Level Of Demand Research Articles

The impact of China’s direct investment on energy industry development in Kazakhstan

The purpose of the research is to study the impact of China’s direct investment on Kazakhstan's Energy industry, it enables them to fi gure out what type of Energy sources need more investment, and the demand level on the Energy services, which require for investigating the feasibility behind investing in Energy industry in Kazakhstan. Research methodology - a regression model of the impact of China’s direct investment on Kazakhstan's Energy industry is established to study the impact of Chinese direct investment on Kazakhstan's Energy industry from four variables: net foreign direct investment in Kazakhstan, Kazakhstan's GDP, China's direct investment in Kazakhstan, and China's direct investment in Kazakhstan's Energy industry. Original / value of the research – China's direct investment in Kazakhstan's Energy industry, compared with other factors, can have a more important impact on Kazakhstan's Energy industry, so Kazakhstan can through cooperation with foreign capital, especially China’s capital, the establishment of joint ventures, to improve the current situation in Kazakhstan's Energy industry bad development. Findings. The results show that the impact of net FDI in Kazakhstan, Kazakhstan's GDP, China's direct investment in Kazakhstan, and China's direct investment in Kazakhstan's Energy industry on Kazakhstan's Energy development is signifi cant and positively related.

Sizing of storage‐based renewable off‐grid system according to supply of electrical and thermal energies considering unscented transformation‐based stochastic optimization: A case study

AbstractThe paper presents the planning (sizing) of a hybrid islanded system containing only renewable sources including wind turbines, photovoltaics, and bio‐waste energy units for the simultaneous supply of electrical and thermal energy. The mentioned renewable sources are used to supply electrical energy. The bio‐waste unit (BEU) is equipped with combined electrical and thermal technology. It is used along with heat pumps to supply thermal energy. Electrical and thermal storage are employed to make the renewable power output as close as possible to the demand level. Electric storage can be either stationary (e.g., battery) or mobile (e.g., electric vehicles), but thermal storage is as stationary type of storage. In the following, the proposed scheme minimizes construction and maintenance costs imposed by power sources, storage devices, and power electronic converters, and expected storage degradation cost. This plan is bound to the model of operation of sources, storage devices, and power electronic converters. In this model, renewables are the main source of power to supply consumers, where storage is adopted to increase the generation level to make it as close as possible to the demand curve. The uncertain parameters are imposed by the load, renewable phenomena, and mobile storage parameters. To model these uncertainties, stochastic optimization based on unscented transformation is used. Finally, the findings of the paper demonstrate that the suggested scheme succeeds in the economic planning of the system with a simultaneous supply of electrical and thermal energy. The BEU equipped with a combined electricity and heat system along with thermal storage and a heat pump to supply thermal load besides providing electric energy can reduce the planning cost by 2.9% compared with the case with only electrical energy. Also, the mobile storage presence in the hybrid system can reduce the number of stationary storage devices, which alone results in a 7.7% decrease in the planning cost of the hybrid system.

Modern Agriculture Development Case in Gobleg Village Banjar Subdistrict Buleleng Regency, Bali Province

The challenges of Indonesia's agricultural development today are climate change and potential droughts. This research aims to analyze the modern agricultural development of the Gobleg Village Case of Banjar district of Buleleng. This research uses a qualitative method with a case study approach. Determination of informants using snowball sampling and data collection methods is done with in-depth interviews, observations, and documentation. Data analysis using interactive model analysis of Miles, Huberman and Saldana (2014). The results of the research show the selection of commodities based on potential income, level of market demand, knowledge, land characteristics and socio-cultural characteristics. The agricultural production process ranges from land processing to post-harvest harvesting. Farmers have already implemented eco-friendly farming by implementing IoT-based fertigation. Institutional support consists of marketing, financing, technical guidance and social capital. The marketing of products is facilitated by the Gobleg PMK cooperation in cooperation with Bali Organic Subak, the marketing is done online with the Fresh Boss application. The cooperation provides facilitation of means of production with the payment system after harvest. In terms of social capital, farmers still exist doing gotong royong in land processing. Farmers are already able to leverage technology like smartphones that are integrated with IoT-based fertigation.

