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This paper studies the optimal decision-making and coordination problem of a dual-channel fresh agricultural product (FAP) supply chain. The purpose is to analyze the impact of information sharing on optimal decisions and propose a coordination mechanism to encourage supply chain members to share information.

The two-echelon dual-channel FAP supply chain includes a manufacturer and a retailer. By using the Stackelberg game theory and the backward induction method, the optimal decisions are obtained under information symmetry and asymmetry and the coordination contract is designed.

The results show that supply chain members should comprehensively evaluate the specific situation of product attributes, coefficient of freshness-keeping cost and network operating costs to make decisions. Asymmetric information can exacerbate the deviation of optimal decisions among supply chain members and information sharing is always beneficial to manufacturers but not to retailers. The improved revenue-sharing and cost-sharing contract is an effective coordination mechanism.

The conclusions can provide theoretical guidance for supply chain managers to deal with information asymmetry and improve the competitiveness of the supply chain.

This paper combines the three characteristics that are most closely related to the reality of supply chains, including horizontal and vertical competition of different channels, the perishable characteristics of FAPs and the uncertainty generated by asymmetric demand information.

This paper is supposed to provide a critical review of current research progress on thermal management in grinding of superalloys, and future directions and challenges. By understanding the current progress and identifying the developing directions, thermal management can be achieved in the grinding of superalloys to significantly improve the grinding quality and efficiency.

The relevant literature is collected from Web of Science, Scopus, CNKI, Google scholar, etc. A total of 185 literature is analyzed, and the findings in the literature are systematically summarized. In this case, the current development and future trends of thermal management in grinding of superalloys can be concluded.

The recent developments in grinding superalloys, demands, challenges and solutions are analyzed. The theoretical basis of thermal management in grinding, the grinding heat partition analysis, is also summarized. The novel methods and technologies for thermal management are developed and reviewed, i.e. new grinding technologies and parameter optimization, super abrasive grinding wheel technologies, improved lubrication, highly efficient coolant delivery and enhanced heat transfer by passive thermal devices. Finally, the future trends and challenges are identified.

Superalloys have excellent physical and mechanical properties, e.g. high thermal stability, and good high-temperature strength. The superalloys have been broadly applied in the aerospace, energy and automobile industries. Grinding is one of the most important precision machining technologies for superalloy parts. Owing to the mechanical and physical properties of superalloys, during grinding processes, forces are large and a massive heat is generated. Consequently, the improvement of grinding quality and efficiency is limited. It is important to conduct thermal management in the grinding of superalloys to decrease grinding forces and heat generation. The grinding heat is also dissipated in time by enhanced heat transfer methods. Therefore, it is necessary and valuable to holistically review the current situation of thermal management in grinding of superalloys and also provide the development trends and challenges.

This research takes Taijiang National Park (TNP) tourists as the study population while gathering the survey data via an online questionnaire. For the data analyses, it uses the importance–performance analysis (IPA) and the Kano two-dimensional quality model to evaluate the tourist satisfaction of TNP. Specifically, it considers the importance of service quality, classifies its service quality attributes, and suggests the priority for service improvement, rendering the TNP valuable reference points to realign service strategies. The study shows that the service quality attributes related to service personnel are the priority item to be improved, which could eventually enhance tourist satisfaction. In addition, brand differentiation could be achieved by improving the attractive quality items identified in this study to enhance tourist loyalty.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

Body weight has a long history of functioning as a symbol of one’s beauty, social status, morality, discipline, and health. It has also been a standard inflicted much more intensely on women than men. While US culture has long idealized thinness for women, even at risky extremes, there is growing evidence that weight standards are broadening. Larger bodies are becoming more visible and accepted, while desire for and approval of a thin ideal has diminished. However, the continued widespread prevalence of anti-fat attitudes and stigma leaves uncertainty about just how much weight standards are changing. This study used an online survey (n = 320) to directly compare evaluations of thin, fat, and average size women through measures of negative stereotypes, prejudicial attitudes, and perceptions about quality of life. Results indicated that, as hypothesized, thin women were perceived less favorably than average weight women. However, fat women were perceived less favorably than both average and thin women. Men were harsher than women in their evaluations of only fat women. Additionally, participants being underweight or overweight did not produce an ingroup bias in their evaluations of underweight and overweight targets, respectively. That is, participants did not rate their own group more favorably, with the exception of overweight participants having lower prejudice toward overweight targets. These findings add to the emerging evidence that women’s weight standards are in transition, marked by an increasingly negative perception of thin women, though not necessarily growing positivity toward fat women. This evidence further points toward the need for more extensive research on attitudes of people across the entire weight spectrum.

The metallic alloys and their components fabricated via laser powder bed fusion (LPBF) suffer from the microvoids formed inevitably due to the extreme solidification rate during fabrication, which are impossible to be removed by heat treatment. This paper aims to remove those microvoids in as-built AlSi10Mg alloys by hot forging and enhance their mechanical properties.

AlSi10Mg samples were built using prealloyed powder with a set of optimized LPBF parameters, viz. 350 W of laser power, 1,170 mm/s of scan speed, 50 µm of layer thickness and 0.24 mm of hatch spacing. As-built samples were preheated to 430°C followed by immediate pressing with two different thickness reductions of 10% and 35%. The effect of hot forging on the microstructure was analyzed by means of X-ray diffraction, scanning electron microscopy, electron backscattered diffraction and transmission electron microscopy. Tensile tests were performed to reveal the effect of hot forging on the mechanical properties.

