Demand Management Research Articles

Behavior-Adaptive Sync-Flow Framework: Integrating frequency setting and passenger routing in oversaturated urban rail transit networks

Urban rail transit (URT) networks serve a large amount of travel demand in metropolitan areas. One of the fundamental challenges in URT demand management is the dynamic interaction between train frequencies and passenger routing behaviors, which becomes even more complicated in oversaturated scenarios. Introducing the behavior-adaptive sync-flow (BASF) framework, this study holistically addresses the tactical frequency settings (train flows) for URT networks and the responsive route choice behaviors of passengers (passenger flows). The proposed integrated model incorporates a schedule-based passenger assignment within space–time networks to model passengers’ routing behaviors based on time-dependent route travel costs. In addition to travel time, the often-overlooked factors such as in-train congestion, number of passengers being left behind, and number of transfers are considered as components influencing travel costs and, consequently, routing behaviors at an individual level. A gradient descent-based heuristic iterative solution approach is developed to address the integrated model by dividing it into three sub-problems. In this iterative process, passengers respond according to a logit-based route choice model based on time-dependent route travel costs, while frequencies are updated using a gradient descent-based strategy. Central to the proposed BASF framework are the mutual adaptations between URT line frequencies and passenger route choices. Numerical examples and a case study of the Beijing URT network highlight the effectiveness and scalability of the model framework in tackling complex, large-scale URT networks, particularly in oversaturated conditions, thus revealing the significance of supply–demand matching.

SAARC super smart grid: Navigating the future - unleashing the power of an energy-efficient integration of renewable energy resources in the saarc region

The major problems in the power system network of the South Asian Association for Regional Cooperation (SAARC) region include the utilization of substantial fossil fuels, which leads to significant emissions of CO2. Moreover, due to the depletion of fossil fuels, it is very difficult to manage the demand requirement of the SAARC regions, which leads to significant power shortage issues. These problems would be resolved through the integration of the substantial amount of renewable energy resources (RERs) that are available in excess in the SAARC regions into the power system networks. This will provide a futuristic roadmap to a sustainable and green energy environment in the SAARC region. In this regard, the SAARC region has devised a new plan to transform its smart grid infrastructure into the super smart grid (SSG), which would connect the SAARC countries using the high voltage transmission lines utilizing each country's substantial RERs. To accelerate this ecofriendly effort, the key objective of this review study is to evaluate the potential of the SAARC SSG for demand management and emissions reduction. This study provides a comprehensive overview of SSG technology, covering its technical background, management, power flow improvement techniques, power stability techniques, simulation models, and future steps for development in the SAARC region. First, the regional conflicts, energy deficiency, and potential of the SAARC region have been discussed. Second, a potential architecture of the SAARC SSG has been simulated. Third, a novel Markov chain modeling has been presented for demand management in the SAARC regions. The results and discussions section presents findings from simulations and models. The paper also discusses CO2 reduction techniques, including methods for capturing, storing, and utilizing carbon in biofuel. The study also discusses futuristic optimization techniques in SSG, including blockchain, federated learning, reinforcement learning, the metaverse, digital twin technology, artificial intelligence, and cloud computing. The SSG challenges and limitations section summarizes the challenges and limitations faced by SSG. Finally, a roadmap to a sustainable and green energy environment for the SAARC power grids has been identified to support the implementation of the futuristic SAARC SSG. The results exhibited that there is a good potential for successful demand management and emissions reduction through the SAARC SSG.

Quantum PSO-Based Power Demand and Supply Management algorithm for Micogrids

Quantum PSO-Based Power Demand and Supply Management algorithm for Micogrids

An eco friendly approach for the development of a dipeptide based anti-TB drug nanocomposites: A greener approach in drug delivery system for pulmonary delivery

