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Accurate and automatic clothing pattern making is very important in personalized clothing customization and virtual fitting room applications. Clothing pattern generating as well as virtual clothing simulation is an attractive research issue both in clothing industry and computer graphics.

Physics-based method is an effective way to model dynamic process and generate realistic clothing animation. Due to conceptual simplicity and computational speed, mass-spring model is frequently used to simulate deformable and soft objects follow the natural physical rules. We present a physics-based clothing pattern generating framework by using scanned human body model. After giving a scanned human body model, first, we extract feature points, planes and curves on the 3D model by geometric analysis, and then, we construct a remeshed surface which has been formatted to connected quad meshes. Second, for each clothing piece in 3D, we construct a mass-spring model with same topological structures, and conduct a typical time integration algorithm to the mass-spring model. Finally, we get the convergent clothing pieces in 2D of all clothing parts, and we reconnected parts which are adjacent on 3D model to generate the basic clothing pattern.

The results show that the presented method is a feasible way for clothing pattern generating by use of scanned human body model.

The main contribution of this work is twofold: one is the geometric algorithm to scanned human body model, which is specially conducted for clothing pattern design to extract feature points, planes and curves. This is the crucial base for suit clothing pattern generating. Another is the physics-based pattern generating algorithm which flattens the 3D shape to 2D shape of cloth pattern pieces.

This papers aims to study lattice structures in terms of geometric variables, manufacturing variables and material-based variants and their correlation with compressive behaviour for their application in a methodology for the design and development of personalized elastic therapeutic products.

Lattice samples were designed and manufactured using extrusion-based additive manufacturing technologies. Mechanical tests were carried out on lattice samples for elasticity characterization purposes. The relationships between sample stiffness and key geometric and manufacturing variables were subsequently used in the case study on the design of a pressure cushion model for validation purposes. Differentiated areas were established according to patient’s pressure map to subsequently make a correlation between the patient’s pressure needs and lattice samples stiffness.

A substantial and wide variation in lattice compressive behaviour was found depending on the key study variables. The proposed methodology made it possible to efficiently identify and adjust the pressure of the different areas of the product to adapt them to the elastic needs of the patient. In this sense, the characterization lattice samples turned out to provide an effective and flexible response to the pressure requirements.

This study provides a generalized foundation of lattice structural design and adjustable stiffness in application of pressure cushions, which can be equally applied to other designs with similar purposes. The relevance and contribution of this work lie in the proposed methodology for the design of personalized therapeutic products based on the use of individual lattice structures that function as independent customizable cells.

This paper addresses a significant research gap in the study of Rayleigh surface wave propagation within a piezoelectric medium characterized by piezoelectric properties, thermal effects and voids. Previous research has often overlooked the crucial aspects related to voids. This study aims to provide analytical solutions for Rayleigh waves propagating through a medium consisting of a nonlocal piezo-thermo-elastic material with voids under the Moore–Gibson–Thompson thermo-elasticity theory with memory dependencies.

The analytical solutions are derived using a wave-mode method, and roots are computed from the characteristic equation using the Durand–Kerner method. These roots are then filtered based on the decay condition of surface waves. The analysis pertains to a medium subjected to stress-free and isothermal boundary conditions.

Computational simulations are performed to determine the attenuation coefficient and phase velocity of Rayleigh waves. This investigation goes beyond mere calculations and examines particle motion to gain deeper insights into Rayleigh wave propagation. Furthermore, this investigates how kernel function and nonlocal parameters influence these wave phenomena.

The results of this study reveal several unique cases that significantly contribute to the understanding of Rayleigh wave propagation within this intricate material system, particularly in the presence of voids.

This investigation provides valuable insights into the synergistic dynamics among piezoelectric constituents, void structures and Rayleigh wave propagation, enabling advancements in sensor technology, augmented energy harvesting methodologies and pioneering seismic monitoring approaches.

This study formulates a novel governing equation for a nonlocal piezo-thermo-elastic medium with voids, highlighting the significance of Rayleigh waves and investigating the impact of memory.

The purpose is to explore the free vibration behaviour of elastic foundation-supported porous functionally graded nanoplates using the Rayleigh-Ritz approach. The goal of this study is to gain a better knowledge of the dynamic response of nanoscale structures made of functionally graded materials and porous features. The Rayleigh-Ritz approach is used in this study to generate realistic mathematical models that take elastic foundation support into account. This research can contribute to the design and optimization of advanced nanomaterials with potential applications in engineering and technology by providing insights into the influence of material composition, porosity and foundation support on the vibrational properties of nanoplates.

