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This study primarily examines the link between carbon and financial performance in the Asia-Pacific region. In addition, the study also explores how the economic impact of carbon performance varies in carbon-intensive and non-carbon-intensive industries.

This study takes a sample of 1,539 non-financial firms from 13 Asia-Pacific countries from 2014 to 2021. It employs a firm-fixed effect panel regression model to examine the objective.

The findings indicate that carbon performance improvement enhances accounting-based and market-based financial performance. The positive impact of carbon abatement stems from increased operational efficiency, energy efficiency and lower production costs. Further, the stock market participants also reward the firm for carbon efficiency. However, the carbon intensity of industrial sectors presents a conflicting picture for this association.

This study adds insights to the literature by providing a contemporary reflection on the nexus between carbon emissions and economic outcomes in the understudied Asia-Pacific region. It also unveils the nuanced difference in the carbon-financial performance relationship attributed to industries' carbon sensitivity.

This study aims to specify whether heterogeneous reference-point-based aspirations are related to the cooperation levels of R&D alliance portfolios in a positive or negative (or nonlinear) way, and to unveil how cooperative behaviors evolve in recurrent project cooperation.

This study establishes a network containing a cooperation subnetwork and a project subnetwork based on patent data in the “deep learning” field to investigate how cooperative behaviors evolve in R&D alliance portfolios. A model of evolutionary games on complex networks is constructed to gain insight into the dynamic evolution of DMs’ strategies.

First, the heterogeneous aspirations of DMs can improve the cooperation level in R&D alliance portfolios. Second, compared to prudent DMs, aggressive DMs are more likely to choose the cooperation strategy, implying that an appropriate aspiration level nurtures cooperative R&D endeavors with partners. Third, the effects of effort complementarity, knowledge reorganization capabilities and cooperation supervision on cooperation are contingent on the distribution of DMs’ aspiration types.

Policymakers should identify aspiration types of DMs when screening partners. They can encourage partners to focus more on historical payoffs and establish relatively higher aspiration levels to improve the cooperation level. Developing highly detailed contracts becomes crucial when cooperating with firms that possess extensive knowledge reorganization capabilities.

This work contributes a theoretical framework for investigating cooperation in R&D alliance portfolios through the lens of evolutionary games on complex networks, thus revealing the effects of heterogeneous reference-point-based aspirations of DMs on R&D cooperation.

The collaborative filtering algorithm is a classical and widely used approach in product recommendation systems. However, the existing algorithms rely mostly on common ratings of items and do not consider temporal information about items or user interests. To solve this problem, this study proposes a new user-item composite filtering (UICF) recommendation framework by leveraging temporal semantics.

The UICF framework fully utilizes the time information of item ratings for measuring the similarity of items and takes into account the short-term and long-term interest decay for computing users’ latest interest degrees. For an item to be probably recommended to a user, the interest degrees of the user on all the historically rated items are weighted by their similarities with the item to be recommended and then added up to predict the recommendation degree.

Comprehensive experiments on the MovieLens and KuaiRec datasets for user movie recommendation were conducted to evaluate the performance of the proposed UICF framework. Experimental results show that the UICF outperformed three well-known recommendation algorithms Item-Based Collaborative Filtering (IBCF), User-Based Collaborative Filtering (UBCF) and User-Popularity Composite Filtering (UPCF) in the root mean square error (RMSE), mean absolute error (MAE) and F1 metrics, especially yielding an average decrease of 11.9% in MAE.

A UICF recommendation framework is proposed that combines a time-aware item similarity model and a time-wise user interest degree model. It overcomes the limitations of common rating items and utilizes temporal information in item ratings and user interests effectively, resulting in more accurate and personalized recommendations.

This paper aims to study the effect of different Ni content on the microstructure and properties of Sn-0.7Cu alloy. Then, the spreading area, wetting angle, interface layer thickness and microstructure of the soldering interface was observed and analyzed at different soldering temperatures and times.

Sn-0.7Cu-xNi solder alloy was prepared by a high-frequency induction melting furnace. Then Sn-0.7Cu-xNi alloy was soldered on a Cu substrate at different soldering temperatures and times.

It was found that Ni made the intermetallic compounds in the Sn-0.7Cu solder alloy gradually aggregate and coarsen, and the microstructure was refined. The phase compositions of the solder alloy are mainly composed of the ß-Sn phase and a few intermetallic compounds, Cu₆Sn₅ + (Cu, Ni)₆Sn₅. The maximum value of 12.1 HV is reached when the Ni content is 0.1 Wt.%. When the Ni content is 0.5 Wt.%, the wettability of the solder alloy increases by about 15%, the interface thickness increases by about 8.9% and the scallop-like structure is the most refined. When the soldering time is 10 min and the soldering temperature is 280 °C, the wettability of Sn-0.7Cu-0.2Ni is the best.

It is groundbreaking to combine the change in soldering interface with the soldering industry. The effects of different soldering temperatures and times on the Sn-0.7Cu-xNi alloy were studied. Under the same conditions, Sn-0.7Cu-0.2Ni exhibits better wettability and more stable solder joint stability.

