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This study aims to investigate the effects of thermal buoyancy and flow incidence angles on mixed convection heat transfer and vortex-induced vibration (VIV) of an elastically mounted circular cylinder. The focus is on understanding how varying these parameters influences the vibration amplitudes in both the x and y directions and the overall heat transfer performance.

The research involves a numerical simulation of thermal fluid-structure interactions by integrating rigid-body motion equations with heat and fluid flow solvers. The cylinder operates at a lower temperature than the mainstream flow, and flow incidence angles range from 0° (opposing gravity) to 90° (perpendicular to gravity). The methodology is validated by comparing the results with established data on VIV for a cylinder vibrating in one direction under thermal buoyancy effects.

The study reveals that, without buoyancy (Ri = 0), increasing the flow angle from 0° to 90° decreases the vibration amplitude along the x-direction (A_x) while increasing it along the y-direction (A_y) across various reduced velocities (U_r). When buoyancy effects are introduced (Ri = −1), A_x peaks at specific U_r values depending on the flow angle, with significant variations observed. The maximum increase in A_x at Ri = −1 is over 15 times at U_r = 9 for a 0° angle, and A_y shows a more than 10-fold increase at U_r = 8 for a 30° angle. Additionally, adjusting the flow angle results in up to an 8% increase in the mean Nusselt number at Ri = −1.

This research provides novel insights into the combined effects of flow incidence angles and thermal buoyancy on VIV and heat transfer in an elastically mounted cylinder.

A real-time production scheduling method for semiconductor back-end manufacturing process becomes increasingly important in industry 4.0. Semiconductor back-end manufacturing process is always accompanied by order splitting and merging; besides, in each stage of the process, there are always multiple machine groups that have different production capabilities and capacities. This paper studies a multi-agent based scheduling architecture for the radio frequency identification (RFID)-enabled semiconductor back-end shopfloor, which integrates not only manufacturing resources but also human factors.

The architecture includes a task management (TM) agent, a staff instruction (SI) agent, a task scheduling (TS) agent, an information management center (IMC), machine group (MG) agent and a production monitoring (PM) agent. Then, based on the architecture, the authors developed a scheduling method consisting of capability & capacity planning and machine configuration modules in the TS agent.

The authors used greedy policy to assign each order to the appropriate machine groups based on the real-time utilization ration of each MG in the capability & capacity (C&C) planning module, and used a partial swarm optimization (PSO) algorithm to schedule each splitting job to the identified machine based on the C&C planning results. At last, we conducted a case study to demonstrate the proposed multi-agent based real-time production scheduling models and methods.

This paper proposes a multi-agent based real-time scheduling framework for semiconductor back-end industry. A C&C planning and a machine configuration algorithm are developed, respectively. The paper provides a feasible solution for semiconductor back-end manufacturing process to realize real-time scheduling.

This study aims to explore an active control strategy for attenuation of in-line and transverse flow-induced vibration (FIV) of two tandem-arranged circular cylinders.

The control system is based on the rotary oscillation of cylinders around their axis, which acts according to the lift coefficient feedback signal. The fluid-solid interaction simulations are performed for two velocity ratios (V_r = 5.5 and 7.5), three spacing ratios (L/D = 3.5, 5.5 and 7.5) and three different control cases. Cases 1 and 2, respectively, deal with the effect of rotary oscillation of front and rear cylinders, while Case 3 considers the effect of applied rotary oscillation to both cylinders.

The results show that in Case 3, the FIV of both cylinders is perfectly reduced, while in Case 2, only the vibration of rear cylinder is mitigated and no change is observed in the vortex-induced vibration of front cylinder. In Case 1, by rotary oscillation of the front cylinder, depending on the reduced velocity and the spacing ratio values, the transverse oscillation amplitude of the rear cylinder suppresses, remains unchanged and even increases under certain conditions. Hence, at every spacing ratio and reduced velocity, an independent controller system for each cylinder is necessary to guarantee a perfect vibration reduction of front and rear cylinders.

The current manuscript seeks to deploy a type of active rotary oscillating (ARO) controller to attenuate the FIV of two tandem-arranged cylinders placed on elastic supports. Three different cases are considered so as to understand the interaction of these cylinders regarding the rotary oscillation.

