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Authors: V. Karthickeyan

Abstract:

The demand for energy is anticipated to increase, due to growing urbanization, industrialization, upgraded living standards and cumulatively increasing human population. The general public is becoming gradually aware of the diminishing fossil fuel resources along with the environmental issues, and it has become clear that biofuel is intended to make significant support to the forthcoming energy needs of the native and industrial sectors. Nowadays, the investigation on biofuels obtained from peels of fruits and vegetables have gained the consideration as an environment-friendly alternative to diesel. In the present work, biofuel was produced from non-edible Lemon Oil (LO) using steam distillation process. LO is characterized by its beneficial aspects like low kinematic viscosity and enhanced calorific value which provides better fuel atomization and evaporation. Furthermore, the heating values of the biofuels are approximately equal to diesel. A single cylinder, four-stroke diesel engine was used for this experimentation. An engine modification technique namely Thermal Barrier Coating (TBC) was attempted. Combustion chamber components were thermally coated with ceramic material namely partially stabilized zirconia (PSZ). The benefit of thermal barrier coating is to diminish the heat loss from engine and transform the collected heat into piston work. Performance characteristics like Brake Thermal Efficiency (BTE) and Brake Specific Fuel Consumption (BSFC) were analyzed. Combustion characteristics like in-cylinder pressure and heat release rate were analyzed. In addition, the following engine emissions namely nitrogen oxide (NO), carbon monoxide (CO), hydrocarbon (HC), and smoke were measured. The acquired performance combustion and emission characteristics of uncoated engine were compared with PSZ coated engine. From the results, it was perceived that the LO biofuel may be considered as the prominent alternative in the near prospect with thermal barrier coating technique to enrich the performance, combustion and emission characteristics of diesel engine.

Keywords: ceramic material, thermal barrier coating, biofuel and diesel engine

Procedia PDF Downloads 154

Authors: Richard Ren

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Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 124

Authors: Vanlounni Sibounheuang, Wanarat Anusornsangiam, Pattarin Kittiboonyakun, Chanthanom Manithip

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In worldwide, one of the most common use of oral anticoagulant is warfarin. Its margin between therapeutic inhibition of clot formation and bleeding complications is narrow. Mahosot Hospital, warfarin clinic had not been established yet. The descriptive study was conducted by investigating drug-related problems of outpatients using warfarin, the value of the international normalized ratio (INR) higher than normal ranges (25.40 % of the total 272 outpatients) were mostly identified at Lao-Luxembourg Heart Centre, Mahosot Hospital, Lao PDR. This result led to the present study conducting qualitative interviews in order to help establish a warfarin clinic at Mahosot Hospital for the better outcomes of patients using warfarin. The purpose of this study was to explore perspectives of healthcare professional providing services for outpatients using warfarin. The face to face, in-depth interviews were undertaken among nine healthcare professionals (doctor=3, nurse=3, pharmacist=3) working at out-patient clinic, Lao-Luxembourg Heart Centre, Mahosot Hospital, Lao PDR. The interview guides were developed, and they were validated by the experts in the fields of qualitative research. Each interview lasted approximately 20 minutes. Three major themes emerged; healthcare professional’s experiences of current practice problems with warfarin therapy, healthcare professionals’ views of medical problems related to patients using warfarin, and healthcare professionals’ perspectives on ways of service improvement. All healthcare professionals had the same views that it’s difficult to achieve INR goal for individual patients because of some important patient barriers especially lack of knowledge about to use warfarin properly and safety, patients not regularly follow-up due to problems with transportations and financial support. Doctors and nurses agreed to have a pharmacist running a routine warfarin clinic and provided counselling to individual patients on the following points: how to take drug properly and safety, drug-drug and food-drug interactions, common side effects and how to manage them, lifestyle modifications. From the interviews, some important components of the establishment of a warfarin clinic included financial support, increased human resources, improved the system of keeping patients’ medical records, short course training for pharmacists. This study indicated the acceptance of healthcare professionals on the important roles of pharmacists and the feasibility of setting up warfarin clinic by working together with the multidisciplinary health care team in order to help improve health outcomes of patients using warfarin at Mahosot Hospital, Lao PDR.

Keywords: perspectives, healthcare professional, warfarin therapy, Mahosot Hospital

Procedia PDF Downloads 100

Authors: Desjardin, Michaels, Martinez, Ulmann

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Copper IUD is one of the most efficient and cost-effective contraception. However, pain at insertion hampers the use of this method. This is especially unfortunate in nulliparous women, often younger, who are excellent candidates for this contraception, including Emergency Contraception. Standard insertion procedure of a copper IUD usually involves measurement of uterine cavity with an hysterometer and the use of a tenaculum in order to facilitate device insertion. Both procedures lead to patient pain which often constitutes a limitation of the method. To overcome these issues, we have developed a modified insertor combined with a copper IUD. The singular design of the inserter includes a flexible inflatable membrane technology allowing an easy access to the uterine cavity even in case of abnormal uterine positions or narrow cervical canal. Moreover, this inserter makes possible a direct IUD insertion with no hysterometry and no need for tenaculum. To assess device effectiveness and patient-reported pain, a study was conducted at two clinics in Fance with 31 individuals who wanted to use a copper IUD as contraceptive method. IUD insertions have been performed by four healthcare providers. Operators completed questionnaire and evaluated effectiveness of the procedure (including IUD correct fundal placement and other usability questions) as their satisfaction. Patient also completed questionnaire and pain during procedure was measured on a 10-cm Visual Analogue Scale (VAS). Analysis of the questionnaires indicates that correct IUD placement took place in more than 93% of women, which is a standard efficacy rate. It also demonstrates that IUD insertion resulted in no, light or moderate pain predominantly in nulliparous women. No insertion resulted in severe pain (none above 6cm on a 10-cm VAS). This translated by a high level of satisfaction from both patients and practitioners. In addition, this modified inserter allowed a simplification of the insertion procedure: correct fundal placement was ensured with no need for hysterometry (100%) prior to insertion nor for cervical tenaculum to pull on the cervix (90%). Avoidance of both procedures contributed to the decrease in pain during insertion. Taken together, the results of the study demonstrate that this device constitutes a significant advance in the use of copper IUDs for any woman. It allows a simplification of the insertion procedure: there is no need for pre-insertion hysterometry and no need for traction on the cervix with tenaculum. Increased comfort during insertion should allow a wider use of the method for nulliparous women and for emergency contraception. In addition, pain is often underestimated by practitioners, but fear of pain is obviously one of the blocking factors as indicated by the analysis of the questionnaire. This evaluation brings interesting information on the use of this modified inserter for standard copper IUD and promising perspectives to set up a changement in the standard of IUD insertion procedure.

