Efficient Resource Utilization Research Articles

Research on Urban Land Suitability Evaluation Based on GIS—A Case Study of Xi'an City

The evaluation of urban land suitability plays a crucial role in urban planning and land management. Taking Xi'an City as a case study, this research, based on ArcGIS software, conducted an in-depth study and evaluation of urban land suitability by comprehensively considering factors such as terrain, land use status, and DEM elevation data. By collecting and analyzing a large amount of spatial data, a set of urban land suitability evaluation models was established. With the functionality of ArcGIS software, spatial analysis and data processing were carried out to generate spatial distribution maps of urban land suitability. The research results indicate that land suitability is influenced by various factors, including terrain features, land use status, and elevation. Therefore, when formulating urban planning and land use policies, it is essential to consider these factors comprehensively to promote sustainable urban development and rational resource utilization. In future urban development, it is necessary to combine the influencing factors of urban land to develop more scientifically sound urban planning, aiming to achieve optimized spatial layout of cities and efficient resource utilization.

Government Expenditure and Economic Growth: A Comparative Analysis of Japan

Purpose: The aim of the study was to investigate the government expenditure and economic growth: a comparative analysis of Japan
 Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries.
 Findings: The comparative analysis of government expenditure and economic growth in Japan revealed a positive correlation between increased public spending and economic expansion. Strategic allocations towards sectors like education and healthcare were found to significantly contribute to long-term growth. Recommendations stressed the importance of transparent and accountable spending practices for sustained economic development, emphasizing prudent fiscal management and efficient resource utilization.
 Unique Contribution to Theory, Practice and Policy: Keynesian economics, wagner's law & endogenous growth theory may be used to anchor future studies on the government expenditure and economic growth: a comparative analysis of Japan. Develop a comprehensive framework for evaluating the effectiveness of government expenditure policies in Japan. Fiscal Sustainability Strategies: Develop strategies for ensuring the long-term sustainability of government finances in Japan, given the challenges posed by an aging population and rising healthcare costs.

Integrated rice-yellow catfish farming resulting in variations in the agricultural environment, rice growth performance, and soil bacterial communities.

Different rice production patterns exert varying comprehensive impacts on the agricultural environment. Integrated rice-fish farming, an advanced and rapidly developing agricultural production pattern, aims to improve resource utilization efficiency and enhance food productivity. To unravel the responses and internal interactions of the agricultural ecological environment to integrated rice-fish farming, we assessed and compared environmental factor, rice growth performance, and soil microbiome in both integrated rice-yellow catfish farming (IRYF) and rice monoculture (RM) systems. Our results revealed significant increases in the total nitrogen and ammonia concentrations in the paddy water and soil induced by the IRYF. Rice growth performance in the IRYF group surpassed that in the RM group. IRYF obviously impacted almost all dominant bacterial phyla, genera, and functional groups (top ten most abundant), enhancing the ability of bacteria to degrade and utilize organic matter. Additionally, IRYF led to noticeable reductions in the Shannon, Simpson, Chao 1, and Pielou_J indices. IRYF strengthened the interconnections between various taxonomic units in bacterial co-occurrence network, resulting in increased complexity, stability, and disturbance resistance in the soil bacterial community. IRYF notably facilitated the transition from a community assembly dominated by stochastic processes to one dominated by deterministic processes for the soil bacterial community. The deterministic process driving this transition was variable selection. All the environmental factors, except for soil nitrate, demonstrated relatively high contributions to alterations in soil bacterial communities, with environmental variables significantly positively correlated with the soil bacterial community in the IRYF group. Alterations in functionality, composition, and diversity of the soil bacterial community were clearly associated with most environmental variables and rice growth performance indices. Our research contributed to understanding the comprehensive impacts of integrated rice-fish farming on agricultural ecosystems and provide theoretical support for achieving the sustainable agricultural production and optimizing the rice production patterns.