The conventional anti tubercular (anti-TB) treatment strategies constitute challenges in terms of patient compliance and treatment outcomes. Nano-therapeutics is an emerging field with increasing demand for the therapeutic management of tuberculosis (TB) and the challenges over acquired drug toxicity and poor availability. Nevertheless, studies based on nanopeptide drug carrier for the delivery of anti-TB drugs are scanty. The present work emphasizes on the development of a nanocarrier system through hydrothermal process for encapsulating anti-TB drugs (rifampicin, isoniazid, pyrazinamide, ethambutol) using carnosine dipeptide for the potential therapeutic application. The carnosine-anti-TB drug nanocomposites were synthesized by treating native carnosine and anti-TB drugs at an equal ratio (1:1) incubated at 65°C for 30 min (pH 5.3). The hybrid clusters were freeze dried and used further for characterization (physiochemical, biological, morphology and in silico methods). The structural and functional annotations of carnosine and anti-TB drug nanocomposites were confirmed from its terminal amine absorption stretching’s and its amino group fingerprinting regions. The homogenous nature of carnosine-anti-TB drug complexes in solutions was demonstrated with the particle size (>1 μm), that is suitable for macrophage uptake. SEM analysis demonstrated the interactions and functional group orientation between carnosine and anti-TB drugs during the self-assembly process. The drug release profile indicated that the carnosine-drug conjugation promoted the sustained release compared to free drugs. The quantum mechanical calculations define the structural modelling of drugs with carnosine to obtain a stable energy-minimized conformation. To conclude, the developed carnosine- anti-TB drug nanoclusters with enhanced stability and uniformity in size makes them suitable for macrophage uptake and targeted delivery approaches during TB treatment.

Seabird bycatch in European waters

AbstractThe incidental capture (bycatch) of seabirds is a global conservation issue and a top threat to European species that demands urgent conservation and management action. Here, we present the first European review of seabird bycatch data, considering all fishing gears and data collection methods available in the region. We calculate seabird bycatch numbers per species, family, country and European marine region and assess the reliability of the data available. The cumulative bycatch estimate extracted from this review suggests that about 195,000 seabirds (ranging from around 130,000 to 380,000) are bycaught in European waters annually. The most affected seabird species is the Common Guillemot Uria aalge with over 31,000 birds killed per year. The marine region with the highest bycatch estimate is the Northeast Atlantic (over 115,000 seabirds year−1). Gillnet fisheries are responsible for the highest bycatch levels, with over 95,000 seabirds year−1, followed by longline fisheries. The families most affected by bycatch are Anatidae and Alcidae. These numbers are likely an underestimation since we were unable to find bycatch estimates, or to extrapolate estimates from available bycatch data for 12 (out of 34) European coastal states. Our assessment also identified significant data gaps in key areas such as Gran Sol (in the north‐east Atlantic), the central and Eastern Mediterranean and the Black Sea. Combining systematic data collection with immediate implementation of mitigation measures will be crucial to fill in knowledge gaps, reduce current mortality levels and meet international conservation commitments such as those of the European Union and the Convention on Migratory Species.

Subjective and Objective Monitoring Markers: Are They Related to Game Performance Indicators in Elite Female Volleyball Players?

This cohort study aimed to investigate the relationship between subjective (wellness and internal training load [ITL]) and objective (neuromuscular fatigue) monitoring markers and performance aspects (reception quality [RQ] and attack efficiency [AE]) in professional female volleyball players. The study was conducted over an 8-week period during the final mesocycle of the competitive phase. A total of 24 training sessions and 10 matches were included in the analysis. Subjective measures of wellness and ITL were assessed, and neuromuscular fatigue was evaluated using countermovement-jump (CMJ) height. RQ and AE were determined based on game statistics. The study found a positive relationship between wellness and RQ, particularly affecting outside hitters and liberos. ITL showed a positive association with AE, primarily impacting outside hitters, opposite hitters, and middle blockers. Additionally, ITL demonstrated a negative correlation with RQ, mainly affecting outside hitters and liberos. CMJ performance was associated with AE, where a decrease in CMJ height was linked to reduced AE. The findings highlight the importance of considering players' wellness scores in training and match strategies for different positions. Careful management of training loads, considering both physical and technical demands, is crucial for optimizing performance outcomes. Monitoring neuromuscular fatigue, as indicated by CMJ performance, is particularly relevant for outside hitters, opposite hitters, and middle blockers involved in attack actions. Coaches, trainers, and sports practitioners can use these insights to develop position-specific training protocols and implement effective strategies for maintaining or improving performance metrics under various stressors.

GIJA:Enhanced geyser‐inspired Jaya algorithm for task scheduling optimization in cloud computing

