Efficient Resource Utilization Research Articles

Effects of Water and Nitrogen Regulation on Apple Tree Growth, Yield, Quality, and Their Water and Nitrogen Utilization Efficiency.

Apple tree productivity is influenced by the quantity of water and nutrients that are supplied during planting. To enhance resource utilization efficiency and optimize yields, a suitable strategy for supplying water and nitrogen must be established. A field experiment was conducted using a randomized block group design on five-year-old apple trees in Ningxia, with two irrigation lower limit levels (55%FC (W1) and 75%FC (W2)) and four N application levels (0 (N1), 120 (N2), 240 (N3), and 360 (N4) kg·ha-1). Our findings showed that leaf N content increased with a higher irrigation lower limit, but the difference was not statistically significant. However, the leaf N content significantly increased with increasing N application. The growth pattern of new shoots followed logistic curve characteristics, with the maximum new shoot growth rate and time of new shoot growth being delayed under high water and high nitrogen treatments. Apple yield and yield components (weight per fruit and number of fruits per plant) were enhanced under N application compared to no N application. The maximum apple yields were 19,405.3 kg·ha-1 (2022) and 29,607 kg·ha-1 (2023) at the N3 level. A parabolic relationship was observed between apple yield and N application level, with the optimal range of N application being 230-260 kg⸱ha-1. Apple quality indicators were not significantly affected by the irrigation lower limit but were significantly influenced by N application levels. The lower limit of irrigation did not have a significant impact on the quality indicators of the apples. Water and N utilization efficiencies improved with the W2 treatment at the same N application level. A negative relationship was observed between the amount of nitrogen applied and the biased productivity of nitrogen fertilizer. The utilization of nitrogen fertilizer was 127.6 kg·kg-1 (2022) and 200.3 kg·kg-1 (2023) in the W2N2 treatment. The apple yield was sustained, the quality of the fruit improved, and a substantial increase in water productivity was achieved with the W2N3 treatment. The findings of this study can be used as a reference for accurate field irrigation.

Enhancing diagnostic precision in thyroid nodule assessment: evaluating the efficacy of a novel cell preservation technique in fine-needle aspiration cytology.

This study aimed to evaluate the effectiveness of thyroid fine needle aspiration cytology (FNAC) using a novel-cell preserving matrix called Cytomatrix in improving diagnostic accuracy for thyroid nodules. Fifty patients undergoing thyroidectomy were enrolled and FNAC was performed on the excised thyroid glands, with the collected sample being placed on the Cytomatrix. The results were compared with histopathological analysis, and diagnostic performance was assessed statistically. Cytomatrix demonstrated an accuracy of 96%, sensitivity of 84.61%, and specificity of 100%. Concordance between cytological and histopathological findings highlighted Cytomatrix's potential to enhance thyroid FNAC accuracy. FNAC using Cytomatrix shows promise in improving diagnostic accuracy for thyroid nodules. Its application, marked by faster processing and efficient resource utilization, coupled with the preservation of cellular architecture, holds considerable potential in enhancing cytological diagnosis, thus optimizing patient management strategies.

Diversity analysis of panicle traits in Chinese prickly ash germplasm resources and their influence on its systematic classification

