluated using 2D gamma map criteria(± 5%/3 mm) and results were 99.82% (axial), 99.78% (sagital), 98.38% (coronal) for VMAT plan and found the agreement between PRESAGE and pinnacle was better than IMRT and 3D-CRT plan excludes a 7 mm rim at the edge of the dosimeter. Profile showed good agreement for all plans between film, PRESAGE and pinnacle and 3D gamma was performed for PTV and OARs, VMAT and 3DCRT endow with better agreement than IMRT. Conclusion: VMAT delivered lowered mean and maximal doses to organs at risk and better PTV coverage during head and neck radiotherapy. TLD, EBT film and PRESAGETM dosimeters suggest that VMAT was better for the treatment of head and neck cancer than IMRT and 3D-CRT.

Keywords: RPC, 3DCRT, IMRT, VMAT, EBT2 film, TLD, PRESAGETM

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Authors: Shubham Gogri, Lucia Florescu

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Medical diagnosis and radiotherapy treatment planning using Computed Tomography (CT) rely on the quantitative accuracy and quality of the CT images. At the same time, requirements for CT imaging include reducing the radiation dose exposure to patients and minimizing scanning time. A solution to this is the sparse-view CT technique, based on a reduced number of projection views. This, however, introduces a new problem— the incomplete projection data results in lower quality of the reconstructed images. To tackle this issue, deep learning methods have been applied to enhance the quality of the sparse-view CT images. A first approach involved employing Mir-Net, a dedicated deep neural network designed for image enhancement. This showed promise, utilizing an intricate architecture comprising encoder and decoder networks, along with the incorporation of the Charbonnier Loss. However, this approach was computationally demanding. Subsequently, a specialized Generative Adversarial Network (GAN) architecture, rooted in the Pix2Pix framework, was implemented. This GAN framework involves a U-Net-based Generator and a Discriminator based on Convolutional Neural Networks. To bolster the GAN's performance, both Charbonnier and Wasserstein loss functions were introduced, collectively focusing on capturing minute details while ensuring training stability. The integration of the perceptual loss, calculated based on feature vectors extracted from the VGG16 network pretrained on the ImageNet dataset, further enhanced the network's ability to synthesize relevant images. A series of comprehensive experiments with clinical CT data were conducted, exploring various GAN loss functions, including Wasserstein, Charbonnier, and perceptual loss. The outcomes demonstrated significant image quality improvements, confirmed through pertinent metrics such as Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) between the corrected images and the ground truth. Furthermore, learning curves and qualitative comparisons added evidence of the enhanced image quality and the network's increased stability, while preserving pixel value intensity. The experiments underscored the potential of deep learning frameworks in enhancing the visual interpretation of CT scans, achieving outcomes with SSIM values close to one and PSNR values reaching up to 76.

Keywords: generative adversarial networks, sparse view computed tomography, CT image correction, Mir-Net

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Authors: Gómez R. Marta, Martín M. Jesús María

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The general aim of this paper identifies the areas of highest concentration of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) around the incinerator through the use of dispersion models. Atmospheric dispersion models are useful tools for estimating and prevent the impact of emissions from a particular source in air quality. These models allow considering different factors that influence in air pollution: source characteristics, the topography of the receiving environment and weather conditions to predict the pollutants concentration. The PCDD/Fs, after its emission into the atmosphere, are deposited on water or land, near or far from emission source depending on the size of the associated particles and climatology. In this way, they are transferred and mobilized through environmental compartments. The modelling of PCDD/Fs was carried out with following tools: Atmospheric Dispersion Model Software (ADMS) and Surfer. ADMS is a dispersion model Gaussian plume, used to model the impact of air quality industrial facilities. And Surfer is a program of surfaces which is used to represent the dispersion of pollutants on a map. For the modelling of emissions, ADMS software requires the following input parameters: characterization of emission sources (source type, height, diameter, the temperature of the release, flow rate, etc.) meteorological and topographical data (coordinate system), mainly. The study area was set at 5 Km around the incinerator and the first population center nearest to focus PCDD/Fs emission is about 2.5 Km, approximately. Data were collected during one year (2013) both PCDD/Fs emissions of the incinerator as meteorology in the study area. The study has been carried out during period's average that legislation establishes, that is to say, the output parameters are taking into account the current legislation. Once all data required by software ADMS, described previously, are entered, and in order to make the representation of the spatial distribution of PCDD/Fs concentration and the areas affecting them, the modelling was proceeded. In general, the dispersion plume is in the direction of the predominant winds (Southwest and Northeast). Total levels of PCDD/Fs usually found in air samples, are from <2 pg/m3 for remote rural areas, from 2-15 pg/m3 in urban areas and from 15-200 pg/m3 for areas near to important sources, as can be an incinerator. The results of dispersion maps show that maximum concentrations are the order of 10-8 ng/m3, well below the values considered for areas close to an incinerator, as in this case.

