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The literature suggests that increasing the intensity of compensation incentives for corporate venture capital (CVC) managers can contribute to successful exits of direct CVCs. This study explores the impact of compensation incentives on the successful exits of indirect CVCs under different geographical distances between parent companies and indirect CVC managers.

The authors observed the compensation terms of CVC managers through investment announcements made by listed companies and used a probit regression model to test the hypotheses from a sample of 241 investment events with indirect CVCs in China.

The results show that if parent companies are geographically close to the managers of indirect CVCs, increasing the intensity of compensation incentives for managers will help the successful exit of indirect CVCs. However, if parent companies are not geographically close to indirect CVC managers, increasing the intensity of compensation incentives for managers will not promote the successful exit of indirect CVCs.

This study contributes significantly to the CVC literature. First, it sharpens our understanding of the differences in operational mechanisms between direct and indirect CVCs. Second, we find that the threshold returns of indirect CVC managers are non-negligible compensation incentives. Finally, the empirical evidence supports that in indirect CVC investments, the geographical distance between parent companies and managers is concerning because it affects whether compensation incentives contribute to the successful exit of indirect CVCs.

The purpose of this study was to examine the relationship between factors in the extended technology acceptance model (TAM) model and teachers' self-efficacy in remote teaching during the COVID-19 pandemic. In addition, the authors sought to listen to classroom teachers as they expressed their unbiased views of the advantages, disadvantages and challenges of teaching remotely during the COVID-19 pandemic.

A survey was employed to examine the relationship between factors in the extended TAM model and teachers' self-efficacy in remote teaching during the COVID-19 pandemic using the 49-item questionnaire. A multiple regression analysis using a stepwise procedure was used to examine the relationship between factors in the extended TAM model and teachers' self-efficacy. Three open-ended questions closely examined remote teaching during the pandemic, related to challenges, advantages and disadvantages.

Qualitative findings challenges included Internet connection, lack of interaction and communication and challenges with motivation and student engagement. Disadvantages included teachers’ level of self-efficacy in using technology to teach, lack of support and resources to teach online and the struggle to motivate and engage students. Perceived benefits included flexibility for the teacher and differentiation, rich resources and a way to support learners when in-person instruction is not possible.

The data suggest that instead, during COVID-19, many teachers were learning about the platforms simultaneously as they were instructing students.

To ensure quality remote instruction and that students receive the support to make instruction equitable, teachers need to perceive that their instructional technology needs are met to focus on teaching, learning and needs of their students.

Teachers need opportunities to explore the platforms and to experience success in this environment before they are exposed to the high stakes of preparing students to meet K-12 standards.

Instructional delivery has not explored teacher motivational and instructional teaching self-efficacy related to satisfaction with the learning management system (LMS).

This paper aims to improve the diversity and richness of haptic perception by recognizing multi-modal haptic images.

First, the multi-modal haptic data collected by BioTac sensors from different objects are pre-processed, and then combined into haptic images. Second, a multi-class and multi-label deep learning model is designed, which can simultaneously learn four haptic features (hardness, thermal conductivity, roughness and texture) from the haptic images, and recognize objects based on these features. The haptic images with different dimensions and modalities are provided for testing the recognition performance of this model.

The results imply that multi-modal data fusion has a better performance than single-modal data on tactile understanding, and the haptic images with larger dimension are conducive to more accurate haptic measurement.

The proposed method has important potential application in unknown environment perception, dexterous grasping manipulation and other intelligent robotics domains.

This paper proposes a new deep learning model for extracting multiple haptic features and recognizing objects from multi-modal haptic images.

This study aims to propose an enhanced eco-driving strategy based on reinforcement learning (RL) to alleviate the mileage anxiety of electric vehicles (EVs) in the connected environment.

In this paper, an enhanced eco-driving control strategy based on an advanced RL algorithm in hybrid action space (EEDC-HRL) is proposed for connected EVs. The EEDC-HRL simultaneously controls longitudinal velocity and lateral lane-changing maneuvers to achieve more potential eco-driving. Moreover, this study redesigns an all-purpose and efficient-training reward function with the aim to achieve energy-saving on the premise of ensuring other driving performance.

To illustrate the performance for the EEDC-HRL, the controlled EV was trained and tested in various traffic flow states. The experimental results demonstrate that the proposed technique can effectively improve energy efficiency, without sacrificing travel efficiency, comfort, safety and lane-changing performance in different traffic flow states.