Review on physiological and ecological characteristics and agronomic regulatory pathways of intercropping to delay root-canopy senescence of crops

Intercropping has been widely used in arid and semi-arid regions because of its high yield, and stable productivity, and efficient utilization of resources. However, in recent years, the high yield of traditional intercropping is mainly attributed to the large amount of purchased resources such as water and fertilizer, plastic film, and mechanical power. It leads to the decline of cultivated land quality and the phenomenon of premature root-canopy senescence of intercrops is become increasing serious. So, the application of traditional intercropping faces major challenges in crop production. In this paper, the manifestations, occurrence mechanisms, and agronomic regulatory pathways of crop senescence were analyzed in detail. The physiological and ecological characteristics of intercropping to delay root-canopy senescence of crops are reviewed in this paper. The main agronomic regulatory pathways of intercropping to delay root-canopy senescence of crops are based on above- and blow-ground interactions, include collocation of crop varieties, spatial arrangement, water and fertilizer management, and tillage and mulch practices. Future research fields of intercropping to delay root-canopy senescence should focus on the aspects of selecting and breeding special varieties, application of molecular biology techniques, and developing or applying models to predict and evaluate root-canopy senescence process of intercrops. Comprehensive analysis and evaluation of different research results could provide a basis for enhancing intercropping delay root-canopy senescence through adopting innovative technologies for regulating physio-ecological characteristics of intercrops. This would provide support for the development and adoption of high-yield, efficient, and sustainable intercropping systems in arid and semi-arid areas with more people and less land, and abundant light and heat resources.

Event-Triggered Adaptive Fuzzy Neural Network Output Feedback Control for Constrained Stochastic Nonlinear Systems.

This article investigates the problem of command-filtered event-triggered adaptive fuzzy neural network (FNN) output feedback control for stochastic nonlinear systems (SNSs) with time-varying asymmetric constraints and input saturation. By constructing quartic asymmetric time-varying barrier Lyapunov functions (TVBLFs), all the state variables are not to transgress the prescribed dynamic constraints. The command-filtered backstepping method and the error compensation mechanism are combined to eliminate the issue of "computational explosion" and compensate the filtering errors. An FNN observer is developed to estimate the unmeasured states. The event-triggered mechanism is introduced to improve the efficiency in resource utilization. It is shown that the tracking error can converge to a small neighborhood of the origin, and all signals in the closed-loop systems are bounded. Finally, a physical example is used to verify the feasibility of the theoretical results.

A workload prediction model for reducing service level agreement violations in cloud data centers

Cloud computing has become an emerging technology that offers services based on the pay-as-usage model. The cloud provides several advantages, but these advantages come with challenges, such as reducing Service Level Agreement (SLA) violations, efficient resource utilization, reducing energy consumption, etc., needing attention to leverage customer satisfaction and benefit cloud service providers. Workload prediction is a strategy that provides many benefits: reduced SLA violation, resource scaling, and resource optimization by predicting future workload. However, due to the varying workload of cloud applications, it is difficult to predict the workload accurately, and it fails for long-term dependencies. We propose a methodology based on Multiplicative Long Short Term Memory (mLSTM) that allows input-dependent transitions and considers long-term dependencies to predict the workload to address this issue. The proposed method is implemented and compared with other variants of LSTM used in literature for workload prediction purposes. The proposed work outperforms existing variants of LSTM in terms of prediction accuracy.

Maximizing efficiency and ensuring safety: Exploring the outcomes of 2 consecutive open radical cystectomies by the same team within a single surgical day

