An efficient design method for a compact and ultra-wideband multi-stage Wilkinson power divider in a parallel stripline (PSL) is proposed. To enhance the frequency bandwidth of the proposed power divider while reducing its size, the isolation branch is modified; that is, two capacitors are connected to both sides of a resistor at each isolation branch. For an efficient design process, the PSL power divider is equivalently represented by two microstrip power dividers, and the design equations are derived. Based on the design equations, an in-house algorithm is utilized to optimally determine the design parameters, including the line impedance, resistance, and capacitance of each stage. For example, a three-stage PSL power divider is designed with three $\lambda /4$ transmission lines at a base frequency of 5 GHz. To verify the accuracy of the design procedure, 3D EM simulations and measurements are performed, and the results show good agreement. Compared with the conventional three-stage Wilkinson power divider, the proposed PSL power divider achieves a wider frequency bandwidth of 1.16 to 6.51 GHz (139.5%) and a 23% shorter transmission line length of 207°, while exhibiting an insertion loss of 0.7 to 1.4 dB. Full article

Mulching is a widely used agricultural water conservation measure in the semiarid regions of Northwest China. In order to explore the response process of different film mulching methods to soil microorganisms, we characterized the effect of different film mulching methods on soil microbial diversity and community structure characteristics in the root zone of drip-irrigated maize during the heading and maturity stages using high-throughput sequencing of 16SrDNA and ITS amplicons combined with bioinformatics analysis. Full mulching (FM) was contrasted to controls of no mulching (NM) and half-mulching (HM), yielding an order of microbial diversity, abundance, and evenness scores of HM > FM > NM. The HM and FM treatments reduced the relative abundance of Proteobacteria and Actinobacteria (the most abundant bacteria) in the bacterial community structure but increased that of Acidobacteria and Chloroflexi. In the fungal community structure, HM decreased the abundance of Sordariomycetes but increased that of Eurotiomycetes (the most abundant fungi). The abundance and community structure of bacteria were significantly correlated with soil temperature and those of fungi with pH. HM improved network complexity and competitive relationships among bacteria, while FM increased the relationship between fungal groups and the symbiosis of fungal communities. HM significantly increased maize yield (20.37% and 6.01% above NM and FM, respectively). In summary, full mulching was more favorable than no mulching for soil microbial diversity and community structure composition, but soil microbial diversity and yield responded better to half-mulching. These results provide a background for improving the yield of drip-irrigated maize and protecting the microbial ecosystems of farmland soils. Full article

In this study, the prognostic value of cellular morphology and spatial configurations in melanoma has been examined, aiming to complement traditional prognostic indicators like mitotic activity and tumor thickness. Through a computational pipeline using machine learning and deep learning methods, we quantified nuclei sizes within different spatial regions and analyzed their prognostic significance using univariate and multivariate Cox models. Nuclei sizes in the invasive band demonstrated a significant hazard ratio (HR) of 1.1 (95% CI: 1.03, 1.18). Similarly, the nuclei sizes of tumor cells and Ki67 S100 co-positive cells in the invasive band achieved HRs of 1.07 (95% CI: 1.02, 1.13) and 1.09 (95% CI: 1.04, 1.16), respectively. Our findings reveal that nuclei sizes, particularly in the invasive band, are potentially prognostic factors. Correlation analyses further demonstrated a meaningful relationship between cellular morphology and tumor progression, notably showing that nuclei size within the invasive band correlates substantially with tumor thickness. These results suggest the potential of integrating spatial and morphological analyses into melanoma prognostication. Full article