In light of the aforementioned discussion, the contributions of this paper are two-fold. An enhanced eco-driving strategy based an advanced RL algorithm in hybrid action space (EEDC-HRL) is proposed to jointly optimize longitudinal velocity and lateral lane-changing for connected EVs. A full-scale reward function consisting of multiple sub-rewards with a safety control constraint is redesigned to achieve eco-driving while ensuring other driving performance.

Titanium alloys and composites have proven to contain desirable properties for use at elevated temperatures. One such material is the Ti750 composite, which can be used at temperatures up to 750°C for a brief period. This paper aims the microstructure, phase compositions, apparent porosity and hardness of both sintered and heat-treated TiC reinforced Ti750 composites for consideration in aircraft engine design.

The fabrication of TiC-reinforced Ti750 composites was achieved through spark plasma sintering (SPS). To analyze the microstructure and X-ray diffraction, a scanning electron microscope (SEM) with model number S-3400N and a D8 advance model machine were used, respectively. The microhardness of the samples was measured using a Vickers hardness tester with model HV-1000. The research incorporated three solid solution treatments: 975°C/3 h/AC, 1,010°C/3 h/AC and 1,025°C/3 h/AC, along with a solid-solution aging treatment at 1,010°C/3 h/AC + 750°C/8 h/AC. Additionally, oxidation analysis was conducted on the samples.

The microstructures contained enhanced TiC and Ti5Si3 phases in the near a-Ti matrix. The microhardness of the sintered composite was over twice that of the matrix alloy, and its porosity was reduced by about 0.35%. The sample treated at 1,010°C/3 h/AC had the highest enhanced peaks and microhardness of 1,277.1 HV. After oxidation at 800°C for 100 h, the accumulated weight of the solid solution composite at 1,010 °C/3 h/AC was the lowest (3.0 mg.cm^-2). The surface microstructure contained oxides of TiO2 and a spalling white area containing a small amount of Al₂O₃ and SiO₂.

There is limited research on Ti-Al-Sn-Zr-Mo-Si-based TMCs using a combination of the SPS method. This study used SiCp as a reinforcement for the Ti750 matrix alloy. The consolidation of SiCp and Ti750 powders using the SPS method, heat treatment of the resulting TiC reinforced Ti750 composites and study of the microstructure and properties of the composites are not found in literature or under consideration for publication in any media.

Managing archives using robots rather than people can considerably enhance efficiency, while need to modify the structure of archive shelves or installation tracks. This paper aims to develop a fully automated archive access robot without modification.

First, a mobile navigation chassis and a motion algorithm based on laser ranging and map matching are created for autonomous movement to any of the archives’ locations. Second, because the existing archives are stacked vertically, the bionic manipulator is made to mimic the movement of manual access to the archives, and it is attached to the robot arm’s end to access different layers of archives. In addition, an industrial camera is used to complete barcode identification of the archives and acquire data on their location and thickness. Finally, the archive bin is created to store archives.

The robot can move, identify and access multiple archival copies placed on floors 1–6 and 2–5 cm thick autonomously without modifying the archival repository or using auxiliary devices.

The robot is currently able to navigate, identify and access files placed on different levels. In the future, the speed of the robot’s navigation and the movement of the robot arm could be even faster, while the level of visualization of the robot could be further improved and made more intelligent.

The archive access robot developed by the authors makes it possible for robots to manage archives instead of human, while being cheaper and easier to deploy than existing robots, and has already been tested in the archive storage room of the State Grid maintenance branch in Jiangsu, China, with better results.

The all-in-one archive access robot can replace existing robotic access solutions, promote intelligent management of the archive industry and the construction of unmanned archive repositories and provide ideas for the development of robots for accessing book-like materials.

This study explores the use of robots to identify and access archives without changing archive shelves or installing auxiliary devices. In this way, the robot can be quickly applied to the storage room to improve the efficiency of archive management.

This paper aims to present a broad review of near-a titanium alloys for high-temperature applications.

Following a brief introduction of titanium (Ti) alloys, this paper considers the near-α group of Ti alloys, which are the most popular high-temperature Ti alloys developed for a high-temperature application, particularly in compressor disc and blades in aero-engines. The paper is relied on literature within the past decade to discuss phase stability and microstructural effect of alloying elements, plastic deformation and reinforcements used in the development of these alloys.