This study aimed to reveal the diversity and variation in panicle traits of the Chinese prickly ash and clarify their influence on the its systematic classification to provide a theoretical basis and technical support for the efficient utilization of Chinese prickly ash germplasm resources and breeding. Sixteen panicle traits were identified from 35 Chinese prickly ash germplasm resources from 2021 to 2022. The diversity of these panicle traits and their role in the plant’s systematic classification were studied using variance, correlation, cluster, and principal component analyses. Cluster analysis showed that the 35 Chinese prickly ash germplasm resources could be divided into two groups with Euclidean distances of 25. Further analysis showed that yield traits such as panicle length, panicle width, primary branching, grain number per panicle, and grain weight per panicle were significantly positively correlated with grain chlorophyll content, while grain anthocyanin content was negatively correlated with both panicle (panicle length, panicle width, panicle length to width ratio, primary branching, grain number per panicle, and grain weight per panicle) and grain characteristics (single grain weight, thousand-grain weight, grain length, grain width and fruit shape index). In conclusion, Chinese prickly ash germplasms have diverse panicle traits. Z. armatum has dark green grains, long and wide panicles, a long conical shape, many primary branches, high grain weight, and high grain number per panicle. In contrast, Z. bungeanum has bright red seeds, a panicle width larger than its length, short and conical panicles, a small number of primary branches, and low grain weight per panicle and number of grains per panicle. Overall, Z. armatum had a significant yield advantage over Z. bungeanum.

Innovation in Education Management and Talent Cultivation Models for New Quality Productivity: Based on Data Driven and Intelligent Teaching Management

The rapid development of information technology and the emergence of new quality productivity, the education management and talent cultivation models that meet the needs of modern society have to be innovated. Data-driven education management combined with intelligence, is an important innovation direction that improves the utilization of teaching resources, optimizes the teaching process, and provides customized learning support for students by leveraging data analysis and intelligent algorithms, has become an important innovation direction. This paper elaborated the key concepts and principles of data-driven, intelligent-based teaching management mode, and analyzed the realization and roles of data-driven, intelligent-based teaching management mode in terms of education management, and talent cultivation. The application of intelligent teaching management model based on data has achieved positive results. Teachers have given a positive evaluation of the model proposing that it can improve the utilization efficiency of teaching resources, optimize the teaching process, and personalize the support of student learning.

Microorganisms usage in enhanced oil recovery: Mechanisms, applications, benefits, and limitations

AbstractIn today's world, where the oil and gas industry faces challenges such as declining production and the increasing need for efficient resource utilization, microbial enhanced oil recovery (MEOR) is introduced as a biological solution. This method, based on mechanisms like surfactant production, reduction of oil viscosity, and improvement of reservoir chemical properties, can increase oil recovery by 15%–20%, reduce operational costs by up to 30%, and is highly environmentally friendly. This study reviews various MEOR methods, including stimulating existing microbial activity in reservoirs or injecting microbes and nutrients. It presents successful examples of this technology in different oil fields, showing how MEOR can be a sustainable alternative to traditional methods. However, challenges such as the need for further research, control of biological processes, and advanced technology usage are also emphasized.

Parametric studies on energy utilization of the Chinese medicine residues: Preparation and properties of densified pellet

The depletion of fossil fuels has fueled an increased interest in biomass resources usage for heat and electricity generation. As an important biomass resource, Chinese medicine residues have great potential in substituting fossil fuels. However, that is basically limited by its poor properties, including low bulk density, high moisture content, and inhomogeneous structure. Herein, a safe and sustainable strategy was reported to prepare a high-quality densified pellet derived from Chinese medicine residues to address these worries. In this process, mixed and simple size materials were densified under various moisture content and pressure using a laboratory electronic tablet press machine equipped a single pellet mold. Results showed that higher pressure, ideal moisture content (∼6.5 %), and mixed particle size could densify better quality pellets. These findings pave the way for the safely and efficient resource utilization of Chinese medicine residues, as well as providing theoretical guidance and technical support for the household heating.