Keywords: atmospheric dispersion, dioxin, furan, incinerator

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Authors: Marius Sebastian Secula, Mihaela Darie, Gabriela Carja

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Persistent organic pollutant discharged by various industries or urban regions into the aquatic ecosystems represent a serious threat to fauna and human health. The endocrine disrupting compounds are known to have toxic effects even at very low values of concentration. The anti-inflammatory agent Ibuprofen is an endocrine disrupting compound and is considered as model pollutant in the present study. The use of light energy to accomplish the latest requirements concerning wastewater discharge demands highly-performant and robust photo-catalysts. Many efforts have been paid to obtain efficient photo-responsive materials. Among the promising photo-catalysts, layered double hydroxides (LDHs) attracted significant consideration especially due to their composition flexibility, high surface area and tailored redox features. This work presents Fe(II) self-supported on ZnMeLDHs (Me =Al3+, Fe3+) as novel efficient photo-catalysts for Fenton-like catalysis. The co-precipitation method was used to prepare ZnAlLDH, ZnFeAlLDH and ZnCrLDH (Zn2+/Me3+ = 2 molar ratio). Fe(II) was self-supported on the LDHs matrices by using the reconstruction method, at two different values of weight concentration. X-ray diffraction (XRD), thermogravimetric analysis (TG/DTG), Fourier transform infrared (FTIR) and transmission electron microscopy (TEM) were used to investigate the structural, textural, and micromorphology of the catalysts. The Fe(II)/ZnMeLDHs nano-hybrids were tested for the degradation of a model pharmaceutical agent, the anti-inflammatory agent ibuprofen, by photocatalysis and photo-Fenton catalysis, respectively. The results point out that the embedment Fe(II) into ZnFeAlLDH and ZnCrLDH lead to a slight enhancement of ibuprofen degradation by light irradiation, whereas in case of ZnAlLDH, the degradation process is relatively low. A remarkable enhancement of ibuprofen degradation was found in the case of Fe(II)/ZnMeLDHs by photo-Fenton process. Acknowledgements: This work was supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CNCS - UEFISCDI, project number PN-II-RU-TE-2014-4-0405.

Keywords: layered double hydroxide, heterogeneous Fenton, micropollutant, photocatalysis

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

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

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

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Authors: Xukai Fu

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The concept of circular economy is interdisciplinary, intersecting environmental engineering, information technology, business, and social science domains. Over the course of its 15-year tenure in the sanitation industry, Jinkai has concentrated its efforts in the past five years on integrating artificial intelligence (AI) technology with street sanitation apparatus and systems. This endeavor has led to the development of various innovations, including the Intelligent Identification Sweeper Truck (Intelligent Waste Recognition and Energy-saving Control System), the Intelligent Identification Water Truck (Intelligent Flushing Control System), the intelligent food waste treatment machine, and the Intelligent City Road Sanitation Surveillance Platform. This study will commence with an examination of prevalent global challenges, elucidating how Jinkai effectively addresses each within the framework of circular economy principles. Utilizing a review and analysis of pertinent environmental management data, we will elucidate Jinkai's strategic approach. Following this, we will investigate how Jinkai utilizes the advantages of circular economy principles to guide the design of street sanitation machinery, with a focus on digitalization integration. Moreover, we will scrutinize Jinkai's sustainable practices throughout the invention and operation phases of street sanitation machinery, aligning with the triple bottom line theory. Finally, we will delve into the significance and enduring impact of corporate social responsibility (CSR) and environmental, social, and governance (ESG) initiatives. Special emphasis will be placed on Jinkai's contributions to community stakeholders, with a particular emphasis on human rights. Despite the widespread adoption of circular economy principles across various industries, achieving a harmonious equilibrium between environmental justice and social justice remains a formidable task. Jinkai acknowledges that the mere development of energy-saving technologies is insufficient for authentic circular economy implementation; rather, they serve as instrumental tools. To earnestly promote and embody circular economy principles, companies must consistently prioritize the UN Sustainable Development Goals and adapt their technologies to address the evolving exigencies of our world.

Keywords: circular economy, core principles, benefits, the tripple bottom line, CSR, ESG, social justice, human rights, Jinkai

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Authors: Mwenya Mubanga, Sula Mazimba