AbstractTask scheduling optimization plays a pivotal role in enhancing the efficiency and performance of cloud computing systems. In this article, we introduce GIJA (Geyser‐inspired Jaya Algorithm), a novel optimization approach tailored for task scheduling in cloud computing environments. GIJA integrates the principles of the Geyser‐inspired algorithm with the Jaya algorithm, augmented by a Levy Flight mechanism, to address the complexities of task scheduling optimization. The motivation for this research stems from the increasing demand for efficient resource utilization and task management in cloud computing, driven by the proliferation of Internet of Things (IoT) devices and the growing reliance on cloud‐based services. Traditional task scheduling algorithms often face challenges in handling dynamic workloads, heterogeneous resources, and varying performance objectives, necessitating innovative optimization techniques. GIJA leverages the eruptive dynamics of geysers, inspired by nature's efficiency in channeling resources, to guide task scheduling decisions. By combining this Geyser‐inspired approach with the simplicity and effectiveness of the Jaya algorithm, GIJA offers a robust optimization framework capable of adapting to diverse cloud computing environments. Additionally, the integration of the Levy Flight mechanism introduces stochasticity into the optimization process, enabling the exploration of solution spaces and accelerating convergence. To evaluate the efficacy of GIJA, extensive experiments are conducted using synthetic and real‐world datasets representative of cloud computing workloads. Comparative analyses against existing task scheduling algorithms, including AOA, RSA, DMOA, PDOA, LPO, SCO, GIA, and GIAA, demonstrate the superior performance of GIJA in terms of solution quality, convergence rate, diversity, and robustness. The findings of GIJA provide a promising solution quality for addressing the complexities of task scheduling in cloud environments (95%), with implications for enhancing system performance, scalability, and resource utilization.

Enriching math teaching guides from a competency-based perspective

This study introduces a novel framework designed to enrich mathematics teaching guides from a competency-based perspective. First, we narrow down the concept of a teaching guide in mathematics education, grounded in the documentational approach to didactics. This definition offers an updated perspective on the structure and function of math teaching guides in educational settings. Second, we provide a comprehensive definition of ‘richness’ in math activities, encompassing content, processes, cognitive demand, and classroom management. Lastly, we introduce an analytical tool developed for assessing and enhancing the richness of math teaching guides. This tool, formed through theoretical analysis and empirical testing, assists educators and curriculum developers in creating more balanced and integrative teaching guides. The results suggest that the tool holds potential for broader applications in curriculum design and teacher education. The findings contribute to the broader understanding of how teaching guides can effectively capture and communicate the richness of activities, thereby serving as a valuable tool for improving mathematical education resources.

Los vehículos eléctricos y su impacto en el sistema eléctrico de distribución: Caso de estudio “Alimentador urbano de la ciudad de Portoviejo”

In Portoviejo, the current use of electric vehicles (EVs) is limited compared to conventional vehicles. However, due to the implementation of laws, regulations, and policies promoting electric mobility in Ecuador, a significant increase in the integration of EVs into the city's electrical system is anticipated in the coming years. To anticipate the impact on the electrical infrastructure, a simulation is conducted using CYMDIST software on an electrical distribution feeder operated by the Public Company Corporación Nacional de Electricidad (CNEL EP), Manabí Business Unit (Portoviejo). The simulation considers three scenarios projected for 2030: 1. Baseline scenario without EV integration, 2. Unrestrained EV integration, and 3. Managed EV integration. This research aims to simulate the integration of up to 230 EVs into the network to provide benchmark data for understanding the potential impacts on the feeder as EV adoption increases, with vehicles being charged over extended periods. The investigation will highlight the importance of demand management with EV integration, demonstratingsignificant effects on the demand curve, voltage profile, and total harmonic distortion rate (THD%) of a 13.8 kV distribution feeder.

Pengaruh Kompetensi, Kompensasi dan Komunikasi terhadap Kinerja Pegawai pada Dinas Kebudayaan dan Pariwisata Provinsi Sumatera Utara

Human resources are critical to a company's success as they impact objectives. Developing this activity demands management. Developing these activities demands management. Companies help related groups develop in various ways. Agency performance is largely influenced by employees. This study aims to examine how competence, compensation, and communication affect employee performance at the Office of Culture and Tourism of North Sumatra Province. This primary data analysis uses employee performance as the independent variable and competence, compensation, and communication as the dependent variable. This research involved employees of the Culture and Tourism Office of North Sumatra Province. Quantitative associative research was used. A saturated sample of 125 respondents was used in this study. This study collected data with a questionnaire. This study uses SPSS to conduct data quality tests (Validity and Reliability), classical assumption tests, and hypothesis testing (Test f, Test t, Test Coefficient of Determination).The results of this study indicate that the competency variable has a significant effect on employee performance with the results obtained from the tcount value of t table 2. 536> t table 1,984 with a significance level of 0.000 <0.05, the compensation variable has a significant effect on employee performance with the results obtained by the tcount value of 10,428> t table 1,984 with a significance value of 0.000 <0.05, the communication variable has a significant effect on employee performance with the results obtained by the tcount value of 1,990> t table 1,984 with a significance value of 0.000 <0.05.

