Management Requirements Research Articles

Water demand and supply under future water development and climate change scenarios in the upper Blue Nile basin

ABSTRACT Integrated methodological approaches to analyzing water demand and supply under changing scenarios in a river basin are crucial for managing water resources. This study evaluates the effects of climatic change and socioeconomic development on the water system in the upper Blue Nile basin. An integrated methodological approach was used, including the Soil and Water Assessment Tool (SWAT) and the Water Evaluation and Planning (WEAP) models. Water development scenarios were created for two time periods: near future (2021–2040) and full development (2041–2060). During the current account period, the amount of water delivered for irrigation purposes was balanced, and existing hydropower plants generated energy at full capacity. However, the irrigation water supply in the near future and full development periods under climate change scenarios indicates a shortfall at the basin level. Despite the fact that the basin's hydropower energy production will increase during the scenario periods, under construction and planned hydropower plants are predicted to operate at less than full capacity. The study concluded that climate change-induced water availability and irrigation expansion would contribute to the basin-level water supply–demand mismatch. As a result, the overall findings recommended water resource management requirements for increasing availability of water, minimizing water demand, and reducing unmet demand.

Personalized MRD Assessment in Peri-surgical ctDNA for Prognostic Prediction in Hepatocellular Carcinoma.

Detecting residual disease is a critical clinical requirement in the peri-surgical management of patients with resectable hepatocellular carcinoma (HCC). Previous studies focused on specific genomic regions exhibiting limited sensitivity and failed to meet the minimal residual disease (MRD) testing threshold. We introduce a next-generation sequencing (NGS) based assay, informed by baseline samples, facilitating MRD detection in hepatectomized HCC patients and offering prognostic predictions. This study involved 88 HCC patients who underwent surgical resections January 2016 to May 2016 in Zhongshan Hospital Fudan University. Tumor and normal tissue samples were collected during surgery, while plasma samples were obtained both before surgery and up to seven days post-surgery. Using an NGS-based personalized circulating tumor DNA assay, we analyzed MRD in both pre-surgical and post-surgical blood samples and the correlation with prognosis. With a median follow-up period of 80.7 months, our findings demonstrated significant correlations between pre-surgical ctDNA tumor fractions, post-surgical plasma MRD status, and both recurrence-free survival (RFS) and overall survival (OS). Post-surgical MRD status emerged as the most significant risk factor for cancer recurrence (HR=2.17, 95% CI: 1.09-4.30, p=0.027) compared to other clinical characteristics in multivariate Cox regression analysis. Notably, MRD status showed potential as a prognostic indicator among clinically low-recurrent-risk patients, such as those with BCLC stage 0-A, CNLC stage I-II. Evaluating personalized MRD provided crucial prognostic insights into RFS and OS. It efficiently identified patients at high risk of recurrence, even among those initially perceived as low-risk cases.

A single mutation G454A in the P450 CYP9K1 drives pyrethroid resistance in the major malaria vector Anopheles funestus reducing bed net efficacy.

Metabolic mechanisms conferring pyrethroid resistance in malaria vectors are jeopardizing the effectiveness of insecticide-based interventions, and identification of their markers is a key requirement for robust resistance management. Here, using a field-lab-field approach, we demonstrated that a single mutation G454A in the P450 CYP9K1 is driving pyrethroid resistance in the major malaria vector Anopheles funestus in East and Central Africa. Drastic reduction in CYP9K1 diversity was observed in Ugandan samples collected in 2014, with selection of a predominant haplotype (G454A mutation at 90%), which was completely absent in the other African regions. However, six years later (2020) the Ugandan 454A-CYP9K1 haplotype was found predominant in Cameroon (84.6%), but absent in Malawi (Southern Africa) and Ghana (West Africa). Comparative in vitro heterologous expression and metabolism assays revealed that the mutant 454A-CYP9K1 (R) allele significantly metabolises more type II pyrethroid (deltamethrin) compared with the wild G454-CYP9K1 (S) allele. Transgenic Drosophila melanogaster flies expressing 454A-CYP9K1 (R) allele exhibited significantly higher type I and II pyrethroids resistance compared to flies expressing the wild G454-CYP9K1 (S) allele. Furthermore, laboratory testing and field experimental hut trials in Cameroon demonstrated that mosquitoes harbouring the resistant 454A-CYP9K1 allele significantly survived to pyrethroids exposure (Odds ratio = 567, p < 0.0001). This study highlights the rapid spread of pyrethroid resistant CYP9K1 allele, under directional selection in East and Central Africa, contributing to reduced bed net efficacy. The newly designed DNA-based assay here will add to the toolbox of resistance monitoring and improving its management strategies.