BackgroundThe purpose of this study was to evaluate the outcomes of performing 2 consecutive open radical cystectomies (RCs) within 1 day by the same surgical team. Patients and MethodsA retrospective analysis was conducted on data from patients who underwent RC at a single tertiary care center from January 2015 to February 2023. Patient characteristics, perioperative outcomes and endpoints were analyzed. Univariable and multivariable logistic regression models were created to predict major complications. ResultsA total of 657 patients were included in the final cohort, containing 64 paired RCs (32 RC1 and 32 RC2) and 593 single RCs. Major complications occurred in 24.7% of the entire cohort, with no significant differences between single RC vs. RC1 and RC2. Paired RCs showed significantly shorter operative time (OT; p = 0.001) and length of stay (LOS; p = 0.047) compared to single RCs. There were no significant differences in transfusion rates, 30-day readmission, 30-day mortality, or histopathological results between paired and single RCs. Multivariable analysis identified patient characteristics such as age (OR = 1.67, p = 0.03), sex (OR = 0.45, p = 0.008), BMI (OR = 1.98, p = 0.007), ASA-score (OR = 1.61, p = 0.04), and OT (OR = 1.87, p = 0.008) as independent predictors of major complications. ConclusionPerforming 2 consecutive open RCs within 1 day by the same surgical team is a safe approach in experienced hands. This strategy optimizes the utilization of surgical resources and addresses the growing demand for urologic care while maintaining high-quality patient care. Preoperative planning should consider patient-specific factors to minimize risks associated with major complications. Micro AbstractThis study evaluates the outcomes of performing 2 consecutive open radical cystectomies (RC) in a single day by the same surgical team. Data from 657 patients who underwent RC at a single tertiary medical center proved that this approach is safe, with no significant differences in major complications. Preoperative planning should consider patient-specific factors for efficient utilization of surgical resources.

Research on the spatial allocation of national fitness resources at the street scale—taking Fuzhou city as an example

To explore the spatial allocation of national fitness resources at different spatial scales in Fuzhou city to provide useful references for optimizing and enhancing the spatial allocation of national fitness resources and urban planning. The equity, spatial distribution characteristics, accessibility and supply-demand balance of national fitness resources in Fuzhou city are analysed in depth by using the two-step mobile search method of multiple travel modes, the Gini coefficient, and exploratory spatial data analysis methods. The results show that the overall spatial allocation of national fitness resources is in a balanced state, but there are serious inequities and spatial mismatches in each district (county); the spatial distribution of national fitness resources is characterized by centralized agglomeration and surface dispersion, being dense in the south and sparse in the north. Areas with insufficient resources per capita have an agglomeration-type scattering distribution; areas with sufficient resources per capita have a dispersed patch distribution. Access to national fitness resources and the relationship between their supply and demand are characterized by positive spatial concentration; however, the layout of the national fitness resources planned for the old urban areas urgently needs to be optimized, with the Chating and Antai streets serving as centres, to increase the effective supply. Finally,we suggestions that Top-level design should be strengthened, the communalization of sports public services should be promoted, the service capacity and utilization efficiency of national fitness resources should be enhanced, and the construction of national fitness resources in new urban areas and new industrial agglomerations should be accelerated.

Towards carbon neutrality: The role of innovation and resources efficiency in China's economic transformation

This study investigates the necessary paradigm shift in redefining productivity. It achieves this by examining the complex interplay between technological innovation, efficiency in natural resource utilization, and the pursuit of green economic recovery as a path towards carbon neutrality. The research employs the Autoregressive Distributed Lag (ARDL) model to analyze the dynamics across these domains, focusing specifically on China for the period 2010–2022. Through comprehensive analysis, the study reveals significant results that illuminate potential pathways for achieving sustainable development. The findings highlight the crucial role of promoting technological innovation and optimizing natural resource use efficiency in driving green economic recovery and mitigating carbon emissions. These results emphasize the importance for policymakers to prioritize investments in innovation, resource efficiency, and green initiatives. This prioritization facilitate the transition towards carbon neutrality and foster long-term environmental sustainability and economic resilience.