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Background: In Zambia, much of the focus on nutrition and health has been on reducing micronutrient deficiencies, wasting and underweight malnutrition and not on the rising global projections of trends in obesity and type 2 diabetes. The aim of this review was to identify and collate studies on the prevalence of obesity, diabetes and diabetes-related cardiovascular disease conducted in Zambia, to summarize their findings and to identify areas that need further research. Methods: The Medical Literature Analysis and Retrieval System (MEDLINE) database was searched for peer-reviewed articles on the prevalence of, and factors associated with obesity, type 2 diabetes, and diabetes-related cardiovascular disease amongst Zambian residents using a combination of search terms. The period of search was from 1 January 2000 to 31 December 2016. We expanded the search terms to include all possible synonyms and spellings obtained in the search strategy. Additionally, we performed a manual search for other articles and references of peer-reviewed articles. Results: In Zambia, the current prevalence of Obesity and Type 2 diabetes is estimated at 13%-16% and 2.0 – 3.0% respectively. Risk factors such as the adoption of western dietary habits, the social stigmatization associated with rapid weight loss due to Tuberculosis and/ or the human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) and rapid urbanization have all been blamed for fueling the increased risk of obesity and type 2 diabetes. However, unlike traditional Western populations, those with no formal education were less likely to be obese than those who attained secondary or tertiary level education. Approximately 30% of those surveyed were unaware of their diabetes diagnosis and more than 60% were not on treatment despite a known diabetic status. Socio-demographic factors such as older age, female sex, urban dwelling, lack of tobacco use and marital status were associated with an increased risk of obesity, impaired glucose tolerance and type 2 diabetes. We were unable to identify studies that specifically looked at diabetes-related cardiovascular disease. Conclusion: Although the prevalence of Obesity and Type 2 diabetes in Zambia appears low, more representative studies focusing on parts of the country outside of the main industrial zone need to be conducted. There also needs to be research on diabetes-related cardiovascular disease. National surveillance, monitoring and evaluation on all non-communicable diseases need to be prioritized and policies that address underweight, obesity and type 2 diabetes developed.

Keywords: type 2 diabetes, Zambia, obesity, cardiovascular disease

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Authors: Shangjun Zou, Zhiyuan Wang, Songhui You

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Introduction In recent years, the Chinese government has issued several policies to promote the institutional reform and innovation of the development of campus football, but many problems have been exposed in the process of policy implementation. Therefore, this paper attempts to conduct an empirical analysis of the campus football policy texts to reveal the dynamic development of the microsystem in the process of policy evolution. Methods The selected policy contents are coded by constructing a two-dimensional analysis framework of campus football policy tool-policy objective. Specifically, the X dimension consists of three oriented policy tools: environment, supply and demand, while the Y dimension is divided into six aspects of policy objectives, including institution, competition, player teaching, coach training, resource guarantee and popularization. And the distribution differences of textual analysis units on X and Y dimensions are tested by using SPSS22.0 so as to evaluate the characteristics and development trend of campus football policy on respective subjects. Results 1) In the policy evolution process of campus football stepping into the 2.0 Era, there were no significant differences in the frequency distribution of policy tools(p=0.582) and policy objectives(p=0.603). The collaborative governance of multiple participants has become the primary trend, and the guiding role of Chinese Football Association has gradually become prominent. 2) There were significant differences in the distribution of policy tools before the evolution at a 95% confidence level(p=0.041). With environmental tools always maintaining the dominant position, the overall synergy of policy tools increased slightly. 3) There were significant differences in the distribution of policy objectives after the evolution at a 90% confidence level(p=0.069). The competition system of policy objective has not received enough attention while the construction of institution and resource guarantee system has been strengthened. Conclusion The upgraded version of campus football should adhere to the education concept of health first, promote the coordinated development of youth cultural learning and football skills, and strive to achieve more solid popularization, more scientific institution, more comprehensive resource guarantee and adequate integration. At the same time, it is necessary to strengthen the collaborative allocation of policy tools and reasonable planning of policy objectives so as to promote the high quality and sustainable development of campus football in the New Era. Endnote The policy texts selected in this paper are “Implementation Opinions on Accelerating the Development of Youth Campus Football” and “Action Plans for the Construction of Eight Systems of National Youth Campus Football”, which were promulgated on August 13, 2015 and September 25, 2020 respectively.

Keywords: campus football, content analysis, evolution characteristics, policy objective, policy tool

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Authors: Ila Gupta

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The government hospitals in India by and large lack the necessary aesthetic therapeutic components, both in their interior and exterior space designs. These components especially in terms of color application are important to the emotional as well as physical well being of the patients and other participants of the space. The preliminary survey of few government hospitals in Uttarakhand, India, reveals that the government health care industry provides a wide scope for intervention. All most all of the spaces do not adhere to a proper therapeutic color scheme which directly helps the well-being of their patients and workers. The paper aims to conduct a survey and come up with recommendations in this regard. The government hospitals also lack a proper signage system which allows the space to be more user-friendly. The hospital spaces in totality also have scope for improvement in terms of space/landscape design which enhances the work environment in an efficient and positive way. This study will thus enable to come up with feasible recommendations for healthcare and built environment as well as retrofitting the existing spaces. The objective of the paper is mainly on few case studies. The present ambience in many government hospitals generally lacks a welcoming ambience. It is proposed to select one or two government hospitals and demonstrate application of appropriate and self-sustainable color schemes, placement of artifacts, changes in outdoor and indoor space design to bring about a change that is conducive for cognitive healing. Exterior changes to existing and old hospital buildings in depressed historic areas signify financial investment and change, and have the potential to play a significant role in both urban preservation and revitalization. Changes to exterior architectural colors are perhaps the most visible signifier of such revitalization, as the use of color changes as a tool in façade and interior improvement programs. The present project will provide its recommendations on the basis of case studies done in the Indian Public Health Care system. Furthermore, the recommendations will be in accordance with the extended study conducted in Indian Ayurvedic, Yogic texts as well as Vastu texts, which provides knowledge about built environments and healing properties of color.