Applying Change Management Theory in Schools to Meet the Requirements of Educational Innovation and Training in Vietnam

The application of change management theory to the management of teaching and learning activities in schools in Vietnam in recent years has attracted much attention, but this theory has not been systematically and clearly defined. The purpose of this article is to establish a theory of change management in schools to apply to school management in the context of education and training innovation in Vietnam today. Based on the approach of the Theory of Change, the article builds a system of theoretical issues on change management in schools. The research aims to establish directional criteria on change management capacity, requirements for change management, and methods of practicing change management. The research results provide a systematic approach to change management in schools that is suitable for the requirements of current education innovation in Vietnam.

Application of Dietary Anthocyanins in Type 2 Diabetes Mellitus Treatment

Type 2 diabetes mellitus (T2DM) is a common metabolic disorder characterized by impaired glucose control around the world that causes huge health challenges globally with increased morbidity and mortality. Inadequate insulin secretion and decreased insulin sensitivity are considered as main contributors to T2DM. Anthocyanin, a type of flavonoid compound, is one potentially feasible dietary intervention for T2DM treatment in addition to clinical drug interference. Dietary anthocyanins can be found in various berries, vegetables, and beverages, which provide vibrant colors. Anthocyanins are also increasingly used as colorants in the food industry. It is also seen as a supplement because of its antioxidation properties. Meanwhile, several evidence demonstrate the potential relationship between dietary anthocyanin intake and T2DM management. In this work, recent epidemiologic studies on the potential effects of anthocyanins in controlling T2DM have been reviewed, especially focusing on the typical indexes such as glycemic levels, insulin levels, etc. Many studies illustrate that appropriate intake of dietary anthocyanins could control glycemic levels, adjust insulin levels, and reduce insulin resistance. Because of these functions, dietary anthocyanins may trigger positive effects on T2DM treatment. Dietary anthocyanins could be seen as a good dietary intervention in T2DM control that meets the requirement of long-term management for the specific chronic disease.

Enhanced Data Security Using 5x5 Hill Cipher with Modular 53

This research presents an optimized approach to the Hill Cipher encryption and decryption algorithm using a 5x5 matrix and modular 53 arithmetic. The traditional Hill Cipher, a well-known symmetric key algorithm, typically utilizes smaller matrices and modular arithmetic, which may not provide sufficient security for contemporary applications. By expanding the key matrix to a 5x5 structure and adopting a larger modulus of 53, the complexity and security of the cipher are significantly enhanced. The study details the methodology for constructing and implementing the 5x5 key matrix, as well as the processes for encryption and decryption under the modular 53 system. The computational efficiency and security improvements achieved through this optimization are analyzed. Comparative assessments with the conventional Hill Cipher demonstrate that the enhanced approach offers superior resistance against cryptographic attacks while maintaining manageable computational requirements. The results of this research indicate that the proposed optimized Hill Cipher can serve as a robust encryption method suitable for securing sensitive data in various modern applications. This study contributes to the field of cryptography by providing a more secure and efficient variant of the classical Hill Cipher algorithm

