Search results for: reduce the demand and supply of illicit drugs
10749 Air Access Liberalisation and Tourism Trade Evidence from a Sids
Authors: Seetanah Boopen, R. V. Sannassee
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The objective of the present study is two-fold. Firstly, to assess the impact of air access liberalization on tourism demand for Mauritius and secondly to analyses the dual impact of the interplay between air access liberalization and marketing promotion efforts on tourism demand. Using an Autoregressive Distributed Lag model, the results suggest that air access liberalization is an important ingredient, albeit to a lesser extent as compared to other classical explanatory variables, of tourism demand. The results also highlight the fact that Mauritius is perceived as a luxurious destination and tourists are deemed price sensitive. Moreover, our dynamic approach interestingly confirms the presence of repeat tourism in the island. Finally, the findings also uncover the positive impact of the interplay between air access liberalization and marketing promotion efforts on fostering tourism demand.Keywords: air access liberalization, ARDL, SIDS, time series
Procedia PDF Downloads 31010748 Forecasting Thermal Energy Demand in District Heating and Cooling Systems Using Long Short-Term Memory Neural Networks
Authors: Kostas Kouvaris, Anastasia Eleftheriou, Georgios A. Sarantitis, Apostolos Chondronasios
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To achieve the objective of almost zero carbon energy solutions by 2050, the EU needs to accelerate the development of integrated, highly efficient and environmentally friendly solutions. In this direction, district heating and cooling (DHC) emerges as a viable and more efficient alternative to conventional, decentralized heating and cooling systems, enabling a combination of more efficient renewable and competitive energy supplies. In this paper, we develop a forecasting tool for near real-time local weather and thermal energy demand predictions for an entire DHC network. In this fashion, we are able to extend the functionality and to improve the energy efficiency of the DHC network by predicting and adjusting the heat load that is distributed from the heat generation plant to the connected buildings by the heat pipe network. Two case-studies are considered; one for Vransko, Slovenia and one for Montpellier, France. The data consists of i) local weather data, such as humidity, temperature, and precipitation, ii) weather forecast data, such as the outdoor temperature and iii) DHC operational parameters, such as the mass flow rate, supply and return temperature. The external temperature is found to be the most important energy-related variable for space conditioning, and thus it is used as an external parameter for the energy demand models. For the development of the forecasting tool, we use state-of-the-art deep neural networks and more specifically, recurrent networks with long-short-term memory cells, which are able to capture complex non-linear relations among temporal variables. Firstly, we develop models to forecast outdoor temperatures for the next 24 hours using local weather data for each case-study. Subsequently, we develop models to forecast thermal demand for the same period, taking under consideration past energy demand values as well as the predicted temperature values from the weather forecasting models. The contributions to the scientific and industrial community are three-fold, and the empirical results are highly encouraging. First, we are able to predict future thermal demand levels for the two locations under consideration with minimal errors. Second, we examine the impact of the outdoor temperature on the predictive ability of the models and how the accuracy of the energy demand forecasts decreases with the forecast horizon. Third, we extend the relevant literature with a new dataset of thermal demand and examine the performance and applicability of machine learning techniques to solve real-world problems. Overall, the solution proposed in this paper is in accordance with EU targets, providing an automated smart energy management system, decreasing human errors and reducing excessive energy production.Keywords: machine learning, LSTMs, district heating and cooling system, thermal demand
Procedia PDF Downloads 14210747 Household Water Practices in a Rapidly Urbanizing City and Its Implications for the Future of Potable Water: A Case Study of Abuja Nigeria
Authors: Emmanuel Maiyanga
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Access to sufficiently good quality freshwater has been a global challenge, but more notably in low-income countries, particularly in the Sub-Saharan countries, which Nigeria is one. Urban population is soaring, especially in many low-income countries, the existing centralised water supply infrastructures are ageing and inadequate, moreover in households peoples’ lifestyles have become more water-demanding. So, people mostly device coping strategies where municipal supply is perceived to have failed. This development threatens the futures of groundwater and calls for a review of management strategy and research approach. The various issues associated with water demand management in low-income countries and Nigeria, in particular, are well documented in the literature. However, the way people use water daily in households and the reasons they do so, and how the situation is constructing demand among the middle-class population in Abuja Nigeria is poorly understood. This is what this research aims to unpack. This is achieved by using the social practices research approach (which is based on the Theory of Practices) to understand how this situation impacts on the shared groundwater resource. A qualitative method was used for data gathering. This involved audio-recorded interviews of householders and water professionals in the private and public sectors. It also involved observation, note-taking, and document study. The data were analysed thematically using NVIVO software. The research reveals the major household practices that draw on the water on a domestic scale, and they include water sourcing, body hygiene and sanitation, laundry, kitchen, and outdoor practices (car washing, domestic livestock farming, and gardening). Among all the practices, water sourcing, body hygiene, kitchen, and laundry practices, are identified to impact most on groundwater, with impact scale varying with household peculiarities. Water sourcing practices involve people sourcing mostly from personal boreholes because the municipal water supply is perceived inadequate and unreliable in terms of service delivery and water quality, and people prefer easier and unlimited access and control using boreholes. Body hygiene practices reveal that every respondent prefers bucket bathing at least once daily, and the majority bathe twice or more every day. Frequency is determined by the feeling of hotness and dirt on the skin. Thus, people bathe to cool down, stay clean, and satisfy perceived social, religious, and hygiene demand. Kitchen practice consumes water significantly as people run the tap for vegetable washing in daily food preparation and dishwashing after each meal. Laundry practice reveals that most people wash clothes most frequently (twice in a week) during hot and dusty weather, and washing with hands in basins and buckets is the most prevalent and water wasting due to soap overdose. The research also reveals poor water governance as a major cause of current inadequate municipal water delivery. The implication poor governance and widespread use of boreholes is an uncontrolled abstraction of groundwater to satisfy desired household practices, thereby putting the future of the shared aquifer at great risk of total depletion with attendant multiplying effects on the people and the environment and population continues to soar.Keywords: boreholes, groundwater, household water practices, self-supply
