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Multiple fillers are adopted to study the filler influences on electrical and mechanical properties of the conductive adhesives. The performances of the developed nano-enhanced interconnect materials in printing process are also evaluated. The paper aims to discuss these issues.

Micron-sized silver flakes are used as the basic fillers, and submicro- and nano-sized silver spheres and carbon nanotubes (CNTs) are adopted to obtain conductive adhesives with multiple fillers. Differential scanning calorimetry measurement is carried out to characterize the curing behavior of the samples with different fillers, four-probe method is used to obtain the bulk resistivity, shear test is conducted for adhesive strength, and environmental loading test is also involved. Furthermore, printing trials with different patterns have been carried out.

The electrical resistivity of the adhesives with submicro-sized silver spheres does not monotonically change with the increasing sphere proportion, and there exists an optimized value for the ratio of silver flakes to spheres. Samples with relatively small amount of CNT additives show improved electrical properties, while their mechanical strengths tend to decrease. For the printing application, the adhesives with 18.3 volume% filler content behave much better than those with lower filler content of 6 percent. The presence of the nano-particles makes a slight improvement in the printing results.

More detailed printing performance and reliability test of the samples need to be carried out in the future.

The conductive adhesives as interconnect materials exhibit some improved properties with optimized bimodal or trimodal fillers. The additive of the nano-fillers affects slightly on the printing quality of the bimodal conductive adhesives.

Liquid Crystal Polymer (LCP) materials are considered to be promising substrates for wireless applications because of their excellent properties. The purpose of this paper is to describe now a novel and compact microstrip ultra‐wideband bandpass filter (UWB BPF) with ultra‐fine conductor traces working over 22 to 29 GHz is fabricated on LCP substrates.

Using standard processing technology, such as photolithography, plasma pretreatment, sputter deposition and wet etching, a microstrip UWB BPF is fabricated on LCP substrates. In order to obtain better adhesion between LCP substrate and copper, the oxygen plasma pretreatment of the LCP substrate surface and a thin titanium adhesion layer are introduced before a copper layer is sputter‐deposited onto the substrate.

The measured and the simulated results agree well. The measured insertion loss is about 8 dB in the passband of the bandpass filter, which is a little high compared to the simulated result (∼5 dB). The out of band performance at both the high frequency and low frequency is very good, almost higher than 35 dB.

This paper presents the realization of (UWB BPF) working over 22 to 29 GHz based on an LCP substrate, which demonstrates the feasibility of the application of the LCP substrate in RF wireless systems and also gives some useful information for later research.

The purpose of this paper is to prepare Ti(C,N) coatings on TA15 treated and not treated by shot peening using double glow plasma alloying technique. The effect of shot peening on the wear behavior of Ti(C,N) coatings is discussed.

The Ti(C,N) coatings were prepared by double glow plasma alloying technique on two different TA15 substrate; one is shot peened and the other is not.

Ti(C,N) coating on SP-treated TA15 was thicker and denser, and the grain size was smaller compared with that on original TA15. Compared with the Ti(C,N) coating on original TA15, the wear resistance of that on SP-treated TA15 is improved. Ti(C,N) coating on SP-treated TA15 showed higher nanohardness and bearing capacity than that on original TA15.

For double glow plasma alloying technique, surface quality, surface activity and other factors will have influence on the thickness and density of the coating. The wear mechanisms of Ti(C,N) coating on original TA15 are serious abrasive wear and oxidation wear. However, the wear mechanism of Ti(C,N) coating on SP-treated TA15 is slightly oxidation wear.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2020-0283/

Coronavirus disease 2019 (COVID-19) has resulted in traveling restrictions and decreased the demand among travelers since the end of 2019. Policies and people’s behaviors are gradually changing with the increase in the number of new diagnoses of COVID-19. Tourism increases tourists’ risk of contracting COVID-19 and will undoubtedly be affected by this disease. Based on this assumption and social cognitive theory, this paper aims to explore the impact of COVID-19 on tourism in terms of people’s willingness to travel.

Based on social cognitive theory, this study has designed the model and variables. The data of the paper came from a survey conducted in 29 provinces of China and a total of 618 responses were used for data analysis after deleting invalid questionnaires. Drawing on the structural equation modeling method, this paper processes the data collected from questionnaires to test the hypotheses and come to the results.

The results indicate that the negative impact of COVID-19 will affect the severity perceptions, personal negative effects and positive effects of tourism during the outbreak, which will ultimately influence people’s willingness to travel. During the outbreak of COVID-19, impacted by environmental factors and personal factors, Chinese people’s willingness to travel has been significantly reduced.