ETL vs ELT: Evolving Approaches to Data Integration

This article explores the evolution of data integration approaches, focusing on the transition from Extract, Transform, Load (ETL) to Extract, Load, Transform (ELT) methodologies. It examines the characteristics, advantages, and challenges of both approaches in the context of modern data management requirements. The article discusses the factors driving the shift towards ELT, including cloud adoption, big data growth, real-time analytics demands, and the rise of data lake architectures. Additionally, it presents best practices for implementing ELT, covering areas such as data cataloging, version control, data quality checks, performance optimization, and security compliance. Through analysis of industry trends and real-world use cases, the article provides insights into why organizations are increasingly adopting ELT frameworks and the considerations involved in this transition.

Effects of economic growth target on the urban–rural income gap in China: An empirical study based on the urban bias theory

Urban–rural imbalance is a common phenomenon, and its prominent manifestation is the sustained expansion of the urban–rural income gap. For emerging countries, this gap encountered during the development process should be addressed by promoting development, which also puts forward high requirements for economic management. Inspired by political economy theory and the widening urban–rural income gap in China, this study constructs a theoretical framework of “purpose-behavior-performance-structure” based on the urban bias theory, and then quantitatively examines the effect of economic growth target on the urban–rural income gap based on panel data at the provincial level. In addition, we explore the mechanism by which economic growth targets affect the urban–rural income gap with the mediating effect model, and investigate the impact of marketization and spatial structure on the relationship between economic growth targets and urban–rural income gap with the moderating effect model. The results show that the economic growth target significantly contributes to the widening urban–rural income gap in the face of the political promotion incentives and economic growth target accountability system, and this effect exhibits substantial spatiotemporal heterogeneity. In addition, fiscal expenditure, fixed asset investment, and labor mismatch under urban bias are important mechanisms that lead to the widening urban–rural income gap, and the marketization level and spatial structure significantly affect this relationship. We put economic growth management, urban bias, and urban–rural income gap into the “purpose-behavior-performance-structure” theoretical framework, which provides a new explanatory perspective for understanding the urban–rural income gap in emerging economies, and new policy insights for rational economic growth management.

Integrated market scheduling with flexibility options

This work presents a generic optimization framework using advanced mixed-integer programming techniques to integrate day-ahead and balancing markets with distributed energy resources such as storage, electric vehicles, demand response, and Transmission and Distribution System Operators' coordination schemes. The day-ahead model determines optimal initial energy scheduling, while the balancing model optimizes energy and reserve products for three market designs with varying Transmission and Distribution System Operators’ coordination. The framework is applied to the interconnected Greek-Bulgarian-Romanian power system, considering 2030 installed capacities.The model outputs illustrate market coupling scenarios among Romania, Bulgaria, and Greece, highlighting clear price signals and distributed energy resources flexibility. Results reveal the significance of a diverse energy mix for energy security and show that Transmission and Distribution System Operators’ coordination significantly influences ancillary service prices, with reductions of up to 80 % in certain scenarios. Net demand values determine electricity flow direction. Flexibility providers like storage can cover up to 100 % of the upward congestion management requirements and 11 % of upward balancing energy, helping smooth energy allocation from intermittent renewables. The impact of electric vehicle penetration on generation scheduling is minimal. The proposed model offers valuable insights for system operators, market participants, and policymakers, enabling them to provide accurate price signals and optimize resource allocation.The integrated day-ahead and balancing market models support efficient renewable energy integration, emissions reduction, enhanced grid stability, and investment in low-carbon technologies. This aligns with the United Nations Framework Convention on Climate Change goals, contributing to the development of sustainable and resilient energy systems.

Construction method for novel power load management system detection environment based on model adaptive equivalence

With the focus on integrating large-scale clean energy, the requirements for demand-side load resource management and maintaining the power system's supply-demand balance have increased. New types of power load management are thus gaining importance. Considering the varied load management needs and response strategies across different scenarios, and taking into account essential network elements like topology and connectivity, a multi-level interactive architecture is established to support hierarchical load control networking models for energy flow. By leveraging statistical analysis and simulation deduction, this approach improves the comprehensive evaluation of load system indicators, particularly in scenarios with small sample sizes and significant randomness. This methodology contributes to more efficient power system management and enhances load control adaptability.