Modern Agriculture Development Case in Gobleg Village Banjar Subdistrict Buleleng Regency, Bali Province

The challenges of Indonesia's agricultural development today are climate change and potential droughts. This research aims to analyze the modern agricultural development of the Gobleg Village Case of Banjar district of Buleleng. This research uses a qualitative method with a case study approach. Determination of informants using snowball sampling and data collection methods is done with in-depth interviews, observations, and documentation. Data analysis using interactive model analysis of Miles, Huberman and Saldana (2014). The results of the research show the selection of commodities based on potential income, level of market demand, knowledge, land characteristics and socio-cultural characteristics. The agricultural production process ranges from land processing to post-harvest harvesting. Farmers have already implemented eco-friendly farming by implementing IoT-based fertigation. Institutional support consists of marketing, financing, technical guidance and social capital. The marketing of products is facilitated by the Gobleg PMK cooperation in cooperation with Bali Organic Subak, the marketing is done online with the Fresh Boss application. The cooperation provides facilitation of means of production with the payment system after harvest. In terms of social capital, farmers still exist doing gotong royong in land processing. Farmers are already able to leverage technology like smartphones that are integrated with IoT-based fertigation.

Simulation-based system reliability estimation of a multi-state flow network for all possible demand levels

Simulation-based system reliability estimation of a multi-state flow network for all possible demand levels

Current wig prescribing practices and financial evaluation in an NHS Foundation Trust: Lessons learnt and future challenges.

Significant psychological burden has been associated with alopecia and the use of wigs can have a positive impact on patients’ wellbeing. Research has highlighted the unequal NHS wig provision which has led to the recommended ‘Charter for Best Practice for NHS wig provision’ by Alopecia UK and the BAD/BHNS published in June 2022. This single-centre review evaluated wig prescribing practices over a 12 month period noting the prescribing department, patient demographics, diagnosis, number and type of wigs per year and cost per prescription. Our results demonstrate the level of demand across all alopecia diagnoses and ages. Thus, access to wigs remains a vital therapy in hair loss management. Further work is required to ensure equitable NHS wig prescribing across all regions.

STATISTICAL ASSESSMENT OF WATER QUALITY PARAMETERS FOR POLLUTION SOURCE IDENTIFICATION IN NOYYAL RIVER, COIMBATORE, TAMILNADU

<p>This study aimed to determine the extent of the water quality decrease in the Noyyal River in Tamilnadu by analyzing the seasonal change of water's physicochemical properties, identifying possible sources of pollution, and grouping the monitoring months based on shared characteristics. The measurements were taken during four different seasons. Forty percent of the water quality indices, including turbidity, DO concentration, EC, Cl concentration, TA, and COD in all seasons, were found to be outside the acceptable limits recommended by various agencies, according to the analytical data. A 95% confidence interval's worth of statistical analysis revealed that 52% of the contrasts differed significantly. Four factors accounted for 93.44% of the variation overall, according to the factor analysis, which showed the best fit between the parameters. The significant pollution loading, primarily attributed to toxicological chemicals and industrial discharge, was reflected in Total Dissolved Solids, Biochemical Oxygen Demand, Chemical Oxygen Demand, Electrical Conductivity, Turbidity, Dissolved Oxygen, and Chloride levels. Cluster analysis revealed a seasonal variation in surface water quality, indicating contamination from rainfall or other sources. Nevertheless, seasons did impact the levels of various physicochemical characteristics, with winter recording the highest pollution values. The Noyyal River's seasonal temperature change and increased rainfall were the causes of this self-refining tendency, which goes winter < summer < pre-winter < rainy season.</p>

Topology reduction through machine learning to accelerate dynamic simulation of district heating

District heating networks (DHNs) provide an efficient heat distribution solution in urban areas, accomplished through interconnected and insulated pipes linking local heat sources to local consumers. This efficiency is further enhanced by the capacity of these networks to integrate renewable heat sources and thermal storage systems. However, integration of these systems adds complexity to the physical dynamics of the network, necessitating complex dynamic simulation models. These dynamic physical simulations are computationally expensive, limiting their adoption, particularly in large-scale networks. To address this challenge, we propose a methodology utilizing Artificial Neural Networks (ANNs) to reduce the computational time associated with the DHNs dynamic simulations. Our approach consists in replacing predefined clusters of substations within the DHNs with trained surrogate ANNs models, effectively transforming these clusters into single nodes. This creates a hybrid simulation framework combining the predictions of the ANNs models with the accurate physical simulations of remaining substation nodes and pipes. We evaluate different architectures of Artificial Neural Network on diverse clusters from four synthetic DHNs with realistic heating demands. Results demonstrate that ANNs effectively learn cluster dynamics irrespective of topology or heating demand levels. Through our experiments, we achieved a 27% reduction in simulation time by replacing 39% of consumer nodes while maintaining acceptable accuracy in preserving the generated heat powers by sources.