Keywords: contraceptio, IUD, innovation, pain

Procedia PDF Downloads 82

Authors: Hsiao-Yung Wang

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This essay aims to examine how the transgender imagery has been constructed in the Taiwanese news media and its evolution from 1953 to 2016. It also explores the discourse patterns and rhetorical strategies in the transgender-related issues which contributed to levels of evaluation in forming ‘social deviance.’ Samples for analysis were selected from mainstream newspapers, including China Times, United Daily and Apple Daily. The time frame for sample selection is from August 1953 (when the first transgender case was reported in Taiwan) to June 2016. To enhance understanding of media representation as nominalistic-based, the author refers to the representative of critical rhetoric Raymie McKerrow for his study on remembrance and forgetfulness in public discourse (especially in his model of ‘critique of domination’); thereby categorizing the 64 years of transgender discourse into five periods: (1) transgender as ‘intersex’ of surgical-reparative medical treatment; (2) transgender as ‘freak gender-bender’ with criminal behaviors; (3) transgender as ‘ladyboy’ (‘katoey in a Thai term) of bar girls or sex workers; (4) transgender as ‘cross dresser’ of transvestite performance; and (5) transgender as ‘life-style or human right’ of spontaneous gender identification. Based on the research findings, this essay argues that the characterization of transgender reporting as a site for the production of compulsory sexism and gender stereotype by the specific forms of name-calling. Besides, the evolution of word-image addressing to transgender issues also pinpoints media as a reflection of fashion of the day. While the transgender imagery might be crystallized as ‘still social problems’ or ‘gender transgression’ in insidious rhetoric; and while the so-called ‘phobia’ persistently embodies in media discourse to exercise name-calling in an ambiguous (rather than in a bullying) way or under the cover of humanist-liberalist rationales, these emergent rhetorical dilemma should be resolved without any delay.

Keywords: critical rhetoric, media representation, McKerrow, nominalistic, social deviance, transgender

Procedia PDF Downloads 312

Authors: Adedayo Racheal Agbonna

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The rising level of graduate unemployment in Nigeria has brought about the introduction of entrepreneurship education as a career option for self–reliance and self-employment. Sequel to this, it is important to have an understanding of the determining factors of entrepreneurial intention. Therefore this research empirically investigated the influence of entrepreneurship education on entrepreneurial intention of undergraduate students of selected universities in Ogun State, Nigeria. The study is significant to researchers, university policy makers, and the government. Survey research design was adopted in the study. The population consisted of 17,659 final year undergraduate students universities in Ogun State. The study adopted stratified and random sampling technique. The table of sample size determination was used to determine the sample size for this study at 95% confidence level and 5% margin error to arrive at a sample size of 1877 respondents. The elements of population were 400 level students of the selected universities. A structured questionnaire titled 'Entrepreneurship Education and students’ Entrepreneurial intention' was administered. The result of the reliability test had the following values 0.716, 0.907 and 0.949 for infrastructure, perceived university support, and entrepreneurial intention respectively. In the same vein, from the construct validity test, the following values were obtained 0.711, 0.663 and 0.759 for infrastructure, perceived university support and entrepreneurial intention respectively. Findings of this study revealed that each of the entrepreneurship education variables significantly affected intention University infrastructure B= -1.200, R²=0.679, F (₁,₁₈₇₅) = 3958.345, P < 0.05) Perceived University Support B= -1.027, R²=0.502, F(₁,₁₈₇₅) = 1924.612, P < 0.05). The perception of respondents in public university and private university on entrepreneurship education have a statistically significant difference [F(₁,₁₈₇₅) = 134.614, p < 0.05) α F(₁,₁₈₇₅) = 363.439]. The study concluded that entrepreneurship education positively influenced entrepreneurial intention of undergraduate students in Ogun State, Nigeria. Also, university infrastructure and perceived university support have negative and significant effect on entrepreneurial intention. The study recommended that to promote entrepreneurial intention of university undergraduate students, infrastructures and the university support that can arouse entrepreneurial intention of students should be put in place.

Keywords: entrepreneurship education, entrepreneurial intention, perceived university support, university infrastructure

Procedia PDF Downloads 232

Authors: Parisa Afshin, Terje Grønning

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Norway, similar to many other countries, has set the focus of its policies in creating new strong and highly innovative sectors in recent years, as the oil and gas sector profitability is declining. Biotechnology sector in Norway has a great potential, especially in marine-biotech and cancer medicine. However, Norway being a periphery faces especial challenges in the path of creating internationally well-known biotech sector and an international knowledge hub. The aim of this article is to analyze the progress of the Norwegian biotechnology industry, its pathway to build up an innovation network and conduct collaborative innovation based on its initial conditions and its own advantage and disadvantages. The findings have important implications not only for politicians and academic in understanding the infrastructure of biotechnology sector in the country, but it has important lessons for other periphery countries or regions aiming in creating strong biotechnology sector and catching up with the strong internationally-recognized regions. Data and methodology: To achieve the main goal of this study, information has been collected via secondary resources such as web pages and annual reports published by the officials and mass media along with interviews were used. The data were collected with the goal to shed light on a brief history and current status of Norway biotechnology sector, as well as geographic distribution of biotech industry, followed by the role of academic and industry collaboration and public policies in Norway biotech. As knowledge is the key input in innovation, knowledge perspective of the system such as knowledge flow in the sector regarding the national and regional innovation system has been studied. Primary results: The internationalization has been an important element in development of periphery regions' innovativeness enabling them to overcome their weakness while putting more weight on the importance of regional policies. Following such findings, suggestions on policy decision and international collaboration, regarding national and regional system of innovation, has been offered as means of promoting strong innovative sector.

Keywords: biotechnology sector, knowledge-based industry, national innovation system, regional innovation system

Procedia PDF Downloads 225

Authors: Andrea Corsale

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The historical and geographical regions of Banat and Crişana in Western Romania have long been characterized by a high degree of ethnic diversity. However, this traditionally complex cultural, linguistic, and religious mosaic has undergone a progressive simplification during the past century due to deportations, emigration, and assimilation, and both regions now have a large Romanian-speaking majority population. This contribution focuses on Jewish heritage in the two largest cities of these two regions, Timişoara (Banat) and Oradea (Crişana). The two cities shared some historical events but also went through different experiences, despite their relative geographic proximity. The Jewish community of Timişoara survived the Holocaust basically intact, an almost unique case in Central-Eastern Europe, but largely left the city after the war. Instead, the Jewish community of Oradea was almost completely deported and killed in Auschwitz, and a renewed post-war community gradually emigrated abroad in the following decades. The two Jewish communities are now very small in size but inherited a vast tangible and intangible heritage (synagogues, cemeteries, community buildings, characteristic architecture, memories, local traditions, and histories), partially restored and recovered in recent years. The author’s fieldwork shows that local Jewish stakeholders are aware of the potential of this heritage in terms of cultural and economic benefits, but significant weaknesses and concerns exist, as the small dimension of these communities, and their financial constraints, challenge their future role in the eventual promotion and management of this heritage, which is now basically in the hands of the non-Jewish public and private stakeholders. Projects, experiences, and views related to Jewish heritage conservation and promotion in these two contexts will be portrayed and analysed in order to contribute to a broader discussion on representations and narratives of minority heritage within cultural tourism development dynamics.