Comparison of outcomes in dogs undergoing hiatal hernia repair with and without use of a gastropexy: 41 cases (2012-2022).

To determine the difference in complication rate, gastrointestinal grade and requirement for ongoing medical and/or surgical management following hiatal hernia repair in dogs with and without gastropexy. Clinical records were reviewed retrospectively for dogs that had undergone surgical hiatal hernia repair at two veterinary referral centres between April 2012 and March 2022. Pre-operative grading of gastrointestinal signs and brachycephalic obstructive airway syndrome was performed. All dogs had an oesophagopexy and phrenoplasty. Referring primary veterinary practices and clients were contacted to obtain follow-up information. Fisher's exact tests and Mann Whitney tests were used to assess pre- and intra-operative similarities between groups. Wilcoxon signed rank tests were used to determine the changes in gastrointestinal grade at short- (<6 months) and long-term (>6 months) follow-up. Forty-one dogs which underwent oesophagopexy and phrenoplasty were included. Fifteen dogs had no gastropexy performed and 26 dogs had left-sided gastropexy performed. Dogs that underwent gastropexy(n=8, 29%, 95% CI: 13 to 51%) were significantly more likely to require further surgery related to the initial surgery or persistence of gastrointestinal signs compared to dogs that had no gastropexy (n=0, 0%, 95% CI: 0 to 18%) . This difference was not significant when dogs which had further surgery to address brachycephalic obstructive airway syndrome were excluded. Gastrointestinal grade significantly improved for both groups at both short- and long-term follow-up. There was no significant difference in overall complication rate, gastrointestinal grade or requirement for further medical treatment between groups. A left-sided gastropexy is not required for successful surgical repair of hiatal hernia in dogs provided oesophagopexy and phrenoplasty are performed.

Research Data Management in German Academia from a Multiple Logic Perspective

The requirements for research data management (RDM) have increased. Due to academia’s neoliberalization, however, researchers already face a high workload within a hypercompetitive environment. The demand to integrate RDM as an additional task into academics’ day-today actions seems to be quixotic. To deepen our understanding of early career researchers’ (ECRs) daily work arbitrage, we need to know more about their behavior, actions, and decisions in relation to RDM. Drawing on a multiple institutional logics perspective at the micro-level, we conducted 40 semistructured interviews at German higher education institutions (HEIs) to investigate how ECRs respond to institutional logics in the context of RDM. Our findings revealed three profiles – the conformist, the waverer, and the resister – that make use of different response strategies to the state, market, professional, and community logic. We contribute to institutional logic research at the micro-level and, in addition, broaden prior research on HEIs and RDM by taking neoliberal academia into account.

Research on the Path of Transition from Financial Accounting to Management Accounting Under the Background of Big Data

Driven by the wave of big data, the traditional financial accounting model faces an urgent need for transformation, as it struggles to adapt to the complex requirements of modern enterprise management. This paper aims to explore the feasible path for transitioning enterprise financial accounting to management accounting in the context of big data. It first analyzes the limitations of financial accounting in the era of big data, then highlights the necessity of transitioning to management accounting. Following this, the paper outlines the various challenges that may arise during this transition and, based on the analysis, proposes a series of corresponding transition strategies. These strategies aim to provide theoretical support and practical guidance for enterprises seeking a smooth transition from financial accounting to management accounting.