Keywords: color, environment, facade, architectural color history, interior improvement programs, community development, district/government hospitals

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Authors: Daisy Dutta, Chhanda Chakraborti

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Background and significance of the study: Menstrual Hygiene Management (MHM) is poor in many Lower and Middle-Income Countries (LMIC) such as India. Poor and inadequate menstrual hygiene has an adverse effect on the health and social life of adolescent girls and women. There are many well-known barriers to adequate Menstrual Hygiene Management (MHM); e.g., lack of awareness, lack of WASH (Water, Sanitation and Hygiene) facilities, lack of affordable menstrual absorbents, etc. But, there is a unique barrier which is very much avoidable; i.e., lack of proper guidance and counseling about menstruation. Menstruation is associated with various social and cultural restrictions and taboos and being a taboo topic; often there is no discussion in the society on this topic. Thus, many adolescent girls encounter the menarche with a lot of unnecessary and avoidable trauma, stress and awkwardness. This trauma, stress, and anxiety are even more prevalent among adolescent girls residing in rural areas. This study argues that this unnecessary stress and anxiety of the adolescent girls can be alleviated by reinforcing social support and adequate information and guidance about MHM and eliminating the futile socio-cultural restrictions during menstruation. Methodology: A qualitative study was conducted in a North-eastern State of India where 45 adolescent girls were interviewed both from rural and urban areas. The adolescent girls were asked about their experiences of stress and anxiety on their first menstruation, their preparedness for menarche, their source of information and guidance, their hygiene-practices, and the various restrictions they follow. Findings: Maximum number of girls did not receive any information about menstruation before menarche. Most of them reported that they were terrified about their first menstruation as they were unprepared. Among those who were aware before menarche, reported that they did not receive proper guidance to manage their menstruation in a hygienic manner. Hygiene-related practices are also influenced by their knowledge about MHM. In maximum cases, girls are bound to follow certain cultural and religious restrictions even if they don’t want to follow which created additional stress in managing their menstruation with dignity. Conclusion: Lack of proper guidance and counseling about menstruation and MHM along with an array of socio-cultural restrictions can enhance a negative attitude in adolescent girls towards menstruation due to which they have to go through an extra and unnecessary burden of stress and trauma. This stress and trauma is preventable by improving the provisions of proper guidance and counseling about menstruation in a supportive environment.

Keywords: adolescent girls, menstrual hygiene management, socio-cultural restrictions, stress, trauma

Procedia PDF Downloads 174

Authors: M. M. Wickramasinghe

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Cholesterol and triglycerides are lipids, mainly essential to maintain the cellular structure of the human body. Cholesterol is also important for hormone production, vitamin D production, proper digestion functions, and strengthening the immune system. Excess fats in the blood circulation, known as hyperlipidemia, become harmful leading to arterial clogging and causing atherosclerosis. Aim of this research is to develop a treatment protocol to efficiently break down and maintain circulatory lipids by improving blood circulation without strenuous physical exercises while immersed in a tub of water. To achieve the target of strong exercise effect, this method involves generating powerful ozone bubbles to spin, collide, and burst in the water. Powerful emission of air into water is capable of transferring locked energy of the water molecules and releasing energy. This method involves water and air-based impact generated by pumping ozone at the speed of 46 lts/sec with a concentration of 0.03-0.05 ppt according to safety standards of The Federal Institute for Drugs and Medical Devices, BfArM, Germany. The direct impact of ozone bubbles on the muscular system and skin becomes the main target and is capable of increasing the heart rate while immersed in water. A total time duration of 20 minutes is adequate to exert a strong exercise effect, improve blood circulation, and stimulate the nervous and endocrine systems. Unstable ozone breakdown into oxygen release onto the surface of the water giving additional benefits and supplying high-quality air rich in oxygen required to maintain efficient metabolic functions. The breathing technique was introduced to improve the efficiency of lung functions and benefit the air exchange mechanism. The temperature of the water is maintained at 39c to 40c to support arterial dilation and enzyme functions and efficiently improve blood circulation to the vital organs. The buoyancy of water and natural hydrostatic pressure release the tension of the body weight and relax the mind and body. Sufficient hydration (3lts of water per day) is an essential requirement to transport nutrients and remove waste byproducts to process through the liver, kidney, and skin. Proper nutritional intake is an added advantage to optimize the efficiency of this method which aids in a fast recovery process. Within 20-30 days of daily treatment, triglycerides, low-density lipoproteins (LDL), and total cholesterol reduction were observed in patients with abnormal levels of lipid profile. Borderline patients were cleared within 10–15 days of treatment. This is a highly efficient system that provides many benefits and is able to achieve a successful reduction of triglycerides, LDL, and total cholesterol within a short period of time. Supported by proper hydration and nutritional balance, this system of natural treatment maintains healthy levels of lipids in the blood and avoids the risk of cerebral stroke, high blood pressure, and heart attacks.

