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Simple Summary: Underwater fish species are an important direction in fishery resource surveys. Rapidly determining species of underwater fish can improve the efficiency of fishery resource surveys. Therefore, this study proposes an effective method for underwater fish measurement, which can quickly acquire underwater fish species. The experimental results demonstrate the accuracy and superiority of our method. The proposed method improves the efficiency of fishery resource surveys and provides crucial data support for the precise management of fishery resources. To improve detection efficiency and reduce cost consumption in fishery surveys, target detection methods based on computer vision have become a new method for fishery resource surveys. However, the specialty and complexity of underwater photography result in low detection accuracy, limiting its use in fishery resource surveys. To solve these problems, this study proposed an accurate method named BSSFISH-YOLOv8 for fish detection in natural underwater environments. First, replacing the original convolutional module with the SPD-Conv module allows the model to lose less fine-grained information. Next, the backbone network is supplemented with a dynamic sparse attention technique, BiFormer, which enhances the model's attention to crucial information in the input features while also optimizing detection efficiency. Finally, adding a 160 × 160 small target detection layer (STDL) improves sensitivity for smaller targets. The model scored 88.3% and 58.3% in the two indicators of mAP@50 and mAP@50:95, respectively, which is 2.0% and 3.3% higher than the YOLOv8n model. The results of this research can be applied to fishery resource surveys, reducing measurement costs, improving detection efficiency, and bringing environmental and economic benefits. [ABSTRACT FROM AUTHOR]

It is worthwhile to calculate the execution cost of a manipulator for selecting a planning algorithm to generate trajectories, especially for an agricultural robot. Although there are various off-the-shelf trajectory planning methods, such as pursuing the shortest stroke or the smallest time cost, they often do not consider factors synthetically. This paper uses the state-of-the-art Python version of the Robotics Toolbox for manipulator trajectory planning instead of the traditional D–H method. We propose a cost function with mass, iteration, and residual to assess the effort of a manipulator. We realized three inverse kinematics methods (NR, GN, and LM with variants) and verified our cost function's feasibility and effectiveness. Furthermore, we compared it with state-of-the-art methods such as Double A* and MoveIt. Results show that our method is valid and stable. Moreover, we applied LM (Chan λ = 0.1) in mobile operation on our agricultural robot platform. [ABSTRACT FROM AUTHOR]

Oxygen, nitrogen and hydrogen elements in inorganic materials have attracted considerable attention. Based on more than 70 current Chinese standards and more than 40 journal papers in the past decade, the current status and development of inert gas fusion infrared absorption or thermal conductivity methods and standards for the determination of oxygen, nitrogen and hydrogen in inorganic material were reviewed, including steel and alloys, rare refractory metal alloys, light or heavy and precious non-ferrous metals, rare earth alloys, ferroalloys, non-ferrous intermediate alloys and inorganic non-metallic functional materials. The parameters in current standards were listed, including applicable objects, quantitative scope, sample mass, reference material and fluxes, as well as the main working conditions m methods from journals, such as analyte, element, instrument, crude, sample mass, fluxes, analytics power and reference material. Finally, the application prospects and development directions of gas analytics in inorganic materials were prospected. [ABSTRACT FROM AUTHOR]

Fisheries and bottom seawater data were collected in July in 2022 and 2023 from 15 sampling stations in the Huanghe River estuary and adjacent seas in China. The patterns of functional alpha and beta diversity of fish communities in this area and their relationships with environmental factors were studied using trait-based analysis. Five functional classifications, which included 16 functional traits, four functional alpha diversity indices (functional richness, functional evenness, functional divergence, and community-weighted mean), three functional beta diversity indices (functional beta diversity and its turnover and nestedness components), and 14 bottom environmental factors were considered. The dominant traits of fish communities were the following: benthivorous feeding habits, small and front-facing mouths, high trophic level, demersal, anguilliform, low growth coefficient, medium resilience, low vulnerability, and adapted to warm temperate conditions. The dominant migration traits and types of fish eggs varied by year, and fish abundance was the main factor affecting the dominant traits of the communities. The results of multiple regression on distance matrices and variance partitioning analysis indicated that ammonia nitrogen content, total phosphorus content, and pH were the main environmental factors that affected fish functional diversity. The N/P ratio had a bottom-up control effect on fish functional diversity. Our findings also revealed that high pH gradients and distant geographical distances can inhibit trait turnover in fish communities. [ABSTRACT FROM AUTHOR]

