Search results for: real-time demand

Authors: A. Almaneea, N. Kapur, J. L. Summers, H. M. Thompson

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Meeting the growth in demand for digital services such as social media, telecommunications, and business and cloud services requires large scale data centres, which has led to an increase in their end use energy demand. Generally, over 30% of data centre power is consumed by the necessary cooling overhead. Thus energy can be reduced by improving the cooling efficiency. Air and liquid can both be used as cooling media for the data centre. Traditional data centre cooling systems use air, however liquid is recognised as a promising method that can handle the more densely packed data centres. Liquid cooling can be classified into three methods; rack heat exchanger, on-chip heat exchanger and full immersion of the microelectronics. This study quantifies the improvements of heat transfer specifically for the case of immersed microelectronics by varying the CPU and heat sink location. Immersion of the server is achieved by filling the gap between the microelectronics and a water jacket with a dielectric liquid which convects the heat from the CPU to the water jacket on the opposite side. Heat transfer is governed by two physical mechanisms, which is natural convection for the fixed enclosure filled with dielectric liquid and forced convection for the water that is pumped through the water jacket. The model in this study is validated with published numerical and experimental work and shows good agreement with previous work. The results show that the heat transfer performance and Nusselt number (Nu) is improved by 89% by placing the CPU and heat sink on the bottom of the microelectronics enclosure.

Keywords: CPU location, data centre cooling, heat sink in enclosures, immersed microelectronics, turbulent natural convection in enclosures

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Authors: Elaine Wong Yee-Sing, Liaw Wee Tong

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Rapid transformations in demographic and socioeconomic shifts are leading to a growing global demand for health and beauty products and services that demands holistic concepts of well-being. In addition, technological breakthroughs such as internet of things make it convenient and offer innovative solutions for well-being and engage consumers to track their own health conditions and fitness goals. This 'new health economy' encompasses three key concepts: well-being, well-conditioned and well-shaped; which are shaped by wellness segments and goals that influence purchasing decisions of consumers. The research protocol aims to examine the feasibility, challenges, and capabilities in provision for each customer with an ecosystem, or platform, that organizes data and insights to create an individual health and fitness, nutrition, and beauty profile. Convenience sampling of 100 consumers residing in private housing within five major districts in Singapore will be selected to participate in the study. Statistical Package for Social Science 25 will be used to conduct descriptive statistics for quantitative data while qualitative data results using focus interviews, will be translated and transcribed to identify improvements in provision of these services. Rising income in emerging global markets is fuelling the demand for these general wellbeing products and services. Combined with technological advances, it is imperative to understand how these highly personalized services with integrated technology can be designed better to support consumer preferences; provide greater flexibility and high-quality service, and generate better health awareness among consumers.

Keywords: beauty, consumers, health, technology, wellness

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Authors: Pierluigi Gallo, Francesco Randazzo, Ignazio Gallo

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In recent years, many new and interesting models of successful online business have been developed. Many of these are based on the competition between users, such as online auctions, where the product price is not fixed and tends to rise. Other models, including group-buying, are based on cooperation between users, characterized by a dynamic price of the product that tends to go down. There is not yet a business model in which both sellers and buyers are grouped in order to negotiate on a specific product or service. The present study investigates a new extension of the group-buying model, called fair, which allows aggregation of demand and supply for price optimization, in a cooperative manner. Additionally, our system also aggregates products and destinations for shipping optimization. We introduced the following new relevant input parameters in order to implement a double-side aggregation: (a) price-quantity curves provided by the seller; (b) waiting time, that is, the longer buyers wait, the greater discount they get; (c) payment time, which determines if the buyer pays before, during or after receiving the product; (d) the distance between the place where products are available and the place of shipment, provided in advance by the buyer or dynamically suggested by the system. To analyze the proposed model we implemented a system prototype and a simulator that allows studying effects of changing some input parameters. We analyzed the dynamic price model in fairs having one single seller and a combination of selected sellers. The results are very encouraging and motivate further investigation on this topic.

Keywords: auction, aggregation, fair, group buying, social buying

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Authors: Alexander B. Barker, Megan Parkin, Shreesh Sinha, Emma Wilson, Rachael L. Murray

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Objectives: Exposure to HFSS imagery is associated with consumption of foods high in fat, sugar, or salt (HFSS), and subsequently obesity, among young people. We report and compare the results of two content analyses, one of two popular terrestrial children’s television channels in the UK and the other of a selection of children’s programs available on video-on-demand (VOD) streaming sites. Design: Content analysis of three days’ worth of programs (including advertisements) on two popular children’s television channels broadcast on UK television (CBeebies and Milkshake) as well as a sample of 40 highest-rated children’s programs available on the VOD platforms, Netflix and Amazon Prime, using 1-minute interval coding. Setting: United Kingdom, Participants: None. Results: HFSS content was seen in 181 broadcasts (36%) and in 417 intervals (13%) on terrestrial television, ‘Milkshake’ had a significantly higher proportion of programs/adverts which contained HFSS content than ‘CBeebies’. In VOD platforms, HFSS content was seen in 82 episodes (72% of the total number of episodes), across 459 intervals (19% of the total number of intervals), with no significant difference in the proportion of programs containing HFSS content between Netflix and Amazon Prime. Conclusions: This study demonstrates that HFSS content is common in both popular UK children’s television channels and children's programs on VOD services. Since previous research has shown that HFSS content in the media has an effect on HFSS consumption, children’s television programs broadcast either on TV or VOD services are likely having an effect on HFSS consumption in children and legislative opportunities to prevent this exposure are being missed.