Keywords: atherosclerosis, cholesterol, hydrotherapy, hyperlipidemia, lipid management, ozone therapy, triglycerides

Procedia PDF Downloads 88

Authors: Sven Tackenberg, Sönke Duckwitz, Andreas Petz, Christopher M. Schlick

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This paper introduces an extension to the well-established Resource-Constrained Project Scheduling Problem (RCPSP) to apply it to complex maintenance problems. The problem is to assign technicians to a team which has to process several tasks with multi-level skill requirements during a work shift. Here, several alternative activities for a task allow both, the temporal shift of activities or the reallocation of technicians and tools. As a result, switches from one valid work process variant to another can be considered and may be selected by the developed evolutionary algorithm based on the present skill level of technicians or the available tools. An additional complication of the observed scheduling problem is that the locations of the construction sites are only temporarily accessible during a day. Due to intensive rail traffic, the available time slots for maintenance and repair works are extremely short and are often distributed throughout the day. To identify efficient working periods, a first concept of a Bayesian network is introduced and is integrated into the extended RCPSP with pre-emptive and non-pre-emptive tasks. Thereby, the Bayesian network is used to calculate the probability of a maintenance task to be processed during a specific period of the shift. Focusing on the domain of maintenance of the railway infrastructure in metropolitan areas as the most unproductive implementation process at construction site, the paper illustrates how the extended RCPSP can be applied for maintenance planning support. A multi-criteria evolutionary algorithm with a problem representation is introduced which is capable of revising technician-task allocations, whereas the duration of the task may be stochastic. The approach uses a novel activity list representation to ensure easily describable and modifiable elements which can be converted into detailed shift schedules. Thereby, the main objective is to develop a shift plan which maximizes the utilization of each technician due to a minimization of the waiting times caused by rail traffic. The results of the already implemented core algorithm illustrate a fast convergence towards an optimal team composition for a shift, an efficient sequence of tasks and a high probability of the subsequent implementation due to the stochastic durations of the tasks. In the paper, the algorithm for the extended RCPSP is analyzed in experimental evaluation using real-world example problems with various size, resource complexity, tightness and so forth.

Keywords: maintenance management, scheduling, resource constrained project scheduling problem, genetic algorithms

Procedia PDF Downloads 230

Authors: Kulwinder Singh

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Punjab is one of the major labour exporting states of India. Every year more than 20,000 youths from Punjab attempt irregular migration. About 84 irregular migrants are from rural areas and 16 per cent from urban areas. Irregular migration could only be achieved if be organized through highly efficient international networks with the countries of origin, transit, and destination. A good number of Punjabis continue to immigrate into the UK for work through unauthorized means entering the country on visit visas and overstaying or getting ‘smuggled into’ the country with the help of transnational networks of agents. Although, the efforts are being made by the government to curb irregular migration through The Punjab Prevention of Human Smuggling Rules (2012, 2014) and Punjab Travel Regulation Act (2012), but yet it exists parallel to regular migration. Despite unprecedented miseries of irregular migrants and strict laws implemented by the state government to check this phenomenon, ‘why do Punjabis migrate abroad irregularly’ is the important question to answer. This study addresses this question through the comparison of irregular migration with regular one. In other words, this analysis reveals major causes, specifically economic ones, of irregular migration from rural Punjab. This study is unique by presenting economics of irregular migration, given previous studies emphasize the role of sociological and psychological factors. Addressing important question “why do Punjabis migrate abroad irregularly?”, the present study reveals that Punjabi, being far-sighted, endeavor irregular migration as it is, though, economically nonviable in short run, but offers lucrative economic gains as gets older. Despite its considerably higher cost viz-a-viz regular migration, it is the better employment option to irregular migrants with higher permanent income than local low paid jobs for which risking life has become the mindset of the rural Punjabis. Although, it carries considerably lower economic benefits as compared to regular migration, but provides the opportunity of migrating abroad to less educated, semi-skilled and language-test ineligible Punjabis who cannot migrate through regular channels. As its positive impacts on source and destination countries are evident, it might not be restricted, rather its effective management, through liberalising restrictive migration policies by destination nations, can protect the interests of all involved stakeholders.

