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The dynamic recrystallization (DRX) and flow stress of Nb‐bearing steels were investigated by means of isothermal single compression testing at temperatures of 850‐105° and at constant strain rate from 0.1 to 20s‐1 using a Gleeble 3800 thermo‐mechanical simulator in order to model the DRX processes and predict the flow stress during plate rolling. On the basis of the measured flow stress, a new model of DRX kinetics was proposed to calculate the volume fraction of dynamically recrystallized grains, which was a function of processing parameters such as deformation temperature, strain, strain rate, the initial austenite grain size and Nb content. The effect of deformation conditions was quantified by the Zener‐Hollomon parameter, in which the activation energy of deformation was expressed as a power function of Nb content. The critical strain was determined by using the method proposed by Jonas and co‐workers. It is shown that the ratio of the critical strain to the peak strain decreases with increasing Nb content, from which an empirical equation was developed. In addition, the influence of Nb content and deformation conditions on the steady state grain size was determined by fitting the experimental results to a linear relationship. Finally, the flow stress of Nb bearing steels was accurately predicted using a one‐internal‐variable evolution equation by taking Nb content as a parameter and including the influence of DRX. The comparison between the experimental and theoretical results confirmed that the modeling had a good accuracy to predict flow stresses during hot deformation.

The increasing accumulation of synthetic plastic waste in oceans and landfills, along with the depletion of non-renewable fossil-based resources, has sparked environmental concerns and prompted the search for environmentally friendly alternatives. Biodegradable plastics derived from lignocellulosic materials are emerging as substitutes for synthetic plastics, offering significant potential to reduce landfill stress and minimise environmental impacts. This study highlights a sustainable and cost-effective solution by utilising agricultural residues and invasive plant materials as carbon substrates for the production of biopolymers, particularly polyhydroxybutyrate (PHB), through microbiological processes. Locally sourced residual materials were preferred to reduce transportation costs and ensure accessibility. The selection of suitable residue streams was based on various criteria, including strength properties, cellulose content, low ash and lignin content, affordability, non-toxicity, biocompatibility, shelf-life, mechanical and physical properties, short maturation period, antibacterial properties and compatibility with global food security. Life cycle assessments confirm that PHB dramatically lowers CO₂ emissions compared to traditional plastics, while the growing use of lignocellulosic biomass in biopolymeric applications offers renewable and readily available resources. Governments worldwide are increasingly inclined to develop comprehensive bioeconomy policies and specialised bioplastics initiatives, driven by customer acceptability and the rising demand for environmentally friendly solutions. The implications of climate change, price volatility in fossil materials, and the imperative to reduce dependence on fossil resources further contribute to the desirability of biopolymers. The study involves fermentation, turbidity measurements, extraction and purification of PHB, and the manufacturing and testing of composite biopolymers using various physical, mechanical and chemical tests.

The patient-side manipulator (PSM) achieves high torque capability by combining harmonic servo system with high reduction ratio and low torque motor. However, high reduction ratio can increase inertia and decrease compliance of the manipulator. To enhance the backdrivability of the minimally invasive surgical robot, this paper aims to propose a resistance torque compensation algorithm.

A resistance torque compensation algorithm based on dynamics and Luenberger observer is proposed. The dynamics are established, considering joint flexibility and an improved Stribeck friction model. The dynamic parameters are experimentally identified by using the least squares method. With the advantages of clear structure, simple implementation and fast solution speed, the Luenberger observer is selected to estimate the unmeasured dynamic information of PSM and realize the resistance torque compensation.

For low-speed surgical robots, the centrifugal force term in the dynamic model can be simplified to reduce computational complexity. Joint flexibility and an improved Stribeck friction model can be considered to improve the accuracy of the dynamic model. Experiment results show that parameter identification and estimated results of the Luenberger observer are accurate. The backdrivability of the PSM is enhanced in ease and smoothness.

This algorithm provides potential application prospects for surgical robots to maintain high torque while remaining compliant. Meanwhile, the enhanced backdrivability of the manipulator helps to improve the safety of the preoperative manual adjustment.

The interval multi-objective optimization problems (IMOPs) are universal and vital uncertain optimization problems. In this study, an interval multi-objective grey wolf optimization algorithm (GWO) based on fuzzy system is proposed to solve IMOPs effectively.

