Wenzhou-Kean University

This work considers the Bi-objective Traveling Salesman Problem (BTSP), where two conflicting objectives, the travel time and monetary cost between cities, are minimized. Our purpose is to compute the trade-off solutions that fulfill the problem requirements. We introduce a novel three-Phase Hybrid Evolutionary Algorithm (3PHEA) based on the Lin–Kernighan Heuristic, an improved version of the Non-Dominated Sorting Genetic Algorithm, and Pareto Variable Neighborhood Search, a multi-objective version of VNS. We conduct a comparative study with three existing approaches dedicated to solving BTSP. To assess the performance of algorithms, we consider 20 BTSP instances from the literature of varying degrees of difficulty (e.g., euclidean, random, mixed, etc.) and different sizes ranging from 100 to 1000 cities. We also compute several multi-objective performance indicators, including running time, coverage, hypervolume, epsilon, generational distance, inverted generational distance, spread, and generalized spread. Experimental results and comparative analysis indicate that the proposed three-phase method 3PHEA is significantly superior to existing approaches covering up to 80% of the true Pareto fronts.

Biocompatible and bioactive composite scaffolds are essential in bone tissue regeneration because of their bioactivity and multilevel porous assemblies. There is a high demand for three-dimensional (3D) scaffolds to treat bone regeneration defects, trauma, and congenital skeletal abnormalities in the current scenario. The main objective of this review is to collect all the possible information concerning synthetic and natural polymer-Bioglass (BG)-based scaffold materials and systematically present them to summarize the importance and need for these materials. The importance of the bone tissue engineering field has been highlighted. Given the current challenges, a comprehensive description of materials fabrication and patterns in scaffold structures is required. This review also includes the most crucial aspect of this study: why are polymeric materials mixed with BG materials? Individually, both BG and polymeric materials lack specific essential characteristics to enhance the scope of these materials. However, preparing the composites of both ensures the researchers that composites of polymers and BG have improved properties that make them versatile materials for bone tissue engineering applications. This study deals with the individual drawbacks of the inorganic BGs, synthetic polymers, and the deficiencies of natural polymers. This study has also included a brief description of various scaffold fabricating techniques. Finally, this study revealed that by manufacturing and developing novel composite materials-scaffolds bearing the capability to repair, heal, and regenerate accidentally damaged or badly injured bones, many occasional problems can be solved in vivo and in vitro. Moreover, this review demonstrated that natural polymeric materials present many advantages over synthetic bone grafts. Yet, synthetic biomaterials have one additional attractive feature, as they have the flexibility to be designed according to the desired demands. These features make them the best choice for a wide range of bone tissue engineering projects for orthopedic surgeons.

Studies investigating the relationship between cognitive function and academic performance have recently shifted focus from differences in intelligence to executive function. To date, these studies have focused disproportionately on samples recruited from Western countries, despite evidence in support of cultural differences in the development of executive function. To address this gap, the present study investigated whether differences in two dimensions of executive function, inhibitory and attentional control, could predict academic performance in a sample of Chinese adolescents (n = 42). Participants reported on demographic details and completed both the Simon task and Attention Network Test. Data were analyzed using multiple linear regression controlling for gender, age, SES, English language proficiency, processing speed, and fluid intelligence. Results showed that one index of inhibitory control derived from non-cue trials on the Attention Network Test explained a significant amount of unique variance in academic performance. Our findings provide evidence that executive function, specifically inhibitory control, plays a significant role in academic performance.

Parental anxiety in children’s education is closely related to children’s developmental and educational outcomes. The current study reported the development and validation of a self-report instrument to evaluate the Sources of Parental Anxiety in Children’s Education (SPACEs). Qualitative analyses suggested that the construct of parental anxiety in children’s education was multidimensional, representing learning performance anxiety, educational environment anxiety, educational input anxiety, and educational outcome anxiety as four primary sources. The results from exploratory and confirmatory factor analyses supported this four-factor structure comprising 17 items to capture this multidimensional construct. The scale also demonstrated adequate internal consistencies, convergent validity, discriminant validity, criterion-related validity, and test-retest reliability. A series of multi-group tests across age, locality, and children’s grades provided evidence of measurement invariance. Overall, the SPACE scale appear to be a reliable and valid tool to measure educational anxiety in parents in the Chinese context.

Using a two-step VAR asymmetric BEKK GARCH model, this research explores the asymmetric return and volatility connectedness between gold and several energy markets during three subperiods: pre-COVID, before vaccination, and after vaccination. Gold’s returns and volatility spillover are generally found to be time- and energy-dependent. In addition, the optimal weights, hedge ratios, and hedging effectiveness of energy commodity and gold pairs are calculated during the three subperiods. The results of optimal weights show that investors should increase their investment in energy commodities more than gold (energy commodities) during the after-vaccination period (the pre-vaccination period). Moreover, the hedging strategy would only be effective within the COVID-19 vaccination period, which could have implications for the strategic asset allocation of policy-makers and international investors. Finally, we examine the potential determinants of conditional correlations between gold and energy markets. VIX, EPU, and new confirmed cases are found to be the main predictors of correlations for most energy commodity-gold pairs during the examined period.