Effective dewatering and resourceful utilization of high-viscosity waste slurry through magnetic flocculation

When a slurry shield tunnel traverses through extensive deposits of silty clay stratum, a considerable amount of high-viscosity waste slurry with elevated particle content is inevitably generated. Failure to promptly address this waste slurry could have a severe impact on project progress and the surrounding environment. To address the challenge of rapid dewatering for high-moisture and high clay-content waste slurry, this paper introduces an efficient waste slurry dewatering technique: magnetic flocculation dewatering technology. Additionally, the paper explores avenues for the resource utilization of waste slurry containing magnetic particles Through conducting flocculation settling experiments, a comparative analysis was carried out on the dewatering effects of traditional flocculation and magnetic flocculation technologies. The paper discusses the dewatering mechanism of magnetic flocculation and determines the optimal process conditions for treating waste slurry utilizing magnetic flocculation. The results indicate: (1) The flocculation and dewatering process of waste slurry can be divided into two stages: a rapid flocculation settling stage and a slow consolidation stage, with the rapid flocculation settling stage playing a dominant role. (2) Under magnetic flocculation, the time required for the rapid flocculation settling stage is only 1/3 of that in traditional flocculation, and the slurry dewatering rate is 1.4 times higher than traditional flocculation. (3) The optimal sequence for adding material under magnetic flocculation is to add magnetic powder first and then the flocculant. The optimum dosage of magnetic powder is 1.0 g/L, and the most suitable magnetic field intensity is 92.0 mT. (4) The magnetically flocculated sludge obtained after magnetic flocculation treatment can be utilized for the production of construction bricks that comply with standard specifications. The research findings of this paper provide a basis and guidance for the efficient reduction and resource utilization of waste slurry.

Qualitative analysis of the effectiveness of audit committees and internal audit functions in the public sector: the case of public establishments in Morocco

This article examines corporate governance and the performance of the audit committee, as well as the functions of internal audit in the public sector of an emerging economy such as Morocco. Both of these functions are crucial for corporate governance, ensuring optimal service delivery by local authorities, particularly public institutions. The study, based on stakeholder theory, qualitatively analyzes corporate governance and the effectiveness of audit committees and internal audit units in the Moroccan public sector. The results suggest good corporate governance with the presence of audit committees and internal audit functions in the public sector. However, the inefficiency of audit committees and internal audit units is highlighted, attributed to the lack of guidance, non-implementation of recommendations, and insufficient resources in the Moroccan public sector. To enhance performance, it is recommended that leaders take into account the findings of audit committees and internal audit units, endorsing and incorporating their conclusions into action plans implemented by management. Audit committees should strengthen their oversight of internal audit functions to ensure their effectiveness. The presence of effective audit committees and internal audit units in the public sector reflects competent and efficient utilization of resources for the benefit of all stakeholders.

Intelligent load balancing in data center software‐defined networks

AbstractIn response to the increasing demand for efficient resource utilization in data center networks (DCNs), the development of intelligent load‐balancing algorithms has become crucial. This article introduces the dual double deep Q network (DDQN) algorithm, designed for software‐defined networking (SDN) environments within data centers. By leveraging deep reinforcement learning, DDQN addresses the challenges posed by dynamic traffic patterns, diverse flow requirements, and the coexistence of elephant and mice flows. Our algorithm adopts a comprehensive SDN approach, evaluating the network's status by analyzing switch load and bandwidth utilization. Using convolutional neural networks for elephant and mice flows in DCN, our algorithm enables adaptive learning and training tailored to the specific demands of elephant flows. Employing a double deep Q network architecture (DDQN), DDQN optimizes paths for both elephant and mice flows independently. Real‐time adaptation mechanisms make routing decisions based on the robust learning capabilities of DDQN, enhancing network utilization and reducing packet loss by generating optimal forwarding paths according to the current network state and traffic patterns. Simulations conducted in a Mininet environment with RYU as the controller, utilizing a fat‐tree data center topology, validate the efficacy of DDQN. The results demonstrate its effectiveness in achieving higher throughput, lower latency, and superior load balancing compared to traditional algorithms like equal‐cost multipath and Hedera.