Softwarized and containerized microservices-based network management analysis with MSN

Microservice architecture is a service-oriented paradigm that enables the decomposition of cumbersome monolithic-based software systems. Using microservice design principles, it is possible to develop flexible, scalable, reusable, and loosely coupled software that could be containerized and deployed in a distributed edge/cloud environment. The flexible deployment of microservices in an edge environment increases system performance in terms due to dynamic service function placement and chaining possibly resulting in latency reduction, fault tolerance, scalability, efficient resource utilization, cost reduction, and energy consumption reduction. On the other hand, virtualization and containerization of microservices add processing and communication overheads. Therefore, to evaluate end-to-end microservices-based system performance, we need to have an end-to-end mathematical formulation of the overall microservice-based network system. Incorporating the virtualization overhead, here we provide end-to-end mathematical formulation considering system parameters: latency, throughput, computational resource usage, and energy consumption. We then evaluate the formulation in a testbed environment with the Microservice-based SDN (MSN) framework that decomposes the Software-defined Networking (SDN) controller in microservices with Docker Container. The final result validates the presented mathematical modeling of the system’s dynamic behavior which can be used to design a microservice-based system.

Effects of Paddy Rain-Flood Storage on Rice Growth Physiological Indices and Nitrogen Leaching under Organic Planting in Erhai Lake Basin.

In order to address the increasingly prominent issues of water resource protection and agricultural non-point source pollution in the Erhai Lake Basin, this study conducted a two-year field experiment in Gusheng Village, located in the Erhai Lake Basin. In 2022, two irrigation treatments were set up: conventional flooding irrigation (CK) and controlled irrigation (C), with three replicates for each treatment. In 2023, aiming to enhance the utilization rate of rainwater resources and reduce the direct discharge of dry-farming tailwater from upstream into Erhai Lake. The paddy field was used as an ecological storage basin, and the water storage depth of the paddy field was increased compared to the depth of 2022. Combined with the deep storage of rainwater, the dry-farming tailwater was recharged into the paddy field to reduce the drainage. In 2023, two water treatments, flooding irrigation with deep storage and controlled drainage (CKCD) and water-saving irrigation with deep storage and controlled drainage (CCD) were set up, and each treatment was set up with three replicates. The growth and physiological index of rice at various stages were observed. Nitrogen leaching of paddy field in surface water, soil water, and groundwater under different water treatments after tillering fertilizer were observed. The research results show that the combined application of organic and inorganic fertilizers under organic planting can provide more reasonable nutrient supply for rice, promote dry matter accumulation and other indices, and also reduce the concentration of NH4+-N in surface water. Compared with CK, the yield, 1000-grain weight, root-to-shoot ratio, and leaf area index of C are increased by 4.8%, 4.1%, 20.9%, and 9.7%, respectively. Compared with CKCD, the yield, 1000-grain weight, root-to-shoot ratio, and leaf area index of CCD are increased by 6.5%, 3.8%, 19.6%, and 21.9%, respectively. The yield in 2023 is 19% higher than that in 2022. Treatment C can increase the growth indicators and reduce the net photosynthetic rate to a certain extent, while CCD rain-flood storage can alleviate the inhibition of low irrigation lower limit on the net photosynthetic rate of rice. Both C and CCD can reduce nitrogen loss and irrigation amount in paddy fields. CCD can reduce the tailwater in the Gusheng area of the Erhai Lake Basin to Erhai Lake, and also can make full use of N, P, and other nutrients in the tailwater to promote the formation and development of rice. In conclusion, the paddy field rain-flood storage methodology in the Erhai Lake Basin can promote various growth and physiological indicators of rice, improve water resource utilization efficiency, reduce direct discharge of tailwater into Erhai Lake, and decrease the risk of agricultural non-point source pollution.

In situ immobilization multi-enzyme biocatalytic system on covalent organic frameworks for efficient conversion of lignocellulose to glucose

Efficient enzyme immobilization is crucial for addressing the resource utilization challenges associated with lignocellulose. However, the widespread application of immobilized enzyme systems faces significant obstacles, including low enzyme activity and the limited pore structure of existing carriers. To overcome these challenges, a novel multi-enzyme biocatalytic system (multi-enzymes@COF) was developed for the in situ immobilization of cellulose and β-glucosidase on covalent organic frameworks (COFs). Results showed that multi-enzyme@COF exhibits good crystallinity and a mesoporous structure, leading to an increased enzyme loading rate of 0.6 g/g and enhanced cellulose conversion efficiency of up to 78.7 %. Additionally, multi-enzymes@COF demonstrated remarkable stability a broader pH range (4−7) and temperature range (50–70 ℃), with the actively above 70 %. Moreover, the enzymes maintained approximately 74.7 % of their activity even after seven cycles. This research presents an innovative strategy for the effective utilization of lignocellulose through enzymatic processes, promoting sustainable and efficient resource utilization.