Keywords: public health, epidemiology, obesity, content analysis

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Authors: Nana Segu Acquaah-Harrison, James Osei Mensah, Richard Aidoo, David Amponsah, Amy Buah, Gilbert Aboagye

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The study aimed at assessing the feasibility of commercial meat rabbit production in the Kumasi Metropolis of Ghana. Structured and unstructured questionnaires were utilized in obtaining information from two hundred meat consumers and 15 meat rabbit farmers. Data were analyzed using Net Present Value (NPV), Internal Rate of Return (IRR), Benefit Cost Ratio (BCR)/Profitability Index (PI) technique, percentages and chi-square contingency test. The study found that the current demand for rabbit meat is low (36%). The desirable nutritional attributes of rabbit meat and other socio economic factors of meat consumers make the potential demand for rabbit meat high (69%). It was estimated that GH¢5,292 (approximately $ 2672) was needed as a start-up capital for a 40-doe unit meat rabbit farm in Kumasi Metropolis. The cost of breeding animals, housing and equipment formed 12.47%, 53.97% and 24.87% respectively of the initial estimated capital. A Net Present Value of GH¢ 5,910.75 (approximately $ 2984) was obtained at the end of the fifth year, with an internal rate return and profitability index of 70% and 1.12 respectively. The major constraints identified in meat rabbit production were low price of rabbit meat, shortage of fodder, pest and diseases, high cost of capital, high cost of operating materials and veterinary care. Based on the analysis, it was concluded that meat rabbit production is feasible in the Kumasi Metropolis of Ghana. The study recommends embarking on mass advertisement; farmer association and adapting to new technologies in the production process will help to enhance productivity.

Keywords: feasibility, commercial meat rabbit, production, Kumasi, Ghana

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Authors: A. Rong, P. B. Luh, R. Lahdelma

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High penetration of intermittent renewable energy sources (RES) such as solar power and wind power into the energy system has caused temporal and spatial imbalance between electric power supply and demand for some countries and regions. This brings about the critical need for coordinating power production and power exchange for different regions. As compared with the power-only systems, the combined heat and power (CHP) systems can provide additional flexibility of utilizing RES by exploiting the interdependence of power and heat production in the CHP plant. In the CHP system, power production can be influenced by adjusting heat production level and electric power can be used to satisfy heat demand by electric boiler or heat pump in conjunction with heat storage, which is much cheaper than electric storage. This paper addresses multi-site CHP systems without considering RES, which lay foundation for handling penetration of RES. The problem under study is the unit commitment (UC) of the transmission-constrained multi-site CHP systems. We solve the problem by combining linear relaxation of ON/OFF states and sequential dynamic programming (DP) techniques, where relaxed states are used to reduce the dimension of the UC problem and DP for improving the solution quality. Numerical results for daily scheduling with realistic models and data show that DP-based algorithm is from a few to a few hundred times faster than CPLEX (standard commercial optimization software) with good solution accuracy (less than 1% relative gap from the optimal solution on the average).

Keywords: dynamic programming, multi-site combined heat and power system, relaxed states, transmission-constrained generation unit commitment

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Authors: Vedansh Gupta, Allyson Lutz, Ameen Razavi, Fatemeh Shirazi

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The agriculture industry is especially vulnerable to forecasted water shortages. In the fresh and fresh-cut produce sector, conventional flume-based washing with recirculation exhibits high water demand. This leads to a large water footprint and possible cross-contamination of pathogens. These can be alleviated through advanced water reuse processes, such as membrane technologies including reverse osmosis (RO). Water reuse technologies effectively remove dissolved constituents but can easily foul without pre-treatment. Biological treatment is effective for the removal of organic compounds responsible for fouling, but not at the low temperatures encountered at most produce processing facilities. This study showed that the Microvi MicroNiche Engineering (MNE) technology effectively removes organic compounds (> 80%) at low temperatures (6-8 °C) from wash water. The MNE technology uses synthetic microorganism-material composites with negligible solids production, making it advantageously situated as an effective bio-pretreatment for RO. A preliminary technoeconomic analysis showed 60-80% savings in operation and maintenance costs (OPEX) when using the Microvi MNE technology for organics removal. This study and the accompanying economic analysis indicated that the proposed technology process will substantially reduce the cost barrier for adopting water reuse practices, thereby contributing to increased food safety and furthering sustainable water reuse processes across the agricultural industry.

Keywords: biological pre-treatment, innovative technology, vegetable processing, water reuse, agriculture, reverse osmosis, MNE biocatalysts

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Authors: Francisco Dos Santos, Diogo Fonseca-Pereira, Sílvia Arroz-Madeira, Henrique Veiga-Fernandes

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Haematopoiesis is a developmental process that generates all blood cell lineages in health and disease. This relies on quiescent haematopoietic stem cells (HSCs) that are able to differentiate, self renew and expand upon physiological demand. HSCs have great interest in regenerative medicine, including haematological malignancies, immunodeficiencies and metabolic disorders. However, the limited yield from existing HSC sources drives the global need for reliable techniques to expand harvested HSCs at high quality and sufficient quantities. With the extensive use of cord blood progenitors for clinical applications, there is a demand for a safe and efficient expansion protocol that is able to overcome the limitations of the cord blood as a source of HSC. StemCell2MAXTM developed a technology that enhances the survival, proliferation and transplantation efficiency of HSC, leading the way to a more widespread use of HSC for research and clinical purposes. StemCell2MAXTM MIX is a solution that improves HSC expansion up to 20x, while preserving stemness, when compared to state-of-the-art. In a recent study by a leading cord blood bank, StemCell2MAX MIX was shown to support a selective 100-fold expansion of CD34+ Hematopoietic Stem and Progenitor Cells (when compared to a 10-fold expansion of Total Nucleated Cells), while maintaining their multipotent differentiative potential as assessed by CFU assays. The technology developed by StemCell2MAXTM opens new horizons for the usage of expanded hematopoietic progenitors for both research purposes (including quality and functional assays in Cord Blood Banks) and clinical applications.