Process design and global sensitivity analysis of hydrogen fuel station with dual-operating modes for a sustainable H2 city: Iterative optimization-based simulation using generalized disjunctive programming

This study proposes a novel process involving dual-mode operation for an on-site hydrogen (H2) refueling station. In particular, two distinct H2 production technologies, steam methane reforming (SMR), and autothermal reforming (ATR), are simultaneously considered, which enables a flexible operational mode that responds to operational variability. By synergistically combining the technical advantages of these two technologies (i.e., the low cost of SMR and the short start-up and shut-down times of ATR), the proposed fuel station can reduce a H2 storage tank cost, which is needed to respond to demand fluctuations. To achieve our goal, we developed iterative optimization-based simulation (IOS) framework. The proposed framework determines the optimal design configuration (e.g., the storage facilities and the capacity of production) and the dual-mode operational strategy (e.g., on/off timing) under demand fluctuations and given CO2 emission targets. The case study showed that lower storage costs and offset the increased capital cost of the production facility, thereby leading to a low H2 supply cost of 3.60 USD/kg and a production capacity of 1.2 tons/day. We then performed a global sensitivity analysis to provide a comprehensive strategy and practices for the deployment of the proposed system over demand levels, regional demand fluctuation, and CO2 emission targets.

FRESHMAN SYNDROME IN MEDICAL UNIVERSITIES: ADAPTATION AND PSYCHOLOGY

The article aims to explore the essence of the freshman syndrome in medical universities, to consider the psychological aspects influencing it, and to propose practical approaches to overcoming this phenomenon. The freshman syndrome in medical universities arises from a combination of factors, such as unusual workload, knowledge and skill requirements, a new social environment, and separation from home. This syndrome can cause stress, anxiety, information overload, and fatigue. Students starting their journey in medical universities face a high level of academic demands and a large volume of material they need to master. This situation often leads to stress and anxiety as students need to adapt to a new pace of learning and choose effective learning methods. Additionally, the new social environment at the university can evoke feelings of isolation and loneliness, especially among those who are distant from family and old friends. This can lead to anxiety and the emergence of the syndrome of social adaptation. Therefore, the freshman syndrome in medical universities can be a complex challenge for students and requires support and adaptation strategies to overcome these problems. The article discusses the psychological aspects of the freshman syndrome and the impact of stress on students of medical universities. It explores how students perceive this syndrome, how to cope with stress, and what practical approaches can help facilitate adaptation.

Designing a collaborative maintenance planning mechanism between airline and maintenance company using a bilevel model – Considering flexible maintenance schedule and service charges

Periodic aircraft Maintenance Repair and Overhaul (MRO) activities are compulsory. To capture the features of MRO operations between airline and maintenance company under MRO outsourcing mode, we consider a collaborative aircraft maintenance planning problem, in which the airline outsources its self-operated maintenance checks to an independent maintenance company. Under such context, MRO planning conflicts between two collaborates exists especially during maintenance peak period, as airline aims to maximize flight operations revenues by receiving timely MRO service. On the other hand, maintenance company strives to accomplish heterogenous demands without causing tardiness and involving excessive MRO resources cost. Therefore, finding an effective mechanism to eliminate the conflicts between maintenance demands (from airline company) and maintenance service supply capability (from maintenance company) is indispensable for collaboration. A bi-level optimization model is formulated to describe the conflicting objectives and maintenance planning features of two independent stakeholders. To facilitates a synchronization of demand and supply and reconcile MRO conflicts, flexible maintenance schedules and service charges decisions from two independent collaborators is involved in the model, enabling a maintenance planning negotiation for finding mutual beneficial maintenance plan. An iterative algorithm deploying bounding updating strategy is developed, which generates a series of convergent-oriented bounding constraints along the iterative negotiation and guides the adjustment of maintenance demand and supply towards equilibrium. Based on the computational results in solving various maintenance planning scenarios, the impacts of different features (e.g. resource availability, resource demands level, and penalty cost of service tardiness) on airline and service company’s planning performance are analysed, revealing that maintenance service company’s own interest can be assured and maintained though it is a follower in the collaboration framework Afterwards, the managerial insights for facilitating the maintenance collaboration are further discussed.