Procedia PDF Downloads 12310746 Counteracting Disruptions during the COVID-19 Pandemic in the Supply Chains of the Automotive Industry: The Example of Polish Enterprises
Authors: Tomasz Rokicki, Piotr Bórawski, Aneta Bełdycka-Bórawska, András Szeberényi
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The aim of the article was to present ways to counteract disruptions during the COVID-19 pandemic occurring in the supply chain of enterprises from the automotive industry. The specific objectives are to determine changes in the automotive industry during the pandemic, to show the types of disruptions in supply chains, and how to counteract these unfavorable situations. Enterprises from the automotive industry operating in Poland were deliberately selected for research. Using the purposive sampling method, ten companies from the automotive industry were selected for qualitative research. In-depth research was carried out in selected enterprises using a personal interview. At the beginning of the pandemic, lockdowns and unpredictability were a problem. The key was to protect employees and introduce appropriate procedures. In the later stages of the pandemic, there were restrictions on the timeliness of deliveries and extension of delivery times. There were problems with the shortage of materials, and the costs of products and transport increased. In automotive companies, counteracting the effects of the pandemic consisted of ensuring the safety of employees, maintaining constant contact and communication with branches and headquarters, as well as with suppliers and contractors. Therefore, appropriate communication, cooperation, and flexibility were important.Keywords: disruptions, automotive industry, supply chain disruption, cooperation in supply chain
Procedia PDF Downloads 6710745 Scientometrics Analysis of Food Supply Chain Risk Assessment Literature: Based On Web of Science Record 1996-2014
Authors: Mohsen Shirani, Shadi Asadzandi, Micaela Demichela
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This paper presents the results of a study to assess crucial aspects and the strength of the scientific basis of a typically interdisciplinary, applied field: food supply chain risk assessment research. Our approach is based on an advanced scientometrics analysis with novel elements to assess the influence and dissemination of research results and to measure interdisciplinary. This paper aims to describe the quantity and quality of the publication trends in food supply chain risk assessment. The population under study was composed of 266 articles from database web of science. The results were analyzed based on date of publication, type of document, language of the documents, source of publications, subject areas, authors and their affiliations, and the countries involved in developing the articles.Keywords: food supply chain, risk assessment, scientometrics, web of science
Procedia PDF Downloads 49510744 Load Forecast of the Peak Demand Based on Both the Peak Demand and Its Location
Authors: Qais H. Alsafasfeh
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The aim of this paper is to provide a forecast of the peak demand for the next 15 years for electrical distribution companies. The proposed methodology provides both the peak demand and its location for the next 15 years. This paper describes the Spatial Load Forecasting model used, the information provided by electrical distribution company in Jordan, the workflow followed, the parameters used and the assumptions made to run the model. The aim of this paper is to provide a forecast of the peak demand for the next 15 years for electrical distribution companies. The proposed methodology provides both the peak demand and its location for the next 15 years. This paper describes the Spatial Load Forecasting model used, the information provided by electrical distribution company in Jordan, the workflow followed, the parameters used and the assumptions made to run the model.Keywords: load forecast, peak demand, spatial load, electrical distribution
Procedia PDF Downloads 49510743 Development of Composition and Technology of Vincristine Nanoparticles Using High-Molecular Carbohydrates of Plant Origin
Authors: L. Ebralidze, A. Tsertsvadze, D. Berashvili, A. Bakuridze
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Current cancer therapy strategies are based on surgery, radiotherapy and chemotherapy. The problems associated with chemotherapy are one of the biggest challenges for clinical medicine. These include: low specificity, broad spectrum of side effects, toxicity and development of cellular resistance. Therefore, anti-cance drugs need to be develop urgently. Particularly, in order to increase efficiency of anti-cancer drugs and reduce their side effects, scientists work on formulation of nano-drugs. The objective of this study was to develop composition and technology of vincristine nanoparticles using high-molecular carbohydrates of plant origin. Plant polysacharides, particularly, soy bean seed polysaccharides, flaxseed polysaccharides, citrus pectin, gum arabic, sodium alginate were used as objects. Based on biopharmaceutical research, vincristine containing nanoparticle formulations were prepared. High-energy emulsification and solvent evaporation methods were used for preparation of nanosystems. Polysorbat 80, polysorbat 60, sodium dodecyl sulfate, glycerol, polyvinyl alcohol were used in formulation as emulsifying agent and stabilizer of the system. The ratio of API and polysacharides, also the type of the stabilizing and emulsifying agents are very effective on the particle size of the final product. The influence of preparation technology, type and concentration of stabilizing agents on the properties of nanoparticles were evaluated. For the next stage of research, nanosystems were characterized. Physiochemical characterization of nanoparticles: their size, shape, distribution was performed using Atomic force microscope and Scanning electron microscope. The present study explored the possibility of production of NPs using plant polysaccharides. Optimal ratio of active pharmaceutical ingredient and plant polysacharids, the best stabilizer and emulsifying agent was determined. The average range of nanoparticles size and shape was visualized by SEM.Keywords: nanoparticles, target delivery, natural high molecule carbohydrates, surfactants
Procedia PDF Downloads 27010742 Drug-Drug Interaction Prediction in Diabetes Mellitus
Authors: Rashini Maduka, C. R. Wijesinghe, A. R. Weerasinghe
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Drug-drug interactions (DDIs) can happen when two or more drugs are taken together. Today DDIs have become a serious health issue due to adverse drug effects. In vivo and in vitro methods for identifying DDIs are time-consuming and costly. Therefore, in-silico-based approaches are preferred in DDI identification. Most machine learning models for DDI prediction are used chemical and biological drug properties as features. However, some drug features are not available and costly to extract. Therefore, it is better to make automatic feature engineering. Furthermore, people who have diabetes already suffer from other diseases and take more than one medicine together. Then adverse drug effects may happen to diabetic patients and cause unpleasant reactions in the body. In this study, we present a model with a graph convolutional autoencoder and a graph decoder using a dataset from DrugBank version 5.1.3. The main objective of the model is to identify unknown interactions between antidiabetic drugs and the drugs taken by diabetic patients for other diseases. We considered automatic feature engineering and used Known DDIs only as the input for the model. Our model has achieved 0.86 in AUC and 0.86 in AP.Keywords: drug-drug interaction prediction, graph embedding, graph convolutional networks, adverse drug effects