Keywords: cord blood, expansion, hematopoietic stem cell, transplantation

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Authors: Ratri Werdiningtyas, Yongping Wei, Andrew Western

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The status quo of social-ecological systems is the results of not only natural processes but also the accumulated consequence of policies applied in the past. Often water management objectives are challenging and are only achieved to a limited degree on the ground. In choosing water management approaches, it is important to account for current conditions and important differences due to varied histories. Since the mid-nineteenth century, Victorian water management has evolved through a series of policy regime shifts. The main goal of this research to explore and identify the stages of the evolution of the water policy instruments as practiced in Victoria from 1890-2016. This comparative historical analysis has identified four stages in Victorian policy instrument development. In the first stage, the creation of policy instruments aimed to match the demand and supply of the resource (reserve condition). The second stage begins after natural system alone failed to balance supply and demand. The focus of the policy instrument shifted to an authority perspective in this stage. Later, the increasing number of actors interested in water led to another change in policy instrument. The third stage focused on the significant role of information from different relevant actors. The fourth and current stage is the most advanced, in that it involved the creation of a policy instrument for synergizing the previous three focal factors: reserve, authority, and information. When considering policy in other jurisdiction, these findings suggest that a key priority should be to reflect on the jurisdictions current position among these four evolutionary stages and try to make improve progressively rather than directly adopting approaches from elsewhere without understanding the current position.

Keywords: policy instrument, policy transformation, socio-ecolgical system, water management

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Authors: Jang kyun Cho, Jeong-dong Lee

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The advent of the Internet, mobile communications, and social network services has stimulated social interactions among consumers, allowing people to affect one another’s innovation adoptions by exchanging information more frequently and more quickly. Previous diffusion models, such as the Bass model, however, face limitations in reflecting such recent phenomena in society. These models are weak in their ability to model interactions between agents; they model aggregated-level behaviors only. The agent based model, which is an alternative to the aggregate model, is good for individual modeling, but it is still not based on an economic perspective of social interactions so far. This study assumes the presence of social utility from other consumers in the adoption of innovation and investigates the effect of individual interactions on innovation diffusion by developing a new model called the interaction-based diffusion model. By comparing this model with previous diffusion models, the study also examines how the proposed model explains innovation diffusion from the perspective of economics. In addition, the study recommends the use of a small-world network topology instead of cellular automata to describe innovation diffusion. This study develops a model based on individual preference and heterogeneous social interactions using utility specification, which is expandable and, thus, able to encompass various issues in diffusion research, such as reservation price. Furthermore, the study proposes a new framework to forecast aggregated-level market demand from individual level modeling. The model also exhibits a good fit to real market data. It is expected that the study will contribute to our understanding of the innovation diffusion process through its microeconomic theoretical approach.

Keywords: innovation diffusion, agent based model, small-world network, demand forecasting

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Authors: Albana Kashtanjeva-Bytyçi, Idriz Vehapi, Rifat Morina, Osman Fetoshi

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The purpose of this study is to determine the water quality in Batllava Leka through which a part of the population of the Prishtina region is supplied with drinking water. Batllava Leka is a lake built in the 70s. This lake is located in the village of Btlava in the municipality of Podujeva, with coordinates 42 ° 49′33 ″ V 21 ° 18′25 ″ L, with an area of 3.07 km2. Water supply is from the river Brvenica- Batllavë. In order to take preventive measures and improve water quality, we have conducted periodic/monthly monitoring of water quality in Lake Batllava, through microbiological and physico-chemical indicators. The monitoring was carried out during the period December 2020 - December 2021. Samples were taken at three sampling sites: at the entrance of the lake, in the middle and at the overflow, on two levels, water surface and at a depth of 30 cm. The microbiological parameters analyzed are: total coliforms, fecal coliforms, fecal streptococci, aerobic mesophilic bacteria and actinomycetes. Within the physico-chemical parameters: Dissolved Oxygen, Saturation with O2, water temperature, pH value, electrical conductivity, total soluble matter, total suspended matter, turbidity, chemical oxygen demand, biochemical oxygen demand, total organic carbon, nitrate, total hardness, hardness of calcium, calcium, magnesium, ammonium ion, chloride, sulfates, flourine, M-alkalines, bicarbonates and heavy metals, such as: Fe, Pb, Mn, Cu, Cd. The results showed that most of the physico-chemical and microbiological parameters are within the limit allowed by the WHO, except in the case of the rainiest season that exceeded some parameters.

Keywords: batllava lake, monitoring of water, physico-chemical, microbiological, heavy metals

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Authors: Oluwaseun Adeleke, Samuel O. Ikani, Fidelis Edet, Anthony Nwala, Mopelola Raji, Simeon Christian Chukwu