Here, we demonstrate that human neutrophil interaction with the bacterium Salmonella typhimurium fuels leukotriene B4 synthesis induced by the chemoattractant fMLP. In this work, we found that extracellular ATP (eATP), the amount of which increases sharply during tissue damage, can effectively regulate fMLP-induced leukotriene B4 synthesis. The vector of influence strongly depends on the particular stage of sequential stimulation of neutrophils by bacteria and on the stage at which fMLP purinergic signaling occurs. Activation of 5-lipoxygenase (5-LOX), key enzyme of leukotriene biosynthesis, depends on an increase in the cytosolic concentration of Ca²⁺. We demonstrate that eATP treatment prior to fMLP, by markedly reducing the amplitude of the fMLP-induced Ca²⁺ transient jump, inhibits leukotriene synthesis. At the same time, when added with or shortly after fMLP, eATP effectively potentiates arachidonic acid metabolism, including by Ca²⁺ fluxes stimulation. Flufenamic acid, glibenclamide, and calmodulin antagonist R24571, all of which block calcium signaling in different ways, all suppressed 5-LOX product synthesis in our experimental model, indicating the dominance of calcium-mediated mechanisms in eATP regulatory potential. Investigation into the adhesive properties of neutrophils revealed the formation of cell clusters when adding fMLP to neutrophils exposed to the bacterium Salmonella typhimurium. eATP added simultaneously with fMLP supported neutrophil polarization and clustering. A cell-derived chemoattractant such as leukotriene B4 plays a crucial role in the recruitment of additional neutrophils to the foci of tissue damage or pathogen invasion, and eATP, through the dynamics of changes in [Ca²⁺]_i, plays an important decisive role in fMLP-induced leukotrienes synthesis during neutrophil interactions with the bacterium Salmonella typhimurium. Full article

It is crucial to discover novel antimicrobial drugs to combat resistance. This study investigated the antibacterial properties of halicin (SU3327), an AI-identified anti-diabetic drug, against 13 kinds of common clinical pathogens of animal origin, including multidrug-resistant strains. Employing minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) assessments, halicin demonstrated a broad-spectrum antibacterial effect. Time-killing assays revealed its concentration-dependent bactericidal activity against Escherichia coli ATCC 25922 (E. coli ATCC 25922), Staphylococcus aureus ATCC 29213 (S. aureus ATCC 29213), and Actinobacillus pleuropneumoniae S6 (APP S6) after 4 h of treatment at concentrations above the MIC. Halicin exhibited longer post-antibiotic effects (PAEs) and sub-MIC effects (PA-SMEs) for E. coli 25922, S. aureus 29213, and APP S6 compared to ceftiofur and ciprofloxacin, the commonly used veterinary antimicrobial agents, indicating sustained antibacterial action. Additionally, the results of consecutive passaging experiments over 40 d at sub-inhibitory concentrations showed that bacteria exhibited difficulty in developing resistance to halicin. Toxicology studies confirmed that halicin exhibited low acute toxicity, being non-mutagenic, non-reproductive-toxic, and non-genotoxic. Blood biochemical results suggested that halicin has no significant impact on hematological parameters, liver function, and kidney function. Furthermore, halicin effectively treated respiratory A. pleuropneumoniae infections in murine models. These results underscore the potential of halicin as a new antibacterial agent with applications against clinically relevant pathogens in veterinary medicine. Full article

Diabetic retinopathy (DR) is a severe complication of diabetes, causing damage to retinal blood vessels due to high blood sugar levels. Early detection is crucial but often requires significant time and expertise from ophthalmologists. While artificial intelligence (AI) and image recognition hold promise for DR detection, inconsistent image quality poses a challenge. Our study presents a novel technique that integrates pixel color amplification and EfficientNetV2 to enhance fundus image attributes, aiming to address issues related to image quality and achieving superior performance in DR detection. Leveraging EfficientNetV2, an advanced convolutional neural network (CNN) architecture, we achieve 84% multiclass accuracy and 99% binary accuracy, surpassing various other CNN models, including VGG16-fc1, VGG16-fc2, NASNet, Xception, Inception ResNetV2, EfficientNet, InceptionV3, MobileNet, and ResNet50. Our research tackles the critical challenge of early detection of DR, essential for preventing vision loss. This advancement holds the potential to enhance the efficiency and accuracy of DR classification, potentially alleviating the burden on medical professionals and ultimately improving the quality of life for individuals at risk of vision loss. Full article

As the urgency of PM_2.5 prediction becomes increasingly ingrained in public awareness, deep-learning methods have been widely used in forecasting concentration trends of PM_2.5 and other atmospheric pollutants. Traditional time-series forecasting models, like long short-term memory (LSTM) and temporal convolutional network (TCN), were found to be efficient in atmospheric pollutant estimation, but either the model accuracy was not high enough or the models encountered certain challenges due to their own structure or some specific application scenarios. This study proposed a high-accuracy, hourly PM_2.5 forecasting model, poly-dimensional local-LSTM Transformer, namely PD-LL-Transformer, by deep-learning methods, based on air pollutant data and meteorological data, and aerosol optical depth (AOD) data retrieved from the Himawari-8 satellite. This research was based on the Yangtze River Delta Urban Agglomeration (YRDUA), China for 2020–2022. The PD-LL-Transformer had three parts: a poly-dimensional embedding layer, which integrated the advantages of allocating and embedding multi-variate features in a more refined manner and combined the superiority of different temporal processing methods; a local-LSTM block, which combined the advantages of LSTM and TCN; and a Transformer encoder block. Over the test set (the whole year of 2022), the model’s R² was 0.8929, mean absolute error (MAE) was 4.4523 µg/m³, and root mean squared error (RMSE) was 7.2683 µg/m³, showing great accuracy for PM_2.5 prediction. The model surpassed other existing models upon the same tasks and similar datasets, with the help of which a PM_2.5 forecasting tool with better performance and applicability could be established. Full article