Keywords: Jewish heritage, ethnic minorities, heritage tourism, Romania

Procedia PDF Downloads 109

Authors: Adamu Muhammed Tukur

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Pulp and paper industry is one of the fastest growing industries due to an increased demand in paper products. For it to satisfy this ever increasing demand, it adopts new technological innovations some of which are proved to affect our environment negatively. Global consumption of paper has increased by 400% in the last four decades and this suggests that more research is required to assess the impact of industrial effluents to our environment and public health. Paper products are generally biodegradable, however, the processes involved in its production which involve the use of mainly bleaching agents and other non-biodegradable substances pose serious problem to the environment. There are more than 250 chemicals released in paper mill waste and some are xenobiotics. Different methods such as physical and chemical methods can be adopted for the remediation of the effluents but are proved to be costly and not safe to the environment. On the other hand, biological method is shown to be less costly and environmentally friendly. Microorganisms and their enzymes have shown a promising future for bioremediation of effluents related to paper mill. Many studies prove that one of the major pollutants in the paper mill effluent is phenol especially its chlorinated derivatives. Pentachlorophenol is extremely hazardous to living cells and therefore need to be removed from the environment. Microorganisms including bacteria and fungi have the potential to degrade phenolic compounds e.g. Bacillus stearothermiphilus, Pseudomonas putida, Coricus versicolor, Sphingomonas chlorophenolica, Fusarium sp, Bacillus subtilis and P. aeroginosa. Enzymes used for the degradation include phenol hydrooxylase, polyphenoloxylase, laccase, peroxidase among others. Lignin is another important pollutant and is resistant to microbial degradation but it has been proved that certain bacteria and fungi like can degrade it. Among the fungi white-rot fungi like Fomes lividus and Trametes vesicolor are the most important bioremediators. This review focused on use of microorganism to reduce or eradicate pollutants released from the paper industry. It can serve as a review for further research to be conducted especially in the field of Biotechnology.

Keywords: bioremediation, pulp and paper, pentachlorophenol, environment

Procedia PDF Downloads 325

Authors: Asma Qudrat, Abid Ullah, Rafi Ullah, Ali Raza, Shah Zeb, Syed Ali Shan Ul-Haq, Shahkar Ahmed Shah, Attiya Hameed Khan, Saad Zaheer, Umama Qasim, Kiran Jamal, Zahoor khan

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Objectives: Coronary artery disease (CAD) is the major public health issue associated with high mortality and morbidity rate worldwide. Young patients with ACS have unique characteristics with different demographic profiles and risk factors. The precise diagnosis and early risk stratification is important in guiding treatment and predicting the prognosis of young patients with ACS. To evaluate the associated demographics, risk factors, and outcomes profile of ACS in young age patients. Methods: The research follow a retrospective design, the single centre study of patients diagnosis with the first event of ACS in young age (>18 and <40) were included. Data collection included demographic profiles, risk factors, and in-hospital outcomes of young ACS patients. The patient’s data was retrieved through Electronic Medical Records (EMR) of Peshawar Institute of Cardiology (PIC), and all characteristic were assessed. Results: In this study, 77% were male, and 23% were female patients. The risk factors were assessed with CAD and shown significant results (P < 0.01). The most common presentation was STEMI, with (45%) most in ACS young patients. The angiographic pattern showed single vessel disease (SVD) in 49%, double vessel disease (DVD) in 17% and triple vessel disease (TVD) was found in 10%, and Left Artery Disease (LAD) (54%) was present to be the most common involved artery. Conclusion: It is concluded that the male sex was predominant in ACS young age patients. SVD was the common coronary angiographic finding. Risk factors showed significant results towards CAD and common presentations.

Keywords: coronary artery disease, Non-ST elevation myocardial infarction, ST elevation myocardial infarction, unstable angina, acute coronary syndrome

Procedia PDF Downloads 162

Authors: Shih-Wen Hsiao, Yi-Cheng Tsao

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In the field of reverse engineering and creative industries, applying 3D scanning process to obtain geometric forms of the objects is a mature and common technique. For instance, organic objects such as faces and nonorganic objects such as products could be scanned to acquire the geometric information for further application. However, although the data resolution of 3D scanning device is increasing and there are more and more abundant complementary applications, the penetration rate of 3D scanning for the public is still limited by the relative high price of the devices. On the other hand, Kinect, released by Microsoft, is known for its powerful functions, considerably low price, and complete technology and database support. Therefore, related studies can be done with the applying of Kinect under acceptable cost and data precision. Due to the fact that Kinect utilizes optical mechanism to extracting depth information, limitations are found due to the reason of the straight path of the light. Thus, various angles are required sequentially to obtain the complete 3D information of the object when applying a single Kinect for 3D scanning. The integration process which combines the 3D data from different angles by certain algorithms is also required. This sequential scanning process costs much time and the complex integration process often encounter some technical problems. Therefore, this paper aimed to apply multiple Kinects simultaneously on the field of developing a rapid 3D mannequin scan platform and proposed suggestions on the number and angles of Kinects. In the content, a method of establishing the coordination based on the relation between mannequin and the specifications of Kinect is proposed, and a suggestion of angles and number of Kinects is also described. An experiment of applying multiple Kinect on the scanning of 3D mannequin is constructed by Microsoft API, and the results show that the time required for scanning and technical threshold can be reduced in the industries of fashion and garment design.