The near-a Ti alloys show high potential for high-temperature applications, and many researchers have explored the incorporation of TiC, TiB SiC, Y₂O₃, La₂O₃ and Al₂O₃ reinforcements for improved mechanical properties. Rolling, extrusion, forging and some severe plastic deformation (SPD) techniques, as well as heat treatment methods, have also been explored extensively. There is, however, a paucity of information on SiC, Y₂O₃ and carbon nanotube reinforcements and their combinations for improved mechanical properties. Information on some SPD techniques such as cyclic extrusion compression, multiaxial compression/forging and repeated corrugation and straightening for this class of alloys is also limited.

This paper provides a topical, technical insight into developments in near-a Ti alloys using literature from within the past decade. It also outlines the future developments of this class of Ti alloys.

In order to study whether far-infrared fabrics can be used as a garment for breast cancer patients, or as an adjuvant rehabilitation underwear for breast cancer patients after postoperative radiotherapy and chemotherapy, to eliminate tissue edema. To explore the effect of different far-infrared fabrics on the proliferation and invasion of breast cancer cells as a basic in vitro study.

Six kinds of fabrics of the same specification with different far-infrared nanoparticles were selected. MCF7 and Bcap37 breast cancer cells were used to study the effect of far-infrared fabrics on cell proliferation and invasion. Six kinds of far-infrared fabrics were used to culture breast cancer cells and explore their effects on breast cancer cell growth and the difference between different far-infrared fabrics.

It is found that the far-infrared emissivity of six kinds of fabrics are different, among which tea carbon fabric is the highest, followed by volcanic fabric, graphene fabric and biomass graphene fabric are the lowest. The results show that the far-infrared fabrics can significantly inhibit the proliferation and invasion of breast cancer cells, the higher the far-infrared emissivity is, and the longer the time of far-infrared radiation, the more significant the inhibition effect is.

Far-infrared fabrics can inhibit proliferation and invasion of breast cancer cells in vitro. Therefore, far-infrared fabrics can be used for adjuvant rehabilitation of breast cancer patients. This conclusion provides a basis for the application of far-infrared functional fabrics in the medical field. This conclusion provides a basis for the application of far-infrared functional fabrics in medical field.

This study examines the relationship between streamers' product descriptions, customer comments and online sales and focuses on the moderating effect of streamer–viewer relationship strength.

Between June 2021 and April 2022, the structured data of 965 livestreaming and unstructured text data of 42,956,147 characters from two major live-streaming platforms were collected for the study. Text analysis and regression analysis methods were employed for data analysis.

First, the authors' analysis reveals an inverted U-shaped relationship between comment length and product sales. Notably, comment volume and comment emotion positively influence product sales. Furthermore, the semantic richness, emotion and readability of streamers' product descriptions also positively influence product sales. Secondly, the authors find that the strength of streamer–viewer relationship weakens the positive effects of comment volume and comment emotion without moderating the inverted U-shaped effect of comment length. Lastly, the strength of streamer–viewer relationship also diminishes the positive effects of emotion, semantics and readability of streamers' product descriptions on product sales.

This study is the first to concurrently examine the direct and interactive effects of user-generated content (UGC) and marketer-generated content (MGC) on consumer purchase behaviors in livestreaming e-commerce, offering a novel perspective on individual decision-making and cue utilization in the social retail context.

The purpose of this paper is to improve the comfort and shaping function of seamless shapewear on the material and structure and develop new seamless shapewear products. The shaping figure effect will be verified as well.

The performance of the knitted fabrics made of Polytrimethylene terephthalate (PTT) filament was analyzed by orthogonal experiment and fuzzy mathematical methods analysis, in order to get the optimal conditions for the best performance. The new products were designed and made based on the results of the material research with the consideration of the aesthetic requirements. The shaping effect of seamless shapewears on local and global figure was tested by the methods of the combination of subjective and objective evaluation.

The sample which renders the optimal performance for shapewear is the one with PTT filament as face yarn, nylon core-spun yarn as ground yarn and 3+1 simulate rib knit structure. The material of face yarn, mixed proportion and structure can influence the shape retention, appearance and comfort of PTT fabric in various degrees. Three shapewears which were developed according to the results of material research have different shaping effect. And women with different figures put different satisfaction degrees on each shapewear’s shaping effect.

This paper provides scientific basis and reference for enterprise to design good tight seamless shapewear as well as for consumer to buy suitable products.

In the view of the problems of present shapewears, this paper completed the development of the shapewears and verified the shaping effect of them on women with different figures. The shapewears can be put into production directly.