Evaluation of Ecotourism Practices: A Comparative Study of Lowlands and Mountains of Nepal

This research provides valuable insights into tourist profiles, market demand, attractions, motivations, amenities, and satisfaction levels in Chitwan National Park (CNP), the lowland park, and Annapurna Conservation Area (ACA), the park in the mountains of Nepal. Through qualitative and quantitative research methods, including surveys, interviews, and field observations, this study compared the current state of ecotourism practices in the protected areas (PAs). Though both the PAs showed consistent growth in tourist flow, ACA exhibited signs of saturation, suggesting the need for strategic management. Attractions differed in the PAs; natural scenery and photography draw visitors to ACA while wildlife and cultural experiences attract tourists to CNP. Disparities in amenities highlight areas for improvement, particularly in ACA. Community engagement is always an added benefit to any tourism development. Overall, satisfaction levels are satisfactory, but challenges such as overcrowding, decreasing quality of tourism, environmental degradation, and accessibility constraints require attention for sustainable tourism development. Collaborative efforts can address these issues and ensure the long-term viability of ecotourism in CNP and ACA while preserving their natural and cultural heritage.

Comparative ecotoxicological study on the current status of artisanal crude oil contaminated mangrove swamps in Rivers State, Southern Nigeria

The rise in illegal crude oil theft and refining in the southern Niger Delta region of Nigeria, especially in Rivers State, has led to significant environmental damage to aquatic ecosystems. A study was carried out to assess the impact of crude oil bunkering on aquatic environments and fish samples from Oproama, Sama-Naguakiri, and Abalama over six months. Findings revealed that Oproama had the highest levels of biological oxygen demand (3.60 ± 0.79 mg/L), electrical conductivity (34.07 ± 3.62 μS/cm), total dissolved solids (28.17 ± 3.77 mg/L), and temperature (29.50 ± 0.74 °C). In contrast, Sama-Naguakiri recorded the highest pH (6.72 ± 0.14) and dissolved oxygen (3.35 ± 0.11 mg/L). Though minor variances were noted between Sama-Naguakiri and Abalama, a significant difference (P < 0.05) was observed between these areas and Oproama. Importantly, all measured values adhered to WHO/FAO standards. Analysis of potentially harmful metals in sediment and water indicated notable distinctions among the three sites, with Sama-Naguakiri exhibiting the highest levels of Zn (114.5 ± 1.5 mg/kg), Cu (237.8 ± 0.9 mg/kg), Pb (3.6 ± 1.2 mg/kg), and Cd (1.1 ± 0.4 mg/kg). Conversely, Abalama showed the lowest zinc (105.2 ± 1.5 mg/kg) and lead (2.4 ± 0.5 mg/kg) concentrations, while Oproama displayed the lowest copper level (0.8 ± 0.3 mg/kg). The concentrations of heavy metals in the water, sediment, and fish surpassed the permissible limits established by NESREA, the EPA, and WHO, except for arsenic. The presence of heavy metals in this region could pose significant ecological and health hazards, underscoring the urgency for immediate remedial measures to safeguard the environment and this fish-dependent community.

Optimizing Station Placement for Free-Floating Electric Vehicle Sharing Systems: Leveraging Predicted User Spatial Distribution from Points of Interest

Rapid growth rate indicates that the free-floating electric vehicle sharing (FFEVS) system leads to a new carsharing idea. Like other carsharing systems, the FFEVS system faces significant regional demand fluctuations. In such a situation, the rental stations and charging stations should be constructed in high-demand areas to reduce the scheduling costs. However, the planning of the FFEVS system includes a series of aspects of rental stations and charging stations, such as the location, size, and number, which interact with each other. In this paper, we first provide a method for forecasting the demand for car sharing based on the land characteristics of Beijing FFEVS station catchment areas. Then, the multi-objective MILP model for planning FFEVS systems is developed, which considers the requirements of vehicle relocation and electric vehicle charging. Afterward, the capabilities of the proposed models are demonstrated by the real data obtained from Beijing, China. Finally, the sensitivity analysis of the model is made based on varying demand and subsidy levels. From the results, the proposed model can provide decision-makers with useful insights about the planning of FFEVS systems, which bring great benefits to formulating more rational policies.