First, the classical genetic operators are embedded into the interval multi-objective GWO as local search strategies, which effectively balanced the global search ability and local development ability. Second, by constructing a fuzzy system, an effective local search activation mechanism is proposed to save computing resources as much as possible while ensuring the performance of the algorithm. The fuzzy system takes hypervolume, imprecision and number of iterations as inputs and outputs the activation index, local population size and maximum number of iterations. Then, the fuzzy inference rules are defined. It uses the activation index to determine whether to activate the local search process and sets the population size and the maximum number of iterations in the process.

The experimental results show that the proposed algorithm achieves optimal hypervolume results on 9 of the 10 benchmark test problems. The imprecision achieved on 8 test problems is significantly better than other algorithms. This means that the proposed algorithm has better performance than the commonly used interval multi-objective evolutionary algorithms. Moreover, through experiments show that the local search activation mechanism based on fuzzy system proposed in this study can effectively ensure that the local search is activated reasonably in the whole algorithm process, and reasonably allocate computing resources by adaptively setting the population size and maximum number of iterations in the local search process.

This study proposes an Interval multi-objective GWO, which could effectively balance the global search ability and local development ability. Then an effective local search activation mechanism is developed by using fuzzy inference system. It closely combines global optimization with local search, which improves the performance of the algorithm and saves computing resources.

The purpose of this paper is to propose two operators for diversity and mutation control in artificial immune systems (AISs).

The proposed operators are applied in substitution to the suppression and mutation operators used in AISs. The proposed mechanisms were tested in the opt-aiNet, a continuous optimization algorithm inspired in the theories of immunology. The traditional opt-aiNet uses a suppression operator based on the immune network principles to remove similar cells and add random ones to control the diversity of the population. This procedure is computationally expensive, as the Euclidean distances between every possible pair of candidate solutions must be computed. This work proposes a self-organizing suppression mechanism inspired by the self-organizing criticality (SOC) phenomenon, which is less dependent on parameter selection. This work also proposes the use of the q-Gaussian mutation, which allows controlling the form of the mutation distribution during the optimization process. The algorithms were tested in a well-known benchmark for continuous optimization and in a bioinformatics problem: the rigid docking of proteins.

The proposed suppression operator presented some limitations in unimodal functions, but some interesting results were found in some highly multimodal functions. The proposed q-Gaussian mutation presented good performance in most of the test cases of the benchmark, and also in the docking problem.

First, the self-organizing suppression operator was able to reduce the complexity of the suppression stage in the opt-aiNet. Second, the use of q-Gaussian mutation in AISs presented better compromise between exploitation and exploration of the search space and, as a consequence, a better performance when compared to the traditional Gaussian mutation.

One of the most important ways to pay attention to sustainable economic development is to invest in green technology and alter the energy consumption structure (ECS) in countries. Changing the ECS can be important in two ways: first, it increases the diversity of energy consumption and reduces energy dependence on other countries. Second, the use of highly polluted nonrenewable energy sources (such as oil and coal) is reduced, leading to the transfer of energy to natural gas with less carbon emissions or renewable energy. To this end, the authors examined the asymmetric effects of eco-innovation on the US ECS from 1980 to 2019. This paper aims to address this issue.

In this research, the nonlinear autoregressive distributed lag (ARDL) (NARDL) model is used and the results are compared with the linear ARDL model.

The ARDL results also confirm the positive effects of oil prices and GDP per capita in the long run. On the other hand, short-term and long-term Wald test results confirm the nonlinear effects of eco-innovation (LPATENT) on US ECS. These results indicate that 1% positive shock in LPATENTˆ+ increases the ECS by 0.179, while 1% negative fluctuations (LPATENTˆ-) leads to a decrease (−0.085) in the ECS. However, the ARDL results, in general, show the positive effects of LPATENT on the ECS in long run. Evidence suggests that ignoring nonlinear effects can lead to inaccurate results. Policy suggestions for environmental technology innovation are presented in the results.

This research has innovations in various aspects so that the previous studies in this field have examined the effects of environmental innovation on renewable or nonrenewable energy consumption, and so far no study has been done on the ECS. In this research, the Shannon–Wiener index has been used to calculate the ECS.

This study examines the impact of China’s mixed-ownership reform on the innovation of non-state-owned acquirers, with a particular focus on the impact on firms with high financing constraints, low-quality accounting information or less tangible assets.