Keywords: 3D scan, depth sensor, fashion and garment design, mannequin, multiple Kinect sensor

Procedia PDF Downloads 366

Authors: Dawit Assefa, Kassaye Tekie, Gebrie Alebachew, Degefu Beyene, Bikila Alemu, Naji Mohammed, Asnakech Agegnehu, Seble Tsehay, Geremew Tasew

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Background: Implementation of a Laboratory Quality Management System (LQMS) is critical to ensure accurate, reliable, and efficient laboratory testing of antimicrobial resistance (AMR). However, limited LQMS implementation and progress toward accreditation in the AMR surveillance laboratory testing setting exist in Ethiopia. By addressing non-conformances (NCs) and working towards accreditation, microbiology laboratories can improve the quality of their services, increase staff competence, and contribute to mitigate the spread of AMR. Methods: Using standard ISO 15189 horizontal and vertical assessment checklists, certified assessors identified NCs at Hawassa and Jimma Hospital microbiology laboratories. The Ethiopian Public Health Institute AMR mentors and IDDS staff prioritized closing the NCs through the implementation of an intensified mentorship program that included ISO 15189 orientation training, resource allocation, and action plan development. Results: For the two facilities to clear their NCs, an intensified mentorship approach was adopted by providing ISO 15189 orientation training, provision of buffer reagents, controls, standards, and axillary equipment, and facilitating equipment maintenance and calibration. Method verification and competency assessment were also conducted along with the implementation of standard operating procedures and recommended corrective actions. This approach enhanced the laboratory's readiness for accreditation. After addressing their NCs, the two laboratories applied to Ethiopian Accreditation Services for ISO 15189 accreditation. Conclusions: Clearing NCs through the implementation of intensified mentorship was crucial in preparing the two laboratories for accreditation and improving quality laboratory test results. This approach can guide other microbiology laboratories’ accreditation attainment efforts.

Keywords: non-conformance clearance, intensified mentorship, accreditation, ISO 15189

Procedia PDF Downloads 89

Authors: M. Baratieri, M. Beccali, S. Corradino, B. Di Pietra, C. La Grassa, F. Monteleone, G. Morosinotto, G. Puglisi

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The energy renovation of existing buildings represents an important opportunity to increase the decarbonization and the sustainability of urban environments. In this context, the work carried out has the objective of demonstrating the technical and economic feasibility of an energy renovate of a public building destined for offices located on the island of Lampedusa in the Mediterranean Sea. By applying the Italian transpositions of European Directives 2010/31/EU and 2009/28/EC, the building has been renovated from the current energy requirements of 111.7 kWh/m² to 16.4 kWh/m². The result achieved classifies the building as nZEB (nearly Zero Energy Building) according to the Italian national definition. The analysis was carried out using in parallel a quasi-stationary software, normally used in the professional field, and a dynamic simulation model often used in the academic world. The proposed interventions cover the components of the building’s envelope, the heating-cooling system and the supply of energy from renewable sources. In these latter points, the analysis has focused more on assessing two aspects that affect the supply of renewable energy. The first concerns the use of advanced logic control systems for air conditioning units in order to increase photovoltaic self-consumption. With these adjustments, a considerable increase in photovoltaic self-consumption and a decrease in the electricity exported to the Island's electricity grid have been obtained. The second point concerned the evaluation of the building's energy classification considering the real efficiency of the heating-cooling plant. Normally the energy plants have lower operational efficiency than the designed one due to multiple reasons; the decrease in the energy classification of the building for this factor has been quantified. This study represents an important example for the evaluation of the best interventions for the energy renovation of buildings in the Mediterranean Climate and a good description of the correct methodology to evaluate the resulting improvements.

Keywords: heat pumps, HVAC systems, nZEB renovation, renewable energy sources

Procedia PDF Downloads 451

Authors: Rene Hellmuth

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Factory planning has the task of designing products, plants, processes, organization, areas, and the construction of a factory. The requirements for factory planning and the building of a factory have changed in recent years. Regular restructuring of the factory building is becoming more important in order to maintain the competitiveness of a factory. Restrictions in new areas, shorter life cycles of product and production technology as well as a VUCA world (Volatility, Uncertainty, Complexity & Ambiguity) lead to more frequent restructuring measures within a factory. A building information model (BIM) is the planning basis for rebuilding measures and becomes an indispensable data repository to be able to react quickly to changes. Use as a planning basis for restructuring measures in factories only succeeds if the BIM model has adequate data quality. Under this aspect and the industrial requirement, three data quality factors are particularly important for this paper regarding the BIM model: up-to-dateness, completeness, and correctness. The research question is: how can a BIM model be kept up to date with required data quality and which visualization techniques can be applied in a short period of time on the construction site during conversion measures? An as-is analysis is made of how BIM models and digital factory models (including laser scans) are currently being kept up to date. Industrial companies are interviewed, and expert interviews are conducted. Subsequently, the results are evaluated, and a procedure conceived how cost-effective and timesaving updating processes can be carried out. The availability of low-cost hardware and the simplicity of the process are of importance to enable service personnel from facility mnagement to keep digital factory models (BIM models and laser scans) up to date. The approach includes the detection of changes to the building, the recording of the changing area, and the insertion into the overall digital twin. Finally, an overview of the possibilities for visualizations suitable for construction sites is compiled. An augmented reality application is created based on an updated BIM model of a factory and installed on a tablet. Conversion scenarios with costs and time expenditure are displayed. A user interface is designed in such a way that all relevant conversion information is available at a glance for the respective conversion scenario. A total of three essential research results are achieved: As-is analysis of current update processes for BIM models and laser scans, development of a time-saving and cost-effective update process and the conception and implementation of an augmented reality solution for BIM models suitable for construction sites.

Keywords: building information modeling, digital factory model, factory planning, restructuring

Procedia PDF Downloads 112

Authors: Getenet Shumet Birhan, Biruk Lelisa Eticha, Gizachew Tilahun Belete, Fisseha Admassu Ayele

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Context: Glaucoma is a significant public health concern globally, being the second leading cause of blindness. This study focuses on adult glaucoma patients in Ethiopia, specifically at the University of Gondar. Research Aim: The main objective is to assess the prevalence of visual impairment and identify associated factors among adult glaucoma patients at the University of Gondar. Methodology: The study used an institution-based cross-sectional design, collecting data from 423 glaucoma patients through interviews and medical chart reviews. Descriptive statistics and logistic regression were employed for analysis. Findings: The study found a high prevalence of visual impairment (77.6%) among adult glaucoma patients, with factors such as female sex, rural residence, glaucoma type, disease stage, and duration of diagnosis significantly associated with visual impairment. Theoretical Importance: This research adds valuable insights into the prevalence and determinants of visual impairment among glaucoma patients in Ethiopia, contributing to the existing literature on eye health in low-resource settings. Data Collection: Data were collected through face-to-face interviews and medical chart reviews at the University of Gondar, utilizing a structured questionnaire. Analysis Procedures: Descriptive statistics, frequency analysis, and binary logistic regression were employed to analyze the data and identify factors associated with visual impairment in adult glaucoma patients. Question Addressed: The study sought to answer the question of the prevalence of visual impairment and its associated factors among adult glaucoma patients at the University of Gondar in Northwest Ethiopia. Conclusion: The research concludes that visual impairment is significantly high among adult glaucoma patients in this setting, with several factors playing a role in its occurrence.