Social media fatigue (SMF) has been widely recognized; however, previous studies have included various concepts into a single fatigue construct. Fatigue has typically been explored from the stressor-strain-outcome (SSO) or stimulus-organism-response (SOR) perspectives. To further investigate SMF, the authors split it into the two constructs of exhaustion and disinterest. Furthermore, the authors introduced the concept of emotional labor and identified rules that may affect surface and deep acting strategies.

The authors designed and conducted a survey to collect data from social networking platform users.

Results from 364 users of social networking platforms supported most of the authors' hypotheses. First, most of the display rules affect the choice of deep or surface acting. Second, both types of acting lead to exhaustion, but only surface acting leads to disinterest. Third, discontinuance intention is affected by both types of fatigue.

This study contributes to SMF research by adding more antecedents (deep and surface acting) based on the emotional labor perspective and showing the impacts of communication rules on emotional labor. In addition, this study also distinguishes disinterest-style fatigue from exhaustion.

Organic coatings are widely used for protecting metal equipment and structures from corrosion. Accurate detection and evaluation of the protective performance and service life of coatings are of great importance. This paper aims to review the research progress on performance evaluation and lifetime prediction of organic coatings.

First, the failure forms and aging testing methods of organic coatings are briefly introduced. Then, the technical status and the progress in the detection and evaluation of coating protective performance and the prediction of service life are mainly reviewed.

There are some key challenges and difficulties in this field, which are described in the end.

The progress is summarized from a variety of technical perspectives. Performance evaluation and lifetime prediction include both single-parameter and multi-parameter methods.

A stochastic technique for solving interval non-linear problems using generalized Hukuhara (GH)-difference is proposed. The non-linear programming problem in interval form is transformed into an equivalent non-linear programming problem with real coefficients by associating a Gaussian random variable to the interval and the six-sigma rule. The conceptualized idea eliminates the decision maker’s instinctive selection of weight functions and provides an alternative to the order relation method, max-min criteria-based methods and bi-level approaches for representing intervals as real numbers. To demonstrate a coherent understanding, numerical examples have been used.

A stochastic approach has been used to develop a solution technique for solving interval nonlinear programming problems which arise in the modeling of scientific and engineering problems under uncertain environments.

The proposed idea eliminates the decision maker’s instinctive selection of weight functions and provides an alternative to the order relation method, max-min criteria-based methods and bi-level approaches for representing intervals as real numbers. This method provides specific results rather than in the interval form, which are more practical and implementable by the decision maker.

This is to certify, that the research paper submitted is an outcome of original work. I have duly acknowledged all the sources from which the ideas and extracts have been taken. This article has not been submitted elsewhere for publication.

The purpose of this study is to campare the corrosion behavior of Az91 films and bulk sample, in the objective to provide reference for the corrosion resistance improvement of Mg alloys.

AZ91 films with various thickness values are produced by magnetron sputtering technique, and the corrosion behavior was characterized by immersion tests and electrochemical measurements.

The AZ91 films exhibited a preferred orientation with basal planes parallel to the surface and increased densification with the increase of thickness, and a superior corrosion resistance for the AZ91 films compared with the bulk sample.

The preferred (0002) basal planes in AZ91 films benefited the corrosion resistance and the nanoscale AZ91 films facilitated the development of a dense passivation film. Consequently, AZ91 film exhibited a superior corrosion resistance.

One of the simplest ways to improve the profitability of a business is by saving energy. Responding to recent calls to investigate the mechanism leading to individuals’ energy-saving behaviors in the workplace, this study aims to investigate combining person-environment (PE) fit theory with normative factors to understand employees’ decisions to engage in energy-saving activities.

The results of an online survey reveal that person-organization fit, person-job fit and moral norm significantly affect employees’ energy-saving intention.

Furthermore, the findings show that moral norm is the strongest predictor of employees’ willingness to save energy. The results also demonstrate the interrelated relationships between PE fit and normative factors.

The results contribute overall to a greater understanding of energy-saving practices in the organizational context. Apart from the theoretical contributions, the findings of the current investigation offer valuable practical insights for organizations and policymakers to promote energy conservation practices.

This paper aims to propose a robust method for non-rigid point set registration, using the Gaussian mixture model and accommodating non-rigid transformations. The posterior probabilities of the mixture model are determined through the proposed integrated feature divergence.

The method involves an alternating two-step framework, comprising correspondence estimation and subsequent transformation updating. For correspondence estimation, integrated feature divergences including both global and local features, are coupled with deterministic annealing to address the non-convexity problem of registration. For transformation updating, the expectation-maximization iteration scheme is introduced to iteratively refine correspondence and transformation estimation until convergence.

The experiments confirm that the proposed registration approach exhibits remarkable robustness on deformation, noise, outliers and occlusion for both 2D and 3D point clouds. Furthermore, the proposed method outperforms existing analogous algorithms in terms of time complexity. Application of stabilizing and securing intermodal containers loaded on ships is performed. The results demonstrate that the proposed registration framework exhibits excellent adaptability for real-scan point clouds, and achieves comparatively superior alignments in a shorter time.

The integrated feature divergence, involving both global and local information of points, is proven to be an effective indicator for measuring the reliability of point correspondences. This inclusion prevents premature convergence, resulting in more robust registration results for our proposed method. Simultaneously, the total operating time is reduced due to a lower number of iterations.