This study mainly focuses on people’s willingness to travel and the demand side of tourism to analyze the effects of COVID-19 on tourism, which neglects the supply side of tourism for analysis. Subsequent research should take account of the supply side of tourism and expanding the sample size worldwide to determine the impact of COVID-19 on the tourism industry from a broader perspective.

This study quantitatively analyzes how COVID-19 influenced the tourism industry and precisely determines the possible mechanism of the effect of COVID-19 on tourism by using social cognitive theory to build a model. The insights from the work help to understand how COVID-19 affects people’s willingness to travel during the pandemic and how to address this issue.

新型冠状病毒（COVID-19）自2019年底以来开始被发现, 随后逐渐蔓延至全球, 给人们的生活带来不小的影响。该病毒的发展使得人们的出行受到了较大的限制, 因而减少了人们对于旅游的需求。随着新冠疫情确诊人数的增加, 政府政策和人们的行为也处在变化之中。基于这一假设和社会认知理论, 本文旨在从人们的旅游意愿角度探究新冠疫情对旅游业的影响。

本文所设计的变量和模型是在社会认知理论的基础之上提出的。本研究的数据来源于面向中国29个省市自治区的问卷调查。在剔除无效问卷后, 总共搜集618份有效问卷进行数据分析。本研究采用了结构方程模型, 对假设进行检验、并得出最终结论。

研究结果表明, 新冠疫情带来的负面影响会增加人们对疫情严重性的认知程度、疫情期间旅游给人带来的负面影响增大、正面影响减少, 从而最终影响人们的旅游意愿。在新冠疫情之下, 受到环境、个人因素的影响, 人们的旅游意愿显著降低。

本研究的数据均来源于中国, 所以将本文的结论应用于其他地区时, 由于不同地区的自然和社会环境差异, 结论可能会产生差异。本研究主要聚焦于人们旅游意愿的变化, 即旅游业的需求端, 来分析新冠疫情对旅游业的影响, 忽视了旅游业的供给端在新冠疫情期间对旅游业的影响分析。后续的研究可以考虑从旅游业供给端的变化进行分析、以及将样本数量扩大到全球范围, 从而可以从更广阔的视角来探究新冠疫情对旅游业的影响。

本研究定量分析了新冠疫情如何影响旅游业, 并利用社会认知理论建立模型来精确判断这一影响的可能机理。本文的发现有助于了解新冠疫情如何影响人们在疫情行期间旅行的意愿, 以及制定相关的应对措施。

El coronavirus (COVID-19) se descubrió desde finales de 2019 y luego se extendió gradualmente a todo el mundo, lo que tuvo un gran impacto en la vida de las personas. La propaganda del coronavirus ha provocado muchas restricciones en los viajes de las personas, por lo tanto, reducía la demanda de viaje de las personas. Con el aumento en el número de casos confirmados de COVID-19, las políticas gubernamentales y el comportamiento de las personas también se están cambiando. Basado en esta hipótesis y teoría cognitiva social, este artículo tiene como objetivo explorar el impacto del COVID-19 en el turismo desde la perspectiva de la disposición de las personas a viajar.

Las variables y modelos diseñados en este artículo se proponen sobre la base de la teoría cognitiva social. Los datos para este estudio provienen de las encuestas por cuestionario de 29 provincias, municipios y regiones autónomas de China. Después de excluir los cuestionarios no válidos, se recopilaron un total de 618 cuestionarios válidos para el análisis de datos. En este estudio, se utiliza el modelo de ecuación estructural y la prueba de la hipótesis, al final llegar a la conclusión.

El resultado de la investigación muestra que el impacto negativo del COVID-19 aumenta la conciencia de las personas sobre la gravedad de la epidemia, y el impacto negativo del turismo durante la epidemia se aumenta y el impacto positivo se disminuye, lo que al fianl afecta la disposición de las personas a viajar. Bajo el COVID-19, afectada por factores ambientales y personales, la disposición de las personas a viajar se ha reducido significativamente.

Los datos de este estudio son todos de China, por lo que cuando las conclusiones de este artículo se aplican a otras regiones, las conclusiones pueden diferir debido a las diferencias en los entornos naturales y sociales de diferentes regiones. Esta investigación se centra principalmente en el cambio del deseo de viajar de las personas, es decir, el lado de la demanda del turismo, para analizar el impacto del COVID-19, por eso ignora el análisis del impacto de la oferta turística en el turismo durante el COVID-19. Los estudios posteriores se pueden considerar desde el aspecto de analizar los cambios en el lado de la oferta del turismo y expandir el número de muestras a una escala global, por lo tanto, se puede explorar el impacto del COVID-19 desde una perspectiva más amplia.