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Background The Delivering Innovations in Selfcare (DISC) project promotes universal access to quality selfcare services beginning with subcutaneous depot medroxy progesterone acetate (DMPA-SC) contraceptive self-injection (SI) option. Self-inject (SI) offers women a highly effective and convenient option that saves them frequent trips to providers. Its increased use has the potential to improve the efficiency of an overstretched healthcare system by reducing provider workloads. State Social and Behavioral Change Communications (SBCC) Officers lead project demand creation and service delivery innovations that have resulted in significant increases in SI uptake among women who opt for injectables. Strategies Service Delivery Innovations The implementation of the "Moment of Truth (MoT)" innovation helped providers overcome biases and address client fear and reluctance to self-inject. Bi-annual program audits and supportive mentoring visits helped providers retain their competence and motivation. Proper documentation, tracking, and replenishment of commodities were ensured through effective engagement with State Logistics Units. The project supported existing state monitoring and evaluation structures to effectively record and report subcutaneous depot medroxy progesterone acetate (DMPA-SC) service utilization. Demand creation Innovations SBCC Officers provide oversight, routinely evaluate performance, trains, and provides feedback for the demand creation activities implemented by community mobilizers (CMs). The scope and intensity of training given to CMs affect the outcome of their work. The project operates a demand creation model that uses a schedule to inform the conduct of interpersonal and group events. Health education sessions are specifically designed to counter misinformation, address questions and concerns, and educate target audience in an informed choice context. The project mapped facilities and their catchment areas and enlisted the support of identified influencers and gatekeepers to enlist their buy-in prior to entry. Each mobilization event began with pre-mobilization sensitization activities, particularly targeting male groups. Context-specific interventions were informed by the religious, traditional, and cultural peculiarities of target communities. Mobilizers also support clients to engage with and navigate online digital Family Planning (FP) online portals such as DiscoverYourPower website, Facebook page, digital companion (chat bot), interactive voice response (IVR), radio and television (TV) messaging. This improves compliance and provides linkages to nearby facilities. Results The project recorded 136,950 self-injection (SI) visits and a self-injection (SI) proportion rate that increased from 13 percent before the implementation of interventions in 2021 to 62 percent currently. The project cost-effectively demonstrated catalytic impact by leveraging state and partner resources, institutional platforms, and geographic scope to scale up interventions. The project also cost effectively demonstrated catalytic impact by leveraging on the state and partner resources, institutional platforms, and geographic scope to sustainably scale-up these strategies. Conclusion Using evidence-informed iterations of service delivery and demand creation models have been useful to significantly drive self-injection (SI) uptake. It will be useful to consider this implementation model during program design. Contemplation should also be given to systematic and strategic execution of strategies to optimize impact.

Keywords: family planning, contraception, DMPA-SC, self-care, self-injection, innovation, service delivery, demand creation.

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Authors: Ahmad Naqi

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Today, the passively controlled buildings are extensively becoming popular due to its excellent lateral load resistance circumstance. Typically, these buildings are enhanced with a damping device that has high market demand. Some manufacturer falsified the damping device parameter during the production to achieve the market demand. Therefore, this paper evaluates the seismic performance of buildings equipped with damping devices, which their parameter modified to simulate the falsified devices, intentionally. For this purpose, three benchmark buildings of 4-, 10-, and 20-story were selected from JSSI (Japan Society of Seismic Isolation) manual. The buildings are special moment resisting steel frame with oil damper in the longitudinal direction only. For each benchmark buildings, two types of structural elements are designed to resist the lateral load with and without damping devices (hereafter, known as Trimmed & Conventional Building). The target building was modeled using STERA-3D, a finite element based software coded for study purpose. Practicing the software one can develop either three-dimensional Model (3DM) or Lumped Mass model (LMM). Firstly, the seismic performance of 3DM and LMM models was evaluated and found excellent coincide for the target buildings. The simplified model of LMM used in this study to produce 66 cases for both of the buildings. Then, the device parameters were modified by ± 40% and ±20% to predict many possible conditions of falsification. It is verified that the building which is design to sustain the lateral load with support of damping device (Trimmed Building) are much more under threat as a result of device falsification than those building strengthen by damping device (Conventional Building).

Keywords: passive control system, oil damper, seismic assessment, lumped mass model

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Authors: Agada N. Ihuoma, Nagata Yasunori

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Artificial intelligence (AI) techniques play a crucial role in predicting the expected energy outcome and its performance, analysis, modeling, and control of renewable energy. Renewable energy is becoming more popular for economic and environmental reasons. In the face of global energy consumption and increased depletion of most fossil fuels, the world is faced with the challenges of meeting the ever-increasing energy demands. Therefore, incorporating artificial intelligence to predict solar radiation outcomes from the intermittent sunlight is crucial to enable a balance between supply and demand of energy on loads, predict the performance and outcome of solar energy, enhance production planning and energy management, and ensure proper sizing of parameters when generating clean energy. However, one of the major problems of forecasting is the algorithms used to control, model, and predict performances of the energy systems, which are complicated and involves large computer power, differential equations, and time series. Also, having unreliable data (poor quality) for solar radiation over a geographical location as well as insufficient long series can be a bottleneck to actualization. To overcome these problems, this study employs the anaconda Navigator (Jupyter Notebook) for machine learning which can combine larger amounts of data with fast, iterative processing and intelligent algorithms allowing the software to learn automatically from patterns or features to predict the performance and outcome of Solar Energy which in turns enables the balance of supply and demand on loads as well as enhance production planning and energy management.

Keywords: artificial Intelligence, backward elimination, linear regression, solar energy

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Authors: Jennifer Holbein, Maritza Wiedel

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Background: Aging is associated with an increased risk of falls in older adults, and as a result, falls have become public health crises. However, the incidence of falls can be reduced through healthy aging and the implementation of a regular exercise and strengthening program. Public health and healthcare professionals authorize the use of evidence‐based, exercise‐focused fall interventions, but there are major obstacles to translating and disseminating research findings into healthcare practices. The purpose of this study was to assess the feasibility of an intervention, A Matter of Balance, in terms of demand, acceptability, and implementation into current exercise programs. Subjects: Seventy-five participants from rural communities, above the age of sixty, were randomized to an intervention or attention-control of the standardized senior fitness test. Methods: Subject completes the intervention, which combines two components: (1) motivation and (2) fall-reducing physical activities with protocols derived from baseline strength and balanced assessments. Participants (n=75) took part in the program after completing baseline functional assessments as well as evaluations of their personal knowledge, health outcomes, demand, and implementation interventions. After 8-weeks of the program, participants were invited to complete follow-up assessments with results that were compared to their baseline functional analyses. Out of all the participants in the study who complete the initial assessment, approximately 80% are expected to maintain enrollment in the implemented prescription. Furthermore, those who commit to the program should show mitigation of fall risk upon completion of their final assessment.