We use a proprietary dataset of firms listed on the Shanghai and Shenzhen Stock Exchanges to investigate the impact of mixed ownership reform on non-state-owned enterprise (non-SOE) innovation. We employ regression analysis to examine the association between mixed ownership reform and firm innovation.

The study finds that non-state-owned firms can improve innovation by acquiring equity in state-owned enterprises (SOEs) under the reform. Eased financing constraints, lowered financing costs, better access to tax incentives or government subsidies, lowered agency costs, better accounting information quality and more credit loans are underlying the impact. Additionally, cross-ownership connections amongst non-SOE executives and government intervention strengthen the impact, whilst regional marketisation weakens it.

This study adds to the literature on the association between mixed ownership reform and firm innovation by focussing on the conditions under which this impact is stronger. It also sheds light on the policy implications for SOE reforms in emerging economies.

In the supply chain disruption risk, the issue of supplier evaluation and selection is solved by an extended VIKOR method based on regret theory.

Considering the influence of irrational emotions of decision makers, an evaluation model is designed by the regret theory and VIKOR method, which makes the decision-making process closer to reality.

The paper has some innovations in the evaluation index system and evaluation model construction. The method has good stability under the risk of supply chain interruption.

The mixed evaluation information is used to describe the attributes, and the evaluation index system is constructed by the combined method of the social network analysis method and the literature research method to ensure the accuracy and accuracy of the extracted attributes. The issue of supplier evaluation and selection is solved by an extended VIKOR method based on regret theory.

To treat water pollution, especially the contamination resulted from organic dyes has aroused significant attention around the world, this study aims to prepare the metal organic framework (MOF) materials hybridizing with poly(p-phenylene terephthalamide) (PPTA) by means of a facile refluxing method and to systematically investigate adsorption performance for anionic dye Congo red as target molecule from aqueous solution.

The MOF materials hybridized by PPTA were fabricated by virtue of a facile refluxing method, characterized by thermogravimetric analysis, X-ray powder diffraction, Fourier transform infrared and pore structure.

The results showed that pseudo-second-order kinetic model could better describe the adsorption process for all the four materials, whereas Elovich model also fitted the process for the hybrid materials with PPTA. Adsorption isotherm analyses indicated that Langmuir isotherm could be used to describe the adsorption process. Introduction of appropriate amount of PPTA could enhance the adsorption affinity of the MOF materials for Congo red, and the maximum adsorption capacity could reach as high as 1,053.41 mg/g while that of the MOF material without PPTA was 666.67 mg/g, indicating introduction of PPTA could change the microenvironment of the MOF materials and increase the adsorption sites, leading to high adsorption efficiency.

The microstructure of MOF hybridized materials in detail is the further and future investigation.

This study will provide a method to prepare MOF materials with high efficiency to treat anionic dyes like Congo red from aqueous solution.

Owing to the special characteristics of PPTA and similar to carbon tube, PPTA was introduced into MOF material to increased corresponding water stability. Because of aromatic ring and amide group on the surface of PPTA, the adsorption efficiency of the hybridized MOF material with appropriate amount of PPTA was greatly enhanced.

The purpose of this paper is twofold, first providing researchers with an overview about the uncertainties occurred in procurement including applicable approaches for analyzing different uncertain scenarios, and second proposing directions to inspire future research by identifying research gaps.

Papers related to supply chain risk management and procurement risk management (PRM) from 1995–2017 in several major databases are extracted by keywords and then further filtered based on the relevance to the topic, number of citations and publication year. A total of over 156 papers are selected. Definitions and current approaches related to procurement risks management are reviewed.

Five main risks in procurement process are identified. Apart from summarizing current strategies, suggestions are provided to facilitate strategy selection to handle procurement risks. Seven major future challenges and implications related PRM and different uncertainties are also indicated in this paper.

Procurement decisions making under uncertainty has attracted considerable attention from researchers and practitioners. Despite the increasing awareness for risk management for supply chain, no detail and holistic review paper studied on procurement uncertainty. Managing procurement risk not only need to mitigate the risk of price and lead time, but also need to have sophisticated analysis techniques in supply and demand uncertainty.

The contribution of this review paper is to discuss the implications of the research findings and provides insight about future research. A novel research framework is introduced as reference guide for researchers to apply innovative approach of operations research to resolve the procurements uncertainty problems.