Keywords: cost, migration, income, irregular, regular, remittances

Procedia PDF Downloads 119

Authors: Alisha M. Ebrahim, Bijoy K. Menon, Eddy Lang, Shelagh B. Coutts, Katie Lin

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Introduction: Frontline emergency physicians require clear and evidence-based approaches to guide neuroimaging investigations for patients presenting with suspected acute stroke or transient ischemic attack (TIA). Various forms of computed tomography (CT) are currently available for initial investigation, including non-contrast CT (NCCT), CT angiography head and neck (CTA), and CT perfusion (CTP). However, there is uncertainty around optimal imaging choice for cost-effectiveness, particularly for minor or resolved neurological symptoms. In addition to the cost of CTA and CTP testing, there is also a concern for increased incidental findings, which may contribute to the burden of overdiagnosis. Methods: In this cross-sectional observational study, analysis was conducted on 586 anonymized triage and diagnostic imaging (DI) reports for neuroimaging orders completed on patients presenting to adult emergency departments (EDs) with a suspected stroke or TIA from January-December 2019. The primary outcome of interest is the diagnostic yield of NCCT+CTA compared to NCCT alone for patients presenting to urban academic EDs with Canadian Emergency Department Information System (CEDIS) complaints of “symptoms of stroke” (specifically acute stroke and TIA indications). DI reports were coded into 4 pre-specified categories (endorsed by a panel of stroke experts): no abnormalities, clinically significant findings (requiring immediate or follow-up clinical action), incidental findings (not meeting prespecified criteria for clinical significance), and both significant and incidental findings. Standard descriptive statistics were performed. A two-sided p-value <0.05 was considered significant. Results: 75% of patients received NCCT+CTA imaging, 21% received NCCT alone, and 4% received NCCT+CTA+CTP. The diagnostic yield of NCCT+CTA imaging for prespecified clinically significant findings was 24%, compared to only 9% in those who received NCCT alone. The proportion of incidental findings was 30% in the NCCT only group and 32% in the NCCT+CTA group. CTP did not significantly increase the yield of significant or incidental findings. Conclusion: In this cohort of patients presenting with suspected stroke or TIA, an NCCT+CTA neuroimaging strategy had a higher diagnostic yield for clinically significant findings than NCCT alone without significantly increasing the number of incidental findings identified.

Keywords: stroke, diagnostic yield, neuroimaging, emergency department, CT

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Authors: Anila Naz, Arusa Lakhani, Kiran Mubeen, Yasmeen Amarsi

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Pakistan's neonatal mortality rate has the highest proportion in the South Asian region and it is higher in the rural areas as compared to the urban areas. Poor resuscitation techniques and lack of basic newborn resuscitation skills in birth attendants, are contributing factors towards neonatal deaths. Based on the significant outcomes of the Helping Baby Breath (HBB) training, a similar training was implemented for Community Midwives (CMWs) in a low resource setting in Gujrat, Pakistan, to improve their knowledge and skills. The training evaluation was conducted and participant feedback was obtained through both qualitative and quantitative methods. The findings of the quantitative assessment of the training evaluation will be published elsewhere. This paper presents the qualitative evaluation of the training. Objective: The objective of the study was to determine the perceptions of HBB trained CMWs about the effectiveness of the HBB training, and the challenges faced in the implementation of HBB skills for newborn resuscitation, at their work settings. The qualitative descriptive design was used in this study. The purposive sampling technique was chosen to recruit midwives and key informants as participants of the training. Interviews were conducted by using a semi-structured interview guide. The study included a total of five interviews: two focus group interviews for CMWs (10 in each group), and three individual interviews of key informants. The content analysis of the qualitative data yielded three themes: the effectiveness of training, challenges, and suggestions. The findings revealed that the HBB training was effective for the CMWs in terms of its usability, regarding improvement in newborn resuscitation knowledge and skills. Moreover, it enhanced confidence and satisfaction in CMWs. However, less volume of patients was a challenge for a few CMWs with regards to practicing their skills. Due to the inadequate number of patients and less opportunities of practice for several CMWs, they required such trainings frequently, in order to maintain their competency. The CMWs also recommended that HBB training should be part of the Midwifery program curriculum. Moreover, similar trainings were also recommended for other healthcare providers working in low resource settings, including doctors and nurses.

Keywords: neonatal resuscitation technique, helping baby breathe, community midwives, training evaluation

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Authors: Bedilu Tafesse

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Home gardens are important social and cultural spaces where knowledge related to agricultural practice is transmitted and through which households may improve their income and livelihood. High levels of inter- and intra-specific plant genetic diversity are preserved in home gardens. Plant diversity is threatened by rapid and unplanned urbanization, which increases environmental problems such as heating, pollution, loss of habitats and ecosystem disruption. Tropical home gardens have played a significant role in conserving plant diversity while providing substantial benefits to households. This research aimed to understand the relationship between household characteristics and plant diversity in western Ethiopia home gardens and the contributions of plants to the household economy. Plant diversity and different uses of plants were studied in a random sample of 111 suburban home gardens in the Ilu Ababora, Jima and Wellega suburban area, western Ethiopia, based on complete garden inventories followed by household surveys on socio-economic status during 2012. A total of 261 species of plants were observed, of which 41% were ornamental plants, 36% food plants, and 22% medicinal plants. Of these 16% were sold commercially to produce income. Avocado, bananas, and other fruits produced in excess. Home gardens contributed the equivalent of 7% of total annual household income in terms of food and commercial sales. Multiple regression analysis showed that education, time spent in gardening, land for cultivation, household expenses, primary conservation practices, and uses of special techniques explained 56% of the total plant diversity. Food, medicinal and commercial plant species had significant positive relationships with time spent gardening and land area for gardening. Education and conservation practices significantly affected food and medicinal plant diversity. Special techniques used in gardening showed significant positive relations with ornamental and commercial plants. Reassessments in different suburban and urban home gardens and proper documentation using same methodology is essential to build a firm policy for enhancing plant diversity and related values to households and surroundings.