Keywords: aging population, exercise, falls, functional assessment, healthy aging

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Authors: Xiaolei Hu, Enrico Ferrera, Riccardo Tomasi, Claudio Pastrone

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Load Forecasting plays a key role in making today's and future's Smart Energy Grids sustainable and reliable. Accurate power consumption prediction allows utilities to organize in advance their resources or to execute Demand Response strategies more effectively, which enables several features such as higher sustainability, better quality of service, and affordable electricity tariffs. It is easy yet effective to apply Load Forecasting at larger geographic scale, i.e. Smart Micro Grids, wherein the lower available grid flexibility makes accurate prediction more critical in Demand Response applications. This paper analyses the application of short-term load forecasting in a concrete scenario, proposed within the EU-funded GreenCom project, which collect load data from single loads and households belonging to a Smart Micro Grid. Three short-term load forecasting techniques, i.e. linear regression, artificial neural networks, and radial basis function network, are considered, compared, and evaluated through absolute forecast errors and training time. The influence of weather conditions in Load Forecasting is also evaluated. A new definition of Gain is introduced in this paper, which innovatively serves as an indicator of short-term prediction capabilities of time spam consistency. Two models, 24- and 1-hour-ahead forecasting, are built to comprehensively compare these three techniques.

Keywords: short-term load forecasting, smart micro grid, linear regression, artificial neural networks, radial basis function network, gain

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Authors: Ginés Hernández-Cánovas, Mª Camino Ramón-Llorens, Johanna Koëter-Kant

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This paper uses a survey data-set of 837 Spanish SMEs to analyze the association between borrower discouragement and prior firm´s strategic decisions, while controlling for firm and owner characteristics. While existing literature has neglected factors limiting the demand for resources by an overreliance on arguments which attempt to explain the existence of discouraged borrowers solely in terms of lack of access to supply of credit. The objective of this paper is to show that factors limiting the demand for resources and, therefore, reducing the availability of funds, can be traced back to the firm manager´s decision. Our hypothesis is that managers that undertake strategic decisions seeking growth or improvement in their business performance participate more in the banking market than those showing contentment with their current business situation. Our results shows that SMEs that undertake an active role in research and development activities and that achieve improvements in the operating performance of their business are less likely to be discouraged from applying for a loan. Who needs credit and who applies for credit is important for firms, prospective lenders and policymakers interested in the financial health of these firms. Credit constrained firms are less likely to invest in R&D and to introduce new products, possibly harming long-term economic growth. Knowing how important borrower discouragement is in Europe, is important for judging the priority which should be attached to government policies aimed at reducing its effects. For example, policy makers could encourage the transparency about credit eligibility and conditions in order to reduce discouragement.

Keywords: discouragement, financial constraints, SMEs financing

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Authors: Alfonso Ippolito, Cristiana Bartolomei

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A growing demand is felt today for realistic 3D models enabling the cognition and popularization of historical-artistic heritage. Evaluation and preservation of Cultural Heritage is inextricably connected with the innovative processes of gaining, managing, and using knowledge. The development and perfecting of techniques for acquiring and elaborating photorealistic 3D models, made them pivotal elements for popularizing information of objects on the scale of architectonic structures.

Keywords: cultural heritage, databases, non-contact survey, 2D-3D models

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Authors: Usama Abdulwahab, Mohammed Wahab

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This paper presents the application of uncapacitated facility location problems (UFLP) and 1-median problems to support decision making in blood supply chain networks. A plethora of factors make blood supply-chain networks a complex, yet vital problem for the regional blood bank. These factors are rapidly increasing demand; criticality of the product; strict storage and handling requirements; and the vastness of the theater of operations. As in the UFLP, facilities can be opened at any of $m$ predefined locations with given fixed costs. Clients have to be allocated to the open facilities. In classical location models, the allocation cost is the distance between a client and an open facility. In this model, the costs are the allocation cost, transportation costs, and inventory costs. In order to address this problem the median algorithm is used to analyze inventory, evaluate supply chain status, monitor performance metrics at different levels of granularity, and detect potential problems and opportunities for improvement. The Euclidean distance data for some Ontario cities (demand nodes) are used to test the developed algorithm. Sitation software, lagrangian relaxation algorithm, and branch and bound heuristics are used to solve this model. Computational experiments confirm the efficiency of the proposed approach. Compared to the existing modeling and solution methods, the median algorithm approach not only provides a more general modeling framework but also leads to efficient solution times in general.

Keywords: approximate dynamic programming, facility location, perishable product, inventory model, blood platelet, P-median problem

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Authors: Misagh Ghobadi, Rich Crane, Karen Hudson-Edwards, Clemens Vinzenz Ullmann