The feasibility of implementing digital predistortion for next-generation wireless communication is faced with a dilemma due to the ever-increasing demand for faster data rates. This causes the utilized bandwidth to increase significantly, as seen in the 5G NR standard in which bandwidths as high as 400 MHz are utilized. Hence, the development of new predistortion techniques in which the forward and feedback paths operate at lower sampling rates is of utmost importance to realize efficient and practical predistortion solutions. In this work, a novel predistortion technique is presented by which the predistortion is divided between the digital and analog domains. The predistorter is composed of a memoryless AM/AM gain function that is implementable in the analog domain, and a nonlinear model with memory effects in the digital domain to relax the sampling rate requirements on both the forward and feedback paths. Experimental validation was carried out with a 20 MHz and a 40 MHz 5G signal, and the results indicate minimal linearization degradation with a sampling rate reduction of 50% and 30%, respectively. This sampling rate reduction is concurrently applied in the digital-to-analog converter of the forward path and the analog-to-digital converter of the feedback path. Full article

Oxidative stress damage in periparturient cows decreases both production and their health; supplementation with complex additives during the periparturient period has been used as an important strategy to enhance the antioxidant status and production of dairy cows. The periparturient cows not only risk a negative energy balance due to reduced dry matter intake but also represent a sensitive period for oxidative stress. Therefore, we have developed an immunomodulatory and nutritional regulation combined additive (INC) that hopefully can improve the immune status and production of cows during the periparturient period and their offspring health and growth by improving their antioxidant stress status. The INC comprised a diverse array of additives, including water-soluble and fat-soluble vitamins, Selenomethionine, and active dry Saccharomyces cerevisiae. Forty-five multiparous Holstein cows were randomly assigned to three treatments: CON (no INC supplementation, n = 15), INC30 (30 g/d INC supplementation, n = 15), and INC60 (60 g/d INC supplementation, n = 15) based on last lactation milk yield, body condition score, and parity. Newborn calves were administered 4 L of maternal colostrum originating from the corresponding treatment and categorized based on the treatment received by their respective dams. The INC not only served to maintain the antioxidative stress system of dairy cows during the periparturient period but also showed a tendency to improve the immune response (lower tumor necrosis factor and interleukin-6) during the perinatal period. A linear decrease in concentrations of alkaline phosphatase postpartum and β-hydroxybutyrate was observed with INC supplementation. Milk fat yield, milk protein yield, and energy-corrected milk yield were also increased linearly with increasing additive supplementation. Calves in the INC30 group exhibited greater wither height and chest girth but no significant effect on average daily gain or body weight. The diarrhea frequency was linearly decreased with the incremental level of INC. Results indicate that supplementation with INC in peripartum dairy cows could be a major strategy to improve immune response, decrease inflammation, maintain antioxidant stress status in transition dairy cows, and have merit in their calves. In conclusion, this study underlines the benefits of INC supplementation during the transition period, as it improved anti-inflammatory capacity, could positively impact antioxidative stress capacity, and eventually enhanced the production performance of dairy cows and the health and growth of calves. Full article

Structured around pivotal elections in France and the United States, recent novels by François Roux and Michel Houellebecq weave together fictional characters with their historical referents, tracing a history of neoliberal economics and its effects on political processes and personal lives. By directly staging the history of Neoliberalism, both Roux and Houellebecq are able to invoke an experience of sudden awareness in their characters—the dedicated businessman Tanguy can, for example, come to view automation as a “genocide of workers” at a climactic moment. By coupling narrative with historical fact, both authors accomplish the difficult task of producing shock at developments so widespread that they have come to be considered inevitable and immune to the influence of democratic politics. Full article