El encuentro de este artículo ayuda a comprender cómo el COVID-19 afecta la disposición de las personas a viajar durante la epidemia y a formular medidas de respuesta relevantes.

Simulation-based optimisation (SO) is a popular optimisation approach for building and civil engineering construction planning. However, in the framework of SO, the simulation is continuously invoked during the optimisation trajectory, which increases the computational loads to levels unrealistic for timely construction decisions. Modification on the optimisation settings such as reducing searching ability is a popular method to address this challenge, but the quality measurement of the obtained optimal decisions, also termed as optimisation quality, is also reduced by this setting. Therefore, this study aims to develop an optimisation approach for construction planning that reduces the high computational loads of SO and provides reliable optimisation quality simultaneously.

This study proposes the optimisation approach by modifying the SO framework through establishing an embedded connection between simulation and optimisation technologies. This approach reduces the computational loads and ensures the optimisation quality associated with the conventional SO approach by accurately learning the knowledge from construction simulations using embedded ensemble learning algorithms, which automatically provides efficient and reliable fitness evaluations for optimisation iterations.

A large-scale project application shows that the proposed approach was able to reduce computational loads of SO by approximately 90%. Meanwhile, the proposed approach outperformed SO in terms of optimisation quality when the optimisation has limited searching ability.

The core contribution of this research is to provide an innovative method that improves efficiency and ensures effectiveness, simultaneously, of the well-known SO approach in construction applications. The proposed method is an alternative approach to SO that can run on standard computing platforms and support nearly real-time construction on-site decision-making.

The purpose of this paper is to investigate the dynamic forming process of the micro dent fabricated by laser shock processing on 2024-T3 aluminum alloy. The effect of laser pluse energy on the deformation of micro dent was also discussed in detail.

It uses finite element analysis method and the corresponding laser shocking experiment.

The results demonstrate that the dynamic formation process of micro dent lasts longer in comparison with the shock wave loading time, and the depths of micro dents increase with the increasing laser energy. In addition, laser shocking with higher energy can result in more obvious pileup occurred at the outer edge of micro dent.

Surface micro dents can serve as fluid reservoirs and traps of the wear debris, which can decrease the effects of the wear and friction in rolling and sliding interfaces. The investigations can not only be propitious to comprehensively understand the forming mechanism of laser-shocked dent, but also be beneficial to get sight into the residual stress field induced by laser shocking.

This paper aims to assess the aeroacoustic and aerodynamic performance of a morphing airfoil with a flexible trailing edge (FTE). The objective is to make a comparison of the aerodynamic noise characteristics between the conventional airfoil with a flap and morphing airfoil and analyse the noise reduction mechanisms of the morphing airfoil.

The computational fluid dynamic method was used to calculate the aerodynamic coefficients of morphing airfoil and the Ffowcs-Williams and Hawking’s acoustic analogy methods were performed to predict the far-field noise of different airfoils.

Results show that compared with the conventional airfoil, the morphing airfoil can generate higher lift and lower noise, but a greater drag. Additionally, the noise caused by the one-unit lift of the morphing airfoil is significantly lower than that of the conventional airfoil. For the morphing airfoil, the shedding vortex in the trailing edge was the main noise resource. As the angle of attack (AoA) increases, the overall sound pressure level of the morphing airfoil increases significantly. With the increase of the trailing edge deflection angle, the amplitude and the period of sound pressure of the morning airfoil fluctuation increase.

Presented results could be very useful during designing the morphing airfoil with FTE, which has significant advantages in aerodynamic efficiency and aeroacoustic performance.

This paper presents the aerodynamic and aeroacoustic characteristics of the morphing airfoil. The effect of trailing edge deflection angle and AoA on morphing airfoil was investigated. In the future, using a morphing airfoil instead of a traditional flap can reduce the aircraft`s fuel consumption and noise pollution.

There are particularly high fresh agricultural product (FAP) loss rates in actual supply chain operation and the development of FAPs e-commerce is hindered to some extent. The purpose of this paper is to achieve the coordination of three-layer FAP supply chain and maximize profit through the contracts among the supply chain members.