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Lithium is recognized as the critical energy metal of the 21st century, comparable in importance to coal in the 19th century and oil in the 20th century, often termed 'white gold'. Current global demand for lithium, estimated at 0.95-0.98 million metric tons (Mt) of lithium carbonate equivalent (LCE) annually in 2024, is projected to rise to 1.87 Mt by 2027 and 3.06 Mt by 2030. Despite anticipated short-term stability in supply and demand, meeting the forecasted 2030 demand will require the lithium industry to develop an additional capacity of 1.42 Mt of LCE annually, exceeding current planned and ongoing efforts. Brine resources constitute nearly 65% of global lithium reserves, underscoring the importance of exploring lithium recovery from underutilized sources, especially geothermal brines. However, conventional lithium extraction from brine deposits faces challenges due to its time-intensive process, low efficiency (30-50% lithium recovery), unsuitability for low lithium concentrations (<300 mg/l), and notable environmental impacts. Addressing these challenges, direct lithium extraction (DLE) methods have emerged as promising technologies capable of economically extracting lithium even from low-concentration brines (>50 mg/l) with high recovery rates (75-98%). However, most studies (70%) have predominantly focused on synthetic brines instead of native (natural/real), with limited application of these approaches in real-world case studies or industrial settings. This study aims to bridge this gap by investigating a geothermal brine sample collected from a real case study site in the UK. A Mn-based lithium-ion sieve (LIS) adsorbent was synthesized and employed to selectively extract lithium from the sample brine. Adsorbents with a Li:Mn molar ratio of 1:1 demonstrated superior lithium selectivity and adsorption capacity. Furthermore, the pristine Mn-based adsorbent was modified through transition metals doping, resulting in enhanced lithium selectivity and adsorption capacity. The modified adsorbent exhibited a higher separation factor for lithium over major co-existing cations such as Ca, Mg, Na, and K, with separation factors exceeding 200. The adsorption behaviour was well-described by the Langmuir model, indicating monolayer adsorption, and the kinetics followed a pseudo-second-order mechanism, suggesting chemisorption at the solid surface. Thermodynamically, negative ΔG° values and positive ΔH° and ΔS° values were observed, indicating the spontaneity and endothermic nature of the adsorption process.

Keywords: adsorption, critical minerals, DLE, geothermal brines, geochemistry, lithium, lithium-ion sieves

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Authors: Akilah A. Jardine

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The integration and expansion of the global economy have indeed brought about a number of positive changes such as access to new goods and services and the opportunity for individuals and businesses to migrate, communicate, and work globally. Nevertheless, the interconnectedness of world economies is not without its negative and shameful side effects. The subsequent overabundance of goods and services has resulted in heightened competition among firms and their supply chains, fuelling the exploitation of impoverished and vulnerable individuals who are unable to equally salvage from the benefits of the integrated economy. To maintain their position in a highly competitive arena, the operations of many businesses have adopted unethical and unscrupulous practices to maximise profit, often targeting the most marginalised members of society. Simultaneously, in a consumerist obsessed society preoccupied with the consumption and accumulation of material wealth, the demand for goods and services greatly contributes to the pressure on firms, thus bolstering the exploitation of labour. This paper aims to examine the impact of business operations on the practice of labour exploitation. It explores corrupt business practices that firms adopt and key labour exploitative conditions outlined by the International Labour Organization, particularly, paying workers low wages, forcing individuals to work in abusive and unsafe conditions, and considers the issue regarding individuals’ consent to exploitative environments. Further, it considers the role of consumers in creating the high demand for goods and services, which in turn fosters the exploitation of labour. This paper illustrates that the practice of labour exploitation in the economy is a by-product of both global competitive business operations and heightened consumer consumption.

Keywords: globalisation, labour exploitation, modern slavery, sweatshops, unethical business practices

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Authors: Vahid Nourani, Atefeh Ashrafi

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Prediction of treated wastewater quality is a matter of growing importance in water treatment procedure. In this way artificial neural network (ANN), as a robust data-driven approach, has been widely used for forecasting the effluent quality of wastewater treatment. However, developing ANN model based on appropriate input variables is a major concern due to the numerous parameters which are collected from treatment process and the number of them are increasing in the light of electronic sensors development. Various studies have been conducted, using different clustering methods, in order to classify most related and effective input variables. This issue has been overlooked in the selecting dominant input variables among wastewater treatment parameters which could effectively lead to more accurate prediction of water quality. In the presented study two ANN models were developed with the aim of forecasting effluent quality of Tabriz city’s wastewater treatment plant. Biochemical oxygen demand (BOD) was utilized to determine water quality as a target parameter. Model A used Principal Component Analysis (PCA) for input selection as a linear variance-based clustering method. Model B used those variables identified by the mutual information (MI) measure. Therefore, the optimal ANN structure when the result of model B compared with model A showed up to 15% percent increment in Determination Coefficient (DC). Thus, this study highlights the advantage of PCA method in selecting dominant input variables for ANN modeling of wastewater plant efficiency performance.

Keywords: Artificial Neural Networks, biochemical oxygen demand, principal component analysis, mutual information, Tabriz wastewater treatment plant, wastewater treatment plant

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Authors: Samira Rostom, Robert Symonds, Robin W. Hughes

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Hydrogen is considered as one of the most important clean and renewable energy carriers for a sustainable energy future. However, its efficient and cost-effective purification remains challenging. This paper presents the potential of using metal–organic frameworks (MOFs) in combination with pressure swing adsorption (PSA) technology for syngas based H2 purification. PSA process analysis is done considering high pressure and elevated temperature process conditions, it reduces the demand for off-gas recycle to the fuel reactor and simultaneously permits higher desorption pressure, thereby reducing the parasitic load on the hydrogen compressor. The elevated pressure and temperature adsorption we present here is beneficial to minimizing overall process heating and cooling demand compared to existing processes. Here, we report the comparative performance of zeolite-5A, Cu-BTC, and the mix of zeolite-5A/Cu-BTC for H2 purification from syngas typical of those exiting water-gas-shift reactors. The MOFs were synthesized hydrothermally and then mixed systematically at different weight ratios to find the optimum composition based on the adsorption performance. The formation of different compounds were characterized by XRD, N2 adsorption and desorption, SEM, FT-IR, TG, and water vapor adsorption technologies. Single-component adsorption isotherms of CO2, CO, CH4, N2, and H2 over single materials and composites were measured at elevated pressures and different temperatures to determine their equilibrium adsorption capacity. The examination of the stability and regeneration performance of metal–organic frameworks was carried out using a gravimetric system at temperature ranges of 25-150℃ for a pressure range of 0-30 bar. The studies of adsorption/desorption on the MOFs showed selective adsorption of CO2, CH4, CO, and N2 over H2. Overall, the findings of this study suggest that the Ni-MOF-74/Cu-BTC composites are promising candidates for industrial H2 purification processes.