Technical efficiency and its determinants in health service delivery of public health centers in East Wollega Zone, Oromia Regional State, Ethiopia: Two-stage data envelope analysis

BackgroundPriority-setting becomes more difficult for decision-makers when the demand for health services and health care resources rises. Despite the fact that the Ethiopian healthcare system places a strong focus on the efficient utilization and allocation of health care resources, studies of efficiency in healthcare facilities have been very limited. Hence, the study aimed to evaluate efficiency and its determinants in public health centers.MethodsA cross-sectional study was conducted in the East Wollega zone, Oromia Regional State, Ethiopia. Ethiopian fiscal year of 2021–2022 data was collected from August 01–30, 2022 and 34 health centers (decision-making units) were included in the analysis. Data envelope analysis was used to analyze the technical efficiency. A Tobit regression model was used to identify determinants of efficiency, declaring the statistical significance level at P < 0.05, using 95% confidence interval.ResultsThe overall efficiency score was estimated to be 0.47 (95% CI = 0.36–0.57). Out of 34 health centers, only 3 (8.82%) of them were technically efficient, with an efficiency score of 1 and 31 (91.2%) were scale-inefficient, with an average score of 0.54. A majority, 30 (88.2%) of inefficient health centers exhibited increasing return scales. The technical efficiency of urban health centers was (β = -0.35, 95% CI: -0.54, -0.07) and affected health centers’ catchment areas by armed conflicts declined (β = -0.21, 95% CI: -0.39, -0.03) by 35% and 21%, respectively. Providing in-service training for healthcare providers increased the efficiency by 27%; 95% CI, β = 0.27(0.05–0.49).ConclusionsOnly one out of ten health centers was technically efficient, indicating that nine out of ten were scale-inefficient and utilized nearly half of the healthcare resources inefficiently, despite the fact that they could potentially reduce their inputs nearly by half while still maintaining the same level of outputs. The location of health centers and armed conflict incidents significantly declined the efficiency scores, whereas in-service training improved the efficiency. Therefore, the government and health sector should work on the efficient utilization of healthcare resources, resolving armed conflicts, organizing training opportunities, and taking into account the locations of the healthcare facilities during resource allocation.

Recycling of UO22+ expanded by metal-organic framework bearing pyrazinoquinoxaline tetracarboxylic acid: pH fluorescence sensing and photocatalytic activity

With the wide application of nuclear energy, the recycling of uranium resources and environmental protection have become the focus of scientific research and industrial attention. Uranyl ions have better electronic configurations and optical properties, but poor energy utilization and recycling as ionic states. Drawing on the structural features of Metal-Organic Frameworks (MOFs), the combination of UO22+ nodes with photoactive ligands should be able to effectively regulate the energy level matching between metal nodes and conjugated ligands, improve the electronic configuration and energy band structure, and thus produce better photoresponsive functional properties. In the present work, an example of a novel two-dimensional layered U-MOF was constructed by self-assembly, which utilizes pyrazinoquinoxaline tetracarboxylic acid. Due to the stable coordination structure, matched energy levels and synergistic photoresponsive behavior of UO22+ with pyrazinoquinoxaline ligands, U-MOF enables fluorescence sensing response in aqueous solution at pH=2–5, 9.5–12 and fluorescence quenching detection of a wide range of substrates. Theoretical calculations reveal that the interaction of the hydrogen ion with pyrazinozinoquinoxaline moiety extends the degree of conjugation of the moiety. Meanwhile, the interaction of hydroxide ions with pyrazinozinoquinoxaline groups elevates the highest occupied molecular orbital (HOMO) energy level, which significantly affects the photoelectric properties of U-MOF. In addition, U-MOF can be used as a photocatalyst to realize the conversion of benzylamine to N-benzylbenzylideneimine by oxidation under mild conditions. The effective electron transfer between uranyl ions and ligands ensured the photogenerated electron-hole separation efficiency and enhanced the energy utilization. Therefore, the related results of U-MOFs illustrate the practicality of introducing UO22+ nodes into MOFs to construct novel photoresponsive materials, which provides a new way for the efficient recycling and utilization of uranium resources.