Keywords: visual impairment, glaucoma, Ethiopia, Gondar

Procedia PDF Downloads 72

Authors: Varis Ransibrahmanakul, Doug Pirhalla, Scott Sheridan, Cameron Lee

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U.S. coastal areas and ecosystems are facing multiple sea level rise threats and effects: heavy rain events, cyclones, and changing wind and weather patterns all influence coastal flooding, sedimentation, and erosion along critical barrier islands and can strongly impact habitat resiliency and water quality in protected habitats. These impacts are increasing over time and have accelerated the need for new tracking techniques, models and tools of flood risk to support enhanced preparedness for coastal management and mitigation. To address this issue, NOAA National Ocean Service (NOS) evaluated new metrics from satellite altimetry AVISO/Copernicus and MODIS IR flood extents to isolate nodes atmospheric variability indicative of elevated sea level and nuisance flood events. Using de-trended time series of cross-shelf sea surface heights (SSH), we identified specific Self Organizing Maps (SOM) nodes and transitions having a strongest regional association with oceanic spatial patterns (e.g., heightened downwelling favorable wind-stress and enhanced southward coastal transport) indicative of elevated coastal sea levels. Results show the impacts of the inverted barometer effect as well as the effects of surface wind forcing; Ekman-induced transport along broad expanses of the U.S. eastern coastline. Higher sea levels and corresponding localized flooding are associated with either pattern indicative of enhanced on-shore flow, deepening cyclones, or local- scale winds, generally coupled with an increased local to regional precipitation. These findings will support an integration of satellite products and will inform seasonal outlook model development supported through NOAAs Climate Program Office and NOS office of Center for Operational Oceanographic Products and Services (CO-OPS). Overall results will prioritize ecological areas and coastal lab facilities at risk based on numbers of nuisance flood projected and inform coastal management of flood risk around low lying areas subjected to bank erosion.

Keywords: AVISO satellite altimetry SSHA, MODIS IR flood map, nuisance flood, remote sensing of flood

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Authors: Natia Tsiklashvili, Tamari Poladashvili

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Education is one of the fundamental factors of economic prosperity in all respects. It is impossible to talk about the sustainable economic development of the country without substantial investments in human capital and investment into higher educational institutions. Education improves the standard of living of the population and expands the opportunities to receive more benefits, which will be equally important for both the individual and the society as a whole. There are growing initiatives among educated people such as entrepreneurship, technological development, etc. At the same time, the distribution of income between population groups is improving. The given paper discusses the scientific literature in the field of sustainable development through higher educational institutions. Scholars of economic theory emphasize a few major aspects that show the role of higher education in economic growth: a) Alongside education, human capital gradually increases which leads to increased competitiveness of the labor force, not only in the national but also in the international labor market (Neoclassical growth theory), b) The high level of education can increase the efficiency of the economy, investment in human capital, innovation, and knowledge are significant contributors to economic growth. Hence, it focuses on positive externalities and spillover effects of a knowledge-based economy which leads to economic development (endogenous growth theory), c) Education can facilitate the diffusion and transfer of knowledge. Hence, it supports macroeconomic sustainability and microeconomic conditions of individuals. While discussing the economic importance of education, we consider education as the spiritual development of the human that advances general skills, acquires a profession, and improves living conditions. Scholars agree that human capital is not only money but liquid assets, stocks, and competitive knowledge. The last one is the main lever in the context of increasing human competitiveness and high productivity. To address the local issues, the present article researched ten educational institutions across Georgia, including state and private HEIs. Qualitative research was done by analyzing in-depth interweaves of representatives from each institution, and respondents were rectors/vice-rectors/heads of quality assurance service at the institute. The result shows that there is a number of challenges that institution face in order to maintain sustainable development and be the strong links to education and the labor market. Mostly it’s contacted with bureaucracy, insufficient finances they receive, and local challenges that differ across the regions.

Keywords: higher education, higher educational institutions, sustainable development, regions, Georgia

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Authors: Olga Giovani

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In this research, Bronfenbrenner's theory will be used to investigate the individual, microsystemic, and exosystemic factors that may affect adolescents' academic achievement as well as their expectations in Greece. First, the topic of academic achievement in an adolescent developmental context will be set as the target of the proposed study while focusing on the aspects of community influences on adolescents. More specifically, the effect of available resources and the perceived sense of safety and support will be further investigated. Then the issue of family factors will be analyzed, as they are subjectively perceived by the adolescents, focusing on the perceived parental style, parental monitor, and involvement as a mesosystemic factor. In turn, the school will also be discussed with emphasis on the perceived school climate and support as well as the academic aspects of student achievement. Finally, the adolescent's individual perspective will be taken into consideration in developmental terms, examining their perceptions regarding their community/neighborhood, their family, their school, as well as their sense of self-concept and self-esteem as these are expressed through their academic performance and prosocial behavior. The aim of the proposed research is to study these associations through the prism of the systemic perspective, the relationship between aspects of educational achievement and socioeconomic background, with an emphasis on the role of the community, which has not been adequately researched in the Greek context. Community will be defined by the available community resources (recreational activities, public library, local orchestras, free entrance museums, etc.), adolescents' own perception of social support, safety, and support inside that community. These perceptions need to be investigated since they may serve as possible predictors of a child's current cognitive, developmental, and psycho-social outcomes, such as their perceived self-concept and self-esteem, as well as on their future expectations related to the entrance to university and job expectations.

Keywords: bioecological model, developmental psychology, ecosystemic approach, student achievement, microsystemic factors, mesosystemic factors, individual perceptions

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Authors: Luis Amador Jimenez, Md. Shohel Amin

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Pavement performance models are based on projections of observed traffic loads, which makes uncertain to study funding strategies in the long run if history does not repeat. Neural networks can be used to estimate deterioration rates but the learning rate and momentum have not been properly investigated, in addition, economic evolvement could change traffic flows. This study addresses both issues through a case study for roads of Montreal that simulates traffic for a period of 50 years and deals with the measurement error of the pavement deterioration model. Travel demand models are applied to simulate annual average daily traffic (AADT) every 5 years. Accumulated equivalent single axle loads (ESALs) are calculated from the predicted AADT and locally observed truck distributions combined with truck factors. A back propagation Neural Network (BPN) method with a Generalized Delta Rule (GDR) learning algorithm is applied to estimate pavement deterioration models capable of overcoming measurement errors. Linear programming of lifecycle optimization is applied to identify M&R strategies that ensure good pavement condition while minimizing the budget. It was found that CAD 150 million is the minimum annual budget to good condition for arterial and local roads in Montreal. Montreal drivers prefer the use of public transportation for work and education purposes. Vehicle traffic is expected to double within 50 years, ESALS are expected to double the number of ESALs every 15 years. Roads in the island of Montreal need to undergo a stabilization period for about 25 years, a steady state seems to be reached after.

