Capacity Utilization Research Articles

The Pasinetti Index and the Rise of Inequality in the Age of Unconventional Monetary Policy in Japan

ABSTRACT There is rising concern in Japan that unconventional monetary policy (UMP) accelerates inequality through the asset price mechanism, allowing the higher-income group to gain additional capital income. UMP has limited effectiveness in creating real wage growth and restoring demand and growth, as the overall economy has been stagnant. We revisit the issue of income inequality in Japan by using Pasinetti’s approach to measure personal income distribution and examine its effect on effective demand and functional income distribution. We implement workers’ debt-augmented Pasinetti Index (PI) as a proxy of personal income distribution, shifting from workers towards rentiers in their interpersonal lending and borrowing relations. Our empirical result with the VAR model for Japan shows that a higher PI restrains effective demand. Furthermore, higher rentier income negatively affects the wage share through decreased capacity utilization.

Digestive and metabolic profile of the resident population of the silverside Odontesthes argentinensis from Mar Chiquita Coastal Lagoon (Buenos Aires, Argentina).

The knowledge about the occurrence and biochemical characteristics of key digestive enzymes is crucial for an enhanced understanding of the dietary ecophysiology of the species. On the other hand, integrative studies on digestive physiology and on tissue content of glycogen, glucose, lipid and protein in groups of ecological and economic importance are currently limited. In this work, we determined the occurrence and biochemical characteristics in intestine of key digestive enzymes activities as indexes of the ability to digest different dietary substrates and of functional differentiation for digestion/absorption of nutrients along with the intestinal coefficient as index of dietary habit and digestion efficiency in adults of Odonthtestes argentinensis inhabiting Mar Chiquita Coastal Lagoon (Buenos Aires, Argentina). Furthermore, to identify storage sites, glycogen, triglycerides and protein content in different tissues were also analyzed. The presence and biochemical characteristics of amylase, maltase, sucrase, lipase, trypsin and aminopeptidase-N activity in intestine, as well as the tissue content of glycogen, triglycerides and protein suggests that adults of O.argentinensis exhibit an adequate digestive battery to potentially perform complete hydrolysis of various dietary substrates and capacity for storage and/or utilization of energy reserves. Our study provides novel insights into the digestive/metabolic traits in adults of the resident silverside O. argentinensis from Mar Chiquita Coastal Lagoon.

Secure channel estimation model for cognitive radio network physical layer security using two-level shared key authentication

Physical Layer Security (PLS) in Cognitive Radio Networks (CRN) improves the confidentiality, availability, and integrity of the external communication between the devices/ users. The security models for sensing and beamforming reduce the impact of adversaries such as eavesdroppers in the signal processing layer. To such an extent, this article introduces a Secure Channel Estimation Model (SCEM) using Channel State Information (CSI) and Deep Learning (DL) to improve the PLS. In this proposed model, the CSI is exploited to evaluate the channel utilization and actual capacity availability throughout the allocation intervals. The change in channel capacity and utilization augments the need for security through 2-level key shared authentication. The deep learning algorithm verifies the authentication completeness for maximum channel capacity utilization irrespective of adversary interference. This verification follows mutual authentication between the primary and secondary users sharing the maximum capacity channel with high secrecy. The learning monitors the outage secrecy rates to verify failed allocations such that the replacement for allocation is pursued. Thus, the physical layer security between different user categories is administered through maximum CSI exploitation with high beamforming abilities. The proposed model leverages the secrecy rate by 10.77% and the probability of detection by 15.01% and reduces the interference rate by 11.07% for the varying transmit powers.

Assessment of the impact of government support to technology business incubators in India

Empirical literature does not adequately throw light on the emergence of institutional intermediaries such as Technology Business Incubators (TBIs) in entrepreneurial ecosystems of emerging economies characterized by underdeveloped market infrastructure and limited private sector participation. The present study aims to understand the role and effectiveness of Government support for the promotion of TBIs in India. We conceptualize incubation support as occurring in two stages: first, the government allocates resources to create incubation infrastructure, followed by startups using the infrastructure and support for their own survival and scaling. A quantitative analysis is carried out based on secondary data on government support provided to 54 incubators in six better-developed states of India. We have carried out logistic regression analyses to analyze our key research objectives. Government support for the promotion of TBIs has led to significant infrastructure development, with a preference for university-based incubators (UBIs). The study makes two contributions: first, preferences attached in resource allocation are hindering the scaling of incubation support in the country. Second, different institutional strategies are required to maximize the creation and utilization of entrepreneurship support capacity, depending on the stage of development of the ecosystem.

