YOLOX-DG robotic detection systems for large-scale underwater concrete structures

Large-scale complex underwater concrete structures have structural damage and the traditional damage detection method mostly uses manual identification, which is inaccurate and inefficient. Therefore, robotic detection systems have been proposed to replace manual identification for underwater concrete structures in ocean engineering. However, the highly corrosive and disruptive environment of the ocean poses great difficulties for the application. Here, we develop a manta ray-inspired underwater robot with well controllability to establish the damage datasets of underwater concrete structures, proposing the YOLOX-DG algorithm to improve the damage detection accuracy, and integrating the model into the robotic detection systems for underwater concrete damages. Eventually, the system is used for ocean testing in real applications (i.e., underwater marine harbors around the East China Sea), and satisfactory detection performance is obtained. The reported manta ray-inspired robotic detection system can be used to accurately monitor and analyze the underwater regions.

Assessing total cost of driving competitiveness of zero-emission trucks

Medium- and heavy-duty vehicles are 21% of US transportation greenhouse gas (GHG) emissions and a major source of air pollution. We explore how the total cost of driving (TCD) of zero-emission vehicles (ZEVs), including battery electric vehicles and hydrogen fuel cell electric vehicles (EVs and FCEVs), could evolve under alternative scenarios. With continued improvements in vehicles and fuels, ZEVs can rapidly become viable, potentially reaching TCD parity or better compared to diesel vehicles by 2035 for all market segments. For heavy long-haul trucks, EVs become competitive on a TCD basis at charging costs below $0.18/kWh, while FCEVs become competitive on a TCD basis at hydrogen costs below $5/kg. A full transition to ZEV sales by 2035 results in 65% emissions reductions by 2050 compared to 2019 without supportive policies. Incentives such as the Inflation Reduction Act vehicle purchase credits further accelerate ZEV TCD competitiveness with major adoption opportunities over the next five years.

Cross-domain pedestrian detection via feature alignment and image quality assessment

Datasets collected under different sensors, viewpoints, or weather conditions cause different domains. Models trained on domain A applied to tasks of domain B result in low performance. To overcome the domain shift, we propose an unsupervised pedestrian detection method that utilizes CycleGAN to establish an intermediate domain and transform a large gap domain-shift problem into two feature alignment subtasks with small gaps. The intermediate domain trained with labels from domain A, after two rounds of feature alignment using adversarial learning, can facilitate effective detection in domain B. To further enhance the training quality of intermediate domain models, Image Quality Assessment (IQA) is incorporated. The experimental results evaluated on Citypersons, KITTI, and BDD100K show that MR of 24.58%, 33.66%, 28.27%, and 28.25% were achieved in four cross-domain scenarios. Compared with typical pedestrian detection models, our proposed method can better overcome the domain-shift problem and achieve competitive results.

Alignment error modeling and control of a double-sided microlens array during precision glass molding

Double-sided microlens arrays (DSMLAs) include combinations of two single-sided MLAs to overcome positioning errors and greatly improve light transmissivity compared to other types of lenses. Precision glass molding (PGM) is used to fabricate DSMLAs, but controlling alignment errors during this process is challenging. In this paper, a mold assembly was manufactured with a novel combination of materials to improve the alignment accuracy of mold cores during PGM by using the nonlinear thermal expansion characteristics of the various materials to improve the DSMLA alignment accuracy. By establishing a mathematical model of the DSMLA alignment error and a thermal expansion model of the mold-sleeve pair, the relationship between the maximum alignment error of the DSMLA and the mold-sleeve gap was determined. This research provides a method to optimize the mold-sleeve gap and minimize the alignment error of the DSMLA. The measured DSMLA alignment error was 10.56 μm, which is similar to the predicted maximum alignment error. Optical measurements showed that the uniformity of the homogenized beam spot was 97.81%, and the effective homogeneous area accounted for 91.66% of the total area. This proposed method provides a novel strategy to improve the performance of DSMLAs.