Keywords: pavement management system, traffic simulation, backpropagation neural network, performance modeling, measurement errors, linear programming, lifecycle optimization

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Authors: Parvaneh Mahmoudi, Ahmad Moeni, Seyed Mojtaba Khayam Nekoei, Mohsen Mardi, Mehrshad Zeinolabedini, Ghasem Hosseini Salekdeh

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Saffron (Crocus sativus L.) is one of the most important spice and medicinal plants. The three-branch style of C. sativus flowers are the most important economic part of the plant and known as saffron, which has several medicinal properties. Despite the economic and biological significance of this plant, knowledge about its molecular characteristics is very limited. In the present study, we, for the first time, constructed a comprehensive dataset for C. sativus stigma through de novo transcriptome sequencing. We performed de novo transcriptome sequencing of C. sativus stigma using the Illumina paired-end sequencing technology. A total of 52075128 reads were generated and assembled into 118075 unigenes, with an average length of 629 bp and an N50 of 951 bp. A total of 66171unigenes were identified, among them, 66171 (56%) were annotated in the non-redundant National Center for Biotechnology Information (NCBI) database, 30938 (26%) were annotated in the Swiss-Prot database, 10273 (8.7%) unigenes were mapped to 141 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database, while 52560 (44%) and 40756 (34%) unigenes were assigned to Gen Ontology (GO) categories and Eukaryotic Orthologous Groups of proteins (KOG), respectively. In addition, 65 candidate genes involved in three stages of crocin biosynthesis were identified. Finally, transcriptome sequencing of saffron stigma was used to identify 6779 potential microsatellites (SSRs) molecular markers. High-throughput de novo transcriptome sequencing provided a valuable resource of transcript sequences of C. sativus in public databases. In addition, most of candidate genes potentially involved in crocin biosynthesis were identified which could be further utilized in functional genomics studies. Furthermore, numerous obtained SSRs might contribute to address open questions about the origin of this amphiploid spices with probable little genetic diversity.

Keywords: saffron, transcriptome, NGS, bioinformatic

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Authors: Rashmi Tomar, A. Srinivasan, Nayan K. Mohanty, Arun K. Jain

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Phthalates have been used as additives in industrial products since the 1930s, and are universally considered to be ubiquitous environmental contaminants. The general population is exposed to phthalates through consumer products, as well as diet and medical treatments. Animal studies showing the existence of an association between some phthalates and testicular toxicity have generated public and scientific concern about the potential adverse effects of environmental changes on male reproductive health. Unprecedented declines in fertility rates and semen quality have been reported during the last half of the 20th century in developed countries and increasing interest exists on the potential relationship between exposure to environmental contaminants, including phthalates, and human male reproductive health Studies. Phthalates may be associated with altered endocrine function and adverse effects on male reproductive development and function, but human studies are limited. The aim of the present study was detection of phthalate compounds, estimation of their metabolites in infertile & fertile male. Blood and urine samples were collected from 150 infertile patients & 75 fertile volunteers recruited through Department of Urology, Safdarjung Hospital, New Delhi. Blood have been collected in separate glass tubes from the antecubital vein of the patients, serum have been separate and estimate the phthalate level in serum samples by Gas Chromatography / Mass Spectrometry using NIOSH / OSHA detailed protocol. Urine of Infertile & Fertile Subjects was collected & extracted using solid phase extraction method, analysis by HPLC. In conclusion, to the best of our knowledge the present study based on human is first to show the presence of phthalate in human serum samples and their metabolites in urine samples. Significant differences were observed between several phthalates in infertile and fertile healthy individuals.

Keywords: Gas Chromatography, HPLC, male infertility, phthalates, serum, toxicity, urine

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Authors: Rhodine Hickman, Craig Wylie, Michael G. McCaul

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Introduction: The World Health Organisation has called on governments around the world to recognise emergency conditions as a global public health problem and respond with appropriate steps for effective preventative strategies. However, to understand the magnitude of the problem, good quality epidemiological data is required. This is especially challenging in low and middle-income countries, where routine data is scarce, specifically within the prehospital setting. Methods: We conducted a retrospective cross-sectional study of a national prehospital private sector EMS database. The database being the property of ER24 (private Emergency Medical Services (EMS) company in South Africa) contains claims submitted by the majority of ambulance services in South Africa during the period between 1 January 2008 to 28 March 2017. We used descriptive statistics and control charts to describe the data using STATA 14. Results: 299,257 calls were included in the analysis. The top clinical conditions requiring ambulance transport were transport accidents (10% of total call volume) and ischaemic heart disease (4.4%). The number of transport accidents consistently increased between 2009 and 2014 and reached beyond the limit for normal variation in 2015. Victims of transport accidents required basic life support services 60% of the time with 80% of injuries being minor to moderate. The frequency of ischaemic heart disease had a steady incline from 2011 to 2016. Advanced life support services were required about 50% of the time, with 60% of patients needing urgent care. Conclusion: Transport accidents, followed by ischaemic heart disease, are the most prevalent conditions in South African private EMS. There is a potential to address these conditions by developing the capacity of low and mid-level providers in trauma and advanced EMS providers in ischaemic heart disease.

Keywords: emergency care, emergency medicine, prehospital providers, South Africa

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Authors: Galih Imaduddin

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Knowledge has been viewed as one of the most important resources in organizations, including those that operate in the healthcare sector. On that basis, Knowledge Management (KM) is crucial for healthcare organizations to improve their productivity and ensure effective utilization of their resources. Despite the growing interests to understand how KM might work for healthcare organizations, there is only a modest amount of empirical inquiries which have specifically focused on the tools and initiatives to share knowledge. Hence, the main purpose of this paper is to investigate the way healthcare organizations, particularly public sector ones, utilize knowledge sharing tools and initiatives for the benefit of patient-care. Employing a qualitative method, 13 (thirteen) Community Health Centers (CHCs) from a high-performing district health setting in Indonesia were observed. Data collection and analysis involved a repetition of document retrievals and interviews (n=41) with multidisciplinary health professionals who work in these CHCs. A single case study was cultivated reflecting on the means that were used to share knowledge, along with the factors that inhibited the exchange of knowledge among those health professionals. The study discovers that all of the thirteen CHCs exhibited and applied knowledge sharing means which included knowledge documents, virtual communication channels (i.e. emails and chatting applications), and social learning forums such as staff meetings, morning briefings, and communities of practices. However, the intensity of utilization was different among these CHCs, in which organizational culture, leadership, professional boundaries, and employees’ technological aptitude were presumed to be the factors that inhibit knowledge sharing processes. Making a distance with the KM literature of other sectors, this study denounces the primacy of technology-based tools, suggesting that socially-based initiatives could be more reliable for sharing knowledge. This suggestion is largely due to the nature of healthcare work which is still predominantly based on the tacit form of knowledge.