Networked Multiagent-Based Safe Reinforcement Learning for Low-Carbon Demand Management in Distribution Networks

Networked Multiagent-Based Safe Reinforcement Learning for Low-Carbon Demand Management in Distribution Networks

TEMPORARY REMOVAL: Principles and Practice in Pediatric Vascular Trauma: Part 2: Fundamental Vascular Principles, Pediatric Nuance, and Follow-up Strategices

As of 2020, penetrating injuries became the leading cause of death among children and adolescents ages 1–19 in the United States. For those patients who survive and receive advanced medical care, vascular injuries are a significant cause of morbidity and trigger notable trauma team angst. Moreover, penetrating injuries can lead to life-threatening hemorrhage and/or limb-threatening ischemia if not addressed promptly. Vascular injury management demands timely and unique expertise, particularly for pediatric patients. In part 1 of this review, we discussed the scope and extent of the epidemic of traumatic vascular injuries in pediatric patients, reviewed current evidence and outcomes, discussed various challenges and advantages of a myriad of existing team structures, and outlined potential outcome targets and solutions. However, in order to optimize care for pediatric vascular trauma, we must also understand the fundamental best practice principles, surgical options and approaches, medical management, and recommendations for ongoing, outpatient follow-up. In part 2, we will address the best evidence, combined with expert consensus, regarding strategies for diagnosing, managing, and ongoing follow-up of vascular trauma, with particular focus on the nuances that define the unique approaches to pediatric patients. Level of Evidencen/a.

TEMPORARY REMOVAL: Principles and Practice in Pediatric Vascular Trauma: Part 1: Scope of Problem, Team Structure, Multidisciplinary Dynamics, and Solutions

As of 2020, penetrating injuries became the leading cause of death among children and adolescents ages 1–19 in the United States. For the patients who initially survive and receive advanced medical care, vascular injuries are a significant cause of morbidity and additionally trigger notable trauma team angst. Moreover, penetrating injuries can lead to life-threatening hemorrhage and/or limb-threatening ischemia if not addressed promptly. Vascular injury management demands timely and unique expertise, particularly for pediatric patients. As the frequency of vascular injuries requiring operative management increases, it becomes clear that an ad hoc approach is not ideal. An integrated team would provide the best approach for rapid hemorrhage control and revascularization, but the structure of vascular response teams at children's hospitals is highly variable. In part 1 of this review, we will evaluate the scope and extent of the epidemic of traumatic vascular injuries in pediatric patients, review current evidence and outcomes, discuss various challenges and advantages of different team structures, and outline potential outcome targets and pediatric vascular trauma response solutions. Level of Evidencen/a.

Application of the K-Nearest Neighbor Method to Predict Demand for Goods from Customers at PT Sinergi Prima Enjineering

PT Sinergi Prima Enjineering, which is engaged in services, has been trusted as a contractor in several companies facing challenges in handling the large number of requests for goods and stock inventory management. This research aims to improve the prediction of demand for goods and inventory management using the calculation of the K-Nearest Neighbor (KNN) method and RapidMiner tools. With the comparison of calculations between KNN and RapidMiner using ten test data, the results are appropriate where the categorical grouping is often ordered totaling five data, moderately ordered totaling two data and rarely ordered totaling three data. The test results show that K = 3 produces a prediction accuracy of 91.98%. These results show that K-Nearest Neighbor can accurately anticipate future stock inventory and items that will be ordered by customers and it is hoped that the company can improve customer satisfaction and overall operational performance.

Examining the Prospects of Residential Water Demand Management Policy Regulations in Ethiopia: Implications for Sustainable Water Resource Management

This study examines the prospects of residential water demand management policy regulations in Ethiopia and their implications for sustainable water resource management. This study aims to evaluate the existing policy regulations and analyze their effectiveness in promoting efficient water use and conservation practices in residential areas. By considering the potential challenges and opportunities associated with these regulations, the research provides insights into the future of residential water demand management in Ethiopia and suggests strategies for enhancing sustainable water resource management. An integrated literature and policy document review, alongside observation and interviews, was used to assess the viability of residential water demand management policies. The assessment of current policy regulations for residential water demand management in Ethiopian urban towns has revealed significant shortcomings in promoting water conservation activities. Simple linear regression analysis of water consumption data from 2010 to 2020 showed no significant reduction in water usage, with an increase in average consumption from 43, 39, and 28 L per capita per day (LPCD) pre-policy to 72, 51, and 42 LPCD post-policy for Arba Minch, Ziway, and Debre Birhan, respectively. Hence, there is a need for significant improvements in the current water resource policy guidelines, which lack specificity, particularly in residential water demand management conservation strategies. The lack of awareness among residents regarding the importance of conserving their limited water resources is evident. To address these challenges and ensure the sustainability of the water supply, the government and policy developers must engage with various stakeholders, including the community, in the process of revising current policy documents. A more precise and tailored approach is necessary for its effective implementation.