A systematic methodology is proposed to evaluate the free vibration characteristics of elastic foundation-supported porous functionally graded nanoplates using the Rayleigh-Ritz approach. The study began by developing the mathematical model, adding material properties and establishing governing equations using the Rayleigh-Ritz approach. Numerical approaches to solve the problem are used, using finite element methods. The results are compared to current solutions or experimental data to validate the process. The results are also analysed, keeping the influence of factors on vibration characteristics in mind. The findings are summarized and avenues for future research are suggested, ensuring a robust investigation within the constraints.

The Rayleigh-Ritz technique is used to investigate the free vibration properties of elastic foundation-supported porous functionally graded nanoplates. The findings show that differences in material composition, porosity and foundation support have a significant impact on the vibrational behaviour of nanoplates. The Rayleigh-Ritz approach is good at modelling and predicting these properties. Furthermore, the study emphasizes the possibility of customizing nanoplate qualities to optimize certain vibrational responses, providing useful insights for engineering applications. These findings expand understanding of dynamic behaviours in nanoscale structures, making it easier to build innovative materials with specific features for a wide range of industrial applications.

The novel aspect of this research is the incorporation of elastic foundation support, porous structures and functionally graded materials into the setting of nanoplate free vibrations, utilizing the Rayleigh-Ritz technique. Few research have looked into this complex combo. By tackling complicated interactions, the research pushes boundaries, providing a unique insight into the dynamic behaviour of nanoscale objects. This novel approach allows for a better understanding of the interconnected effects of material composition, porosity and foundation support on free vibrations, paving the way for the development of tailored nanomaterials with specific vibrational properties for advanced engineering and technology applications.

Stereolithography (SLA) additive manufacturing (AM) technique has enabled the production of inconspicuous and aesthetically pleasing orthodontics that are also hygienic. However, the staircase effect poses a challenge to the application of invisible orthodontics in the dental industry. The purpose of this study is to implement chemical postprocessing technique by using isopropyl alcohol as a solvent to overcome this challenge.

Fifteen experiments were conducted using a D-optimal design to investigate the effect of different concentrations and postprocessing times on the surface roughness, material removal rate (MRR), hardness and cost of SLA dental parts required for creating a clear customized aligner, and a container was constructed for chemical treatment of these parts made from photocurable resin.

The study revealed that the chemical postprocessing technique can significantly improve the surface roughness of dental SLA parts, but improper selection of concentration and time can lead to poor surface roughness. The optimal surface roughness was achieved with a concentration of 90 and a time of 37.5. Moreover, the dental part with the lowest concentration and time (60% and 15 min, respectively) had the lowest MRR and the highest hardness. The part with the highest concentration and time required the greatest budget allocation. Finally, the results of the multiobjective optimization analysis aligned with the experimental data.

This paper sheds light on a previously underestimated aspect, which is the pivotal role of chemical postprocessing in mitigating the adverse impact of stair case effect. This nuanced perspective contributes to the broader discourse on AM methodologies, establishing a novel pathway for advancing the capabilities of SLA in dental application.

Concrete, the second most used material in the world, surpassed only by water, relies on a vast amount of cement. The process of cement production emits substantial amounts of carbon dioxide (CO₂). Consequently, it is crucial to search for cement alternatives. Geopolymer concrete (GC) uses industrial by-product material instead of traditional cement, which not only reduces CO₂ emissions but also enhances concrete durability. On the other hand, the disposal of concrete waste in the landfills represents a significant environmental challenge, emphasising the urgent need for sustainable solutions. This study aimed to investigate waste concrete's best form and rate as the alternative aggregates in self-compacting and ambient-cured GC to preserve natural resources, reduce construction and demolition waste and decrease pertinent CO₂ emissions. The binding material employed in this research encompasses fly ash, slag, micro fly ash and anhydrous sodium metasilicate as an alkali activator. It also introduces the best treatment method to improve the recycled concrete aggregate (RCA) quality.

A total of25%, 50% and 100% of coarse aggregates are replaced with RCAs to cast self-compacting geopolymer concrete (SCGC) and assess the impact of RCA on the fresh, hardened and water absorption properties of the ambient-cured GC. Geopolymer slurry was used for coating RCAs and the authors examined the effect of one-day and seven-day cured coated RCA. The mechanical properties (compressive strength, splitting tensile strength and modulus of elasticity), rheological properties (slump flow, T500 and J-ring) and total water absorption of RCA-based SCGC were studied. The microstructural and chemical compositions of the concrete mixes were studied by the methods of energy dispersive X-Ray and scanning electron microscopy.