Procedia PDF Downloads 10010741 Risk Management and Security Practice in Customs Supply Chain: Application of Cross ABC Method to the Moroccan Customs
Authors: Lamia Hammadi, Abdellah Ait Ouhman, Aomar Ibourk
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It is widely assumed that the case of Customs Supply Chain is classified as a complex system, due to not only the variety and large number of actors, but also their complex structural links, and the interactions between these actors, that’s why this system is subject to various types of Risks. The economic, political and social impacts of those risks are highly detrimental to countries, businesses and the public, for this reason, Risk management in the customs supply chain is becoming a crucial issue to ensure the sustainability, security and safety. The main characteristic of customs risk management approach is determining which goods and means of transport should be examined? To what extend? And where future compliance resources should be directed? The purposes of this article are, firstly to deal with the concept of customs supply chain, secondly present our risk management approach based on Cross Activity Based Costing (ABC) Method as an interactive tool to support decision making in customs risk management. Finally, analysis of case study of Moroccan customs to putting theory into practice and will thus draw together the various elements of a structured and efficient risk management approach.Keywords: cross ABC method, customs supply chain, risk, risk management
Procedia PDF Downloads 37910740 A Systematic Review of Business Strategies Which Can Make District Heating a Platform for Sustainable Development of Other Sectors
Authors: Louise Ödlund, Danica Djuric Ilic
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Sustainable development includes many challenges related to energy use, such as (1) developing flexibility on the demand side of the electricity systems due to an increased share of intermittent electricity sources (e.g., wind and solar power), (2) overcoming economic challenges related to an increased share of renewable energy in the transport sector, (3) increasing efficiency of the biomass use, (4) increasing utilization of industrial excess heat (e.g., approximately two thirds of the energy currently used in EU is lost in the form of excess and waste heat). The European Commission has been recognized DH technology as of essential importance to reach sustainability. Flexibility in the fuel mix, and possibilities of industrial waste heat utilization, combined heat, and power (CHP) production and energy recovery through waste incineration, are only some of the benefits which characterize DH technology. The aim of this study is to provide an overview of the possible business strategies which would enable DH to have an important role in future sustainable energy systems. The methodology used in this study is a systematic literature review. The study includes a systematic approach where DH is seen as a part of an integrated system that consists of transport , industrial-, and electricity sectors as well. The DH technology can play a decisive role in overcoming the sustainability challenges related to our energy use. The introduction of biofuels in the transport sector can be facilitated by integrating biofuel and DH production in local DH systems. This would enable the development of local biofuel supply chains and reduce biofuel production costs. In this way, DH can also promote the development of biofuel production technologies that are not yet developed. Converting energy for running the industrial processes from fossil fuels and electricity to DH (above all biomass and waste-based DH) and delivering excess heat from industrial processes to the local DH systems would make the industry less dependent on fossil fuels and fossil fuel-based electricity, as well as the increasing energy efficiency of the industrial sector and reduce production costs. The electricity sector would also benefit from these measures. Reducing the electricity use in the industry sector while at the same time increasing the CHP production in the local DH systems would (1) replace fossil-based electricity production with electricity in biomass- or waste-fueled CHP plants and reduce the capacity requirements from the national electricity grid (i.e., it would reduce the pressure on the bottlenecks in the grid). Furthermore, by operating their central controlled heat pumps and CHP plants depending on the intermittent electricity production variation, the DH companies may enable an increased share of intermittent electricity production in the national electricity grid.Keywords: energy system, district heating, sustainable business strategies, sustainable development
Procedia PDF Downloads 16910739 A Theoretical Study of and Phase Change Material Layered Roofs under Specific Climatic Regions in Turkey and the United Kingdom
Authors: Tugba Gurler, Irfan Kurtbas
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Roof influences considerably energy demand of buildings. In order to reduce this energy demand, various solutions have been proposed, such as roofs with variable thermal insulation, cool roofs, green roofs, heat exchangers and ventilated roofs, and phase change material (PCM) layered roofs. PCMs suffer from relatively low thermal conductivity despite of their promise of the energy-efficiency initiatives for thermal energy storage (TES). This study not only presents the thermal performance of the concrete roof with PCM layers but also evaluates the products with different design configurations and thicknesses under Central Anatolia Region, Turkey and Nottinghamshire, UK weather conditions. System design limitations and proposed prediction models are discussed in this study. A two-dimensional numerical model has been developed, and governing equations have been solved at each time step. Upper surfaces of the roofs have been modelled with heat flux conditions, while lower surfaces of the roofs with boundary conditions. In addition, suitable roofs have been modeled under symmetry boundary conditions. The results of the designed concrete roofs with PCM layers have been compared with common concrete roofs in Turkey. The UK and the numerical modeling results have been validated with the data given in the literature.Keywords: phase change material, regional energy demand, roof layers, thermal energy storage
Procedia PDF Downloads 10210738 The Design and Implementation of a Calorimeter for Evaluation of the Thermal Performance of Materials: The Case of Phase Change Materials
Authors: Ebrahim Solgi, Zahra Hamedani, Behrouz Mohammad Kari, Ruwan Fernando, Henry Skates