A three-layer FAP supply chain that consists of a fresh produce e-commerce enterprise, third-party logistics service provider (TPLSP) and community convenience store under e-commerce environment is considered. New game models are developed and optimal decisions in centralized and decentralized channel are characterized. Different contract coordination mechanisms are designed to improve the supply chain performance. Finally, computational studies are conducted.

The decentralized supply chain cannot be coordinated by a freshness-keeping cost-sharing contract, and it can be coordinated by a freshness-keeping cost-sharing and revenue-sharing contract. The optimal unit online selling price, unit logistics distribution price, fresh-keeping effort and unit self-collection service price can all be achieved.

The paper provides a practical guideline to managers in fresh produce industry in terms of how to cooperate with other supply chain members so as to maximize total profit and achieve Pareto improvement while also supply the freshest and safest produce to the target market under e-commerce environment.

Few studies have explored the coordination of three-layer FAP supply chain under e-commerce environment with TPLSP and community convenience store’s participation in decisions, especially considering that the market demand for FAPs is affected by freshness and unit online selling price. In this paper, all these scenarios are taken into account and corresponding mathematical models are developed. In particular, different contract coordination mechanisms are designed and examined simultaneously.

The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems for the design optimization and inspection process. The research may form the basis for a rational, comprehensive evaluation and provide the most effective way of improving the quality of management decision-making. It is of practical significance to improve the rationality and reliability of the index system and provide standardized, scientific reference standards and theoretical guidance for the design and construction of the index system.

Using modern methods such as complex networks and machine learning, a system for the quality diagnosis of index data and the classification and stratification of index systems is designed. This guarantees the quality of the index data, realizes the scientific classification and stratification of the index system, reduces the subjectivity and randomness of the design of the index system, enhances its objectivity and rationality and lays a solid foundation for the optimal design of the index system.

Based on the ideas of statistics, system theory, machine learning and data mining, the focus in the present research is on “data quality diagnosis” and “index classification and stratification” and clarifying the classification standards and data quality characteristics of index data; a data-quality diagnosis system of “data review – data cleaning – data conversion – data inspection” is established. Using a decision tree, explanatory structural model, cluster analysis, K-means clustering and other methods, classification and hierarchical method system of indicators is designed to reduce the redundancy of indicator data and improve the quality of the data used. Finally, the scientific and standardized classification and hierarchical design of the index system can be realized.

The innovative contributions and research value of the paper are reflected in three aspects. First, a method system for index data quality diagnosis is designed, and multi-source data fusion technology is adopted to ensure the quality of multi-source, heterogeneous and mixed-frequency data of the index system. The second is to design a systematic quality-inspection process for missing data based on the systematic thinking of the whole and the individual. Aiming at the accuracy, reliability, and feasibility of the patched data, a quality-inspection method of patched data based on inversion thought and a unified representation method of data fusion based on a tensor model are proposed. The third is to use the modern method of unsupervised learning to classify and stratify the index system, which reduces the subjectivity and randomness of the design of the index system and enhances its objectivity and rationality.

China has proposed two-stage goals of carbon peaking by 2030 and carbon neutralization by 2060. The carbon emission reduction effect of the power industry, especially the thermal power industry, will directly affect the progress of the goal. This paper aims to reveal the spatial-temporal characteristics and influencing factors of carbon emission efficiency of the thermal power industry and proposes policy suggestions for realizing China’s carbon peak and carbon neutralization goals.

This paper evaluates and compares the carbon emission efficiency of the thermal power industry in 29 provinces and regions in China from 2014 to 2019 based on the three-stage slacks-based measure (SBM) of efficiency in data envelopment analysis (DEA) model of undesired output, excluding the influence of environmental factors and random errors.

Empirical results show that during the sample period, the carbon emission efficiency of China’s thermal power industry shows a fluctuating upward trend, and the carbon emission efficiency varies greatly among the provincial regions. The carbon emission efficiency of the interregional thermal power industry presents a pattern of “eastern > central > western,” which is consistent with the level of regional economic development. Environmental factors such as economic level and environmental regulation level are conducive to the improvement of carbon emission efficiency of the thermal power industry, but the proportion of thermal power generation and industrial structure is the opposite.

This paper adopts the three-stage SBM–DEA model of undesired output and takes CO₂ as the undesired output to reveal the spatial-temporal characteristics and influencing factors of carbon emission efficiency in China’s thermal power industry. The results provide a more comprehensive perspective for regional comparative evaluation and influencing factors of carbon emission efficiency in China’s thermal power industry.