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Africa has the most deaths from infections yet lacks adequate capacity to engage in vaccine development, production and distribution, the cornerstone of efficiently managing and eliminating several infectious diseases. Research has scarcely explored the role of institutional logics in vaccine development, production and distribution, collectively known as end-to-end vaccine manufacturing. This study aims to explore how institutional logics influence firms to engage in the vaccine manufacturing value chain in Africa.

We conducted multiple case study research using five vaccine manufacturing firms from four African countries in three regions. Qualitative interviews were conducted among 18 executives in 5 vaccine manufacturing firms.

We identified that the state, corporate and market institutional logics disparately influence the different parts of the vaccine manufacturing value chain. These institutional logics co-exist in a constellation that also shapes the organizational forms. Their constellation has dominant logics that guide behavior, while subdominant and subordinate logics influence behavior to a limited extent. The findings show that institutional logics are a function of contextual factors, such as historical events, technological changes and pandemics.

The study developed a typology that identifies vaccine manufacturing firm archetypes, institutional logics and their constellations underpinned by contextual factors. The findings have implications for firms and policymakers, as they may guide the end-to-end vaccine manufacturing interventions adapted for their regions.

With the deep development of the new technological revolution and industrial transformation, the development, application, expansion and integration of digital technology provide opportunities for transforming the manufacturing industry from traditional manufacturing to intelligent manufacturing. However, little research currently focuses on analyzing the influencing factors of intelligent development in this field. There is a lack of research from the perspective of the digital innovation ecosystem to explore the intrinsic mechanism that drives intelligent development. Therefore, this article starts with high-end equipment manufacturing enterprises as the research subject to explore how their digital innovation ecosystem promotes the effectiveness of enterprise intelligent development, providing theoretical support and policy guidance for enterprises to achieve intelligent development at the current stage.

This article constructs a logical framework for the digital innovation ecosystem using a “three-layer core-periphery” structure, collects data using crawling for subsequent indicator measurement and assessment and uses the fuzzy set Qualitative Comparative Analysis method (fsQCA) to explore how the various components of the digital innovation ecosystem in high-end equipment manufacturing enterprises work together to promote the development of enterprise intelligently.

This article finds that the various components of the digital innovation ecosystem of high-end equipment manufacturing enterprises, through mutual coordination, can help improve the level of enterprise intelligence. Empirical analysis shows four specific configuration implementation paths for the digital innovation ecosystem of high-end equipment manufacturing enterprises to promote intelligent development. The core conditions and their combinations that affect the intelligent development of enterprises differ in each configuration path.

Firstly, this article discusses the practical problems of intelligent transformation and development in the manufacturing industry and focuses on the intelligent development effectiveness of various components of the digital innovation ecosystem of high-end equipment manufacturing enterprises in the context of digitalization. Secondly, this article uses crawling, text sentiment analysis and other methods to creatively collect relevant data to overcome the research dilemma of being limited to theoretical analysis due to the difficulty in obtaining data in this field. At the same time, based on the characteristics of high-end equipment manufacturing enterprises, the “three-layer core-periphery” digital innovation ecosystem framework constructed in this article helps to gain a deep understanding of the development characteristics of the industry's enterprises, provides specific indicator analysis for their intelligent development, opening the “black box” of intelligent development in the industry's enterprises and bridging the gap between theory and practice. Finally, this study uses the fsQCA research method of configuration analysis to explore the complexity of the antecedents and investigate the combined effects of multiple factors on intelligent development, providing new perspectives and rich research results for relevant literature on the intelligent development of high-end equipment manufacturing enterprises.

This paper aims to use redundant manipulators to solve the challenge of collision avoidance in construction operations such as welding and painting.

In this paper, a null-space-based task-priority adjustment approach is developed to avoid collisions. The method establishes the relative position of the obstacle and the robot arm by defining the “link space,” and then the priority of the collision avoidance task and the end-effector task is adjusted according to the relative position by introducing the null space task conversion factors.

Numerical simulations demonstrate that the proposed method can realize collision-free maneuvers for redundant manipulators and guarantee the tracking precision of the end-effector task. The experimental results show that the method can avoid dynamic obstacles in redundant manipulator welding tasks.