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The use of thermal energy storage (TES) as part of a passive design strategy can reduce a building’s energy demand. TES materials do this by increasing the lag between energy consumption and energy supply by absorbing, storing and releasing energy in a controlled manner. The increase of lightweight construction in the building industry has made it harder to utilize thermal mass. Consequently, Phase Change Materials (PCMs) are a promising alternative as they can be manufactured in thin layers and used with lightweight construction to store latent heat. This research investigates utilizing PCMs, with the first step being measuring their performance under experimental conditions. To do this requires three components. The first is a calorimeter for measuring indoor thermal conditions, the second is a pyranometer for recording the solar conditions: global, diffuse and direct radiation and the third is a data-logger for recording temperature and humidity for the studied period. This paper reports on the design and implementation of an experimental setup used to measure the thermal characteristics of PCMs as part of a wall construction. The experimental model has been simulated with the software EnergyPlus to create a reliable simulation model that warrants further investigation.Keywords: phase change materials, EnergyPlus, experimental evaluation, night ventilation
Procedia PDF Downloads 25610737 The Effect on Lead Times When Normalizing a Supply Chain Process
Authors: Bassam Istanbouli
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Organizations are living in a very competitive and dynamic environment which is constantly changing. In order to achieve a high level of service, the products and processes of these organizations need to be flexible and evolvable. If the supply chains are not modular and well designed, changes can bring combinatorial effects to most areas of a company from its management, financial, documentation, logistics and its information structure. Applying the normalized system’s concept to segments of the supply chain may help in reducing those ripple effects, but it may also increase lead times. Lead times are important and can become a decisive element in gaining customers. Industries are always under the pressure in providing good quality products, at competitive prices, when and how the customer wants them. Most of the time, the customers want their orders now, if not yesterday. The above concept will be proven by examining lead times in a manufacturing example before and after applying normalized systems concept to that segment of the chain. We will then show that although we can minimize the combinatorial effects when changes occur, the lead times will be increased.Keywords: supply chain, lead time, normalization, modular
Procedia PDF Downloads 12510736 Urban Roof Farming: A Smart City Solution Leading to Sustainability
Authors: Phibankhamti Ryngnga
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It is a common phenomenon worldwide that farmland has been gradually converted for urban development particularly in the 21st century keeping in mind the population increase on the other hand. Since food demand and supply are not in equilibrium in urban set up, therefore, there is a need for alternative to feed the hungry urban settlers worldwide. In this regard, urban rooftop farming is the only way out to meet the growing demand for food production with the extra benefits of making our urban areas and cities greener and when the populace is exposed to nature and vegetation, it in turn provides an array of psychological benefits, from decreased anxiety to increased productivity. Bare roofs in cities absorb and then radiate heat — a phenomenon known as the “heat island effect. This increases energy usage and contributes to the poor air quality that often plagues big cities. But Urban rooftop farming do provide many solutions to help cool buildings, ultimately reducing carbon emissions, and by growing food in the communities they serve, rooftop farmers lessen the environmental impact of food transportation. This paper will emphasise the significance of Urban roof farming in the present century which in itself a multi-solution to various city problems.Keywords: urban, roof farming, smart solution, sustainability
Procedia PDF Downloads 14010735 Hospital 4.0 Maturity Assessment Model Development: Case of Moroccan Public Hospitals
Authors: T. Benazzouz, K. Auhmani
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This paper presents a Hospital 4.0 Maturity Assessment Model based on the Industry 4.0 concepts. The self-assessment model defines current and target states of digital transformation by considering multiple aspects of a hospital and a healthcare supply chain. The developed model was validated and evaluated on real-life cases. The resulting model consisted of 5 domains: Technology, Strategy 4.0, Human resources 4.0 & Culture 4.0, Supply chain 4.0 management, and Patient journeys management. Each domain is further divided into several sub-domains, totally 34 sub-domains are identified, that reflect different facets of a hospital 4.0 mature organization.Keywords: hospital 4.0, Industry 4.0, maturity assessment model, supply chain 4.0, patient
Procedia PDF Downloads 9010734 Inventory Decisions for Perishable Products with Age and Stock Dependent Demand Rate
Authors: Maher Agi, Hardik Soni
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This paper presents a deterministic model for optimized control of the inventory of a perishable product subject to both physical deterioration and degradation of its freshness condition. The demand for the product depends on its current inventory level and freshness condition. Our model allows for any positive amount of end of cycle inventory. Some useful conditions that characterize the optimal solution of the model are derived and an algorithm is presented for finding the optimal values of the price, the inventory cycle, the end of cycle inventory level and the order quantity. Numerical examples are then given. Our work shows how the product freshness in conjunction with the inventory deterioration affects the inventory management decisions.Keywords: inventory management, lot sizing, perishable products, deteriorating inventory, age-dependent demand, stock-dependent demand
Procedia PDF Downloads 23410733 Inventory Management System of Seasonal Raw Materials of Feeds at San Jose Batangas through Integer Linear Programming and VBA
Authors: Glenda Marie D. Balitaan
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The branch of business management that deals with inventory planning and control is known as inventory management. It comprises keeping track of supply levels and forecasting demand, as well as scheduling when and how to plan. Keeping excess inventory results in a loss of money, takes up physical space, and raises the risk of damage, spoilage, and loss. On the other hand, too little inventory frequently causes operations to be disrupted and raises the possibility of low customer satisfaction, both of which can be detrimental to a company's reputation. The United Victorious Feed mill Corporation's present inventory management practices were assessed in terms of inventory level, warehouse allocation, ordering frequency, shelf life, and production requirement. To help the company achieve their optimal level of inventory, a mathematical model was created using Integer Linear Programming. Due to the season, the goal function was to reduce the cost of purchasing US Soya and Yellow Corn. Warehouse space, annual production requirements, and shelf life were all considered. To ensure that the user only uses one application to record all relevant information, like production output and delivery, the researcher built a Visual Basic system. Additionally, the technology allows management to change the model's parameters.Keywords: inventory management, integer linear programming, inventory management system, feed mill
Procedia PDF Downloads 8310732 Leveraging Information for Building Supply Chain Competitiveness
Authors: Deepika Joshi