Comparative analysis of call admission control techniques for efficient resource utilization and QoS in IEEE 802.16e network

Comparative analysis of call admission control techniques for efficient resource utilization and QoS in IEEE 802.16e network

Response of Runoff Change to Soil and Water Conservation Measures in the Jing River Catchment of China

Soil and water conservation measures (SWCMs) are vital in reducing runoff and ultimately affect water security and regional development. However, previous studies have mainly focused on the impact of a single SWCM, neglecting to distinguish between the effects of different SWCMs on runoff reduction. A Soil and Water Assessment Tool (SWAT) model was established in the Jing River catchment to identify the responses to runoff changes resulting from climate change and human activities. The model was used to quantitatively analyse the impact of different SWCMs on runoff reduction. The results indicated that human activities contributed significantly more to runoff reduction than climate change. The reduction benefits of different unit area changes for each SWCM on discharge, surface runoff and water yield at the outlet were ranked as follows: changing cultivated land to forest land > changing cultivated land to grassland > building terraces on a 5–15° slope > building terraces on a 5–25° slope > building terraces on a 15–25° slope. Regional authorities should comprehensively consider the effects of various SWCMs on water reduction, and optimise the layout of vegetation and terracing measures, to support the efficient utilization of water resources in the Jing River catchment.

The Role of Competitor Analysis, Market Orientation, and Service Quality in Working Capital Management and Operational Leverage as Links to Financial Stability of Manufacturing Companies Listed on the IDX: A Qualitative Approach

This study investigates the interconnectedness of competitor analysis, market orientation, service quality, working capital management, and operational leverage in shaping organizational financial stability. The research aims to identify strategic implications for effective management of these factors and provide insights for both theoretical understanding and managerial practice. The study employs a systematic literature review methodology to analyze existing research across various domains and synthesizes findings to elucidate the relationships among the variables. The results reveal that competitor analysis serves as a foundational element in strategic planning by providing insights into market dynamics and competitive positioning. Market orientation complements this by emphasizing customer-centricity and responsiveness to market needs, while service quality emerges as a critical determinant of organizational success. Effective working capital management and operational leverage strategies significantly impact financial stability by optimizing resource utilization and cost efficiency. The findings suggest that organizations must adopt a multidimensional approach to strategic management, integrating insights from marketing, finance, and operations. Managerial implications include prioritizing investments in market intelligence, fostering a customer-centric culture, optimizing working capital management practices, and carefully managing operational leverage. Collaboration across functional areas and agile decision-making are essential for adapting strategies to dynamic market conditions. Overall, the study contributes to a deeper understanding of the complex interplay among these factors and provides actionable recommendations for enhancing financial stability and sustaining competitive advantage.

The Design of FIR Filter Based on improved DA Algorithm and its FPGA implementation: REVIEW

The Design of FIR Filter Based on improved DA Algorithm and its FPGA implementation: REVIEW

Automatic gate controlling system for sustainable agriculture water management in Sri Lanka: A review

This research introduces an automatic gate-controlling system explicitly tailored for sustainable paddy cultivation in Sri Lanka. Paddy fields, critical to the nation's food security, often face water management and resource efficiency challenges. Given the pressing concerns of water scarcity and the need for efficient resource utilization in Sri Lanka's agricultural landscape, the automatic gate-controlling system emerges as a cutting-edge solution. This research explores the transformative potential of this technology in revolutionizing traditional irrigation practices. It provides a detailed examination of the system's components and functionalities, emphasizing the integration of smart sensors to gather real-time data on soil moisture levels, weather conditions, and crop water requirements. This data is then processed through advanced analytics, facilitating informed decision-making for the automated control of irrigation gates. These data inputs are then processed by an intelligent control system that automates the operation of water gates. By precisely regulating water flow, the system minimizes water wastage and mitigates over-irrigation risks, contributing to sustainable paddy cultivation practices. The automated nature of the system reduces the dependency on manual labor, providing farmers with an efficient and reliable tool for water management. By adopting this technology, the study envisions increased yields in paddy cultivation while promoting responsible use of water resources. This research marks a significant stride towards sustainable agriculture in Sri Lanka, particularly in the crucial paddy cultivation sector.