Keywords: MOF, H2 purification, high T, PSA

Procedia PDF Downloads 101

Authors: Korpapa Srisamai, Pawee Siriruk

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The purpose of this study is to forecast product demands and develop appropriate and adequate procurement plans to meet customer needs and reduce costs. When the product exceeds customer demands or does not move, it requires the company to support insufficient storage spaces. Moreover, some items, when stored for a long period of time, cause deterioration to dead stock. A case study of the wholesale company of electronic equipment and components, which has uncertain customer demands, is considered. The actual purchasing orders of customers are not equal to the forecast provided by the customers. In some cases, customers have higher product demands, resulting in the product being insufficient to meet the customer's needs. However, some customers have lower demands for products than estimates, causing insufficient storage spaces and dead stock. This study aims to reduce the loss of sales opportunities and the number of remaining goods in the warehouse, citing 30 product samples of the company's most popular products. The data were collected during the duration of the study from January to October 2022. The methods used to forecast are simple moving averages, weighted moving average, and exponential smoothing methods. The economic ordering quantity and reorder point are used to calculate to meet customer needs and track results. The research results are very beneficial to the company. The company can reduce the loss of sales opportunities by 20% so that the company has enough products to meet customer needs and can reduce unused products by up to 10% dead stock. This enables the company to order products more accurately, increasing profits and storage space.

Keywords: demand forecast, reorder point, lost sale, dead stock

Procedia PDF Downloads 121

Authors: Asibor Godwin, Adeniyi Funsho

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This study was carried out to investigate the impact of biological treated effluent on the physico-chemical properties of receiving waterbodies and also to establish its suitability for other purposes. It focused on the changes of some physic-chemical variables as one move away from the point of discharge downstream of the waterbodies. Water samples were collected from 14 sampling stations made up of the untreated effluent, treated effluent and receiving streams (before and after treated effluent discharge) over a period of 6 months spanning the dry and rainy seasons. Analyses were carried out on the following: temperature, turbidity, pH, conductivity, major anions and cation, dissolved oxygen, percentage oxygen Saturation, biological oxygen demand (BOD), solids (total solids, suspended solids and dissolved solids), nitrates, phosphates, organic matter and flow discharge using standard analytical methods. The relationships between investigated sites with regards to their physico-chemical properties were analyzed using student-t statistics. Also changes in the treated effluent receiving streams after treated effluent outfall was discussed fully. The physico-chemical water quality of the receiving water bodies meets most of the general water requirements for both domestic and industrial uses. The untreated effluent quality was shown to be of biological origin based on the biological oxygen demand, chloride, dissolved oxygen, total solids, pH and organic matter. The treated effluent showed significant improvement over the raw untreated effluent based on most parameters assessed. There was a significant difference (p<0.05) between the physico-chemical quality of untreated effluent and the treated effluent for the most of the investigated physico-chemical quality. The difference between the discharged treated effluent and the unimpacted section of the receiving waterbodies was also significant (p<0.05) for the most of the physico-chemical parameters.

Keywords: eflluent, Opa River, physico-chemical, waterbody

Procedia PDF Downloads 261

Authors: Abolghasem Yousefi-Babadi, Ali Bozorgi-Amiri, Aida Kazempour, Reza Tavakkoli-Moghaddam, Maryam Irani

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All over the world, natural disasters (e.g., earthquakes, floods, volcanoes and hurricanes) causes a lot of deaths. Earthquakes are introduced as catastrophic events, which is accident by unusual phenomena leading to much loss around the world. Such could be replaced by disasters or any other synonyms strongly demand great long-term help and relief, which can be hard to be managed. Supplies and facilities are very important challenges after any earthquake which should be prepared for the disaster regions to satisfy the people's demands who are suffering from earthquake. This paper proposed disaster response facility allocation problem for disaster relief operations as a mathematical programming model. Not only damaged people in the earthquake victims, need the consumable commodities (e.g., food and water), but also they need non-consumable commodities (e.g., clothes) to protect themselves. Therefore, it is concluded that paying attention to disaster points and people's demands are very necessary. To deal with this objective, both commodities including consumable and need non-consumable commodities are considered in the presented model. This paper presented the multi-objective multi-period mathematical programming model regarding the minimizing the average of the weighted response times and minimizing the total operational cost and penalty costs of unmet demand and unused commodities simultaneously. Furthermore, a Chebycheff multi-objective solution procedure as a powerful solution algorithm is applied to solve the proposed model. Finally, to illustrate the model applicability, a case study of the Tehran earthquake is studied, also to show model validation a sensitivity analysis is carried out.