Construction of a quantitative model for ski resort water demand and preliminary exploration of drainage irrigation pathways

In China, natural snowfall is insufficient, and ski resorts often require artificial snowmaking in winter and turf management in summer, which results in high overall water consumption and considered as one of the high water-consuming service industries, with an urgent need for theoretical foundations related to water management. Based on life cycle theory, we examined the characteristics of the water systems of ski resorts in winter and summer. A Monte Carlo simulation was used to construct a stochastic model to quantify the theoretical water consumption for snowmaking at ski resorts and to investigate the mechanisms by which various factors influence this consumption. We summarize the necessity of summer turf management and irrigation requirements at ski resorts, explore the interaction between ski resorts and agricultural irrigation. The results show that the theoretical water demand of ski resorts is basically consistent with the actual water consumption of ski resorts, that the constructed model is feasible, and that snowmaking water is the most important water use of ski resorts. Exploring the collection and reuse of meltwater or rainwater from ski resorts for agricultural irrigation in the spring and summer could provide more possibilities for the sustainable management of regional water resources. The research findings can provide a theoretical basis for scientifically and reasonably setting the norm of water intake for ski resorts and for developing comprehensive water resource management plans for ski resorts and agricultural irrigation.

SAPPNet: students’ academic performance prediction during COVID-19 using neural network

A variety of reasons have made it more difficult for educators and tutors to anticipate students’ performance. Numerous researchers have used various predictive models to identify students who may be at-risk of dropping out early. Additionally, these methods were used to forecast final semester grades based on various datasets. However, these prediction models still fall short of meeting educational management requirements. In this paper, we propose the deep learning (DL) based model named students academic performance prediction network (SAPPNet) to predict the students’ grades. We consider the questionnaire-based Jordan University dataset which contains demographic information, usage of digital tools before and after COVID-19, sleep times before and after COVID-19, social interaction, psychological state, and academic performance. SAPPNet consists of spatial convolution modules which are designed to extract spatial dependencies includes categorical and numerical attributes that represent static features (gender, level/year, age, digital tools used before and after COVID-19, psychological condition using prolonged e-learning tools) and temporal module for temporal dependencies involves sequences that capture changes before and after COVID-19. Additionally, we also try to implement classical machine learning (ML) models including support vector machine, k nearest neighbor, decision tree, and random forest, and DL models named artificial neural network, convolutional neural network, long short-term memory, and students learning prediction network. Simulation results show that SAPPNet achieved the best performance compared to state-of-the-art methods, with an accuracy, precision, recall, and an F1-score of 93%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$93\\%$$\\end{document}. The proposed model with spatial and temporal modules improves the prediction performance, and it implies new aspect of the educational dataset.

Regulatory and legal principles of management of sports schools for children and youth

The activities of sports schools for children and youth play a key role in shaping the physical culture of young people, promoting a healthy lifestyle, and preparing future professional athletes. The successful functioning of these schools relies on appropriate legal frameworks that outline the operational rules, requirements for educational processes, funding, and management of facilities. there is a pressing need to analyze the current legal framework governing the management of sports school for children and youth. Considering the constant changes in the legislation and the growing requirements for the quality of sports institutions, there is a pressing need to analyze the current legal framework governing the management of sports schools for children and youth. The purpose of this article is to analyze the regulatory and legal principles of managing the activities of sports schools for children and youth in Ukraine. The key legislative acts regulating the organizational, financial, and legal aspects of the functioning of sports schools for children and youth have been analyzed, including the Constitution of Ukraine, the Law ‘On Physical Culture and Sports,’ and the orders of the Ministry of Education and Science and the Ministry of Youth and Sports. This resolution provides a comprehensive framework for the operation of sports schools for children and youth as well as defines the forms of ownership, legal foundations of their activities, funding procedures, and requirements for athlete training. Particular attention is given to the state social standard in physical culture and sports, which sets requirements for the quality of services, infrastructure, and athlete training. The mechanisms of management that contribute to increasing the efficiency of sports schools for children and youth are highlighted.