Engineered stone (ES) is a popular building product, due to its architectural versatility and generally lower cost. However, the fabrication of organic resin-based ES kitchen benchtops from slabs has been associated with alarming rates of silicosis among workers. In 2024, fifteen years after the first reported ES-related cases in the world, Australia became the first country to ban the use and importation of ES. A range of interacting factors are relevant for ES-associated silicosis, including ES material composition, characteristics of dust exposure and lung cell-particle response. In turn, these are influenced by consumer demand, work practices, particle size and chemistry, dust control measures, industry regulation and worker-related characteristics. This literature review provides an evidence synthesis using a narrative approach, with the themes of product, exposure and host. Exposure pathways and pathogenesis are explored. Apart from crystalline silica content, consideration is given to non-siliceous ES components such as resins and metals that may modify chemical interactions and disease risk. Preventive effort can be aligned with each theme and associated evidence. Full article

The implementation of low-carbon healthcare practices will be significantly enhanced by the role of anesthesia personnel. While there is a lack of data on the specific measures being implemented by anesthesia departments in Austria, we conducted interviews with six experts in sustainability within anesthesia to address this knowledge gap. These experts provided insights on strategies for reducing the CO₂ impact in the operating theatre, the level of interest among anesthetists in sustainability, the role of green teams in hospitals, and future prospects for sustainable anesthesia. While Austria has made progress in reducing the use of Desfluran, waste separation within operating theatres remains a significant issue. Green teams are present in hospitals, but there is a need for the greater inclusion of anesthetists and clinical staff. The topic of sustainability is becoming increasingly important in the field of anesthesia, and the past three years have witnessed a significant push towards reducing CO₂ emissions in hospitals across Austria. The experts identified key steps towards achieving sustainable anesthesia, emphasizing the need for an internal motivation to drive meaningful change. This study highlights the numerous measures that have already been implemented in the pursuit of sustainability in anesthesia and the ongoing efforts towards further improvement. Full article

Heart rate variability (HRV) is defined as the fluctuation of time intervals between adjacent heartbeats and is commonly used as a surrogate measure of autonomic function. HRV has become an increasingly measured variable by wearable technology for use in fitness and sport applications. However, with its increased use, a gap has arisen between the research and the application of this technology in strength and conditioning. The goal of this narrative literature review is to discuss current evidence and propose preliminary guidelines regarding the application of HRV in strength and conditioning. A literature review was conducted searching for HRV and strength and conditioning, aiming to focus on studies with time-domain measurements. Studies suggest that HRV is a helpful metric to assess training status, adaptability, and recovery after a training program. Although reduced HRV may be a sign of overreaching and/or overtraining syndrome, it may not be a sensitive marker in aerobic-trained athletes and therefore has different utilities for different athletic populations. There is likely utility to HRV-guided programming compared to predefined programming in several types of training. Evidence-based preliminary guidelines for the application of HRV in strength and conditioning are discussed. This is an evolving area of research, and more data are needed to evaluate the best practices for applying HRV in strength and conditioning. Full article

For large-scale optimization that covers a wide range of optimization problems encountered frequently in machine learning and deep neural networks, stochastic optimization has become one of the most used methods thanks to its low computational complexity. In machine learning and deep learning problems, nonconvex problems are common, while convex problems are rare. How to find the global minimum for nonconvex optimization and reduce the computational complexity are challenges. Inspired by the phenomenon that the stagewise stepsize tuning strategy can empirically improve the convergence speed in deep neural networks, we incorporate the stagewise stepsize tuning strategy into the iterative framework of Nesterov’s acceleration- and variance reduction-based methods to reduce the computational complexity, i.e., the stagewise stepsize tuning strategy is incorporated into randomized stochastic accelerated gradient and stochastic variance-reduced gradient. The proposed methods are theoretically derived to reduce the complexity of the nonconvex and convex problems and improve the convergence rate of the frameworks, which have the complexity $O(1/\mu ϵ)$ and $O(1/\mu \sqrt{ϵ})$, respectively, where $\mu$ is the PL modulus and L is the Lipschitz constant. In the end, numerical experiments on large benchmark datasets validate well the competitiveness of the proposed methods. Full article