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Operations in automotive industry rely greatly on information shared between Supply Chain (SC) partners. This leads to efficient and effective management of SC activity. Automotive sector in India is growing at 14.2 percent per annum and has huge economic importance. We find that no study has been carried out on the role of information sharing in SC management of Indian automotive manufacturers. Considering this research gap, the present study is planned to establish the significance of information sharing in Indian auto-component supply chain activity. An empirical research was conducted for large scale auto component manufacturers from India. Twenty four Supply Chain Performance Indicators (SCPIs) were collected from existing literature. These elements belong to eight diverse but internally related areas of SC management viz., demand management, cost, technology, delivery, quality, flexibility, buyer-supplier relationship, and operational factors. A pair-wise comparison and an open ended questionnaire were designed using these twenty four SCPIs. The questionnaire was then administered among managerial level employees of twenty-five auto-component manufacturing firms. Analytic Network Process (ANP) technique was used to analyze the response of pair-wise questionnaire. Finally, twenty-five priority indexes are developed, one for each respondent. These were averaged to generate an industry specific priority index. The open-ended questions depicted strategies related to information sharing between buyers and suppliers and their influence on supply chain performance. Results show that the impact of information sharing on certain performance indicators is relatively greater than their corresponding variables. For example, flexibility, delivery, demand and cost related elements have massive impact on information sharing. Technology is relatively less influenced by information sharing but it immensely influence the quality of information shared. Responses obtained from managers reveal that timely and accurate information sharing lowers the cost, increases flexibility and on-time delivery of auto parts, therefore, enhancing the competitiveness of Indian automotive industry. Any flaw in dissemination of information can disturb the cycle time of both the parties and thus increases the opportunity cost. Due to supplier’s involvement in decisions related to design of auto parts, quality conformance is found to improve, leading to reduction in rejection rate. Similarly, mutual commitment to share right information at right time between all levels of SC enhances trust level. SC partners share information to perform comprehensive quality planning to ingrain total quality management. This study contributes to operations management literature which faces scarcity of empirical examination on this subject. It views information sharing as a building block which firms can promote and evolve to leverage the operational capability of all SC members. It will provide insights for Indian managers and researchers as every market is unique and suppliers and buyers are driven by local laws, industry status and future vision. While major emphasis in this paper is given to SC operations happening between domestic partners, placing more focus on international SC can bring in distinguished results.Keywords: Indian auto component industry, information sharing, operations management, supply chain performance indicators
Procedia PDF Downloads 55010731 Part of Geomatics Technology in the Capability to Implement an on Demand Transport in Oran Wilaya (the Northwestern of Algeria)
Authors: N. Brahmia
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The growing needs of displacements led advanced countries in this field install new specific transport systems, able to palliate any deficiencies, especially when regular public transport does not adequately meet the requests of users. In this context, on-demand transport systems (ODT) are very efficient; they rely on techniques based on the location of trip generators which should be assured effectively with the use of operators responsible of the advance reservation, planning and organization, and studying the different ODT criteria. As the advanced countries in the field of transport, some developing countries are involved in the adaptation of the new technologies to reduce the deficit in their communication system. This communication presents the study of an ODT implementation in the west of Algeria, by developing the Geomatics side of the study. This part requires the use of specific systems such as Geographic Information System (GIS), Road Database Management System (RDBMS)… so we developed the process through an application in an environment of mobility by using the computer tools dedicated to the management of the entities related to the transport field.Keywords: geomatics, GIS, ODT, transport systems
Procedia PDF Downloads 59910730 Water Productivity as an Indicator of Bioenergetic Sustainability in Sugarcane
Authors: Rubens Duarte Coelho, Timóteo Herculino da Silva Barros, Jefferson de Olveira Costa
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Brazil has an electrical matrix of predominantly renewable origin, with emphasis on water sources, which account for 65.2%, biomass energy for 8.2%, wind for 6.8% and solar for 0.13% of the domestic supply. Among these sources, sugarcane cultivation stands out, aiming both at the production of bioethanol and biomass to supply “clean energy”. However, like all other crops, sugar cane demands a large volume of a natural resource that is increasingly “scarce” in quantity and quality: water. Adequate and strategic water management throughout the entire sugarcane cycle is of fundamental importance, and water productivity can be used to adjust irrigation planning and decision-making, increasing the productivity of stalks, bioethanol, biomass, and sugar. In this way, water productivity is a good indicator for analysis and decision-making considering the sustainability of cultivation, as it allows evaluation of the variation in the ratio between production and the amount of water used, suggesting values that maximize the use of this natural resource. In this context, studies that relate water demand, in this case, expressed by water productivity, with the energy production of this crop, in this case, expressed by the production of bioethanol, biomass and sugar, are fundamental to obtaining an efficient production of renewable energy, which aims at the rational use of natural resources, especially water. The objective of the present work was to evaluate the response of sugarcane varieties subjected to different water availability to obtain better sustainability in bioenergy production, presenting water productivity indices for Bioethanol, Sugar and Biomass. The variety that responded best was RB966928, with a bioethanol yield of 68.7 L Mg-1. Future research should focus on the water response under each of the sugarcane fractions in terms of their elemental composition so that the influence of water on the energy supply of this crop can be better understood.Keywords: energy matrix, water use, water use efficiency, sustainability
Procedia PDF Downloads 7510729 Urban Energy Demand Modelling: Spatial Analysis Approach
Authors: Hung-Chu Chen, Han Qi, Bauke de Vries