Keywords: facility location, multi-objective model, disaster response, commodity

Procedia PDF Downloads 257

Authors: Jang-Hwan Jo

Abstract:

Implementing sustainable island forest management policies requires categorizing islands into groups based on key indicators and establishing a consistent management system. Building on the results of previous studies, a typology of forested islands was established: Type 1 – connected islands with high natural vegetation cover; Type 2 – connected islands with moderate natural vegetation cover; Type 3 – connected islands with low natural vegetation cover; Type 4 – unconnected islands with high natural vegetation cover; Type 5 – unconnected islands with moderate natural vegetation cover; and Type 6 – unconnected islands with low natural vegetation cover. An AHP analysis was conducted with island forest experts to identify priority ecosystem services (ESs) for the sustainable management of each island type. In connected islands, provisioning services (natural resources, natural medicines, etc.) assumed greater importance than regulating (erosion control) and supporting services (genetic diversity). In unconnected islands, particularly those with a small proportion of natural vegetation, regulating services (erosion control) requires greater emphasis in management. Considering that Type 3 islands require urgent management as connectivity to the mainland makes natural vegetation-sparse island forest ecosystems vulnerable to anthropogenic activities, the land-use scoring method was carried out on Jin-do, a Type 3 forested island. Comparisons between AHP-derived expert demand for key island ESs and the spatial distribution of ES supply potential revealed mismatches between the supply and demand of erosion control, freshwater supply, and habitat provision. The framework developed in this study can help guide decisions and indicate where interventions should be focused to achieve sustainable island management.

Keywords: ecosystem service, sustainable management, forested islands, Analytic hierarchy process

Procedia PDF Downloads 75

Authors: Alhaji M. H. Conteh, Xiangbin Yan, Issa Fofana, Brima Gegbe, Tamba I. Isaac

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Rice grain is Sierra Leone’s staple food and the nation imports over 120,000 metric tons annually due to a shortfall in its cultivation. Thus, the insufficient level of the crop's cultivation in Sierra Leone is caused by many problems and this led to the endlessly widening supply and demand for the crop within the country. Consequently, this has instigated the government to spend huge money on the importation of this grain that would have been otherwise cultivated domestically at a cheaper cost. Hence, this research attempts to explore the response of rice supply with respect to its demand in Sierra Leone within the period 1980-2010. The Nerlovian adjustment model to the Sierra Leone rice data set within the period 1980-2010 was used. The estimated trend equations revealed that time had significant effect on output, productivity (yield) and area (acreage) of rice grain within the period 1980-2010 and this occurred generally at the 1% level of significance. The results showed that, almost the entire growth in output had the tendency to increase in the area cultivated to the crop. The time trend variable that was included for government policy intervention showed an insignificant effect on all the variables considered in this research. Therefore, both the short-run and long-run price response was inelastic since all their values were less than one. From the findings above, immediate actions that will lead to productivity growth in rice cultivation are required. To achieve the above, the responsible agencies should provide extension service schemes to farmers as well as motivating them on the adoption of modern rice varieties and technology in their rice cultivation ventures.

Keywords: Nerlovian adjustment model, price elasticities, Sierra Leone, trend equations

Procedia PDF Downloads 233

Authors: Montserrat Crespi-Vallbona; Oscar Mascarilla-Miró

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Mature destinations have different challenges trying to attract tourism and please its citizens. Hence, they have to maintain their touristic interest to standard demand and also not to undeceive those tourists with more advanced experiences. Second, they have to be concerned for the daily life of citizens and avoid the negative effects of touristification. This balance is quite delicate and often has to do with the sensitivity and commitment of the party in the local government. However, what is a general consensus is the need for destinations to differentiate from the homogeneous rest of regions and create new content, consumable resources or marketing events to guarantee their positioning. In this sense, the main responsibility of destinations is to satisfy users, tourists and citizens. Hence, its aim has to do with holistic experiences, which collect these wide approaches. Specifically, this research aims to analyze the volume and growth of tourist houses in the central touristic neighborhoods of Barcelona (this is Ciutat Vella) as the starting point to identify the behavior of tourists regarding their interests in searching for local heritage attractiveness and community atmosphere. Then, different cases are analyzed in order to show how Barcelona struggles to keep its attractive brand for the visitors, as well as for its inhabitants. Methodologically, secondary data used in this research comes from official registered tourist houses (Catalunya Government), Open Data (Barcelona municipality), the Airbnb tourist platform, from the Incasol Data and Municipal Register of Inhabitants. Primary data are collected through in-depth interviews with neighbors, social movement managers and political representatives from Turisme de Barcelona (local DMO, Destination Management Organization). Results show what the opportunities and priorities are for key actors to design policies to find a balance between all different interests.

Keywords: touristification, tourist houses, governance, tourism demand, airbnbfication

Procedia PDF Downloads 65

Authors: Salah Hosseini, Hadi Ramezani, Bagher Shahbazi, Hossein Rabiei, Jafar Hooshmand, Hiwa Khaldi

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Diversity of energy portfolio and fluctuation of urban energy demand establish the need for more operational flexibility of combined Cooling, Heat, and Power Plants. Currently, the most common way to achieve these specifications is the use of heat storage devices or wet operation of gas turbines. The current work addresses using variable extraction steam turbine in conjugation with a gas turbine inlet cooling system as an alternative way for enhancement of a CCHP cycle operating range. A thermodynamic model is developed and typical apartments building in PARDIS Technology Park (located at Tehran Province) is chosen as a case study. Due to the variable Heat demand and using excess chiller capacity for turbine inlet cooling purpose, the mentioned steam turbine and TIAC system provided an opportunity for flexible operation of the cycle and boosted the independence of the power and heat generation in the CCHP plant. It was found that the ratio of power to the heat of CCHP cycle varies from 12.6 to 2.4 depending on the City heating and cooling demands and ambient condition, which means a good independence between power and heat generation. Furthermore, selection of the TIAC design temperature is done based on the amount of ratio of power gain to TIAC coil surface area, it was found that for current cycle arrangement the TIAC design temperature of 15 C is most economical. All analysis is done based on the real data, gathered from the local weather station of the PARDIS site.

Keywords: CCHP plant, GTG, HRSG, STG, TIAC, operational flexibility, power to heat ratio

Procedia PDF Downloads 281