Institutional shaping of CDE implementation in BIM-enabled AEC projects

The common data environment (CDE) for information sharing is one of the fundamental requirements for effective workflow management to harness the potential of building information modeling (BIM). While studies are replete on BIM from a technology adoption perspective, notably lacking in the literature is the understanding of the influence of institutions and their pressures on CDE adoption as an information management platform. This study aims to address this gap. Using the action research approach, a flagship university construction project in India was studied to understand the interplay of institutions and CDE adoption. Institutional theory was used as a theoretical lens to illuminate and analyze the implementation issues of CDE. The findings show that CDE implementation undergoes a series of transformations due to institutional pressures. The responses to institutional pressures are conformance, coupling and decoupling, and mutations. Insights of this study guide practitioners to be aware of the processes through which institutional pressures contextualize and transform the intended change. Accordingly, findings can help managers and public sector agents on aspects related to nudging and shaping the implementation of change through action strategies and tactics. The study extends the BIM adoption/localization literature by highlighting that institutional pressures modify the objectives of CDE. It theorizes the processes through which institutional pressures contextualize and transform a change agenda.

Simulation Design and Research of Flame Generation in Virtual Fire Scene Based on Unity3D

Since the 21st century, with the continuous development and progress of science and technology, the possibility of fire danger is also rising, the requirements of public fire safety management have also been improved accordingly, and the problems in its fire safety management work make it difficult to meet the management requirements. The selection of firefighters has also become the top priority of management, good psychological quality of firefighters can keep calm in the face of fire explosions and various emergencies, and can make the most correct choice to complete the rescue and fire fighting work. In this paper, a building in a certain location is selected as the location to simulate the scene of fire. Through human-computer interaction to judge the psychological quality of firefighters. First use major modeling software such as 3ds Max, Adobe Fusecc, or find material in the Unity3D store to create models of fire scenes and people and import them into Unity3D. Using Unity3D's own particle system component to build flame models, adding collision body components to all models to detect their collision detection mechanism and the mechanism of flame spreading combustion. A Scenario-based Communication Ability Evaluation System Based on Traditional Cognitive Behavior Measurement and Advanced Eye Movement, EEG and NIR Acquisition Techniques.

Transforming reservoir management in petroleum processing: a synergistic approach with IoT and Blockchain for enhanced emissions monitoring and regulatory reporting

This article proposes an innovative method to transform reservoir management in petroleum processing through the integration of the Internet of Things (IoT) and Blockchain technologies. In response to increasing demands for strict emissions monitoring and regulatory compliance, our approach aims to increase the precision, transparency, and security of data collection and reporting. In our proposed framework, we leverage IoT technology to deploy sensor networks across reservoirs and processing plants. The collected data is integrated into a Blockchain. This creates an immutable and transparent ledger for emissions-related information. Blockchain’s decentralized and tamper-proof features preserve data integrity and facilitate secure information sharing between stakeholders, including regulators and operators. Considering the specific scalability and performance requirements for data management in the petroleum industry, we propose a 4-layer system architecture. Our study examines the practical implementation and benefits of this innovative synergy.

Advancements in Battery Management through Multi-Scale Digital Twin Technology: Principles and Applications

To achieve peak carbon and carbon neutral goals, the development of electric cars has become strategically important. It is necessary to have precise battery management technology because the lifespan and safety of power batteries change dynamically as they are used. This leads to rapid capacity degradation brought on by the inconsistent performance of single cells and thermal runaway brought on by short board batteries or internal defects. New battery management capabilities have been made possible by the development of the digital twin model, which is now one of the technical trends in the industry. Based on the development trend of battery management technology , the article concentrates on the analysis of basic principles of battery digital twin modeling from the aspects of system modeling to management and control requirements. The article systematically introduces the construction method of multi-dimensional, multi- scale and multi-physical field fusion of digital twin battery. Combined with the previous research of the team, the practical case of the digital twin battery was analyzed. Finally, the application perspective of digital twin battery is discussed in production design, life cycle management and other scenarios, which provided ideas and references for the development of battery management technology.