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Advanced composites with superior wave attenuation or vibration isolation capacity are in high demand in engineering practice. In this study, we develop the hybrid dynamic shear-lag model with Bloch's theorem to investigate the hybrid effect of reinforcement on wave attenuation in bioinspired staggered composites. We present for the first time the relationship between macroscopic wave filtering and hybridization of building blocks in staggered composites. Viscoelasticity was taken into account for both reinforcement and matrix to reflect the damping effect on wave transmission. Our findings indicate that reinforcement hybridization significantly enhances wave attenuation performance through two critical parameters: the linear stiffness and linear density of reinforcements. For purely elastic constituents, reinforcement hybridization consistently improves wave attenuation by reducing the initial frequency of the first bandgap and broadening it. For viscoelastic constituents, increasing the heterogeneity of reinforcements can benefit wave attenuation, particularly in ultralow frequency regimes, due to the strengthening of the damping effect. Our case study demonstrates that controlling the difference in linear density can result in up to a 59 % reduction in energy transmission. Our analysis suggests that hybridizing reinforcements could provide a new approach to designing and synthesizing advanced composites with exceptional wave attenuation performance., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Acoustic cavitation, an intriguing phenomenon resulting from the interaction of sound waves with a liquid medium, has emerged as a promising avenue in agri-food processing, offering opportunities to enhance established processes improving primary production of ingredients and further food processing. This comprehensive review provides an in-depth analysis of the mechanisms, design considerations, challenges and scale-up strategies associated with acoustic cavitation for agri-food applications. The paper starts by elucidating the fundamental principles of acoustic cavitation and its measurement, delving then into the diverse effects of different parameters associated with, the acoustic wave, mechanical design and operation of the ultrasonic system, along with those related to the food matrix. The technological advancements achieved in the design and set-up of ultrasonic reactors addressing limitations during scale up are also discussed. The design, engineering and mathematical modelling of ultrasonic equipment tailored for agri-food applications are explored, along with strategies to maximize cavitation intensity and efficiency in the application of brining, freezing, drying, emulsification, filtration and extraction. Advanced US equipment, such as multi-transducers (tubular resonator, FLOW:WAVE®) and larger processing surface areas through innovative designing (Barbell horn, CascatrodesTM), are one of the most promising strategies to ensure consistency of US operations at industrial scale. This review paper aims to provide valuable insights into harnessing acoustic cavitation's potential for up-scaling applications in food processing via critical examination of current research and advancements, while identifying future directions and opportunities for further research and innovation.

Summary: Basketball, as one of the most popular sports in the world, has millions of followers and massive economic value. Basketball evolves so fast that it requires teams with smarter strategies, better skills, and stronger players. However, the competition strategies and training methods in basketball are still experience-based, lacking precise data to drive for more efficient training and strategies. On the other hand, flexible sensors, as a new class of sensors, have been a hotspot for scientific research and widely applied in various fields. Due to their excellent characteristics of flexibility, wearing comfort, convenience, and response speed, integrating flexible sensors into basketball has the potential to greatly promote all aspects of the sport. This paper aims to bring more fusion between basketball and flexible sensors. In this perspective, we first perform a review of the history of sensing technologies in the basketball sport and discuss mechanisms of flexible sensors applied on basketball players. Then specific scenarios for flexible sensors applied in basketball were elaborated on in detail. Finally, we envision the potential applications of flexible sensors in basketball and present our views on future development directions. We hope this paper can depict how flexible sensing technology is integrated into basketball systems and point out the future development of basketball with the help of flexible sensors.

Summary: In this paper, we review, compare, and analyze previous studies on agricultural machinery automatic navigation and path planning technologies. First, the paper introduces the fundamental components of agricultural machinery autonomous driving, including automatic navigation, path planning, control systems, and communication modules. Generally, the methods for automatic navigation technology can be divided into three categories: Global Navigation Satellite System (GNSS), Machine Vision, and Laser Radar. The structures, advantages, and disadvantages of different methods and the technical difficulties of current research are summarized and compared. At present, the more successful way is to use GNSS combined with machine vision to provide guarantee for agricultural machinery to avoid obstacles and generate the optimal path. Then the path planning methods are described, including four path planning algorithms based on graph search, sampling, optimization, and learning. This paper proposes 22 available algorithms according to different application scenarios and summarizes the challenges and difficulties that have not been completely solved in the current research. Finally, some suggestions on the difficulties arising in these studies are proposed for further research.

In this paper, we consider the evolution of a new probability distribution called the exponential flexible Weibull distribution. The proposed exponential flexible Weibull distribution is obtained by combining the flexible Weibull extension with the exponential T-X strategy. For the exponential flexible Weibull, the estimators of the model parameters are derived mathematically. The appraisal of these parameters is accomplished through a simulation study. The applicability and virtuoso of the exponential flexible Weibull distribution are exemplified via two data sets. Furthermore, we implement the state-of-the-art deep learning algorithms, specifically Artificial Neural Networks and Extreme Gradient Boosting, which are widely employed in real-world applications. A comprehensive comparative analysis is conducted to assess the relative performance of these methodologies.