Gastric acid secretion is closely associated with the development and treatment of chronic gastritis, gastric ulcers, and reflux esophagitis. However, gastric acid secretion is affected by complex physiological and pathological factors, and real-time detection and control are complicated and expensive. A gastric delivery system for antacids and therapeutics in response to low pH in the stomach holds promise for smart and personalized treatment of stomach diseases. In this study, pH-responsive modular units were used to assemble various modular devices for self-regulation of pH and drug delivery to the stomach. The modular unit with a release window of 50 mm² could respond to pH and self-regulate within 10 min, which is related to its downward floatation and internal gas production. The assembled devices could stably float downward in the medium and detach sequentially at specific times. The assembled devices loaded with antacids exhibited smart pH self-regulation under complex physiological and pathological conditions. In addition, the assembled devices loaded with antacids and acid suppressors could multi-pulse or prolong drug release after rapid neutralization of gastric acid. Compared with traditional coating technology, 3D printing can print the shell layer by layer, flexibly adjust the internal and external structure and composition, and assemble it into a multi-level drug release system. Compared with traditional coating, 3D-printed shells have the advantage of the flexible adjustment of internal and external structure and composition, and are easy to assemble into a complex drug delivery system. This provides a universal and flexible strategy for the personalized treatment of diseases with abnormal gastric acid secretion, especially for delivering acid-unstable drugs. Full article

This article delves into the dynamics of managing religious diversity within the healthcare field in Argentina. It focuses on the articulations between health practices and individual belief systems among healthcare professionals and users. Applying a comparative approach based on qualitative interviews, we draw conclusions that underscore the imperative of acknowledging the sociocultural diversity within our societies. This recognition is fundamental in cultivating healthcare environments that not only respect users’ diverse worldviews but also healthcare professionals’ religious perspectives. Our findings advocate for incorporating religious diversity management principles in healthcare, emphasizing the development of inclusive approaches in dealing with health, illness, and wellbeing. Full article

Lagenaria siceraria (Molina) Standley, a member of the Cucurbitaceae family, is valued for its medicinal and nutritive properties. The nutrient status of sequentially harvested shoots and fruits at various growth stages in L. siceraria has not been documented to date. This study aimed to compare the nutritional status of L. siceraria landrace shoots and fruits harvested at different maturity stages. Micronutrients, macronutrients, and proximate composition of shoots and fruits were determined using inductively coupled plasma–optical emission spectrometry (ICP-OES). Data were subjected to multivariate statistical analysis. The nutrient attributes differed significantly (p < 0.05) within and among landraces at different growth stages. Correlation of nutritional traits was primarily based on shared absorption sites and comparable chemical composition. The first five principal components in shoots and fruits had 90.218 and 89.918% total variability, respectively. The micronutrients Ca, Mg, K, P, and N in shoots and the macronutrients Fe, Zn, Cu, and Al in fruits were the main contributors to variability. The biplot and dendrogram clustered landraces with comparable nutrient values. Shoot traits classified landraces into three major clusters, where clusters I and II grouped landraces with superior and inferior Mg, P, K, N, Fe, K/Ca+Mg, ADL, and protein levels at 42–63 DAS. Cluster III consisted of landraces with more Ca, Na, Mn, Zn, and Cu. However, the fruit nutrient status classified landraces into two major clusters. Cluster I comprised landrace KSC (as a singlet) with the highest Ca, P, N, Mn, Fe, Zn, and Cu contents at various stages of growth (7–21 DAA). Cluster II had landraces with higher K, C/N ratio, Na, moisture content, ash, protein, and fat. The nutritional status of shoots and fruits determined at different stages of growth is essential for selecting the best harvest time and landrace(s) for required daily nutrient intake. Full article

Arid coastal regions are threatened by land desertification, which poses a serious threat to desert ecosystems, urban areas, and sustainability on a local as well as global scale. The present study aims to map desertification and the degree of its severity over the Jazan province on the western coast of Saudi Arabia. This investigation was conducted through the integration of remote sensing data (2001 and 2020) and statistical techniques. A scatter diagram, Karl Pearson correlation coefficient, and significance p-value test were performed on various spectral indices and tasseled cap transformation (TCT) derivative matrices to determine the strong significant relation of the spectral indices combination. Based on these analyses, the desertification degree index (DDI) was developed using a NDVI–TCG combination. The desertification grades were mapped and categorized into five classes, namely, non-desertification, low, moderate, severe, and extreme desertification. The results indicated that the spatial distribution of desertification grades declined from west to east during the period from 2001 to 2020. The degree of desertification improved during the study period since there was a significant reduction in extremely serious desertification land by 15.5% and an increase in weak desertification land by 7.8%. The dynamic changes in the DDI classes in the Jazan province mainly involve transformation from extremely serious to serious, serious to moderate, and moderate to weak, with areas of 2268.1 km², 1518.5 km², and 1062.5 km², respectively. Generally, over the 19-year period, the restoration of vegetated areas accounted for 41.99% of the total study area, while desertification degradation land represented 15.57% of the total area of the Jazan province. Full article