Optimizing water quality in urban distribution networks: Leveraging digital twin technology for real-time demand management

Optimizing water quality in urban distribution networks: Leveraging digital twin technology for real-time demand management

Determinants and Complexities of Halal Logistics in Malaysia: A Systematic Literature Review

This study employs a systematic literature review to examine the challenges of halal logistics in Malaysia, addressing a significant gap in the literature concerning the operational difficulties in maintaining halal integrity throughout supply chain processes. As the world’s Muslim population grows, understanding the complexities of halal logistics becomes crucial for industry stakeholders. Through Google Scholar and Scopus databases, this research identifies and analyzes 14 pertinent articles, focusing on the challenges within halal logistics. The thematic analysis reveals six primary challenges faced in Malaysia: high operational costs, lack of knowledge, limited demand for halal logistics services, operational complexities, inadequate management, and difficulties in the implementation of halal standards. These findings not only enhance the theoretical understanding of halal logistics but also offer practical insights for improving its implementation. By pinpointing these challenges, the study suggests a need for strategic efforts to foster market growth and service competitiveness in the halal logistics sector. Future research should broaden the review scope and explore solutions to these challenges, promoting best practices in halal logistics.

Jointly modelling activity start time, travel mode, companionship, and destination location choices

Activity-travel decisions, including time use (i.e. activity start time), travel choices (i.e. mode and companionship), and destination location choices are interdependent and complex in nature. They are often controlled by observed factors such as sociodemographic, vehicle ownership, built environment, land use, and unobserved factors like attitude, preference, or habits which typically are not captured in the survey data. To accommodate these complex interactions and capture trade-offs among the time use-travel-land use choices, this study proposes a joint discrete choice model by introducing unobserved factors that are common to them. The model results confirm the presence of complex interdependencies among these choice dimensions. In addition, this study highlights the contribution of observed and unobserved factors introduced in the model by calculating the total variance of utility differences. Lastly, this study provides behavioural insights on the activity-travel patterns, which can be further used to develop robust travel demand management policies.

Operational optimisation of a microgrid using non-stationary hybrid switched model predictive control with virtual storage-based demand management

Demand-shaping mechanisms are a key component of modern energy management systems, although not unproblematic. The degree of social acceptance of interference with demand or generation and the ease of integration of various types of non-critical loads depends on the method of their implementation. In addition, the critical load pool typically includes devices with different response times. The energy management systems currently in use often cannot meet user expectations. Especially when considering other vital aspects, such as energy market spread, storage wear, or connection to the utility grid and neighbouring microgrids. The authors adopted an approach of unifying demand side management and response in the form of virtual energy storage. Said store allows for the accommodation of loads operating under differing scheduling horizons. Such a new concept allows management not only in terms of quantity but also in terms of time. The storage is the focal point of a comprehensive energy management system based on switched model predictive control. The receding horizon algorithm relies on a non-stationary hybrid microgrid model. The study compares the operating costs of microgrids with virtual storage, allowing only demand postponement, preponement or bidirectional operation. The energy management system is also examined for sensitivity to changes in the weight matrices of the cost function, horizon length and forecast inaccuracy. Introducing virtual energy storage reduces microgrid operating costs by up to 16%. The decrease in control performance is proportional to the prediction accuracy, and the sensitivity allows for customisation.

Managing laboratory test ordering: a challenge in the new laboratory medicine model.

The role of Laboratory Medicine in patient care has evolved in the last decades. The same has occurred to the laboratory model, which has evolved from a traditional model where the laboratory is merely involved in clinical decision-making to a leading model where the laboratory is not only involved but also determines decision-making. The advent of new technologies and automation of processes have enabled laboratory professionals to focus on the first and last phase of the analytical process namely, test ordering and decision-making based on laboratory results. These phases are more error-prone than the analytical phase, and where action must be taken to improve the quality of patient care. We share our experience in the design and establishment of laboratory test demand management interventions that facilitated diagnosis of occult disease, improved adherence to clinical guidelines, and optimized patient safety. A description is provided of key points in the management of laboratory test over/underutilization. The objective of this review is to promote the involvement of laboratory professionals in the design and implementation of demand management interventions and in the development of the new Leader Laboratory model.