Organizational capital and stock performance during Crises: Moderating role of generalist CEO

This study examines the relationship between organizational capital (OC) and stock performance during the two recent crisis periods, namely the GFC and COVID-19. Economic crises highlight the sustainable competitiveness of firms, providing an opportunity to identify the role of OC. OC is intangible capital that encompasses intrinsic business processes and expertise, facilitating more efficient resource utilization than competitors. Results show that a greater OC is significantly associated with higher stock returns during both crisis periods. The association is robust to the models with firm-fixed effects and instrumental variables. In addition, we find evidence that generalist CEOs strengthen this relationship while specialist CEOs do not. This study emphasizes the pivotal role of OC as a protective buffer against external shocks, particularly during periods when the market pays more attention to corporate sustainability.

Effects of mulberry leaf enrichment with Lepidium sativum L. seed powder suspension on the economic parameters of Bombyx mori L

The phytochemicals of high nutritional and functional properties in Lepidium sativum L. (garden cress) seeds have nominated their seed powder (regardless of the concentration used) for enrichment of mulberry leaves in order to enhance Bombyx mori L. larval feeding, and consequently to gain ground in sericulture industry. As expected, B. mori larval feeding on L. sativum-enriched mulberry leaves showed not only a remarkable increase in mean values of certain economic parameters of B. mori, such as cocoon weight, cocoon shell weight, pupal weight, and egg yield, compared with the control group, but also showed a phenomenal increase in egg counts (on average, ca. 958–1256 eggs laid per female moth) and a significant increase in egg size (measured as egg surface area and egg volume). Male or female moth larval diet has significantly influenced the reproductive performance or fitness of both sexes of B. mori in terms of large-sized moths (measured as forewing, hind femur, and hind tibia lengths) and highly fecund moths (i.e., increased fecundity and spermatophore counts per female moth, and large-sized eggs). On the basis of B. mori female moth reproductive index, the female moths from L. sativum-fed larvae proved to have a lower reproductive index compared to their corresponding value for females of the control group, indicating more efficient utilization of larval resources for B. mori reproduction. Quantification of the three main physiological resources viz., protein, lipid and carbohydrate in the internal reproductive tract of B. mori female moths at death has nominated the female moth abdomens, or simply their bodies, as being a reasonable natural source of protein, lipid, and carbohydrate, to be involved in certain manufactures (e.g., pet feed formulations) instead of discarding them as a source of environmental pollution. Evidently, the L. sativum seed powder is of considerable interest because it remarkably improves the performance of such an economically important insect, B. mori. This is the first study for evaluating the efficacy of L. sativum seed powder in sericulture field to enhance B. mori productivity parameters.

Towards Efficient Resource Utilization Forecasting in Acute Heat Events Using OMOP.

Predicting resource utilization can help to optimize the distribution of limited resources in the healthcare system. This requires different climatic and medical data from different sources, which can lead to problems with interoperability. In the paper we describe which data is needed for the prediction and how the data can be made interoperable using OMOP CDM.