Examining the Integration of a GPS-based Staff Performance Monitoring and Assessment System within Academic Settings

Research evidence of manipulations of appraisal systems of various institutions in Nigeria abound, and little is known about the application of a Geographical positioning system (GPS) enabled system in this context. To cover this gap, this study investigates the integration of a real-time staff performance monitoring and assessment system with GPS technology, within academic settings. With the increasing emphasis on quality education and efficient resource utilization, academic institutions are exploring innovative approaches to monitor staff performance and student outcomes. The integration of real-time performance systems offers a promising avenue to achieve these goals by providing timely feedback, fostering accountability, and facilitating data-driven decision-making processes. This study outlines the key components of such a system, including its technological infrastructure, data collection methods, and performance evaluation metrics. Additionally, it explores the potential benefits and challenges associated with its adoption, considering factors such as staff engagement, privacy concerns, and institutional culture. Through a comprehensive examination of existing literature and case studies, this research aims to provide valuable insights and recommendations for academic institutions seeking to leverage real-time staff performance monitoring for institutional enhancement and educational excellence. While this study highlights the significance of stakeholder collaboration and continuous improvement mechanisms in ensuring the successful integration and sustained effectiveness of the monitoring system, it introduces a nuanced novel GPS technology and highlights some design implications which will guide future human-computer interaction researchers.

MADRLOM: A Computation offloading mechanism for software-defined cloud-edge computing power network

Cloud-edge computing power network often exhibits complex and heterogeneous structures, posing several challenges to computation offloading that significantly impact network performance and the efficient utilization of computation resources. In this paper, we propose a cloud-edge computing power network architecture that efficiently integrates cloud and edge computing resources into a single network system using software-defined networking technology to support upper-layer business applications. In this context, existing computation offloading methods struggle with issues like users' personalized requirements for latency and energy consumption, as well as the inability to adapt to dynamically complex environments. To overcome these challenges, we introduce a computation offloading mechanism, MADRLOM, focusing on the network's heterogeneity and modeling the computation offloading problem at the cloud-edge end. We formalize the offloading problem as a Markov process and employ a multi-agent deep reinforcement learning algorithm based on priority experience replay sampling to address the planning problem of computation offloading, allowing user equipment to continuously optimize offloading strategies in response to environmental changes and achieve rational resource allocation. Through dynamic offloading strategies, computation tasks can be intelligently allocated to appropriate computing nodes, thereby achieving optimal resource utilization. We utilized the Mininet simulation platform to construct the experimental environment for the software-defined cloud-edge computing power network and compared it with several representative computation offloading strategies. The experimental results demonstrate that the MADRLOM significantly reduces the total system overhead in the software-defined cloud-edge computing network and shows excellent adaptability to environmental changes.

Enzymatic pretreatment of Panax notoginseng leaves alleviates obesity and modulates the gut microbiota in high-fat diet-fed mice

The root of Panax notoginseng (Burk.) F.H. is one of the most famous natural medicines and functional foods for numerous diseases. The saponin constituents present in Panax notoginseng leaves (PNGL) demonstrate an elevated level of glycosylation in comparison to those in the roots, resulting in a significantly diminished bioavailability. In this study, we systematically screened nine recombinant thermostable glycosidases and identified a synergistic combination, namely Tpexy3 and Tpebgl3, to catalyze PNGL. At 70 °C, 2000 U of both glycosidases were added before and after 1 g of PNGL, yielding 650 mg of new fractions, of which ginsenosides Rg3, F2, CK, and PPD were identified as the major products. The enzymatic PNGL demonstrated a lipid droplet-lowering effect on the 3 T3-L1 lipid deposition model. Furthermore, the enzymatic PNGL exhibited significant inhibitory effects on weight gain, hyperlipidemia, hyperglycemia, and inflammation in high-fat diet (HFD) mice. Importantly, the enzymatic PNGL restored the HFD-induced increase in the Firmicutes/Bacteroidetes (F/B) ratio and promoted the growth of beneficial gut microbes with anti-inflammatory properties, improved lipid metabolism, and short-chain fatty acid production. These results strongly indicate that enzyme-catalyzed pretreatment of PNGL can effectively enhance its bioavailability and anti-obesity effects. Biological enzyme catalysis not only provides technical support for the development of specific functional products but also promotes the efficient and high-value utilization of natural product resources.