Intelligent Saturation Power Limit Load Distribution Algorithm (ISPLLDA) for Cooperative Manipulators Applications

Cooperative manipulators face challenges related to an inadequate distribution of external loads and a decrease in Dynamic Load Carrying Capacity (DLCC). Understanding the impact of optimal load distribution on power consumption, load carrying capacity, and gripper error is crucial. This paper presents the Intelligent Saturation Power Limit Load Distribution Algorithm (ISPLLDA), a novel method that achieves optimal external load distribution. ISPLLDA dynamically distributes the external load among manipulators based on torque-bearing capacity and actuator position. Additionally, nonlinearity in system dynamics introduces uncertainties, leading to incorrect DLCC evaluation, increased error, and higher actuator power consumption. To address this, a Radial Basis Function Neural Network (RBFNN) accurately determines actuator saturation limits in the presence of uncertainty, enabling correct estimation of system dynamics and external disturbances. ISPLLDA ensures near-simultaneous saturation of all manipulators' actuators, maximizing their capacity utilization. The proposed method is validated through simulations and experimental tests on cooperative manipulators. Results demonstrate a 17% increase in load-carrying capacity, as well as more than 35% improvement in error and torque indexes compared to the Lagrange multipliers method.

Impact of Feeding Frequency on Growth Performance and Antioxidant Capacity of Litopenaeus vannamei in Recirculating Aquaculture Systems.

Feeding frequency is crucial for the growth and development of white shrimp (Litopenaeus vannamei) at various life stages. Although higher feeding frequencies can enhance growth, manual feeding methods significantly increase labor costs. Automatic feeding systems offer a cost-effective and efficient alternative, yet their application in intensive shrimp culture remains under-researched. This study evaluates different feeding frequencies for L. vannamei in intensive aquaculture tanks, focusing on growth performance, survivability, feed utilization, digestive and antioxidant capacities, and economic viability. Juvenile shrimp (3.85 ± 0.3 g) were cultured for 63 days with feeding frequencies of 6, 8, 10, and 12 times/day (A6, A8, A10, and A12 groups, respectively) using automatic feeders, with a control group fed manually 6 times/day (M6). Results indicated that automatic feeding significantly improved final body weight, specific growth rate, and feed conversion ratio compared to manual feeding. Among automatic feeding groups, A6 and A8 showed optimal performance, with a quadratic regression identifying 7.83 times/day as the optimal frequency. While digestive enzyme activity remained consistent across groups, A6 and A8 demonstrated significantly higher antioxidant enzyme levels (superoxide dismutase (SOD) and glutathione peroxidase (GPx)) and lower lipid peroxidation (MDA), suggesting superior digestive and antioxidant capacities. Pearson's correlation confirmed a positive relationship between SOD and GPx. Economically, the A8 group achieved the highest profitability. Consequently, a feeding frequency of 6-8 times/day using automatic feeders is recommended as an optimal and feasible strategy for intensive white shrimp culture in this life stage.

Growth of microbes in competitive lifestyles promotes increased ARGs in soil microbiota: insights based on genetic traits

