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This paper aims to review recent reports on mechanical properties of Sn-Bi and Sn-Bi-X solders (where X is an additional alloying element), in terms of the tensile properties, hardness and shear strength. Then, the effects of alloying in Sn-Bi solder are compared in terms of the discussed mechanical properties. The fracture morphologies of tensile shear tested solders are also reviewed to correlate the microstructural changes with mechanical properties of Sn-Bi-X solder alloys.

A brief introduction on Sn-Bi solder and reasons to enhance the mechanical properties of Sn-Bi solder. The latest reports on Sn-Bi and Sn-Bi-X solders are combined in the form of tables and figures for each section. The presented data are discussed by comparing the testing method, technical setup, specimen dimension and alloying element weight percentage, which affect the mechanical properties of Sn-Bi solder.

The addition of alloying elements could enhance the tensile properties, hardness and/or shear strength of Sn-Bi solder for low-temperature solder application. Different weight percentage alloying elements affect differently on Sn-Bi solder mechanical properties.

This paper provides a compilation of latest report on tensile properties, hardness, shear strength and deformation of Sn-Bi and Sn-Bi-X solders and the latest trends and in-depth understanding of the effect of alloying elements in Sn-Bi solder mechanical properties.

Surface acoustic wave (SAW) sensors have attracted great attention worldwide for a variety of applications in measuring physical, chemical and biological parameters. However, stability has been one of the key issues which have limited their effective commercial applications. To fully understand this challenge of operation stability, this paper aims to systematically review mechanisms, stability issues and future challenges of SAW sensors for various applications.

This review paper starts with different types of SAWs, advantages and disadvantages of different types of SAW sensors and then the stability issues of SAW sensors. Subsequently, recent efforts made by researchers for improving working stability of SAW sensors are reviewed. Finally, it discusses the existing challenges and future prospects of SAW sensors in the rapidly growing Internet of Things-enabled application market.

A large number of scientific articles related to SAW technologies were found, and a number of opportunities for future researchers were identified. Over the past 20 years, SAW-related research has gained a growing interest of researchers. SAW sensors have attracted more and more researchers worldwide over the years, but the research topics of SAW sensor stability only own an extremely poor percentage in the total researc topics of SAWs or SAW sensors.

Although SAW sensors have been attracting researchers worldwide for decades, researchers mainly focused on the new materials and design strategies for SAW sensors to achieve good sensitivity and selectivity, and little work can be found on the stability issues of SAW sensors, which are so important for SAW sensor industries and one of the key factors to be mature products. Therefore, this paper systematically reviewed the SAW sensors from their fundamental mechanisms to stability issues and indicated their future challenges for various applications.

More people share their tourism experiences on social media today than in the past, and as a result, more people follow these posts in their trip planning. However, studies into tourists' intention to follow such posts are scarce. Therefore, this study investigates the antecedents influencing social media users' intentions to follow tourism-related posts (TRPs) when planning their trips.

Questionnaires were collected from 402 social media users who had followed TRPs for their trip planning. Data were then analyzed using partial least squares structural equation modeling (PLS-SEM) and artificial neural networks.

The authors found that blogger–user fit and users' involvement with TRPs influenced behavior components (attitudes toward TRPs and intention to follow TRPs) via assessment components (bloggers' credibility and content quality), and the authors developed a framework to explain this relationship.

The findings advance prior studies by investigating (1) the antecedents of intention to follow TRPs when trip planning, (2) the two main social media elements – bloggers and posts – to understanding the role of social media on travel behavior and (3) involvement with TRPs and their impacts on travel behavior. This study contributes to the research on social media and tourism marketing and proposes practical indications for bloggers, social media platforms and destination marketing organizations.

The purpose of this study is to explore the impact of online reviews on answer adoption in virtual Q&A communities, with an eye toward extending knowledge exchange and community management.

Online reviews contain rich cognitive and emotional information about community members regarding the provided answers. As feedback information on answers, it is crucial to explore how online reviews affect answer adoption. Based on signaling theory, a research model reflecting the influence of online reviews on answer adoption is established and empirically examined by using secondary data with 69,597 Q&A data and user data collected from Zhihu. Meanwhile, the moderating effects of the informational and emotional consistency of reviews and answers are examined.

The negative binomial regression results show that both answer-related signals (informational support and emotional support) and answerers-related signals (answerers’ reputations and expertise) positively impact answer adoption. The informational consistency of reviews and answers negatively moderates the relationships among information support, emotional support and answer adoption but positively moderates the effect of answerers’ expertise on answer adoption. Furthermore, the emotional consistency of reviews and answers positively moderates the effect of information support and answerers’ reputations on answer adoption.