Keywords: knowledge management, knowledge sharing, knowledge sharing tools and initiatives, knowledge sharing inhibitors, primary health care organizations

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Authors: Till Gramberg

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In the dynamic world of machine and plant engineering, stagnation in the growth of new product sales compels companies to reconsider their business models. The increasing shift toward service orientation, known as "servitization," along with challenges posed by digitalization and sustainability, necessitates an adaptation of product portfolio management (PPM). Against this backdrop, this study investigates the current challenges and requirements of PPM in this industrial context and develops a framework for the application of generative artificial intelligence (AI) to enhance agility and efficiency in PPM processes. The research approach of this study is based on a mixed-method design. Initially, qualitative interviews with industry experts were conducted to gain a deep understanding of the specific challenges and requirements in PPM. These interviews were analyzed using the Gioia method, painting a detailed picture of the existing issues and needs within the sector. This was complemented by a quantitative online survey. The combination of qualitative and quantitative research enabled a comprehensive understanding of the current challenges in the practical application of machine and plant engineering PPM. Based on these insights, a specific framework for the application of generative AI in PPM was developed. This framework aims to assist companies in implementing faster and more agile processes, systematically integrating dynamic requirements from trends such as digitalization and sustainability into their PPM process. Utilizing generative AI technologies, companies can more quickly identify and respond to trends and market changes, allowing for a more efficient and targeted adaptation of the product portfolio. The study emphasizes the importance of an agile and reactive approach to PPM in a rapidly changing environment. It demonstrates how generative AI can serve as a powerful tool to manage the complexity of a diversified and continually evolving product portfolio. The developed framework offers practical guidelines and strategies for companies to improve their PPM processes by leveraging the latest technological advancements while maintaining ecological and social responsibility. This paper significantly contributes to deepening the understanding of the application of generative AI in PPM and provides a framework for companies to manage their product portfolios more effectively and adapt to changing market conditions. The findings underscore the relevance of continuous adaptation and innovation in PPM strategies and demonstrate the potential of generative AI for proactive and future-oriented business management.

Keywords: servitization, product portfolio management, generative AI, disruptive innovation, machine and plant engineering

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Authors: Rose Antony, Vivekanand B. Khanapuri, Karuna Jain

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Online groceries have transformed the way the supply chains are managed. These are facing numerous challenges in terms of product wastages, low margins, long breakeven to achieve and low market penetration to mention a few. The e-grocery chains need to overcome these challenges in order to survive the competition. The purpose of this paper is to carry out a structural analysis of the enablers in e-grocery chains by applying Interpretive Structural Modeling (ISM) and MICMAC analysis in the Indian context. The research design is descriptive-explanatory in nature. The enablers have been identified from the literature and through semi-structured interviews conducted among the managers having relevant experience in e-grocery supply chains. The experts have been contacted through professional/social networks by adopting a purposive snowball sampling technique. The interviews have been transcribed, and manual coding is carried using open and axial coding method. The key enablers are categorized into themes, and the contextual relationship between these and the performance measures is sought from the Industry veterans. Using ISM, the hierarchical model of the enablers is developed and MICMAC analysis identifies the driver and dependence powers. Based on the driver-dependence power the enablers are categorized into four clusters namely independent, autonomous, dependent and linkage. The analysis found that information technology (IT) and manpower training acts as key enablers towards reducing the lead time and enhancing the online service quality. Many of the enablers fall under the linkage cluster viz., frequent software updating, branding, the number of delivery boys, order processing, benchmarking, product freshness and customized applications for different stakeholders, depicting these as critical in online food/grocery supply chains. Considering the perishability nature of the product being handled, the impact of the enablers on the product quality is also identified. Hence, study aids as a tool to identify and prioritize the vital enablers in the e-grocery supply chain. The work is perhaps unique, which identifies the complex relationships among the supply chain enablers in fresh food for e-groceries and linking them to the performance measures. It contributes to the knowledge of supply chain management in general and e-retailing in particular. The approach focus on the fresh food supply chains in the Indian context and hence will be applicable in developing economies context, where supply chains are evolving.

Keywords: interpretive structural modelling (ISM), India, online grocery, retail operations, supply chain management

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Authors: Tamara Jimah, Priscilla Kehoe, Pamela Pimentel, Amir Rahmani, Nikil Dutt, Yuqing Guo

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Ensuring equitable access to maternal health care is critical for public health. Particularly for underserved women, community health workers (CHWs) have been invaluable in providing support through health education and strategies for improved maternal self-care management. Our research aimed to assess the acceptance of technology by CHWs and perinatal women to promote healthy pregnancy and postpartum wellness. This pilot study was conducted at a local community organization in Orange County, California, where CHWs play an important role in supporting low-income women through home visitations. Questionnaires were administered to 14 CHWs and 114 pregnant and postpartum women, literate in English and/or Spanish. CHWs tested two wearable devices (Galaxy watch and Oura ring) and shared their user experience, including potential reception by the perinatal women they served. In addition, perinatal women provided information on access to a smart phone and the internet, as well as their interest in using wearable devices to self-monitor personal health with guidance from a CHW. Over 85% of CHWs agreed that it was useful to track pregnancy with the smart watch and ring. The majority of perinatal women owned a smartphone (97.4%), had access to the internet (80%) and unlimited data plans (78%), expressed interest in using the smart wearable devices to self-monitor health, and were open to receiving guidance from a CHW (87%). Community health workers and perinatal women embraced the use of wearable technology to monitor maternal health. These preliminary findings have formed the basis of an ongoing research study that integrates CHW guidance and technology (i.e., smart watch, smart ring, and a mobile phone app) to promote self-efficacy and self-management among underserved perinatal women.