BackgroundThe widespread selective pressure of antibiotics in the environment has led to the propagation of antibiotic resistance genes (ARGs). However, the mechanisms by which microbes balance population growth with the enrichment of ARGs remain poorly understood. To address this, we employed microcosm cultivation at different antibiotic (i.e., Oxytetracycline, OTC) stresses across the concentrations from the environmental to the clinical. Paired with shot-gun metagenomics analysis and quantification of bacterial growth, trait-based assessment of soil microbiota was applied to reveal the association between key ARG subtypes, representative bacterial taxa, and functional-gene features that drive the growth of ARGs.ResultsOur results illuminate that resistome variation is closely associated with bacterial growth. A non-monotonic change in ARG abundance and richness was observed over a concentration gradient from none to 10 mg/l. Soil microbiota exposed to intermediate OTC concentrations (i.e., 0.1 and 0.5 mg/l) showed greater increases in the total abundance of ARGs. Community compositionally, the growth of representative taxa, i.e., Pseudomonadaceae was considered to boost the increase of ARGs. It has chromosomally carried kinds of multidrug resistance genes such as mexAB-oprM and mexCD-oprJ could mediate the intrinsic resistance to OTC. Streptomycetaceae has shown a better adaptive ability than other microbes at the clinical OTC concentrations. However, it contributed less to the ARGs growth as it represents a stress-tolerant lifestyle that grows slowly and carries fewer ARGs. In terms of community genetic features, the community aggregated traits analysis further indicates the enhancement in traits of resource acquisition and growth yield is driving the increase of ARGs abundance. Moreover, optimizations in energy production and conversion, alongside a streamlining of bypass metabolic pathways, further boost the growth of ARGs in sub-inhibitory antibiotic conditions.ConclusionThe results of this study suggest that microbes with competitive lifestyles are selected under the stress of environmental sub-inhibitory concentrations of antibiotics and nutrient scarcity. They possess greater substrate utilization capacity and carry more ARGs, due to this they were faster growing and leading to a greater increase in the abundance of ARGs. This study has expanded the application of trait-based assessments in understanding the ecology of ARGs propagation. And the finding illustrated changes in soil resistome are accompanied by the lifestyle switching of the microbiome, which theoretically supports the ARGs control approach based on the principle of species competitive exclusion.4ZqjNsN9dRS1iWJDwru5hLVideo

The integration of optimizing train timetables with EMU route plans

Generally, to address the resource management issues in high-speed railway operations, particularly in the context of large-scale networked high-speed train transportation organizations, a phased optimization approach is introduced. This approach divides the problem into two stages: the high-speed train timetabling and the planning of Electric Multiple Unit (EMU) route. The lack of direct integration between these stages has hindered the flexible and efficient utilization of line capacity and EMU resources based on large-scale network, limiting the potential for mutual compensation and coordination among different types of resources across different regions. Furthermore, the coupling between interconnected resources has been overlooked. Compared to the aforementioned phased research areas, this study proposes an integrated optimization of train timetables and EMU routing plans in the context of networking. This study is capable of handling a large number of comprehensive optimization decision variables, which increase exponentially as the number of trains and EMUs considered grows. It thoroughly examines the importance of the linkage and coupling relationships between train timetables and EMUs, providing a new feasible method as the theoretical foundation. Adopting a resource linkage perspective, this paper employs complex system modeling, combined with empirical data from actual high-speed rail cases. This approach can significantly shorten the preparation period for high-speed train timetables and EMU routing plans, accelerating the frequency of updates and upgrades to high-speed rail passenger transportation services. To verify the feasibility and effectiveness of the proposed model and method, a case study was conducted on the EMU circulation plan and draft train timetable for the Beijing-Shanghai high-speed railway, with the results analyzed accordingly.

Improvement of plant growth and fruit quality by introducing a phosphoribosylpyrophosphate synthetase mutation into Methylorubrum populi.

The aim of this study was to evaluate the impact of the introduction of a phosphoribosylpyrophosphate synthetase (PRS) mutation into a plant growth-promoting strain of Methylorubrum on the enhancement of phyllosphere colonization, with the ultimate goal of improving plant growth and quality. A strain of Methylorubrum populi (named HS04) was isolated from the groundnut leave and found to process the plant-promoting traits, including the ability to produce indole acetic acid, siderophore, 1-aminocyclopropane-1- carboxylate deaminase, and to fix nitrogen. The application via foliar spray significantly increased the fresh weight of cucumber seedlings cultivated in a standard growth chamber, with 43.0% higher than the control group. Genomic analysis revealed that the presence of an array of genes involved in plant growth promotion, including accD, aldB, ltaE as well as potential nitrogen-fixation-related genes, including nifA, bchlLNB and bchXYZ, in the HS04 strain. The introduction of the PRS mutation (an aspartic acid to an asparagine residue, D38N) in the HS04 strain (named HS04PTR) enhanced the utilization capacity of low concentrations of methanol and multi-carbon sources (C2 to C5 carbon sources). The HS04PTR strain indicated a notable enhancement in the phyllosphere colonization, with the subsequent application further promoting the growth of cucumber seedlings. An agricultural solar greenhouse experiment was thus performed to assess the efficiency of the HS04PTR strain, sprayed at low abundance, in improving the growth and quality of cucumber plants, including vitamin C, reducing sugars, and total sugars. Our findings provide insights into the potential of Methylorubrum/ Methylobacterium strains with the PRS mutations as an efficient inoculant for advantageous agricultural applications.