A new formula for task priority adjustment for collision avoidance of redundant manipulators is proposed, and the original task tracking accuracy is guaranteed under the premise of safety.

The paper has a twofold purpose: (1) to test the application of means-end theory to providers of hospitality goods and services, and (2) to explore this question in the context of winery tasting rooms when they had a unique opportunity to restructure their hospitality experience due to government restrictions in response to COVID.

A qualitative approach was adopted, and a convenience sample was used to conduct semi-structured laddering interviews. Forty interview transcripts were coded as means-end ladders, which were analyzed using a custom computer program to develop the implication matrix and the hierarchical value map.

This paper demonstrates that means-end is a useful approach to investigate the values and behaviors of the producer, specifically hospitality hosts. It finds that the principal goal of tasting rooms is to generate sales, and offering a compelling guest experience is the characteristic that contributes the most to achieving that goal. The staff and the atmosphere created for the guests are the two factors with the greatest influence on the guest experience.

This is the first paper to use means-end theory to study the hospitality host, or the producer of goods and services in general, and the first to study winery hospitality primarily through the lens of means-end theory. The study also helps fill a gap in research on tasting room sales focused on the winery’s goals.

The main purpose of this study was to evaluate the tensile strengths of JIS G3549 super high-strength steel strand wire ropes (1,570 MPa-class high-carbon steels) and wire rope open swaged socket connections at fire and post fire.

Steady-state tests from ambient temperature (20 °C) to 800 °C, transient-state tests under the allowable design tensile force and tensile tests in an ambient temperature environment after heating (heating temperatures of 200–800 °C) were conducted.

The tensile strengths of the wire rope and end-connection specimens at both fire and post fire were obtained. The steel wire rope specimens possessed larger reduction factors than general hot-rolled mild steels (JIS SS400) and high-strength steel bolts (JIS F10T). The end-connection specimens with sufficient socket lengths exhibited ductile fracture of the wire rope part at both fire and post fire; however, those with short socket lengths experienced a pull-out fracture at the socket.

The fundamental and important tensile test results of the super high-strength steel strand wire ropes (1,570 MPa-class high-carbon steels) and wire rope open swaged socket connections were accumulated at fire and post fire, and the fracture modes were clarified. The obtained test results contribute to fire resistance performance-based design of cable steel structures at fire and fire-damage investigations to consider their reusability post fire.

In response to the challenge of reduced efficiency or failure of robot motion planning algorithms when faced with end-effector constraints, this study aims to propose a new constraint method to improve the performance of the sampling-based planner.

In this work, a constraint method (TC method) based on the idea of cross-sampling is proposed. This method uses the tangent space in the workspace to approximate the constrained manifold pattern and projects the entire sampling process into the workspace for constraint correction. This method avoids the need for extensive computational work involving multiple iterations of the Jacobi inverse matrix in the configuration space and retains the sampling properties of the sampling-based algorithm.

Simulation results demonstrate that the performance of the planner when using the TC method under the end-effector constraint surpasses that of other methods. Physical experiments further confirm that the TC-Planner does not cause excessive constraint errors that might lead to task failure. Moreover, field tests conducted on robots underscore the effectiveness of the TC-Planner, and its excellent performance, thereby advancing the autonomy of robots in power-line connection tasks.

This paper proposes a new constraint method combined with the rapid-exploring random trees algorithm to generate collision-free trajectories that satisfy the constraints for a high-dimensional robotic system under end-effector constraints. In a series of simulation and experimental tests, the planner using the TC method under end-effector constraints efficiently performs. Tests on a power distribution live-line operation robot also show that the TC method can greatly aid the robot in completing operation tasks with end-effector constraints. This helps robots to perform tasks with complex end-effector constraints such as grinding and welding more efficiently and autonomously.

The purpose of this study is to investigate the mechanical properties of denim fabrics constructed from ring-spun and open-end rotor spun yarns.