This study investigates the impact of intellectual capital on the sustainable performance of banks in Saudi Arabia, focusing on the period from 2012 to 2022. Utilizing data from 10 major Saudi banks, the research examines how different components of intellectual capital—Human capital efficiency (HCE), Structural capital efficiency (SCE), and Capital employed efficiency (CEE)—influence key financial performance indicators such as return on equity (ROE) and Net profit margin (NPM). The study is grounded in the resource-based view of the firm, which suggests that a firm’s internal resources can provide a sustainable competitive advantage. The analysis employs panel data techniques, including fixed and random effect models, to assess the relationships between intellectual capital components and bank performance while controlling for variables like bank size (SIZE), financial leverage (LEV), gross domestic product growth (GGDP), inflation (INF), and the impact of the COVID-19 pandemic (COV). The findings reveal that intellectual capital significantly enhances bank performance in Saudi Arabia, with human capital efficiency showing the most decisive influence on ROE and NPM. Structural capital and capital employed efficiency also contribute positively but vary in their impact on different performance measures. This research contributes to the theoretical and practical understanding of the role of intellectual capital in promoting sustainable banking practices. It underscores the importance of the strategic management of intellectual capital in enhancing financial performance and achieving sustainability goals, particularly in the context of Saudi Arabia’s Vision 2030. The study’s insights are relevant for bank managers and policymakers who leverage intellectual capital for economic diversification and sustainable development. Full article

Neurofibromatosis type 1 (NF1) is a neurocutaneous disorder. Plexiform neurofibromas (PNFs) are benign tumors commonly formed in patients with NF1. PNFs have a high incidence of developing into malignant peripheral nerve sheath tumors (MPNSTs) with a 5-year survival rate of only 30%. Therefore, the accurate diagnosis and differentiation of MPNSTs from benign PNFs are critical to patient management. We studied a fluorine-18 labeled tryptophan positron emission tomography (PET) radiotracer, 1-(2-[¹⁸F]fluoroethyl)-L-tryptophan (L-[¹⁸F]FETrp), to detect NF1-associated tumors in an animal model. An ex vivo biodistribution study of L-[¹⁸F]FETrp showed a similar tracer distribution and kinetics between the wild-type and triple mutant mice with the highest uptake in the pancreas. Bone uptake was stable. Brain uptake was low during the 90-min uptake period. Static PET imaging at 60 min post-injection showed L-[¹⁸F]FETrp had a comparable tumor uptake with [¹⁸F]fluorodeoxyglucose (FDG). However, L-[¹⁸F]FETrp showed a significantly higher tumor-to-brain ratio than FDG (n = 4, p < 0.05). Sixty-minute-long dynamic PET scans using the two radiotracers showed similar kidney, liver, and lung kinetics. A dysregulated tryptophan metabolism in NF1 mice was further confirmed using immunohistostaining. L-[¹⁸F]FETrp is warranted to further investigate differentiating malignant NF1 tumors from benign PNFs. The study may reveal the tryptophan–kynurenine pathway as a therapeutic target for treating NF1. Full article

With the rapid development of new power systems, diverse new power services have imposed stricter requirements on network resources and performance. However, the traditional method of transmitting request data to the IoT management platform for unified processing suffers from large delays due to long transmission distances, making it difficult to meet the delay requirements of new power services. Therefore, to reduce the transmission delay, data transmission, storage and computation need to be performed locally. However, due to the limited resources of individual nodes in the local power wireless communication network, issues such as tight coupling between devices and resources and a lack of flexible allocation need to be addressed. The collaborative allocation of resources among multiple nodes in the local network is necessary to satisfy the multi-dimensional resource requirements of new power services. In response to the problems of limited node resources, inflexible resource allocation, and the high complexity of multi-dimensional resource allocation in local power wireless communication networks, this paper proposes a multi-objective joint optimization model for the collaborative allocation of communication, storage, and computing resources. This model utilizes the computational characteristics of communication resources to reduce the dimensionality of the objective function. Furthermore, a mouse swarm optimization algorithm based on multi-strategy improvements is proposed. The simulation results demonstrate that this method can effectively reduce the total system delay and improve the utilization of network resources. Full article