Keywords: plant genetic diversity, urbanization, suburban home gardens, Ethiopia

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Authors: Deepanwita Deka, Dhruva Kumar Jha

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Endophytes are the microbes that colonize living, internal tissues of plants without causing any immediate, overt negative effects. Endophytes are rich source of therapeutic substances like antimicrobial, anticancerous, herbicidal, insecticidal, immunomodulatory compounds. Brucea mollis, commonly known as Quinine in Assam, belonging to the family Simaroubaceae, is a shrub or small tree, recorded as endangered species in North East India by CAMP survey in 2003. It is traditionally being used as antimalarial and antimicrobial agent and has antiplasmodial, cytotoxic, anticancer, diuretic, cardiovascular effect etc. Being endangered and medicinal; this plant may host certain noble endophytes which need to be studied in depth. The aim of the present study was isolation and identification of potent endophytic fungi from Brucea mollis, an endangered medicinal plant, to protect it from extinction due to over use for medicinal purposes. Aseptically collected leaves, barks and roots samples of healthy plants were washed and cut into a total of 648 segments of about 2 cm long and 0.5 cm broad with sterile knife, comprising 216 segments each from leaves, barks and roots. These segments were surface sterilized using ethanol, mercuric chloride (HgCl2) and aqueous solution of sodium hypochlorite (NaClO). Different media viz., Czapeck-Dox-Agar (CDA, Himedia), Potato-Dextrose-Agar (PDA, Himedia), Malt Extract Agar (MEA, Himedia), Sabourad Dextrose Agar (SDA, Himedia), V8 juice agar, nutrient agar and water agar media and media amended with plant extracts were used separately for the isolation of the endophytic fungi. A total of 11 fungal species were recovered from leaf, bark and root tissues of B. mollis. The isolates were screened for antimicrobial, antioxidant and enzymatic activities using certain protocols. Cochliobolus geniculatus was identified as the most dominant species. The mycelia sterilia (creamy white) showing highest inhibitory activity against Candida albicans (MTCC 183) was induced to sporulate using modified PDA media. The isolate was identified as Geosmithia pallida. The internal transcribed spacer of rDNA was sequenced for confirmation of the taxonomic identity of the sterile mycelia (creamy white). The internal transcribed spacer r-DNA sequence was submitted to the NCBI (KU693285) for the first time from India. G. pallida and Penicillium showed highest antioxidant activity among all the isolates. The antioxidant activity of G. pallida and Penicillium didn’t show statistically significant difference (P˃0.05). G. pallida, Cochliobolus geniculatus and P. purpurogenum respectively showed highest cellulase, amylase and protease activities. Thus, endopytic fungal isolates may be used as potential natural resource of pharmaceutical importance. The endophytic fungi, Geosmithia pallida, may be used for synthesis of pharmaceutically important natural products and consequently can replace plants hitherto used for the same purpose. This study suggests that endophytes should be investigated more aggressively to better understand the endophyte biology of B. mollis.

Keywords: Antimicrobial activity, antioxidant activity, Brucea mollis, endophytic fungi, enzyme activity, Geosmithia pallida

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Authors: V. Saccà, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

Abstract:

The work aim was to evaluate how well Random Forest (RF) and Support Vector Machine (SVM) algorithms could support the early diagnosis of Multiple Sclerosis (MS) from resting-state functional connectivity data. In particular, we wanted to explore the ability in distinguishing between controls and patients of mean signals extracted from ICA components corresponding to 15 well-known networks. Eighteen patients with early-MS (mean-age 37.42±8.11, 9 females) were recruited according to McDonald and Polman, and matched for demographic variables with 19 healthy controls (mean-age 37.55±14.76, 10 females). MRI was acquired by a 3T scanner with 8-channel head coil: (a)whole-brain T1-weighted; (b)conventional T2-weighted; (c)resting-state functional MRI (rsFMRI), 200 volumes. Estimated total lesion load (ml) and number of lesions were calculated using LST-toolbox from the corrected T1 and FLAIR. All rsFMRIs were pre-processed using tools from the FMRIB's Software Library as follows: (1) discarding of the first 5 volumes to remove T1 equilibrium effects, (2) skull-stripping of images, (3) motion and slice-time correction, (4) denoising with high-pass temporal filter (128s), (5) spatial smoothing with a Gaussian kernel of FWHM 8mm. No statistical significant differences (t-test, p < 0.05) were found between the two groups in the mean Euclidian distance and the mean Euler angle. WM and CSF signal together with 6 motion parameters were regressed out from the time series. We applied an independent component analysis (ICA) with the GIFT-toolbox using the Infomax approach with number of components=21. Fifteen mean components were visually identified by two experts. The resulting z-score maps were thresholded and binarized to extract the mean signal of the 15 networks for each subject. Statistical and machine learning analysis were then conducted on this dataset composed of 37 rows (subjects) and 15 features (mean signal in the network) with R language. The dataset was randomly splitted into training (75%) and test sets and two different classifiers were trained: RF and RBF-SVM. We used the intrinsic feature selection of RF, based on the Gini index, and recursive feature elimination (rfe) for the SVM, to obtain a rank of the most predictive variables. Thus, we built two new classifiers only on the most important features and we evaluated the accuracies (with and without feature selection) on test-set. The classifiers, trained on all the features, showed very poor accuracies on training (RF:58.62%, SVM:65.52%) and test sets (RF:62.5%, SVM:50%). Interestingly, when feature selection by RF and rfe-SVM were performed, the most important variable was the sensori-motor network I in both cases. Indeed, with only this network, RF and SVM classifiers reached an accuracy of 87.5% on test-set. More interestingly, the only misclassified patient resulted to have the lowest value of lesion volume. We showed that, with two different classification algorithms and feature selection approaches, the best discriminant network between controls and early MS, was the sensori-motor I. Similar importance values were obtained for the sensori-motor II, cerebellum and working memory networks. These findings, in according to the early manifestation of motor/sensorial deficits in MS, could represent an encouraging step toward the translation to the clinical diagnosis and prognosis.