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Energy consumption in the urban environment has attracted numerous researches in recent decades. However, it is comparatively rare to find literary works which investigated 3D spatial analysis of urban energy demand modelling. In order to analyze the spatial correlation between urban morphology and energy demand comprehensively, this paper investigates their relation by using the spatial regression tool. In addition, the spatial regression tool which is applied in this paper is ordinary least squares regression (OLS) and geographically weighted regression (GWR) model. Normalized Difference Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), and building volume are explainers of urban morphology, which act as independent variables of Energy-land use (E-L) model. NDBI and NDVI are used as the index to describe five types of land use: urban area (U), open space (O), artificial green area (G), natural green area (V), and water body (W). Accordingly, annual electricity, gas demand and energy demand are dependent variables of the E-L model. Based on the analytical result of E-L model relation, it revealed that energy demand and urban morphology are closely connected and the possible causes and practical use are discussed. Besides, the spatial analysis methods of OLS and GWR are compared.Keywords: energy demand model, geographically weighted regression, normalized difference built-up index, normalized difference vegetation index, spatial statistics
Procedia PDF Downloads 14810728 Graph Clustering Unveiled: ClusterSyn - A Machine Learning Framework for Predicting Anti-Cancer Drug Synergy Scores
Authors: Babak Bahri, Fatemeh Yassaee Meybodi, Changiz Eslahchi
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In the pursuit of effective cancer therapies, the exploration of combinatorial drug regimens is crucial to leverage synergistic interactions between drugs, thereby improving treatment efficacy and overcoming drug resistance. However, identifying synergistic drug pairs poses challenges due to the vast combinatorial space and limitations of experimental approaches. This study introduces ClusterSyn, a machine learning (ML)-powered framework for classifying anti-cancer drug synergy scores. ClusterSyn employs a two-step approach involving drug clustering and synergy score prediction using a fully connected deep neural network. For each cell line in the training dataset, a drug graph is constructed, with nodes representing drugs and edge weights denoting synergy scores between drug pairs. Drugs are clustered using the Markov clustering (MCL) algorithm, and vectors representing the similarity of drug pairs to each cluster are input into the deep neural network for synergy score prediction (synergy or antagonism). Clustering results demonstrate effective grouping of drugs based on synergy scores, aligning similar synergy profiles. Subsequently, neural network predictions and synergy scores of the two drugs on others within their clusters are used to predict the synergy score of the considered drug pair. This approach facilitates comparative analysis with clustering and regression-based methods, revealing the superior performance of ClusterSyn over state-of-the-art methods like DeepSynergy and DeepDDS on diverse datasets such as Oniel and Almanac. The results highlight the remarkable potential of ClusterSyn as a versatile tool for predicting anti-cancer drug synergy scores.Keywords: drug synergy, clustering, prediction, machine learning., deep learning
Procedia PDF Downloads 7910727 The Influence of Green Supply Chain Management Practices' Implementation on Organizational Performance: An Empirical Case Study in Spain
Authors: Keivan Amirbagheri, Ana Nuñez-Carballosa, Laura Guitart-Tarrés
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Over the last couple of decades, enterprises have begun to accept the need for environmental management and have started to implement environmental management programs to compete in the markets. The implementation of green supply chain management (GSCM) practices can provide valuable opportunities to improve firm performance. Through the prior investigations, the ascending tendency of the numbers of published papers in the field of green supply chain management practices has been reported and it shows the high interest level of the authors to work in this area. Besides, there is still a gap to study more about the relationship of GSCM to the organizational performance (OP). So, the purpose of this research is to study the practices related to green supply chain management that influence the results of the company as an organizational performance. Based on our previous works, from one part we have collected these GSCM practices (planning, operational, and communication practices) and classified them through conducting some literature reviews to analyze their effects on the OP’s factors (balanced scorecard’s perspectives). To do so we design a case study methodology through semi-structured interviews and secondary data from some multinational well-known companies based in Spain. The cases have been selected with the criterion of trying to collect members of the entire supply chain to have a vision as global as possible. The results report the considerable influence of green supply chain management practices on the organizational performance of the companies of the study. In addition, they represent that the implementation of green supply chain management practices especially in a long-term perspective can be economically justified. From the point of view of the personal, they feel better about being a member of this type of company that has been structured on environmental issues. Also, for these companies, the image that has been created by the implementation of these practices helps them to facilitate their marketing program.Keywords: green supply chain management, organizational performance, case study, Spain
Procedia PDF Downloads 19010726 Scientific Perspectives on Autism Over Time
Authors: Gian Marco Di Feo
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Purpose: The study was conducted to examine changes in the beliefs and contents of articles on autism since the mid-twentieth century. Characteristics analyzed were the mentioning of pharmaceutical drugs, country, and institution of the first author, methodologies used, journal, and the year of publication. Methods: All articles (N=566) analyzed were published between January 1st, 1943 and December 31st, 2021. Inter rater reliability was assessed and there was a 94.4 percent agreement amongst raters. All articles were analyzed through both PubMed and PsycInfo. Results: A one way chi square indicated that there was a significant number of articles expressing mixed beliefs on the cause of autism. Scientific perspectives on the cause of autism have changed significantly over time. Particularly, the belief of empiricism (environmental factors) has decreased significantly, while both mixed beliefs and nativism have increased remarkably. Additionally, the mentioning of pharmaceutical drugs is involved with the beliefs on the cause of autism. Conclusion: Articles in the twenty first century are most likely to express both nativist and empiricist viewpoints on the cause of autism. Articles that express mixed beliefs are most likely to mention drugs in their study. The results impact scientific self-understanding on autism and beliefs in high-income countries, and advance scientific understanding globally.Keywords: autism, beliefs, nativism, empiricism, nature, nurture
Procedia PDF Downloads 7210725 Optimization and Coordination of Organic Product Supply Chains under Competition: An Analytical Modeling Perspective
Authors: Mohammadreza Nematollahi, Bahareh Mosadegh Sedghy, Alireza Tajbakhsh