Analysis of educational needs of migrant families raising children with disabilities

Problem and purpose. In terms of increasing migration flow, it is important to provide conditions for building an open, accessible multicultural educational space. To accomplish this objective, it is required to study in detail the educational needs of migrant families. Particularly relevant are studies that involve the analysis of parents’ requests for children with disabilities to receive preschool primary and basic education. The purpose of the study is to analyze the educational needs of migrant families raising children with disabilities of school age. Materials and methods. 228 respondents took part in the pilot study. The experiment used a questionnaire developed by the authors for migrants raising children with disabilities of school age. The criteria for its compilation are presented and the structural components are described. The questionnaire was supplemented by conversations with migrants raising children and special and inclusive education teachers. Results. The results obtained make it possible to analyze the direction and content of requests to an educational organization and a teacher. The expectations and ideas of respondents regarding children's education were studied. 60.5% of parents prioritize their child’s mastery of the educational program, especially in-depth study of the Russian language. All participants in the experiment show a high level of demands on the correctional, developmental and educational work of the school. 68.8% of families do not expect teachers to help in carrying out career guidance work with students with disabilities. Requests for psychological support from parents were not presented in the results of the experiment, and all participants in the survey expected the teacherpsychologist support for the child. Conclusion. The conclusions obtained during the pilot study can be useful for building a comprehensive system of school support for migrant families raising children with disabilities. Taking into account the risks and problem areas in the interaction between the educational organization and parents will optimize the process of adaptation of migrants to new socio-cultural conditions and make education accessible and open.

Examination of Grade 7 Ratio Concept Tasks Designed by ChatGPT Based on Cognitive Demand Levels

The process that enables students to achieve objectives while performing mathematical tasks is defined as an activity. The task creation process is a lengthy and challenging journey involving many complex stages. Artificial intelligence technologies can facilitate this process. For instance, ChatGPT can assist teachers on various issues and help them create tasks. This study aimed to evaluate the tasks prepared for the Grade 7 ratio concept using ChatGPT, focusing on cognitive demand levels. It employed a case study design to examine the cognitive demand levels of tasks created with ChatGPT 3.5 and ChatGPT 4, identifying any potential deficiencies. The content analysis was performed to analyze the data. It was concluded that the created tasks could be used with necessary improvements, allowing teachers to enrich their course content while saving time and energy.

A Closed-Loop Supply Chain Inventory Model with Carbon Emissions and Green Technology Investment

This paper proposes an inventory model that integrates a manufacturer and a retailer in a supply chain system. The model employs environmentally friendly technology investments to reduce the emissions produced in the process. Furthermore, the demand at the retailer's end is unpredictable, and green investments affect the average demand levels. This research aims to identify the optimal delivery lot, the number of deliveries, the Safety Factor, the level of green technology, and the collection level to maximize the joint total profit. Numerical examples illustrate the model's practical application, and algorithms are developed to solve the problem. Sensitivity analysis is used to determine the key model parameters' effect on the model's behavior. Green investments have been shown to reduce emissions and increase returns on second-hand goods, thus enhancing the environmental efficiency of supply chains.

Faktor-faktor yang Mempengaruhi Permintaan Tempe di Kecamatan Sukomanunggal Kota Surabaya

This study discusses the factors that influence the demand for tempeh in Sukamanunggal District, Surabaya City. The independent variables consist of the price of tempe, the price of white tofu, the level of income, the type of tempe, and the number of dependents while the dependent variable is the demand for tempe. This study uses quantitative methods, and the sample used is 398 respondents with the slovin calculation formula. The analytical method used is multiple linear regression. The results of the simultaneous test of this study showed that the price of tempeh, the price of white tofu, the level of income, the type of tempeh, and the number of dependents had a significant influence on the level of demand for tempeh in the community of Sukamanunggal District, Surabaya City. The partial test results show that the price of tempeh, the price of white tofu, and the level of income have a positive and significant influence on the level of demand for tempeh in the community of Sukamanunggal District, Surabaya City. While the type of tempe, and the number of dependents have a negative and significant effect on the level of demand for tempeh in the community of Sukamanunggal District, Surabaya City.