Although previous studies have investigated the impacts of answer content, answer source credibility and personal characteristics of knowledge seekers on answer adoption in virtual Q&A communities, few have examined the impact of online reviews on answer adoption. This study explores the impacts of informational and emotional feedback in online reviews on answer adoption from a signaling theory perspective. The results not only provide unique ideas for community managers to optimize community design and operation but also inspire community users to provide or utilize knowledge, thereby reducing knowledge search costs and improving knowledge exchange efficiency.

Poverty alleviation is a global challenge. Human society has never ceased to fight against poverty. China was once the developing country with the largest rural poor population in the world. Remarkable achievements have been made in China’s antipoverty program over the past decades, shaping a unique poverty reduction strategy with Chinese characteristics. The purpose of this paper is to first review the history of China’s rural reform and antipoverty, and then analyze the related policy systems, mechanism innovations and future challenges in poverty alleviation and development. At last, some specific policy implications were provided.

Literature on China’s antipoverty history was reviewed and mechanism innovations on targeted poverty alleviation strategy were investigated.

Along with the deepening of the rural reform, the poverty alleviation and development in new China have undergone six stages, and experienced a transformation from relief-oriented to development-oriented poverty alleviation. The object of poverty alleviation has gradually targeted with a transformation from poor counties/areas to villages/households, and the effectiveness of poverty alleviation is also gradually improved. However, the increase in the difficulty of antipoverty, fragile ecological environment, rapid population aging and rural decline poses challenges to the construction of a well-off society in an all-round way in China. Specific antipoverty measures were put forward based on the investigation. Finally, the authors emphasize the importance of strengthening the study of poverty geography.

This study investigates the history of China’s antipoverty policy and analyzes the future challenges for implementing targeted poverty alleviation policy. These findings will lay a foundation for the formulation of China’s antipoverty policies after 2020, and provide experience for poverty alleviation in other developing countries around the world.

Knowledge adoption is the key to effective knowledge exchange in virtual question-and-answer (Q&A) communities. Although previous studies have examined the effects of knowledge content, knowledge source credibility and the personal characteristics of knowledge seekers on knowledge adoption in virtual Q&A communities from a static perspective, the impact of answer deviation on knowledge adoption has rarely been explored from a context-based perspective. The purpose of this study is to explore the impact of two-way deviation on knowledge adoption in virtual Q&A communities, with the aim of expanding the understanding of knowledge exchange and community management.

The same question and the same answerer often yield multiple answers. Knowledge seekers usually read multiple answers to make adoption decisions. The impact of deviations among answers on knowledge seekers' knowledge adoption is critical. From a context-based perspective, a research model of the impact of the deviation of horizontal and vertical answers on knowledge adoption is established based on the heuristic-systematic model (HSM) and empirically examined with 88,287 Q&A data points and answerer data collected from Zhihu. Additionally, the moderation effects of static factors such as answerer reputation and answer length are examined.

The negative binomial regression results show that the content and emotion deviation of horizontal answers negatively affect knowledge seekers' knowledge adoption. The content deviation of vertical answers is negatively associated with knowledge adoption, while the emotion deviation of vertical answers is positively related to knowledge adoption. Moreover, answerer reputation positively moderates the negative effect of the emotion deviation of horizontal answers on knowledge adoption. Answer length weakens the negative correlation between the content deviation of horizontal and vertical answers and knowledge adoption.

This study extends previous research on knowledge adoption from a static perspective to a context-based perspective. Moreover, information deviation is expanded from a one-way variable to a two-way variable. The combined effects of static and contextual factors on knowledge adoption are further uncovered. This study can not only help knowledge seekers identify the best answers but also help virtual Q&A community managers optimize community design and operation to reduce the cost of knowledge search and improve the efficiency of knowledge exchange.

The coupling process between the loading mechanism and the tank car mouth is a crucial step in the tank car loading process. The purpose of this paper is to design a method to accurately measure the pose of the tanker car.

The collected image is first subjected to a gray enhancement operation, and the black parts of the image are extracted using Otsu’s threshold segmentation and morphological processing. The edge pixels are then filtered to remove outliers and noise, and the remaining effective points are used to fit the contour information of the tank car mouth. Using the successfully extracted contour information, the pose information of the tank car mouth in the camera coordinate system is obtained by establishing a binocular projection elliptical cone model, and the pixel position of the real circle center is obtained through the projection section. Finally, the binocular triangulation method is used to determine the position information of the tank car mouth in space.