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The last two decades have witnessed substantial attention to organic and sustainable agricultural supply chains. Motivated by real-world practices, this paper aims to address two main challenges observed in organic product supply chains: decentralized decision-making process between farmers and their retailers, and competition between organic products and their conventional counterparts. To this aim, an agricultural supply chain consisting of two farmers, a conventional farmer and an organic farmer who offers an organic version of the same product, is considered. Both farmers distribute their products through a single retailer, where there exists competition between the organic and the conventional product. The retailer, as the market leader, sets the wholesale price, and afterward, the farmers set their production quantity decisions. This paper first models the demand functions of the conventional and organic products by incorporating the effect of asymmetric brand equity, which captures the fact that consumers usually pay a premium for organic due to positive perceptions regarding their health and environmental benefits. Then, profit functions with consideration of some characteristics of organic farming, including crop yield gap and organic cost factor, are modeled. Our research also considers both economies and diseconomies of scale in farming production as well as the effects of organic subsidy paid by the government to support organic farming. This paper explores the investigated supply chain in three scenarios: decentralized, centralized, and coordinated decision-making structures. In the decentralized scenario, the conventional and organic farmers and the retailer maximize their own profits individually. In this case, the interaction between the farmers is modeled under the Bertrand competition, while analyzing the interaction between the retailer and farmers under the Stackelberg game structure. In the centralized model, the optimal production strategies are obtained from the entire supply chain perspective. Analytical models are developed to derive closed-form optimal solutions. Moreover, analytical sensitivity analyses are conducted to explore the effects of main parameters like the crop yield gap, organic cost factor, organic subsidy, and percent price premium of the organic product on the farmers’ and retailer’s optimal strategies. Afterward, a coordination scenario is proposed to convince the three supply chain members to shift from the decentralized to centralized decision-making structure. The results indicate that the proposed coordination scenario provides a win-win-win situation for all three members compared to the decentralized model. Moreover, our paper demonstrates that the coordinated model respectively increases and decreases the production and price of organic produce, which in turn motivates the consumption of organic products in the market. Moreover, the proposed coordination model helps the organic farmer better handle the challenges of organic farming, including the additional cost and crop yield gap. Last but not least, our results highlight the active role of the organic subsidy paid by the government as a means of promoting sustainable organic product supply chains. Our paper shows that although the amount of organic subsidy plays a significant role in the production and sales price of organic products, the allocation method of subsidy between the organic farmer and retailer is not of that importance.Keywords: analytical game-theoretic model, product competition, supply chain coordination, sustainable organic supply chain
Procedia PDF Downloads 11110724 [Keynote Talk]: Green Supply Chain Management Concepts Applied on Brazilian Animal Nutrition Industries
Authors: Laura G. Caixeta, Maico R. Severino
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One of the biggest challenges that the industries find nowadays is to incorporate sustainability practices into its operations. The Green Supply Chain Management (GSCM) concept assists industries in such incorporation. For the full application of this concept is important that enterprises of a same supply chain have the GSCM practices coordinated among themselves. Note that this type of analyses occurs on the context of developed countries and sectors considered big impactors (as automotive, mineral, among others). The propose of this paper is to analyze as the GSCM concepts are applied on the Brazilian animal nutrition industries. The method used was the Case Study. For this, it was selected a supply chain relationship composed by animal nutrition products manufacturer (Enterprise A) and its supplier of animal waste, such as blood, viscera, among others (Enterprise B). First, a literature review was carried out to identify the main GSCM practices. Second, it was done an individual analysis of each one selected enterprise of the application of GSCM concept. For the observed practices, the coordination of each practice in this supply chain was studied. And, it was developed propose of GSCM applications for the practices no observed. The findings of this research were: a) the systematization of main GSCM practices, as: Internal Environment Management, Green Consumption, Green Design, Green Manufacturing, Green Marketing, Green Packaging, Green Procurement, Green Recycling, Life Cycle Analysis, Consultation Selection Method, Environmental Risk Sharing, Investment Recovery, and Reduced Transportation Time; b) the identification of GSCM practices on Enterprise A (7 full application, 3 partial application and 3 no application); c) the identification of GSCM practices on Enterprise B (2 full application, 2 partial application and 9 no application); d) the identification of how is the incentive and the coordination of the GSCM practices on this relationship by Enterprise A; e) proposals of application and coordination of the others GSCM practices on this supply chain relationship. Based on the study, it can be concluded that its possible apply GSCM on animal nutrition industries, and when occurs the motivation on the application of GSCM concepts by a supply chain echelon, these concepts are deployed for the others supply chain echelons by the coordination (orchestration) of the first echelon.Keywords: animal nutrition industries, coordination, green supply chain management, supply chain management, sustainability
Procedia PDF Downloads 13110723 Preparation, Characterization, and in-Vitro Drug Release Study of Methotrexate-Loaded Hydroxyapatite-Sodium Alginate Nanocomposites
Authors: Friday G. Okibe, Edit B. Agbaji, Victor O. Ajibola, Christain C. Onoyima
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Controlled drug delivery systems reduce dose-dependent toxicity associated with potent drugs, including anticancer drugs. In this research, hydroxyapatite (HA) and hydroxyapatite-sodium alginate nanocomposites (HASA) were successfully prepared and characterized using Fourier Transform Infrared spectroscopy (FTIR) and Scanning Electron Microscopy (SEM). The FTIR result showed absorption peaks characteristics of pure hydroxyapatite (HA), and also confirmed the chemical interaction between hydroxyapatite and sodium alginate in the formation of the composite. Image analysis from SEM revealed nano-sized hydroxyapatite and hydroxyapatite-sodium alginate nanocomposites with irregular morphologies. Particle size increased with the formation of the nanocomposites relative to pure hydroxyapatite, with no significant change in particles morphologies. Drug loading and in-vitro drug release study were carried out using synthetic body fluid as the release medium, at pH 7.4 and 37 °C and under perfect sink conditions. The result shows that drug loading is highest for pure hydroxyapatite and decreased with increasing quantity of sodium alginate. However, the release study revealed that HASA-5%wt and HASA-20%wt presented better release profile than pure hydroxyapatite, while HASA-33%wt and HASA-50%wt have poor release profiles. This shows that Methotrexate-loaded hydroxyapatite-sodium alginate if prepared under optimal conditions is a potential carrier for effective delivery of Methotrexate.Keywords: drug-delivery, hydroxyapatite, methotrexate, nanocomposites, sodium alginate