Test-retest reliability and validity of vagally-mediated heart rate variability to monitor internal training load in older adults: a within-subjects (repeated-measures) randomized study

BackgroundVagally-mediated heart rate variability (vm-HRV) shows promise as a biomarker of internal training load (ITL) during exergame-based training or motor-cognitive training in general. This study evaluated the test-retest reliability of vm-HRV during exergaming in healthy older adults (HOA) and its validity to monitor ITL.MethodsA within-subjects (repeated-measures) randomized study was conducted that included baseline assessments and 4 measurement sessions. Participants played 5 exergames at 3 standardized levels of external task demands (i.e., “easy”, “challenging”, and “excessive”) in random order for 90 s. Test-retest reliability was assessed on the basis of repeated-measures analyses of variance (ANOVA), intraclass correlation coefficients (ICC3,1), standard errors of measurement (SEM), and smallest detectable differences (SDD). Validity was determined by examining the effect of game level on vm-HRV in the ANOVA.ResultsFourty-three HOA (67.0 ± 7.0 years; 58.1% females (25 females, 18 males); body mass index = 23.7 ± 3.0 kg·m−2) were included. Mean R-R time intervals (mRR) and parasympathetic nervous system tone index (PNS-Index) exhibited mostly good to excellent relative test-retest reliability with no systematic error. Mean SEM% and SDD% were 36.4% and 100.7% for mRR, and 44.6% and 123.7% for PNS-Index, respectively. Significant differences in mRR and PNS-Index were observed between standardized levels of external task demands, with mostly large effect sizes (mean r = 0.847). These results persisted irrespective of the type of neurocognitive domain trained and when only motoric and cognitive demands were manipulated while physical intensity was kept constant. The remaining vm-HRV parameters showed inconsistent or poor reliability and validity.ConclusionOnly mRR and PNS-Index demonstrated reliable measurement and served as valid biomarkers for ITL during exergaming at a group level. Nonetheless, the presence of large SEMs hampers the detection of individual changes over time and suggests insufficient precision of these measurements at the individual level. Future research should further investigate the reliability and validity of vm-HRV with a specific focus on comparing different measurement methodologies and exercise conditions, particularly focusing on ultra-short-term HRV measurements, and investigate the potential implications (i.e., superiority to other markers of ITL or monitoring strategies?) of using vm-HRV as a biomarker of ITL.

Tuberculosis preventive treatment in eight SEAR countries – Current practices, implementation challenges and operations research priorities

ObjectivesCountries in the South East Asian region face similar challenges in control of infectious diseases. There is limited access to experiences and learnings of neighboring countries. The Indian Council - of Medical Research (ICMR) has established a Regional Enabler for the South-East Asia Research Collaboration for Health (RESEARCH) Platform for South East Asian Region (SEAR) countries to address the above issues. This paper discusses about current practices, implementation challenges and operations research priorities of Tuberculosis Preventive therapy (TPT) in eight SEAR countries. MethodsA three day workshop on “Capacity Building for TB Research under Programmatic Settings”. was conducted under the aegis of this RESEARCH platform jointly ICMR and the Union which was participated by eight SEAR countries. Data were collected from a semi-structured questionnaire prior to the workshop and open discussions during the workshop. ResultsThe various challenges faced for TPT implementation were broadly categorized as poor demand and low level of acceptance by the beneficiary, low level of acceptance to provide TPT among the providers, challenges in ruling out active TB, issues with supply and supply chain management of diagnostic tests and drugs. Many operations research priorities like person centric TPT driven models, capacity building for improving cascade of care for latent TB infection, health system strengthening and effective risk communication were identified. ConclusionFull implementation of the TPT guidelines requires focused attention and coordinated action from all stakeholders of the country to attain the full benefit of TB preventive therapy and the ultimate TB elimination goal.