Yarns of 10s Ne count using cotton fibers were spun using the ring and open-end rotor spinning technologies. The yarns were used to produce a denim fabric on an air-jet loom with a 3/1 twill weave structure. Mechanical tests – tensile strength, tear strength, abrasion resistance and pilling resistance – of denim fabrics were evaluated. The test results were analyzed using analysis of variance with the help of Software Package for Social Sciences.

Denim fabrics made by using ring-spun yarns exhibited better tensile and tear strength properties than denim fabrics made by using open-end rotor spun yarns. On the contrary, denim produced using open-end rotor yarns have better abrasion resistance, pilling resistance and air permeability than those produced using ring-spun yarns.

Both spinning techniques have a significant influence on the properties of denim fabrics. Whenever better tensile and tear strength is required, it is better to use ring-spun yarns, while if the requirement is better abrasion resistance and pilling resistance with high air permeability, then open-end rotor spun yarns shall be used.

This paper aims to facilitate the research and development of resilient navigation approaches, explore the robustness of adversarial training to different interferences and promote their practical applications in real complex environments.

In this paper, the authors first summarize the real accidents of self-driving cars and develop a set of methods to simulate challenging scenarios by introducing simulated disturbances and attacks into the input sensor data. Then a robust and transferable adversarial training approach is proposed to improve the performance and resilience of current navigation models, followed by a multi-modality fusion-based end-to-end navigation network to demonstrate real-world performance of the methods. In addition, an augmented self-driving simulator with designed evaluation metrics is built to evaluate navigation models.

Synthetical experiments in simulator demonstrate the robustness and transferability of the proposed adversarial training strategy. The simulation function flow can also be used for promoting any robust perception or navigation researches. Then a multi-modality fusion-based navigation framework is proposed as a light-weight model to evaluate the adversarial training method in real-world.

The adversarial training approach provides a transferable and robust enhancement for navigation models both in simulation and real-world.

Emergency service dispatchers perform a vital role in assisting callers by helping them through the emergency they are in and ensuring the delivery of first responders. If an emergency caller prematurely hangs up a call, before the arrival of first responders, it can impact a dispatcher’s ability to provide them with assistance. This paper aims to understand why staged callers, who are attempting to cover up a crime, and authentic callers hang up by identifying which linguistic and behavioural indicators occur prior to the end of a call.

A sample of 40 emergency calls (20 staged; 20 authentic) related to health and welfare emergencies were analysed with a temporal measure known as indicator waves. This provided a means to identify which indicators occurred above the level expected by chance near the end of authentic and staged calls.

The results of the current study show that the indicators that proceeded hanging up in authentic calls reflected the nature of the situation (e.g. nonurgency wherein the victim is deceased or is in a stable condition). Whereas the indicators that proceeded hanging up in staged calls focused on the “staging” aspect of the incident by accounting for forensic evidence that could be incriminating.

The identification of indicators that occur before the end of staged and authentic calls provides further insight into the differences between the two call types and offers opportunities for further research, potentially leading to application.

A main cause of defects within material extrusion (MatEx) additive manufacturing is the nonisothermal condition in the hot end, which causes inconsistent extrusion and polymer welding. This paper aims to validate a custom hot end design intended to heat the thermoplastic to form a melt prior to the nozzle and to reduce variability in melt temperature. A full 3D temperature verification methodology for hot ends is also presented.

Infrared (IR) thermography of steady-state extrusion for varying volumetric flow rates, hot end temperature setpoints and nozzle orifice diameters provides data for model validation. A finite-element model is used to predict the temperature of the extrudate. Model tuning demonstrates the effects of different model assumptions on the simulated melt temperature.

The experimental results show that the measured temperature and variance are functions of volumetric flow rate, temperature setpoint and the nozzle orifice diameter. Convection to the surrounding air is a primary heat transfer mechanism. The custom hot end brings the melt to its setpoint temperature prior to entering the nozzle.

This work provides a full set of steady-state IR thermography data for various parameter settings. It also provides insight into the performance of a custom hot end designed to improve the robustness of melting in MatEx. Finally, it proposes a strategy for modeling such systems that incorporates the metal components and the air around the system.