It is evident from the test observations that 100% replacement of natural aggregate with coated RCA using geopolymer slurry containing fly ash, slag, micro fly ash and anhydrous sodium metasilicate cured for one day before mixing enhances the concrete's quality and complies with the flowability requirements. Assessment is based on the fresh and hardened properties of the SCGC with various RCA contents and coating periods. The fresh properties of the mix with a seven-day curing time for coated RCA did not meet the requirements for self-compacting concrete, while this mix demonstrated better compressive strength (31.61 MPa) and modulus of elasticity (15.39 GPa) compared to 29.36 MPa and 9.8 GPa, respectively, for the mix with one-day cured coated RCA. However, incorporating one-day-cured coated RCA in SCGC demonstrated better splitting tensile strength (2.32 MPa) and water absorption (15.16%).

A potential limitation of this study on SCGC with coated RCAs is the focus on the short-term behaviour of this concrete. This limited time frame may not meet the long-term requirements for ensuring the sustained durability of the structures throughout their service life.

This paper highlights the treatment technique of coating RCA with geopolymer slurry for casting SCGC.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

This empirical study uncovers emotional sensemaking factors that cause changes in management perceptions about wicked strategic problems under dynamic complexity. These perception changes improve understanding of, and solutions to, the wicked problem.

Senior managers from three large organizations in different sectors participated in gaming simulation workshops. The strategic issues at stake were intractable and divisive. Qualitative methods captured participants' perceptions of the problems and the dynamic complexity that they faced and how they changed.

Flawed management perceptions were revised as sensemaking processes were catalyzed by emotions of shock/surprise that came from experiencing unexpected stakeholder conduct within a simulation. The plausibility of the conduct was strengthened because managers were role-playing stakeholders. The shock/surprise emotion uncoupled attachment to entrenched beliefs, leading to a willingness to revise the flawed perceptions. The changed perceptions created new insights for a solution to the wicked problem.

Practical implications are how management practitioners can improve the tackling of wicked strategic problems through the use of shock and surprise in a gaming simulation.

This research extends theory on the role of emotions in sensemaking under dynamic complexity. The authors uncover how a hierarchy of managers' emotions used in sensemaking explains the catalytic effect of the shock and surprise of unexpected stakeholder conduct on revisions to their perceptions of the outcomes of the dynamic complexity.

The use of recycled coarse aggregate in concrete structures promotes environmental sustainability; however, performance of these structures might be negatively impacted when it is used as a replacement to traditional aggregate. This paper aims to simulate recycled concrete beams strengthened with carbon fiber-reinforced polymer (CFRP), to advance the modeling and use of recycled concrete structures.

To investigate the performance of beams with recycled coarse aggregate concrete (RCAC), finite element models (FEMs) were developed to simulate 12 preloaded RCAC beams, strengthened with two CFRP strengthening schemes. Details of the modeling are provided including the material models, boundary conditions, applied loads, analysis solver, mesh analysis and computational efficiency.

Using FEM, a parametric study was carried out to assess the influence of CFRP thickness on the strengthening efficiency. The FEM provided results in good agreement with those from the experiments with differences and standard deviation not exceeding 11.1% and 3.1%, respectively. It was found that increasing the CFRP laminate thickness improved the load-carrying capacity of the strengthened beams.

The developed models simulate the preloading and loading up to failure with/without CFRP strengthening for the investigated beams. Moreover, the models were validated against the experimental results of 12 beams in terms of crack pattern as well as load, deflection and strain.

In recent decades, the field of robotic mapping has witnessed widespread research and development in light detection and ranging (LiDAR)-based simultaneous localization and mapping (SLAM) techniques. This paper aims to provide a significant reference for researchers and engineers in robotic mapping.

This paper focused on the research state of LiDAR-based SLAM for robotic mapping as well as a literature survey from the perspective of various LiDAR types and configurations.

This paper conducted a comprehensive literature review of the LiDAR-based SLAM system based on three distinct LiDAR forms and configurations. The authors concluded that multi-robot collaborative mapping and multi-source fusion SLAM systems based on 3D LiDAR with deep learning will be new trends in the future.

To the best of the authors’ knowledge, this is the first thorough survey of robotic mapping from the perspective of various LiDAR types and configurations. It can serve as a theoretical and practical guide for the advancement of academic and industrial robot mapping.