Based on the data of 253 A-share listed new energy enterprises from 2010–2021, this paper studies the correlations among equity incentives, the three contract elements of equity incentives and the financial performance of new energy enterprises by using fixed-effect regression analysis, and on this basis, Granger causality analysis is applied to determine the causal relationship, and finally, the degree of influence of equity incentives contract elements is further studied by Grey Relational Analysis. It is found that equity incentives positively affect the financial performance of new energy enterprises as a whole. In terms of the choice of equity incentive contract elements, the influence is more significant when the granting method is stock options, when the exercise duration is longer, and when the exercise conditions are stricter. As to the degree of influence, the influence of equity incentive method and exercise conditions on the financial performance of new energy enterprises is greater, but the influence of exercise duration is the lowest. Therefore, it is suggested that new energy enterprises can choose more stock options for equity incentives, create stricter exercise conditions and set the duration of the equity incentive scheme between 5 and 10 years with their own characteristics.

Domination is a well-known graph theoretic concept due to its significant real-world applications in several domains, such as design and communication network analysis, coding theory, and optimization. For a connected graph Γ = V , E , a subset U of V Γ is called a dominating set if every member present in V − U is adjacent to at least one member in U . The domatic partition is the partition of the vertices V Γ into the disjoint dominating set. The domatic number of the graph Γ is the maximum cardinality of the disjoint dominating sets. In this paper, we improved the results for the middle and central graphs of a cycle, respectively. Furthermore, we discuss the domatic number for some other cycle-related graphs and graphs of convex polytopes.

Malfunctions in the immune system cause multiple sclerosis (MS), which initiates mild to severe nerve damage. MS will disturb the signal communication between the brain and other body parts, and early diagnosis will help reduce the harshness of MS in humankind. Magnetic resonance imaging (MRI) supported MS detection is a standard clinical procedure in which the bio-image recorded with a chosen modality is considered to assess the severity of the disease. The proposed research aims to implement a convolutional neural network (CNN) supported scheme to detect MS lesions in the chosen brain MRI slices. The stages of this framework include (i) image collection and resizing, (ii) deep feature mining, (iii) hand-crafted feature mining, (iii) feature optimization with firefly algorithm, and (iv) serial feature integration and classification. In this work, five-fold cross-validation is executed, and the final result is considered for the assessment. The brain MRI slices with/without the skull section are examined separately, presenting the attained results. The experimental outcome of this study confirms that the VGG16 with random forest (RF) classifier offered a classification accuracy of >98% MRI with skull, and VGG16 with K-nearest neighbor (KNN) provided an accuracy of >98% without the skull.

The COVID-19 pandemic infection control measures severely impacted mental well-being, allowing insight into possible protective parameters. With religion playing a role during challenging times, this study investigated theism and religiosity on the mental well-being of university students during the COVID19 pandemic and how social support and resilience can mediate this effect. One hundred eighty-five university students between 17 and 42 years old responded to online surveys on their theism, religious affiliations, religiosity, well-being, perceived support, and resilience. Pearson’s correlations and single and sequential mediation analyses showed that theism did not significantly predict well-being (r = 0.049), but religiosity mediated the relationship (r = 0.432, effect size = 0.187). Sequential mediation analysis showed that resilience did not mediate the relationship between religiosity and well-being, but perceived social support significantly positively mediated religiosity and well-being with an effect size of 0.079. The findings reveal that factors, such as religiosity and social support could thus aid in the mental well-being of future challenging times such as the pandemic.

This study examines whether foreign ownership plays a moderating role in the relation between income smoothing and firm value. We first find that income smoothing is negatively related to firm value. We then find that the negative relation between income smoothing and firm value is weaker for firms with high foreign ownership than for those with low foreign ownership. This finding suggests that foreign ownership serves a positive moderating role in the income smoothing-firm value relation. Finally, we further find that the positive moderating effect of foreign ownership on the income smoothing-firm value nexus is stronger for firms that have higher profitability and pay dividends. Overall, our empirical evidence sheds light on the moderating role of foreign ownership in the association between income smoothing and firm value.

After almost two decades of continuous development in bio, circular, and green economy, it is time to assess the major achievements and challenges that private and public enterprises face today for further enhancing global sustainability concepts. To this end, the present thematic issue accommodates twenty articles on different topics related to circular economy development and green growth, proposing a contribution to the field of environmental economics and policy. The central feature of this Special Issue is the focus on the best practices and challenges in terms of green growth and eco-innovation in developing and transitioning structurally challenged areas. Hence, the study elaborates on the pathways of bio, circular, and green growth and eco-innovation in the context of countries with relatively low per capita income. By doing this, the collection shows that the empirically established environmental Kuznets curve—i.e., the inverted U-shaped income-environment nexus—can and must be critically questioned, at least in the contexts mentioned within the framework of our Special Issue. Hence, the geographic frontiers of environmental upgrading, carbon-saving bioeconomic development, and green growth are not limited to the economically advanced areas.