Keywords: feature selection, machine learning, multiple sclerosis, random forest, support vector machine

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Authors: Mmamapudi Kubjane, Natacha Berkowitz, Rene Goliath, Naomi S. Levitt, Robert J. Wilkinson, Tolu Oni

Abstract:

Background: South Africa remains a high tuberculosis (TB) burden country globally and the burden of diabetes – a TB risk factor is growing rapidly. As an infectious disease, TB also induces transient hyperglycaemia. Therefore, screening for diabetes in newly diagnosed tuberculosis patients may result in misclassification of transient hyperglycaemia as diabetes. Objective: The objective of this study was to determine and compare the prevalence of hyperglycaemia (diabetes and impaired glucose regulation (IGR)) in TB patients and to assess the cross-sectional association between TB and hyperglycaemia at enrolment and after three months of follow-up. Methods: Consecutive adult TB and non-TB participants presenting at a TB clinic in Cape Town were enrolled in this cross-sectional study and follow-up between July 2013 and August 2015. Diabetes was defined as self-reported diabetes, fasting plasma glucose (FPG) ≥ 7.0 mmol·L⁻¹ or glycated haemoglobin (HbA1c) ≥ 6.5%. IGR was defined as FPG 5.5– < 7.0 mmol·L⁻¹ or HbA1c 5.7– < 6.5%. TB patients initiated treatment. After three months, all participants were followed up and screened for diabetes again. The association between TB and hyperglycaemia was assessed using logistic regression adjusting for potential confounders including sex, age, income, hypertension, waist circumference, previous prisoner, marital status, work status, HIV status. Results: Diabetes screening was performed in 852 participants (414 TB and 438 non-TB) at enrolment and in 639 (304 TB and 335 non-TB) at three-month follow-up. The prevalence of HIV-1 infection was 69.6% (95% confidence interval (CI), 64.9–73.8 %) among TB patients, and 58.2% (95% CI, 53.5–62.8 %) among the non-TB participants. Glycaemic levels were much higher in TB patients than in the non-TB participants but decreased over time. Among TB patients, the prevalence of IGR was 65.2% (95% CI 60.1 - 69.9) at enrollment and 21.5% (95% CI 17.2-26.5) at follow-up; and was 50% (45.1 - 54.94) and 32% (95% CI 27.9 - 38.0) respectively, among non-TB participants. The prevalence of diabetes in TB patients was 12.5% (95% CI 9.69 – 16.12%) at enrolment and 9.2% (95% CI, 6.43–13.03%) at follow-up; and was 10.04% (95% CI, 7.55–13.24%) and 8.06% (95% CI, 5.58–11.51) respectively, among non-TB participants. The association between TB and IGT was significant at enrolment (adjusted odds ratio (OR) 2.26 (95% CI, 1.55-3.31) but disappeared at follow-up 0.84 (0.53 - 1.36). However, the TB-diabetes association remained positive and significant both at enrolment (2.41 (95% CI, 1.3-4.34)) and follow-up (OR 3.31 (95% CI, 1.5 - 7.25)). Conclusion: Transient hyperglycaemia exists during tuberculosis. This has implications on diabetes screening in TB patients and suggests a need for diabetes confirmation tests during or after TB treatment. Nonetheless, the association between TB and diabetes noted at enrolment persists at 3 months highlighting the importance of diabetes control and prevention for TB control. Further research is required to investigate the impact of hyperglycaemia (transient or otherwise) on TB outcomes to ascertain the clinical significance of hyperglycemia at enrolment.

Keywords: diabetes, impaired glucose regulation, transient hyperglycaemia, tuberculosis

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