Sodium selenite enhanced the selenium content in black soldier fly

This study focuses on the effects of different levels of sodium selenite on the growth, selenium content, and antioxidant capacity of black soldier fly (Hermetia illucens). The experiment used different doses of sodium selenite for treatment, including a basic diet with no supplements (control) and diets supplemented with 10 mg/kg (Se10), 20 mg/kg (Se20), 30 mg/kg (Se30), and 40 mg/kg (Se40) sodium selenite, and results show that sodium selenite supplementation significantly increases selenium content and improves selenium utilization and antioxidant capacity (P < 0.05). However, it also negatively affects growth performance and the utilization of other nutrients. The optimal level of sodium selenite supplementation depends on the ration of selenium enrichment with the overall health and productivity of black soldier fly.

A bilayer host electrode strategy for lithium metal anode to enable superior cycling performance and capacity utilization

A bilayer host electrode strategy for lithium metal anode to enable superior cycling performance and capacity utilization

Enhanced video steganography using genetic algorithms, scrambling techniques, and RSA encryption for secure data embedding

This study presents a novel approach for secure data embedding into video frames using a combination of RSA encryption, wavelet transforms, and genetic algorithm-based scrambling techniques. The primary focus of the work is to embed image data securely into video frames while preserving the quality of both the video and the extracted image. The method begins by encrypting critical data parameters (such as frame dimensions, block sizes, and other metadata) using the RSA encryption algorithm. These encrypted parameters are then embedded into the last row of the first frame for secure retrieval. The image data is first divided into blocks, processed using a two-level discrete wavelet transform (DWT), and embedded into the high-frequency sub-bands of the video frames. A genetic algorithm-based scrambling technique is used to increase the security and robustness of the embedding process by scrambling the coefficients before embedding. The embedded data is then spread across multiple video frames, ensuring efficient utilization of frame capacity and maintaining imperceptibility. During extraction, the embedded data is retrieved from the video frames, unscrambled using the best key, and decrypted using RSA to reconstruct the original parameters and image. The performance of the proposed method was evaluated using the Signal-to-Noise Ratio (SNR) metric. The SNR for video frames ranged from 36.7 dB to 39.9 dB, indicating minimal distortion. Furthermore, the reconstructed image achieved an SNR of 31.1 dB, showcasing the method's capability to maintain image quality after the embedding and extraction processes. This method demonstrates a secure and efficient approach for video steganography and data hiding, with potential applications in secure communication, copyright protection, and digital watermarking.

EXCHANGE RATE FLUCTUATION AND PERFORMANCE OF MANUFACTURING COMPANIES IN NIGERIA

Exchange rate fluctuation poses a significant threat to the stability of a nation's economy. Every economy must strive to ensure stability in exchange rate to strengthen the purchasing power. The volatile movement of exchange rate in Nigeria induces increase in cost which adversely affects the manufacturing sector. Hence, this study investigated the effect of exchange rate fluctuation on performance of manufacturing sector in Nigeria. Auto Regressive Distributed Lag was used to analyse the secondary data that were collected from Central Bank statistical bulletin and annual reports. The study revealed that there is existence of a long run negative relationship between exchange rate fluctuation and contribution of manufacturing sector to GDP. There is also existence of a long run negative relationship amongst exchange rate fluctuation and manufacturing output in Nigeria. Finally, the study revealed that exchange rate fluctuation affects manufacturing capacity utilization in Nigeria. The study concluded that exchange rate volatility negatively affects Nigeria manufacturing sector. The study therefore recommends that macro-economic variables are known to affect performance of manufacturing sector therefore the monetary policies should be managed in a way that it will be favourable to manufacturing sector in Nigeria.