Optimization of multi-energy complementary power generation system configuration based on particle swarm optimization

The multi-energy complementary power generation system, incorporating wind, solar, thermal, and storage energy sources, plays a crucial role in facilitating the coexistence and mutual reinforcement of conventional thermal power and renewable energy. Against the backdrop of evolving power systems and the increasing integration of wind, solar, thermal, and storage technologies, scientifically optimizing the configuration of multi-energy complementary power generation systems has become an essential prerequisite for their sustainable development. This study introduces a dual-layer optimization model for configuring multi-energy complementary power generation systems based on the particle swarm optimization algorithm. The outer layer optimization aims to maximize the net revenue from wind, solar, and storage power generation while the inner layer optimization focuses on minimizing carbon emissions from thermal power units. The proposed approach comprehensively considers both environmental benefits and economic gains of multi-energy complementary power generation systems. Simulation results demonstrate that this method effectively enhances annual net income while significantly reducing carbon emissions by 1.1058 million tons. It establishes a rational capacity configuration scheme that not only improves economic performance but also promotes efficient utilization of clean energy resources. Furthermore, it highlights the advantages of coordinated carbon electricity market trading over traditional modes.

Spatial Allocation Rationality Analysis of Medical Resources Based on Multi-Source Data: Case Study of Taiyuan, China.

Reasonably allocating medical resources can effsectively optimize the utilization efficiency of such resources. This paper took Taiyuan City as an example and established a model to evaluate the rationality of medical resource spatial allocation, incorporating two key dimensions: the spatial layout and the supply and demand of medical resources. In terms of the spatial layout, three indexes were included: Firstly, the service coverage rates of different levels of medical institutions, based on residents' medical orientations, were calculated using network analysis methods. Secondly, the Huff-2SFCA method was improved to calculate the accessibility of medical resources for four different modes of transportation. Then, the Health Resource Agglomeration Degree (HRAD) and Population Agglomeration Degree (PAD) were used to quantify the equity of medical resources. In terms of the supply and demand of medical resources, one index was included: the supply-demand ratio of medical resources during sudden public health events, which was calculated using the number of beds per thousand people as an indicator. These four indexes were weighted using the entropy weight method to obtain the rationality grade of medical resource spatial allocation in Taiyuan City. The study found that the rationality evaluation level of medical resource allocation in the central urban area of Taiyuan City followed a "concentrically decreasing" pattern. The rating ranged from "very reasonable" to "less reasonable", with the area of each level expanding gradually. The areas rated within the top two categories only accounted for 19.92% of the study area, while the area rated as "less reasonable" occupied 38.73% of the total area. These results indicate that the model accounted for residents' travel for various medical orientations and the availability of resources during public health emergencies. It considered both the spatial layout and supply and demand of medical resources, offering recommendations for the precise allocation of urban medical resources.

Green transformation of oily sludge through geopolymer: Material properties and hydration mechanisms

Oily sludge (OS) is a kind of hazardous waste generated from the petrochemical industry. Currently, pyrolysis has been widely applied for OS disposal, while low-oil content (<5 wt%) OS still lacks novel technology to achieve efficient resource utilization and harmful substances immobilization. In this study, a kind of OS-based geopolymer was developed by OS and ground granulated blast furnace slag (GGBS). The results showed that in geopolymer with 30 wt% OS, the content of total petroleum hydrocarbons (TPHs) decreased by 82%, Zn achieved 100% stabilization, and the 28 d compressive strength could still reach 32.8 MPa. The appropriate oil content filled the pores and cracks in geopolymer matrix. The constructed model compounds further elucidated the hydration mechanisms of OS-geopolymer. The nucleation effect of crude oil and micro-aggregate effect of minerals jointly improved the polymerization degree of C-(A)-S-H gels. OS promoted the transformation of [SiO4]4− monomers into C-(A)-S-H unbranched middle groups and three-dimensional networks, thereby efficiently stabilizing harmful substances. Sustainability analysis showed that OS-based geopolymer had good environmental and economic benefits. Overall, this work provides theoretical guidance for the green transformation of OS in the construction field.