Keywords: community health workers, health promotion and education, health equity, maternal and child health, technology

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Authors: Sataroopa Mishra, Mona Basker, Sneha Varkki, Ram Kumar Pandian, Grace Rebekah

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Background: Sleep deprivation is a matter of public health importance among adolescents. We used adolescent sleep wake scale and adolescent sleep hygiene scale to determine the sleep quality and sleep hygiene respectively of school going adolescents in Vellore city of India. The objective of the study was to do factorial analysis of the scales and validate it for use in local population. Methods: Observational questionnaire based cross sectional study. Setting: Community based school survey in a semi-urban setting in three schools in Vellore city. Data collection: Non probability sample was collected form students studying in standard 9 and 11. Students filled Adolescent Sleep Wake scale (ASWS) and Adolescent Sleep Hygiene Scale (ASHS) translated into vernacular language. Data Analysis: Exploratory Factorial Analysis was used to see the factor loading of various components of the two scales. Confirmatory factorial analysis is subsequently planned for assessing the internal validity of the scales.Results: 557 adolescents were included in the study of 12 – 17 years old. Exploratory factorial analysis of adolescent sleep hygiene scale indicated significant factor loading for 18 items from 28 items originally devised by the authors and has been reconstructed to four domains instead of 9 domains in the original scale namely sleep stability, cognitive – emotional, Physiological - bed time routine - behavioural arousal factor (activites before bedtime and during bed time), Sleep environment (lighting and bed sharing). Factorial analysis of Adolescent sleep wake scale showed factor loading of 18 items out of 28 items in original scale reconstructed into 5 aspects of sleep quality. Conclusions: The factorial analysis gives a reconstructed scale useful for the local population. Further a confirmatory factorial analysis has been subsequently planned to determine the internal consistency of the scale for local population.

Keywords: factorial analysis, sleep hygiene, sleep quality, adolescent sleep scale

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Authors: Melissa Mattos, Camila Lima, Ibraim Castro, Augusto Carioca, Saulo Magalhães, Paula Freitas, Keciany Oliveira

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Obesity is a chronic, multifactorial, relapsing disease that has increased dramatically over the years. Its control is considered a public health issue, and more and more treatments and interventions are being studied to reduce its prevalence. When interventions in lifestyle and the use of drugs do not generate lasting results, bariatric procedures emerge as a resource for obesity control. The main guidelines for the treatment of obesity emphasize the need for pre-procedure and post-procedure nutritional monitoring to avoid nutritional deficiencies that may occur. The individual who undergoes bariatric surgery needs to understand the changes that will be necessary for life in view of the intense anatomical and metabolic changes that result from surgical techniques. To assess the nutritional profile of patients who undergo bariatric surgery, we analyzed data from the medical records of all people who underwent sleeve-type bariatric surgery from January to June 2022 at a clinic in the City of Fortaleza. 38 patients were analyzed, 32 women and 6 men in the pre-surgical period, 6 and 12 months after surgery. The data showed an average weight loss of 24.45% at 6 months and 30.85% at 12 months, with a reduction of 21.32% and 30.41%, respectively, in the fat percentage, also indicating that 13.15% used drugs for weight loss during this period, leading to reflection on the isolated long-term efficacy of bariatric surgery, requiring multidisciplinary follow-up for a change in lifestyle. Only 12 individuals, corresponding to 31.57%, reached eutrophic BMI 12 months after surgery, 20 individuals remained overweight, corresponding to 52.63% of the sample, and 6 individuals (15.78%) remained in the BMI obese class I. As for body composition, there was a 52.39% reduction in fat mass and a 12.82% reduction in muscle mass, and 21% of individuals underwent cholecystectomy. Sleeve-type bariatric surgery promoted significant weight loss after 1 year of the procedure, with a reduction in body fat percentage and fat mass. Most patients were still overweight and had a significant reduction in muscle mass.

Keywords: bariatric surgery, sleeve gastrectomy, obesity, sleeve

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Authors: Moh’d Anwer Al-Shboul

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The year 2011 was a challenging year for Jordanian economy, which felt a variety of effects from the Arab Spring which took place in neighboring countries. Since February, 5th 2012, the Arab Gas Supply Pipeline, which carries natural gas from Egypt through the Sinai Peninsula and to Jordan and Israel, has been attacked more than 39 times. Jordan imported about 80 percent of its necessity of natural gas (about 250 million cubic feet of natural gas per day) from Egypt to generate particularly electricity, with the reminder of being produced locally. Jordan has utilized multiple alternatives to address the interruption of available natural gas supply from Egypt. The Jordanian distributed power plants now rely on the use of heavy fuel oil and diesel for electricity generation, in this case, it costs Jordan about four times than natural gas. The substitution of Egyptian natural gas supplies by fuel oil and diesel, coupled with the 32 percent rise in global fuel prices, has increased Jordan’s energy import bill by over 50 percent in 2011, reaching more than 16 percent of the 2011 GDP. The increase in the cost of electricity generation pushed the Jordanian economy to borrow from multiple internal and external resource channels, thus increasing the public debt. The Jordanian government’s short-term solution to the reduced natural gas supply from Egypt was alternatively purchasing the necessary quantities from some Gulf countries such as Qatar and/or Saudi Arabia, which can be imported with two possible methods. The first method is to rent a ship equipped with a liquefied natural gas (LNG) terminal, which is currently operating. The second method requires equipping the Aqaba port with an LNG terminal, which also currently is operating. In the long-term, a viable solution to depending on importing expensive and often unreliable natural gas supplies from surrounding countries is to depend more heavily on renewable supply energy, including solar, wind, and water energy.

Keywords: energy supply resources, Arab spring, liquefied natural gas, pipeline, Jordan

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Authors: Hossein Afzali

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Increasingly, decision analytic models are used to inform decisions about whether or not to publicly fund new health technologies. It is well noted that the accuracy of model predictions is strongly influenced by the appropriateness of model structuring. However, there is relatively inadequate methodological guidance surrounding this issue in guidelines developed by national funding bodies such as the Australian Pharmaceutical Benefits Advisory Committee (PBAC) and The National Institute for Health and Care Excellence (NICE) in the UK. This presentation aims to discuss issues around model structuring within decision making with a focus on (1) the need for a transparent and evidence-based model structuring process to inform the most appropriate set of structural aspects as the base case analysis; (2) the need to characterise structural uncertainty (If there exist alternative plausible structural assumptions (or judgements), there is a need to appropriately characterise the related structural uncertainty). The presentation will provide an opportunity to share ideas and experiences on how the guidelines developed by national funding bodies address the above issues and identify areas for further improvements. First, a review and analysis of the literature and guidelines developed by PBAC and NICE will be provided. Then, it will be discussed how the issues around model structuring (including structural uncertainty) are not handled and justified in a systematic way within the decision-making process, its potential impact on the quality of public funding decisions, and how it should be presented in submissions to national funding bodies. This presentation represents a contribution to the good modelling practice within the decision-making process. Although the presentation focuses on the PBAC and NICE guidelines, the discussion can be applied more widely to many other national funding bodies that use economic evaluation to inform funding decisions but do not transparently address model structuring issues e.g. the Medical Services Advisory Committee (MSAC) in Australia or the Canadian Agency for Drugs and Technologies in Health.

Keywords: decision-making process, economic evaluation, good modelling practice, structural uncertainty

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