The temperature difference of the various applications such as microchannel heat exchangers, microelectronics, solar collectors, automotive systems, micro fuel cells, and microelectromechanical systems (MEMS) is relatively large. The buoyancy force (mixed convection) modeled by the conventional Boussinesq approximation is inadequate since the density of the operating fluids fluctuates non‐linearly with the temperature difference. Therefore, the mixed non‐linear convective transport of the flow of Cross fluid through three different geometric aspects (horizontal, vertical, and inclined) of the microchannel under the non‐linear Boussinesq (NBA) approximation is investigated. Mechanisms of internal heat source, Rosseland radiative heat flux, and frictional heating are incorporated into the thermal analysis. The mathematical construction is proposed using the Cross fluid model for a steady‐state, and subsequent non‐linear differential equations are deciphered by the spectral quasi‐linearization method (SQLM). Graphical sketches were constructed and displayed that explore the stimulus of various key parameters on Bejan number, velocity, temperature, and entropy generation. It is found that the Bejan number and entropy production improved due to the non‐linear density temperature variation. The convective heating boundary conditions augment the entropy production. The pressure gradient accelerates the transport of fluid in a microchannel. Furthermore, among three different geometries, the velocity, entropy production, and temperature are the highest for the vertical microchannel.

Abstract Straw returning is an effective management measure to improve or maintain soil fertility in agricultural ecosystems. This study investigated the effects of straw returning combined with compound fertilizer on the bacterial community, enzyme activities, and soil nutrients’ contents in a rape-rice rotation soil aggregates. To do so, a 5-year field trial (November 2016 to October 2021) was carried out in a paddy soil with three treatments: no straw + no fertilization (CK), compound fertilizer (F), and straw returning + compound fertilizer (SF). Soil aggregates were classified into mega-aggregates (> 2 mm), macro-aggregates (0.25–2 mm), micro-aggregates (0.053–0.25 mm), and silt–clay ( 2 mm aggregates by 3.17% and significantly decreased the content of 0.053–0.25 mm aggregates by 20.27%. The contents of organic carbon and total nitrogen in > 0.053 mm straw amended aggregates increased by 15.29 and 18.25%, respectively. Straw returning significantly increased the urease activity of > 0.053 mm aggregates with an average of 43.08%, while it decreased the phosphatase and invertase activities of soil aggregates by 7.71–40.66%. The Shannon indices of the bacterial community in each particle sizes soil aggregates decreased by an average of 1.16% and the Chao indices of the bacterial community in

Diabetic retinopathy (DR) and adult vitelliform macular dystrophy (AVMD) may cause significant vision impairment or blindness. Prompt diagnosis is essential for patient health. Photographic ophthalmoscopy checks retinal health quickly, painlessly, and easily. It is a frequent eye test. Ophthalmoscopy images of these two illnesses are challenging to analyse since early indications are typically absent. We propose a deep learning strategy called ActiveLearn to address these concerns. This approach relies heavily on the ActiveLearn Transformer as its central structure. Furthermore, transfer learning strategies that are able to strengthen the low-level features of the model and data augmentation strategies to balance the data are incorporated owing to the peculiarities of medical pictures, such as their limited quantity and generally rigid structure. On the benchmark dataset, the suggested technique is shown to perform better than state-of-the-art methods in both binary and multiclass accuracy classification tasks with scores of 97.9% and 97.1%, respectively.

China is a collectivist nation that varies socially and culturally from most Western countries. Recently, the country has been an attractive destination for international students. A contemporary digital platform such as WeChat Moments (WMs) is a leading social media platform among locals and international students to communicate and interact in cross-cultural settings for various purposes, including maintaining friendships and establishing new social capital. Prior research has overlooked the beneficial effects of such domestic social media platforms on international students in China, especially for strengthening their existing friendship quality and guanxi networking. Based on the self-disclosure theory, this study examines the relationship between international students’ WMs use intensity, online self-disclosure, closeness to friends, and guanxi network building using data from 445 international students employing structural equation modeling. This study reveals that WMs use has a substantial effect on the formation of guanxi networks and that online self-disclosure mediates the connection between WMs use and friendship closeness and guanxi network building. Several theoretical and practical recommendations are provided in the context of the guanxi network.

This paper explores the dynamic connectedness between Defi assets and sector stock markets focused around the COVID-19 pandemic crisis. For that aim, this research applies the TVP-VAR model, and it also computes the optimal weights and hedge ratios for the Defi assets–sector equity portfolios using the DCC-GARCH model. Our main findings reveal that static connectedness is slightly economy- and sector-dependent. Regarding the dynamic connectedness, as expected, the total spillover index changes over time, showing a cruel impact of the global pandemic declaration. Net spillover indices show relevant differences between the Defi assets and certain sectors (net receivers) and sectors such as industrials, materials and information technology (time-varying net transmitters). Finally, the optimal hedge ratios reveal similar levels of coverage in all the periods analyzed, with slight upturns in the cost of such coverage in the crisis period caused by COVID-19.