Summary: This paper presents a multidisciplinary analysis of the Fukushima Dai-ichi Nuclear Power Plant accident. Along with the latest observations and simulation studies, we synthesize the time-series and event progressions during the accident across multiple disciplines, including in-plant physics and engineering systems, operators’ actions, emergency responses, meteorology, radionuclide release and transport, land contamination, and health impacts. We identify three key factors that exacerbated the consequences of the accident: (1) the failure of Unit 2 containment venting, (2) the insufficient integration of radiation measurements and meteorology data in the evacuation strategy, and (3) the limited risk assessment and emergency preparedness. We conclude with new research and development directions to improve the resilience of nuclear energy systems and communities, including (1) meteorology-informed proactive venting, (2) machine learning-enabled adaptive evacuation zones, and (3) comprehensive risk-informed emergency planning while leveraging the experience from responses to other disasters.

Summary: Marine activities typically face various risk factors such as marine animal attacks or unexpected collisions. In this paper, we develop underwater smart glasses (USGs) based on visual-tactile fusion for underwater hazard detection in real-time, ensuring operational safety. The proposed USG is composed of the vision module by artificial intelligence (AI)-enabled optical sensing and the tactile module by triboelectric metamaterials-enabled mechanical sensing. The vision module is obtained based on the underwater target detection algorithm you only look once-underwater hazard (YOLO-UH) developed by the dataset to detect toxic marine organisms in the visual field. The tactile module is designed with the kirigami tribo-materials (KTMs) to sensitively detect and warn of collisions outside the visual field. Through numerical simulations, laboratory tests, and real-world experiments, we validated the performance of both modules. The reported USG with its visual-tactile fusion concept enables near-far all-around hazard detection and reduces the danger for divers working underwater.

Mannan and outer structural yeast cell wall polysaccharides have recently garnered attention for their health defense and cosmetic applications. In addition, many studies have confirmed that yeast cell wall mannans exhibit various biological activities, such as antioxidant, immune regulation, reducing hyperlipidemia, and gut health promotion. This paper elucidates yeast cell wall mannan structural features, biological activities, underlying molecular mechanisms, and biosynthesis. Moreover, mannan-overproducing strategies through yeast strain engineering are emphasized and discussed. This review will provide a scientific basis for yeast cell wall mannan research and industrial applications.

Summary: This study proposed two kinds of tensegrity hopping robots, which were actuated by push-pull electromagnets and servo motors, respectively. Both tensegrity robots are able to conduct stable and consecutive hopping actions. This paper covers the robots’ structural designs, theoretical modeling of the hopping actuators, and detailed analysis of the robot’s self-righting properties, all of which are validated by corresponding experimental and simulational results. The first hopping robot could hop forward at an average speed of 0.641 body length/s. Although the second robot has a lower moving speed of 0.237 body length/s, its average jumping height of 0.301 m is nearly 2.5 times higher than that of the first robot. Then compared with other tensegrity rolling robots, the proposed two robots show obvious advantages in locomotion performance over their counterparts. Therefore, the proposed robots can have large potential in many fields such as space exploration, urban search, military surveillance, etc.

Summary: Aiming at the current SPI (solder paste inspection) system for printing solder paste similar defects detection accuracy is not high, the system intelligence degree is low and so on, design a for the solder paste similar defects and combined with phase modulation profile measurement technique and improve the YOLOX intelligent detection system. The core of the system is the improved YOLOX depth model based on s-mosica and kt-iou algorithms proposed in this paper. The experimental results show that the proposed s-mosica and kt-iou algorithms can effectively improve the detection accuracy of printed solder paste, and when combined with the YOLOX model, the best 90.33% detection accuracy is obtained, which is better than the detection performance of the existing algorithms in the same scenario, and it provides an effective and feasible reference program for the design of the SPI high-precision intelligent detection system.

Summary: China as a major coal-consuming economy faces the challenge of balancing economic development and carbon neutrality goal. This paper incorporates both efficiency-based and equity-based carbon neutrality policies into a numerical model to quantitatively assess how coal reduction under various carbon-neutral policies affects energy mix, economic growth, and industrial structures by 2060. Results show the nationwide coal intensity will ultimately plunge by over 95% from 2017 to 2060, mainly attributed to the coal-phasing-out in most industries. National Gross Domestic Product losses reaches 4,951 billion USD in efficiency-based scenarios by 2060, and the economic losses are even more severe in less developed provinces, especially provinces in Northern China. Although the equity-based policy can reduce the economic burden for the Northern China, the equity-based policy is accompanied by a significant regional shift in coal across the country: eastern coal-intense industries will be relocated northward, leading to increases in embodied coal consumption.

Rose is a beautiful and fragrant plant with a variety of medicinal and substance uses. Various parts of rose such as fruits, flowers, leaves, and bark can be used in various product development, including cosmetics, food, pharmaceuticals, and engineering. The medical benefits of roses include the treatment of inflammation, diabetes, dysmenorrhea, depression, stress, seizures, and aging. Rose water is precious beauty water for skin care and has antibacterial effects on various microbiota. The surface of a rose petal exhibits a hierarchical structure comprising microscale papillae, with each papilla further featuring intricate nanofolds. With this structural feature, rose petals have high water contact angles together with antagonistic wetting properties. The hierarchical structures of rose petals were shown to have anti-reflection and light-harvesting abilities, which have the potential to be materials for various electronic products. Rose petals are an excellent biomimetic/bioinspired material that can be applied to the popular material graphene. This paper reviews the medical function and material application of roses. During the COVID-19 pandemic, medical materials or food shortages have become a global issue. Natural biomaterials could be a good alternative. Roses, with so many benefits, definitely deserve more exploration and promotion.