Carbon Emissions Dynamics and Environmental Sustainability in China’s Tourism Sector: A 22-Year Comprehensive Regional Study

China’s tourism industry has rapidly grown over the past two decades, significantly contributing to the national economy but also increasing carbon emissions. This has raised concerns about environmental sustainability, especially given China’s commitments to peak carbon emissions by 2030 and achieve carbon neutrality by 2060. This study analyzes the changes in carbon emissions, carbon carrying capacity, and the Tourism Carbon Pressure Index (TCPI) of China’s tourism industry from 2000 to 2022, aiming to support the green transition of the sector. Examining data from 31 provinces, we observed a significant growth trend in carbon emissions, with a temporary decline during the COVID-19 pandemic in 2020, followed by a rebound in 2021 and 2022. The findings reveal that carbon emissions and carrying capacity are relatively stable in the eastern regions, but more pronounced in central and western regions, particularly the west. The TCPI is higher in the east, indicating greater environmental pressure, while it is rapidly increasing in central and western regions. To achieve sustainable tourism development, we propose promoting green transportation, eco-friendly hotels, and green scenic spots, improving resource utilization efficiency, enhancing policy support and technological innovation, and adopting regional development strategies. These measures will help reduce tourism-related carbon emissions and contribute to national carbon neutrality goals. This study provides a comprehensive analysis and actionable insights to guide the sustainable transformation of China’s tourism industry.

Wind power prediction through acoustic data-driven online modeling and active wake control

Accurate online prediction of wind power is essential for the reliable operation of power systems. However, the precision of wind turbine power forecasts is often hindered by wake effects and inadequate online modeling capabilities. To tackle this issue, this paper proposes a data-driven online prediction method for wind turbine power, leveraging acoustic data for training. The approach involves a neural network that learns acoustic feature changes related to wind output power, by enhancing the kernel extreme learning machine (KELM) technique and applying data augmentation. Additionally, to address the wake effects in real wind fields, active wake control is integrated, considering that most wind turbines operate in the wake of upstream turbines. Experiments using actual wind tunnel measurement data were conducted to assess the performance of the proposed method. The findings demonstrate that this method surpasses other techniques without increasing computational costs. The mean absolute error (MAE) of the proposed method was only 0.4111 and 0.4302, and the root mean square error (RMSE) was just 0.4868 and 0.5195, respectively, in both experiments. Moreover, the proposed acoustic data-driven online power prediction method proves stable in high background noise environments and achieves accurate wind power prediction with just a 10% data sample following the implementation of the active wake control strategy. This work significantly contributes to the efficient utilization of wind energy resources.

The Driving Mechanism of Phytoplankton Resource Utilization Efficiency Variation on the Occurrence Risk of Cyanobacterial Blooms.

Algae are highly sensitive to environmental factors, especially nutrient fluctuations; excessive nutrients can lead to the proliferation of specific algae species, resulting in dominance. In this study, we aimed to reevaluate changes in algal dominance from the perspective of resource utilization efficiency (RUE). We established 80 monitoring sites across different water systems, collecting water and phytoplankton samples. Using canonical correspondence analysis (CCA) and a generalized additive model (GAM), we analyzed the correlation between phytoplankton RUE and nutrient concentrations, quantifying the corresponding relationship between algal dominance and RUE. Our results indicate a significant negative correlation between the RUE of total phosphorus (TP) and total nitrogen (TN) concentration, but a positive correlation with N:P. The RUE of TN was negatively correlated with TN concentration and N:P. We constructed GAMs with interaction terms and confirmed a nonlinear relationship between algal dominance and RUE. When the RUE of TN was low, a positive correlation was observed, while a negative correlation was observed otherwise. These findings reveal the ecological adaptability of algal communities and provide valuable insights for predicting the risk of algal bloom outbreaks.