Altering Specificity and Enhancing Stability of the Antimicrobial Peptides Nisin and Rombocin through Dehydrated Amino Acid Residue Engineering

Nisin serves as the prototype within the lantibiotic group of antimicrobial peptides, exhibiting a broad-spectrum inhibition against Gram-positive bacteria, including important food-borne pathogens and clinically relevant antibiotic-resistant strains. The gene-encoded nature of nisin allows for gene-based bioengineering, enabling the generation of novel derivatives. It has been demonstrated that nisin mutants can be produced with improved functional properties. Here, we particularly focus on the uncommon amino acid residues dehydroalanine (Dha) and dehydrobutyrin (Dhb), whose functions are not yet fully elucidated. Prior to this study, we developed a new expression system that utilizes the nisin modification machinery NisBTC to advance expression, resulting in enhanced peptide dehydration efficiency. Through this approach, we discovered that the dehydrated amino acid Dhb at position 18 in the peptide rombocin, a short variant of nisin, displayed four times higher activity compared to the non-dehydrated peptide against the strain Lactococcus lactis. Furthermore, we observed that in the peptides nisin and rombocin, the dehydrated amino acid Dha at residue positon 18 exhibited superior activity compared to the dehydrated amino acid Dhb. Upon purifying the wild-type nisin and its variant nisinG18/Dha to homogeneity, the minimum inhibitory concentration (MIC) indicated that the variant exhibited activity similar to that of wild-type nisin in inhibiting the growth of Bacillus cereus but showed twice the MIC values against the other four tested Gram-positive strains. Further stability tests demonstrated that the dehydrated peptide exhibited properties similar to wild-type nisin under different temperatures but displayed higher resistance to proteolytic enzymes compared to wild-type nisin.

Yeast cell wall mannan structural features, biological activities, and production strategies

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.

Near-zero stiffness accelerometer with buckling of tunable electrothermal microbeams

Pre-shaped microbeams, curved or inclined, are widely used in MEMS for their interesting stiffness properties. These mechanisms allow a wide range of positive and negative stiffness tuning in their direction of motion. A mechanism of pre-shaped beams with opposite curvature, connected in a parallel configuration, can be electrothermally tuned to reach a near-zero or negative stiffness behavior at the as-fabricated position. The simple structure helps incorporate the tunable spring mechanism in different designs for accelerometers, even with different transduction technologies. The sensitivity of the accelerometer can be considerably increased or tuned for different applications by electrothermally changing the stiffness of the spring mechanism. Opposite inclined beams are implemented in a capacitive micromachined accelerometer. The measurements on fabricated prototypes showed more than 55 times gain in sensitivity compared to their initial sensitivity. The experiments showed promising results in enhancing the resolution of acceleration sensing and the potential to reach unprecedent performance in micromachined accelerometers.

Equity-based carbon neutral plan induces cross-regional coal leakage and industrial relocation

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.

Intelligent health and sport: An interplay between flexible sensors and basketball

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.

A self-powered and self-sensing knee negative energy harvester

Wearable devices realize health monitoring, information transmission, etc. In this study, the human-friendliness, adaptability, reliability, and economy (HARE) principle for designing human energy harvesters is first proposed and then a biomechanical energy harvester (BMEH) is proposed to recover the knee negative energy to generate electricity. The proposed BMEH is mounted on the waist of the human body and connected to the ankles by ropes for driving. Double-rotor mechanism and half-wave rectification mechanism design effectively improves energy conversion efficiency with higher power output density for more stable power output. The experimental results demonstrate that the double-rotor mechanism increases the output power of the BMEH by 70% compared to the single magnet-rotor mechanism. And the output power density of BMEH reaches 0.07 W/kg at a speed of 7 km/h. Furthermore, the BMEH demonstrates the excitation mode detection accuracy of 99.8% based on the Gate Recurrent Unit deep learning model with optimal parameters.

Alpha oscillations reflect similar mapping mechanisms for localizing touch on hands and tools

It has been suggested that our brain re-uses body-based computations to localize touch on tools, but the neural implementation of this process remains unclear. Neural oscillations in the alpha and beta frequency bands are known to map touch on the body in external and skin-centered coordinates, respectively. Here, we pinpointed the role of these oscillations during tool-extended sensing by delivering tactile stimuli to either participants' hands or the tips of hand-held rods. To disentangle brain responses related to each coordinate system, we had participants' hands/tool tips crossed or uncrossed at their body midline. We found that midline crossing modulated alpha (but not beta) band activity similarly for hands and tools, also involving a similar network of cortical regions. Our findings strongly suggest that the brain uses similar oscillatory mechanisms for mapping touch on the body and tools, supporting the idea that body-based neural processes are repurposed for tool use.