This study aims to numerically explore the heat transfer characteristics in turbulent two-degree-of-freedom vortex-induced vibrations (VIVs) of three elastically mounted circular cylinders.

The cylinders are at the vertices of an isosceles triangle with a base and height that are the same. The finite volume technique is used to calculate the Reynolds-averaged governing equations, whereas the structural dynamics equations are solved using the explicit integration method. Simulations are performed for three different configurations, constant mass ratio and natural frequency, as well as distinct reduced velocity values.

As a numerical challenge, the super upper branch observed in the experiment is well-captured by the current numerical simulations. According to the computation findings, the vortex-shedding around the cylinders increases flow mixing and turbulence, hence enhancing heat transfer. At most reduced velocities, the Nusselt number of downstream cylinders is greater than that of upstream cylinders due to the impact of wake-induced vibration, and the maximum heat transfer improvement of these cylinders is 21% (at U_r = 16), 23% (at U_r = 5) and 20% (at U_r = 15) in the first, second and third configurations, respectively.

The main novelty of this study is inspecting the thermal behavior and turbulent flow–induced vibration of three circular cylinders in the triangular arrangement.

The motivation behind this research refers to the significant role of integration of production-distribution plans in effective performance of supply chain networks under fierce competition of today’s global marketplace. In this regard, this paper aims to deal with an integrated production-distribution planning problem in deterministic, multi-product and multi-echelon supply chain network. The bi-objective mixed-integer linear programming model is constructed to minimize not only the total transportation costs but also the total delivery time of supply chain, subject to satisfying retailer demands and capacity constraints where quantity discount on transportation costs, fixed cost associated with transportation vehicles usage and routing decisions have been included in the model.

As the proposed mathematical model is NP-hard and that finding an optimum solution in polynomial time is not reasonable, two multi-objective meta-heuristic algorithms, namely, non-dominated sorting genetic algorithm II (NSGAII) and multi-objective imperialist competitive algorithm (MOICA) are designed to obtain near optimal solutions for real-sized problems in reasonable computational times. The Taguchi method is then used to adjust the parameters of the developed algorithms. Finally, the applicability of the proposed model and the performance of the solution methodologies in comparison with each other are demonstrated for a set of randomly generated problem instances.

The practicality and applicability of the proposed model and the efficiency and efficacy of the developed solution methodologies were illustrated through a set of randomly generated real-sized problem instances. Result. In terms of two measures, the objective function value and the computational time were required to get solutions.

The main contribution of the present work was addressing an integrated production-distribution planning problem in a broader view, by proposing a closer to reality mathematical formulation which considers some real-world constraints simultaneously and accompanied by efficient multi-objective meta-heuristic algorithms to provide effective solutions for practical problem sizes.

This article reports on a national project being developed by the Royal National Institute of the Blind. It is aimed at improving health and social care for older people with sight problems, by focusing on some of the standards of the National Service Framework for older people and applying them to older people with sight problems. The project will identify, develop and disseminate good practice by establishing two pilot sites and conducting desk research.

Rapid prototyping (RP) technology is widely used in many fields in recent years. Bone tissue engineering (TE) is an interdisciplinary field involving life sciences, engineering and materials science. Hydroxyapatite (HAp) are similar to natural bone and it has been extensively studied due to its excellent biocompatibility and osteoconductivity. This paper aims to review nanoscaled HAp-based scaffolds with high porosity fabricated by various RP methods for bone regeneration.

The review focused on the fabrication methods of HAp composite scaffolds through RP techniques. The paper summarized the evaluation of these scaffolds on the basis of their biocompatibility and biodegradability through in vitro and in vivo tests. Finally, a summary and perspectives on this active area of research are provided.

HAp composite scaffold fabricated by RP methods has been widely used in bone TE and it has been deeply studied by researchers during the past two decades. However, its brittleness and difficulty in processing have largely limited its wide application in TE. Therefore, the formability of HAp combined with biocompatible organic materials and fabrication techniques could be effectively enhanced, and it can be used in bone TE applications finally.

This review paper presented a comprehensive study of the various types of HAp composite scaffold fabricated by RP technologies and introduced their potential application in bone TE, as well as future roadmap and perspective.

Higher education plays an essential role in achieving the United Nations sustainable development goals (SDGs). However, there are only scattered studies on monitoring how universities promote SDGs through their curriculum. The purpose of this study is to investigate the connection of existing common core courses in a university to SDG education. In particular, this study wanted to know how common core courses can be classified by machine-learning approach according to SDGs.