Resonance frequency prediction of dielectric antennas for liquid sensing via support vector regression

This paper presents a slot antenna integrated with a split ring resonator (SRR) and feed line, designed to achieve a high Q-factor while maximizing channel capacity utilization. By incorporating a lens into the dielectric resonator antenna (DRA), we enhance both bandwidth and directivity, with the dielectric material’s permittivity serving as a key control parameter for radiation characteristics. We explore water and ethanol as controllable dielectrics within the terahertz (THz) frequency range (0.5-1 THz), implementing these liquids through microfluidic techniques. This novel design serves two purposes, functioning as both an antenna system and a highly sensitive material sensing device. The antenna’s performance is evaluated using the Debye model for pure water and ethanol, with electromagnetic full-wave simulations employing the Finite Integration Technique (FIT) to model both the antenna and microchannel structures. For predicting resonant frequencies based on antenna dimensions, we implement a Support Vector Regression (SVR) algorithm, comparing its performance against various models including Linear Regression, Regression Trees, Ensemble Bagged Trees, Ensemble Boosted Trees, and Three-layered Neural Network Models. The SVR demonstrates superior prediction accuracy by effectively capturing non-linear relationships between antenna dimensions and resonant frequencies.

The Nexus between Electricity Generation and Agricultural Development in Africa

This study examines the dynamic connections between electricity generation and agricultural development, utilizing dynamic generalized method of moments (GMM) estimation techniques and annual time series data spanning from 2000 to 2020. The findings offer valuable insights into the impact of electricity generation on agricultural progress. Firstly, both electric power generation and energy generation capacity were negatively and significantly linked to agricultural development in Africa. This suggests that despite increases in electric power and energy generation, agricultural development may not improve due to inefficiencies in the energy infrastructure, including inadequate transmission and distribution networks, unreliable grid connectivity, energy losses, and distribution issues that prevent electricity from reaching rural areas where agriculture is predominantly concentrated. Second, further analysis reveals a significant and positive association between electricity consumption, access to electricity, and agricultural development in Africa. This indicates that expanding electricity access and increasing its consumption in agricultural activities can significantly enhance agricultural productivity and growth across the continent. These results emphasize the importance of improving infrastructure and optimizing capacity utilization to ensure that the growth in electricity generation capacity translates into tangible benefits for agricultural development in Africa. Thus, the study underscores the pivotal role of electricity generation, consumption, and access in promoting agricultural development, while highlighting the need to address infrastructure inefficiencies to achieve sustainable growth.

Development of a clinical predictive model for cement loosening after vertebral augmentation in osteoporotic vertebral compression fractures

PurposeThis study aims to identify the risk factors associated with bone cement loosening after percutaneous vertebroplasty/kyphoplasty (PVP/PKP) for osteoporotic vertebral compression fractures (OVCF) and to develop a clinical prediction model for bone cement loosening.MethodsClinical data of patients who underwent PVP/PKP for OVCF at Guangzhou Panyu Hospital from June 2017 to June 2021 were collected, with a division into loosening group and normal group based on postoperative follow-up imaging. Univariate analysis was conducted to explore the correlation between clinical data and bone cement loosening. Multivariate logistic regression analysis was performed to identify independent risk factors for bone cement loosening after PVP/PKP for OVCF. The nomogram prediction model was constructed using R and evaluated through DCA, calibration curve, and ROC curve assessments.Results① Multivariate analysis indicated age, time from injury to surgery, bone density, thoracolumbar kyphosis(TLK), anti-osteoporosis therapy, surgical approach, and bone cement shape were independent risk factors for bone cement loosening after PVP/PKP for OVCF. ② The nomogram clinical prediction model based on multivariate regression showed an area under the ROC curve of 0.86. The DCA curve and calibration curve demonstrated good consistency between predicted and actual results.ConclusionThe clinical prediction model for bone cement loosening after PVP/PKP in OVCF indicates that advanced age, longer time from injury to surgery, low bone density, inadequate correction of thoracolumbar kyphosis, PKP, non-anti-osteoporosis therapy, and block-type bone cement are associated with a higher risk of bone cement loosening, showing excellent discriminative capacity and promising clinical utility.

Urban Management for Building-Sector Decarbonization: Focusing on the Role of Low-Carbon Policies

The building sector is a major source of anthropogenic carbon emissions worldwide. While existing studies have extensively explored the socioeconomic and technological impacts on carbon emissions generated from building operations, few have assessed the effectiveness of low-carbon policies in curbing the increasing trend of building sector carbon emissions. This study examines the impacts of low-carbon policy intensity on building sector carbon emissions using a two-way fixed effects model on a 6-year panel (2015–2020) dataset for 286 cities in China. Our findings indicate that, on average, the aggregated intensity of low-carbon policies fails to pose any significant impacts on carbon emissions from building operations. This is partly due to the variations in different types of policy. Specifically, a 10% increase in the intensity of energy conservation policy results in a 0.05% decrease in carbon emissions, whereas capacity utilization policies are associated with an increase in building-operation carbon emissions. Moreover, these policy–emission relationships vary across building types and end-use sources. In particular, energy conservation policies are negatively associated with emissions from cooking and heating, but positively related to emissions generated from appliances and cooling. In comparison, capacity utilization policies tend to encourage additional emissions from most sources. This study highlights the partial effectiveness of energy conservation policies in curbing building sector carbon emissions and underscores the need for additional efforts in tackling the rebound effects to realize building sector decarbonization.