A human-system integration framework and its application for special vehicle interface design under typical human readiness levels

Life cycle Human System Integration (HSI) practices are crucial for optimizing human system performance, reducing costs, and ensuring safety. To address the limited HSI practices under typical Human Readiness Levels (HRLs), our study proposes an HSI theoretical framework and applies it to the design of human-machine interfaces (HMIs) for special vehicles. A stakeholder survey evaluates effectiveness of the framework and its application. Conclusions: (1) The framework, based on the input-process-output model, covers HSI processes and their support across HRLs. (2) The case study of HMI design in HRLs 4-6 identifies key processes and their specific support, contributing to the refinement of the framework. (3) The stakeholder survey underscores the importance and effectiveness of HSI processes and their support in the case study for life cycle human factor practices, suggesting areas for improvement in structuring and operability. The study offers insights into HSI practices under typical HRLs, merging theoretical and case study perspectives.

Design of intelligent inspection system for solder paste printing defects based on improved YOLOX

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.

A resonant high-pressure microsensor based on a composite pressure-sensitive mechanism of diaphragm bending and volume compression

In this paper, a composite pressure-sensitive mechanism combining diaphragm bending and volume compression was developed for resonant pressure microsensors to achieve high-pressure measurements with excellent accuracy. The composite mechanism was explained, and the sensor structure was designed based on theoretical analysis and finite element simulation. An all-silicon resonant high-pressure microsensor with multiple miniaturized cavities and dual resonators was developed, where dual resonators positioned in two resonant cavities with suitably different widths are used to perform opposite characteristics in pressure and the same characteristics at different temperatures, which can improve pressure sensitivities and realize temperature self-compensation by differential frequency output. The microsensor was fabricated by microfabrication, and the experimental results showed that the sensor had an accuracy of ±0.015% full scale (FS) in a pressure range of 0.1~100 MPa and a temperature range of -10~50 °C. The pressure sensitivity of the differential frequency was 261.10 Hz/MPa (~2523 ppm/MPa) at a temperature of 20 °C, and the temperature sensitivities of the dual resonators were -1.54 Hz/°C (~-14.5 ppm/°C) and -1.57 Hz/°C (~-15.6 ppm/°C) at a pressure of 2 MPa. The differential output had an outstanding stability within ±0.02 Hz under constant temperature and pressure. Thus, this research provides a convenient solution for high-pressure measurements because of its advantages, namely, large range, excellent accuracy and stability.

Breakthrough application of electrochromism: Multifunctional artificial muscle

In the article (Advanced Materials 2023; 2305914, https://doi.org/10.1002/adma.202305914) reported by Wang et al., electrochemically driven multifunctional electrochromic artificial muscles (EAMs) are demonstrated with intricate actuation and eye-catching color-change behaviors, which were assembled from V2O5 nanowires-carbon nanotube fibers-based high-twist electrochromic artificial muscle yarn (EAMY). With combined wet winding and wet twisting, excellent mechanical properties and uniform color change were achieved in the core-sheath EAMYs. Followed by hot pouring and molding of gel electrolyte, the contact problem between electrode and electrolyte was resolved and EAMs were fabricated with stable operation in the air, harvesting a high shrinkage stroke of 12% and a high reflectivity contrast of 51%. The judicious device architecture design and integration of multifunctionality will open new avenues for electrochromic technology.

Reducing China's building material embodied emissions: Opportunities and challenges to achieve carbon neutrality in building materials

Embodied emissions from the production of building materials account for 17% of China's carbon dioxide (CO2) emissions and are important to focus on as China aims to achieve its carbon neutrality goals. However, there is a lack of systematic assessments on embodied emissions reduction potential of building materials that consider both the heterogeneous industrial characteristics as well as the Chinese buildings sector context. Here, we developed an integrated model that combines future demand of building materials in China with the strategies to reduce CO2 emissions associated with their production, using, and recycling. We found that measures to improve material efficiency in the value-chain has the largest CO2 mitigation potential before 2030 in both Low Carbon and Carbon Neutrality Scenarios, and continues to be significant through 2060. Policies to accelerate material efficiency practices, such as incorporating embodied emissions in building codes and conducting robust research, development, and demonstration (RD&D) in carbon removal are critical.