Procedia PDF Downloads 27810722 The Impact of Quality Cost on Revenue Sharing in Supply Chain Management
Authors: Fayza M. Obied-Allah
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Customer’ needs, quality, and value creation while reducing costs through supply chain management provides challenges and opportunities for companies and researchers. In the light of these challenges, modern ideas must contribute to counter these challenges and exploit opportunities. Perhaps this paper will be one of these contributions. This paper discusses the impact of the quality cost on revenue sharing as a most important incentive to configure business networks. No doubt that the costs directly affect the size of income generated by a business network, so this paper investigates the impact of quality costs on business networks revenue, and their impact on the decision to participate the revenue among the companies in the supply chain. This paper develops the quality cost approach to align with the modern era, the developed model includes five categories besides the well-known four categories (namely prevention costs, appraisal costs, internal failure costs, and external failure costs), a new category has been developed in this research as a new vision of the relationship between quality costs and innovations of industry. This new category is Recycle Cost. This paper is organized into six sections, Section I shows quality costs overview in the supply chain. Section II discusses revenue sharing between the parties in supply chain. Section III investigates the impact of quality costs in revenue sharing decision between partners in supply chain. The fourth section includes survey study and presents statistical results. Section V discusses the results and shows future opportunities for research. Finally, Section VI summarizes the theoretical and practical results of this paper.Keywords: quality cost, recycle cost, revenue sharing, supply chain management
Procedia PDF Downloads 44310721 Ozonation as an Effective Method to Remove Pharmaceuticals from Biologically Treated Wastewater of Different Origin
Authors: Agne Jucyte Cicine, Vytautas Abromaitis, Zita Rasuole Gasiunaite, I. Vybernaite-Lubiene, D. Overlinge, K. Vilke
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Pharmaceutical pollution in aquatic environments has become a growing concern. Various active pharmaceutical ingredient (API) residues, hormones, antibiotics, or/and psychiatric drugs, have already been discovered in different environmental compartments. Due to existing ineffective wastewater treatment technologies to remove APIs, an underestimated amount can enter the ecosystem by discharged treated wastewater. Especially, psychiatric compounds, such as carbamazepine (CBZ) and venlafaxine (VNX), persist in effluent even post-treatment. Therefore, these pharmaceuticals usually exceed safe environmental levels and pose risks to the aquatic environment, particularly to sensitive ecosystems such as the Baltic Sea. CBZ, known for its chemical stability and long biodegradation time, accumulates in the environment, threatening aquatic life and human health through the food chain. As the use of medication rises, there is an urgent need for advanced wastewater treatment to reduce pharmaceutical contamination and meet future regulatory requirements. In this study, we tested advanced oxidation technology using ozone to remove two commonly used psychiatric drugs (carbamazepine and venlafaxine) from biologically treated wastewater effluent. Additionally, general water quality parameters (suspended matter (SPM), dissolved organic carbon (DOC), chemical oxygen demand (COD), and bacterial presence were analyzed. Three wastewater treatment plants (WWTPs) representing different anthropogenic pressures were selected: 1) resort, 2) resort and residential, and 3) residential, industrial, and resort. Wastewater samples for the experiment were collected during the summer season after mechanical and biological treatment and ozonated for 5, 10, and 15 minutes. The initial dissolved ozone concentration of 7,3±0,7 mg/L was held constant during all the experiments. Pharmaceutical levels in this study exceeded the predicted no-effect concentration (PNEC) of 500 and 90 ng L⁻¹ for CBZ and VNX, respectively, in all WWTPs, except CBZ in WWTP 1. Initial CBZ contamination was found to be lower in WWTP 1 (427.4 ng L⁻¹), compared with WWTP 2 (1266.5 ng L⁻¹) and 3 (119.2 ng L⁻¹). VNX followed a similar trend with concentrations of 341.2 ng L⁻¹, 361.4 ng L⁻¹, and 390.0 ng L⁻¹, respectively, for WWTPs 1, 2, and 3. It was determined that CBZ was not detected in the effluent after 5 minutes of ozonation in any of the WWTPs. Contrarily, VNX was still detected after 5, 10, and 15 minutes of treatment with ozone, however, under the limits of quantification (LOD) (<5ng L⁻¹). Additionally, general pollution of SPM, DOC, COD, and bacterial contamination was reduced notably after 5 minutes of treatment with ozone, while no bacterial growth was obtained. Although initial pharmaceutical levels exceeded PNECs, indicating ongoing environmental risks, ozonation demonstrated high efficiency in reducing pharmaceutical and general contamination in wastewater with different pollution matrices.Keywords: Baltic Sea, ozonation, pharmaceuticals, wastewater treatment plants
Procedia PDF Downloads 1910720 The Environmental and Economic Analysis of Extended Input-Output Table for Thailand’s Biomass Pellet Industry
Authors: Prangvalai Buasan, Boonrod Sajjakulnukit, Thongchart Bowonthumrongchai
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The demand for biomass pellets in the industrial sector has significantly increased since 2020. The revised version of Thailand’s power development plan as well as the Alternative Energy Development Plan, aims to promote biomass fuel consumption by around 485 MW by 2030. The replacement of solid fossil fuel with biomass pellets will affect medium-term and long-term national benefits for all industries throughout the supply chain. Therefore, the evaluation of environmental and economic impacts throughout the biomass pellet supply chain needs to be performed to provide better insight into the goods and financial flow of this activity. This study extended the national input-output table for the biomass pellet industry and applied the input-output analysis (IOA) method, a sort of macroeconomic analysis, to interpret the result of transactions between industries in the monetary unit when the revised national power development plan was adopted and enforced. Greenhouse gas emissions from consuming energy and raw material through the supply chain are also evaluated. The total intermediate transactions of all economic sectors, which included the biomass pellets sector (CASE 2), increased by 0.02% when compared with the conservative case (CASE 1). The control total, which is the sum of total intermediate transactions and value-added, the control total of CASE 2 is increased by 0.07% when compared with CASE 1. The pellet production process emitted 432.26 MtCO2e per year. The major sharing of the GHG is from the plantation process of raw biomass.Keywords: input-output analysis, environmental extended input-output analysis, macroeconomic planning, biomass pellets, renewable energy
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