Understanding the Dynamics of Sulfur Droplets Formation in Lean-Electrolyte and Low-Temperature Lithium-Sulfur Batteries.

Lithium-sulfur batteries (LSBs) afford great promises as the next-generation rechargeable batteries due to the high energy density and low cost of sulfur cathodes. Lean-electrolyte condition constitutes the prerequisite for high-energy LSBs, but the insulating sulfur particles hinder capacity utilization, especially at low temperatures. Here, the electrochemical generation of liquid sulfur droplets in the LSB system are studied and elucidate the polysulfide oxidation reaction (SOR) kinetics under different electrolyte/sulfur (E/S) ratios and low-temperature conditions. The real-time observations under in situ optical and Raman microscopies indicate that the formation of liquid sulfur during SOR is independent of the E/S ratio and can be preserved over a wide range of operating temperatures. Quantification of the polysulfide reactant concentrations and the amounts of the liquid sulfur product under different charging conditions reveal pseudo-zero-order kinetics and E/S ratio-dependent reaction constants for the SOR process. In addition, under extreme conditions of -20°C and E/S ratio of 5µLmg-1, liquid sulfur can still be preserved by following the rapid SOR kinetics. These findings provide new insights into the liquid sulfur generation dynamics in Li─S chemistry, which enables a deeper understanding of the effects of the E/S ratio and working temperature on the oxidation kinetics in LSBs.

Economic efficiency of energy storage systems for renewable energy power plants integration in the energy system

The features of the main flexibility mechanisms, limitations to their application, and price characteristics have been considered. The advantages of equipping RES-based generation with energy storage devices have been noted. Investment and operating costs of a storage device for 60 kW capacity and their ratio with the corresponding costs of solar power plants have been analyzed. On the basis of model calculations, the change in the levelized cost of electricity (LCOE) when a solar power plant is supplemented with a storage device has been estimated. It has been shown that equipping a solar power plant with an accumulator, despite high capital costs, will lead to an increase in the electricity cost on average for the entire period of operation by only 3–17 % due to the expected increase in utilization and volume of electricity production, as well as the projected decrease in the cost of accumulators. At the same time, a significant increase in the energy system stability will be ensured. It has been noted that it is necessary to tighten the requirements for the installed capacity utilization rates of power plants and to give priority to projects with storage facilities in the competitive selection of RES generation under capacity supply contract programs.

A novel supply-demand matching model for shared manufacturing resources

ABSTRACT Shared manufacturing is an innovative application of the sharing economy in manufacturing field, aiming to optimize capacity utilization and improve the efficiency of supply-demand matching. The supply-demand matching of manufacturing resources is a key issue on the shared manufacturing platform. In practice, shared manufacturing is proposed based on the objective of optimizing capacity utilization of idle manufacturing resources. In addition, multi-attributes on manufacturing resources are negotiated simultaneously, such as price, quality, and delivery time. However, the existing supply-demand matching models neither consider the optimization objective of capacity utilization nor multi-attribute negotiation requirements. The objective of this research is to propose a novel supply-demand matching model for the shared manufacturing resources, including a double auction-based supply-demand matching relationship determination and a multi-attribute negotiation-based transaction detail determination. In the first stage, a double auction model of manufacturing resources is proposed to determine the matching relationship between provider and demanders. In the proposed double auction model, utility functions for both parties are constructed to express their personalized preferences on bidding attributes; bidding strategies for both parties are determined to generate bidding values; a winner determination model is proposed to determine the matched provider and demander of manufacturing resources maximizing social welfare and capacity utilization. In the second stage, a multi-attribute negotiation model is developed to determine the concrete deal information of manufacturing resources, such as transaction prices, quality, and delivery time. Finally, the feasibility and efficiency of the proposed model is verified through numerical examples.