In this report, the authors used machine learning techniques to tag the 166 common core courses in a university with SDGs and then analyzed the results based on visualizations. The training data set comes from the OSDG public community data set which the community had verified. Meanwhile, key descriptions of common core courses had been used for the classification. The study used the multinomial logistic regression algorithm for the classification. Descriptive analysis at course-level, theme-level and curriculum-level had been included to illustrate the proposed approach’s functions.

The results indicate that the machine-learning classification approach can significantly accelerate the SDG classification of courses. However, currently, it cannot replace human classification due to the complexity of the problem and the lack of relevant training data.

The study can achieve a more accurate model training through adopting advanced machine learning algorithms (e.g. deep learning, multioutput multiclass machine learning algorithms); developing a more effective test data set by extracting more relevant information from syllabus and learning materials; expanding the training data set of SDGs that currently have insufficient records (e.g. SDG 12); and replacing the existing training data set from OSDG by authentic education-related documents (such as course syllabus) with SDG classifications. The performance of the algorithm should also be compared to other computer-based and human-based SDG classification approaches for cross-checking the results, with a systematic evaluation framework. Furthermore, the study can be analyzed by circulating results to students and understanding how they would interpret and use the results for choosing courses for studying. Furthermore, the study mainly focused on the classification of topics that are taught in courses but cannot measure the effectiveness of adopted pedagogies, assessment strategies and competency development strategies in courses. The study can also conduct analysis based on assessment tasks and rubrics of courses to see whether the assessment tasks can help students understand and take action on SDGs.

The proposed approach explores the possibility of using machine learning for SDG classifications in scale.

The complexity of projects has become a serious issue and obstacle in their successful completion. In order to overcome these complexities, it has become imperative to identify the relevant management competencies of project managers. The purpose of this paper is to address the problem of cost, time and scope in engineering infrastructure projects due to their complexities through management competencies.

In the first phase of the study, 32 experts were interviewed through semi-structured pre-tested questionnaire. In this phase, essential elements of complexities were identified initially. This was followed by finding required dimensions of competencies to counter these complexities and to acquire improved performance. In the final stage, required levels of competencies for specific elements of complexity were identified. In the second phase, 85 “project managers” were also approached to get feedback about their recently completed public sector engineering infrastructure projects in Pakistan.

The study identified additional dimensions, i.e. honesty, enthusiasm and dedication, in the case of competencies and adverse law and order situation, political instability, land issues, energy crisis and weak authorization of project managers in the case of complexities. Leadership, management skill, communication skill, effectiveness and result orientation were identified as top quality traits required. The study concluded that there is a significant impact of management competencies and complexities on project performance.

The study contributes to a better understanding of how to improve performance in complex engineering infrastructure projects through adopting management competencies. It also empirically illustrates the relations among project management competencies, complexities and project performance. Although the research is grounded on public sector infrastructure projects, its findings may also be helpful for practices in project management of other sectors.

The purpose of this paper is to develop a new method for biomolecular recognition based on light scattering of ZnS:Mn nano‐particle functionalised with biotin.

ZnS:Mn nano‐particles was successfully synthesised from quaternary water‐in‐oil micro‐emulsion system. The addition of biotin and the subsequent specific binding events alter the dielectric environment of the nano‐particle, resulting in a spectral shift of the particle plasmon resonance. Cyclohexane was used as oil, Triten X‐100 as surfactant, n‐hexanol as a co‐surfactant and mercaptoethanol for the best linking of biological part to nano‐particle. Measurement of the content of avidin was achieved by detecting the Department of Biomedical Engineering change in the excited emission. For qualitative and quantitative analyses of this product, scanning electron microscopy, transmission electron microscopy, energy dispersive X‐ray spectroscopy and spectrograph techniques were used.

It was observed that with reducing particle size, emission shifted to the lower wave lengths. In addition, with conjugation between avidin and biotin by mercaptoethanol in biologic media, spectral emission decreased.

The method developed could be utilised for synthesis of a variety of ZnS:Mn nano‐particles for a wide range of diagnostic applications.

The method for biomolecular recognition based on light scattering of ZnS:Mn nano‐particle functionalised with biotin developed was novel.