By using hot forging, the large number of microvoids in both as-built and post heat-treated samples were mostly healed. Moreover, the Si particles were finer in forged condition (∼150 nm) compared with those in heat-treated condition (∼300 nm). Tensile tests showed that compared with heat treatment, the hot forging process could noticeably increase tensile strength at no expense of ductility. Consequently, the toughness (integration of tensile stress and strain) of forged alloy increased by ∼86% and ∼24% compared with as-built and heat-treated alloys, respectively.

Hot forging can effectively remove the inevitable microvoids in metals fabricated via LPBF, which is beneficial to the mechanical properties. These findings are inspiring for the evolution of the LPBF technique to eliminate the microvoids and boost the mechanical properties of metals fabricated via LPBF.

Classification of remote sensing images (RSI) is a challenging task in computer vision. Recently, researchers have proposed a variety of creative methods for automatic recognition of RSI, and feature fusion is a research hotspot for its great potential to boost performance. However, RSI has a unique imaging condition and cluttered scenes with complicated backgrounds. This larger difference from nature images has made the previous feature fusion methods present insignificant performance improvements.

This work proposed a two-convolutional neural network (CNN) fusion method named main and branch CNN fusion network (MBC-Net) as an improved solution for classifying RSI. In detail, the MBC-Net employs an EfficientNet-B3 as its main CNN stream and an EfficientNet-B0 as a branch, named MC-B3 and BC-B0, respectively. In particular, MBC-Net includes a long-range derivation (LRD) module, which is specially designed to learn the dependence of different features. Meanwhile, MBC-Net also uses some unique ideas to tackle the problems coming from the two-CNN fusion and the inherent nature of RSI.

Extensive experiments on three RSI sets prove that MBC-Net outperforms the other 38 state-of-the-art (STOA) methods published from 2020 to 2023, with a noticeable increase in overall accuracy (OA) values. MBC-Net not only presents a 0.7% increased OA value on the most confusing NWPU set but also has 62% fewer parameters compared to the leading approach that ranks first in the literature.

MBC-Net is a more effective and efficient feature fusion approach compared to other STOA methods in the literature. Given the visualizations of grad class activation mapping (Grad-CAM), it reveals that MBC-Net can learn the long-range dependence of features that a single CNN cannot. Based on the tendency stochastic neighbor embedding (t-SNE) results, it demonstrates that the feature representation of MBC-Net is more effective than other methods. In addition, the ablation tests indicate that MBC-Net is effective and efficient for fusing features from two CNNs.

This study aims to explore the impact of key parameters of brake pads on the dynamic characteristics of the braking system.

This study conducted experimental research based on a friction testing machine with a slider-disc structure. The experiment studied the impact of key parameters of brake pads (rotation speed, pressure, mass, braking radius, etc.) and the braking environment (dry friction, wetness, sand, etc.) on the stability of the braking system. At the same time, a dynamic model of the brake pad braking system was established and compared with experimental results using the mathematical tool of autocorrelation coefficient.

The key parameters of brake pads have a significant impact on the dynamic characteristics of the braking system; under different conditions of brake pad mass, tribological parameters, brake pad radius and braking environment, the chaotic characteristics of the braking friction force signal show a trend of expansion or contraction, which can be suppressed by adjusting the key parameters of brake pads.

This study can provide a reference for optimizing the braking strategy and reducing noise and vibration in brake pad systems.

Thermal fractures initiated under cooling at the surfaces of a 2-D or 3-D structure propagate, arrest and coalesce, leading to its structural failure and material-property changes, while the same processes can happen in the rock mass between parallel hydraulic fractures filled with cold fluid, leading to enhanced fracture connectivity and permeability.

This study used a 2-D plane strain fracture model for mixed-mode thermal fractures from two parallel cooling surfaces. Fracture propagation was governed by the theory of linear elastic fracture mechanics, while the displacement and temperature fields were discretized using the adaptive finite element method. This model was validated using two numerical benchmarks with strong fracture curvature and then used to simulate the propagation and coalescence of thermal fractures in a long rock mass.

Modeling results show two regimes: (1) thermal fractures from a cooling surface propagate and arrest by following the theoretical solutions of half-plane fractures before the unfractured portion decreases to 20% rock-mass width and (2) some pairs of fractures from the opposite cooling surfaces tend to eventually coalesce. The fracture coalescence time is in a power law with rock-mass width.

These findings are relevant to both subsurface engineering and material engineering: structure failure is a key concern in the latter, while fracture coalescence can enhance the connectivity of thermal and hydraulic fractures and thus reservoir permeability in the former.

This study aims to examine the effects of coworker incivility on employees' behaviors using a moderated mediation model that conceptualizes coworker exchange (CWX) as a mediator and servant leadership as a moderator.

The data were collected using a multi-temporal research design. The hypotheses were tested on a sample of 1,272 participants using confirmatory factor analysis (CFA), hierarchical regression analysis and moderated path analysis. In addition, supervisor incivility was added as a control variable to partial out the potential influence on employees' behaviors.

The results of CFA ensured that all measures had discriminant and convergent validity. In addition, the results of hierarchical regression analysis and moderated path analysis indicated that CWX mediates the relationship between coworker incivility and employees' behaviors. Furthermore, servant leadership exacerbates the negative relationship between coworker incivility and CWX.

Leaders and practitioners should invest in communication training programs for developing employees' communication skills to avoid incivility. In addition to viewing incivility as inappropriate behavior, leaders and practitioners should understand the meaning beyond those incivilities.

This study utilized incivility spiral theory to examine how coworker incivility affects employees' behaviors. The mediated path analysis found that CWX mediates the relationship between these variables, which has been ignored by previous research. Furthermore, this study introduced servant leadership as a moderator to account for the “when” in incivility spiral theory, i.e. what kind of social context facilitates or inhibits the influence of coworker incivility on CWX.