Experimental results have shown that this method for measuring the position and orientation of the tank car mouth is highly accurate and can meet the requirements for industrial loading accuracy.

A method for extracting the contours of various types of complex tanker mouth is proposed. This method can accurately extract the contour of the tanker mouth when the contour is occluded or disturbed. Based on the binocular elliptic conical model and perspective projection theory, an innovative method for measuring the pose of the tanker mouth is proposed, and according to the space characteristics of the tanker mouth itself, the ambiguity of understanding is removed. This provides a new idea for the automatic loading of ash tank cars.

This study aims to develop a new kind of functional low molecular weight organic dyes, which is highly efficient, meanwhile inexpensive and easily prepared and modified and can be used in photoacoustic (PA) imaging and photothermal therapy (PTT). To further realize the release of molecules under the biomedical condition, the releasing efficiency of micellar nanoparticles under different stimuli were represented.

A class of azo and Schiff base derivatives with different click reagents were characterized by PA imaging and photothermal (PT) experiments. The molecule with best PT effect was loaded into a temperature-stimuli-sensitive amphiphilic block copolymer which demonstrated the capability of releasing the polymers under the near-infrared (NIR) light of 650 nm.

The PA and PT effects of a series of azo and Schiff base derivatives with different click reagents were characterized. Introducing the click reagent F4-TCNQ can result in red shift of peaks of PA intensity. Stimulated with 650 nm laser irradiation, the polymer processed higher release rate than being stimulated by temperature stimuli.

This paper not only guides the design of NIR dyes with good PA intensity but also provides a method which has great potential for the application of NIR photothermal dyes in the field of biotechnology for controlled release.

This paper uses click reagents to modify azo and Schiff derivatives and an amphiphilic block copolymer under NIR light to realize controlled release.

Vision transformers (ViT) detectors excel in processing natural images. However, when processing remote sensing images (RSIs), ViT methods generally exhibit inferior accuracy compared to approaches based on convolutional neural networks (CNNs). Recently, researchers have proposed various structural optimization strategies to enhance the performance of ViT detectors, but the progress has been insignificant. We contend that the frequent scarcity of RSI samples is the primary cause of this problem, and model modifications alone cannot solve it.

To address this, we introduce a faster RCNN-based approach, termed QAGA-Net, which significantly enhances the performance of ViT detectors in RSI recognition. Initially, we propose a novel quantitative augmentation learning (QAL) strategy to address the sparse data distribution in RSIs. This strategy is integrated as the QAL module, a plug-and-play component active exclusively during the model’s training phase. Subsequently, we enhanced the feature pyramid network (FPN) by introducing two efficient modules: a global attention (GA) module to model long-range feature dependencies and enhance multi-scale information fusion, and an efficient pooling (EP) module to optimize the model’s capability to understand both high and low frequency information. Importantly, QAGA-Net has a compact model size and achieves a balance between computational efficiency and accuracy.

We verified the performance of QAGA-Net by using two different efficient ViT models as the detector’s backbone. Extensive experiments on the NWPU-10 and DIOR20 datasets demonstrate that QAGA-Net achieves superior accuracy compared to 23 other ViT or CNN methods in the literature. Specifically, QAGA-Net shows an increase in mAP by 2.1% or 2.6% on the challenging DIOR20 dataset when compared to the top-ranked CNN or ViT detectors, respectively.

This paper highlights the impact of sparse data distribution on ViT detection performance. To address this, we introduce a fundamentally data-driven approach: the QAL module. Additionally, we introduced two efficient modules to enhance the performance of FPN. More importantly, our strategy has the potential to collaborate with other ViT detectors, as the proposed method does not require any structural modifications to the ViT backbone.

Generation Z makes up 20% of China’s population, and accounts for the highest share of household spend at 13% (vs. 3% for the United Kingdom and 4% for the United States). To advance marketers’ understanding about this group of consumers and capitalise on China’s booming market, this chapter uses rich statistics and information to show that China’s Generation Z has distinct behaviour patterns, which can be attributed to the unique background in which they grew up: (1) rigidity of social stratification, (2) abundance of materialism, (3) digital era, (4) limited (vs. extended) family, and (5) heavy schoolwork. Growing up in such a background, Generation Z’s lifestyle and consumption-related attitudes and behaviour are distinct from their predecessors. The chapter presents specific actions that marketers can take when targeting this distinct group of consumers in China, along with useful guidelines to HR managers for hiring them.