The unregulated metallic deposition and continuous cracking of the fragile solid electrolyte interphase are considered the critical barriers that compromise the cyclability of lithium metal batteries (LMB), especially under low N/P ratio (<3) pairing modes. Herein, an ultra‐thin (5 µm), lightweight (0.25 mg cm−2), and moisture‐proof interfacial layer composed of the high‐entropy alloys (denoted as HEAs) and interweaved carbon nanotubes (CNTs) scaffold is constructed to modify the current collector, moreover, the thermally‐induced Li22Si5 alloy blended with the hydrophobic ethylene‐vinyl acetate copolymer (EVA) is infiltrated into the scaffold pores as the moisture‐proof cation reservoir. The HEA@CNT/Li22Si5@EVA interfacial layer not only maximizes the Li‐utilization degree with minimal voltage divergence in symmetric cells but also compensates for irreversible Li depletion in the pouch‐format anode‐less models. As the HEA@CNT/Li22Si5@EVA‐Cu substrate paired with the LiNi0.8Mn0.1Co0.1O2 cathode in a 200 mAh prototype, the phase evolution of oxide cathode and efficient Li utilization at the anode substrate can be real‐time monitored by the transmission‐mode operando X‐ray diffraction. This interfacial layer strategy affords multifunctionality to enable the LMB prototyping without excessive Li abuse. Consequently, cycling endurance and the balanced energy densities (420.1 Wh kg−1) are obtained on the whole cell. [ABSTRACT FROM AUTHOR]

The implementation of solid polymer electrolytes (SPEs) in energy‐dense batteries faces severe challenges including sluggish ionic diffusion, oxidation tendency at the cathode interface, dendrite protrusion from the metallic anode, as well as the technological incompatibility with the layer stack‐up cell assembly. Herein, an in‐situ polymerization strategy is presented to deal with above dilemma for the solid battery prototyping. The in situ cross‐linked poly(ethylene glycol) diglycidyl ether is embedded within the nanocellulose framework, endowing SPE membrane with the reinforced mechanical strength (11.31 MPa) at the thickness of 10 µm as well as superior ionic conductance (150 mS). After a rigorous selection, the sacrificial triphenylphosphine additive preferentially oxidizes on the LiNi0.8Mn0.1Co0.1O2 (NCM811) cathode to form the cathode electrolyte interface during the formation charging. Concurrently, the solvated zinc(II) bis(trifluoromethylsulfonyl)imide constructs the polyether/LiZn mosaic layer on the Li foil, which effectively promotes interfacial cation diffusion and horizontal deposits propagation. By pairing the polymerized SPE with the thin‐layer Li foil (50 µm) and the NCM811 cathode (25 mg cm−2), the 94 mAh pouch‐format cell can realize a gravimetric/volumetric energy density of 397.5 Wh kg−1 and 1197.6 Wh L−1, high‐voltage tolerance till 4.5 V, and robust cyclability (95.1% capacity retention for 200 cycles). [ABSTRACT FROM AUTHOR]

With the development of agricultural information technology, the Internet of Things and blockchain have become important in the traceability of agricultural products. Sensors collect real-time data in agricultural production and a blockchain provides a secure and transparent storage medium for these data, which improves the transparency and credibility of agricultural product traceability. However, existing agricultural product traceability solutions are limited by the immutability of the blockchain, making it difficult to delete erroneous data and modify the scope of data sharing. This damages the credibility of traceability data and is not conducive to the exchange and sharing of information among enterprises. In this article, we propose an agricultural product traceability data management scheme based on a redactable blockchain. This scheme allows agricultural enterprises to encrypt data to protect privacy. In order to facilitate the maintenance and sharing of data, we introduce a chameleon hash function to provide data modification capabilities. Enterprises can fix erroneous data and update the access permissions of the data. To improve the efficiency of block editing, our scheme adopts a distributed block editing method. This method supports threshold editing operations, avoiding single-point-of-failure issues. We save records of data modifications on the blockchain and establish accountability mechanisms to identify malicious entities. Finally, in this paper we provide a security analysis of our proposed solution and verify its effectiveness through experiments. Compared with the existing scheme, the block generating speed is improved by 42% and the block editing speed is improved by 29.3% at 125 nodes. [ABSTRACT FROM AUTHOR]

Semiconductor lasers with a wavelength of 2 µm, composed of antimonide materials, find important applications in trace gas detection, laser medicine, and free-space optical communication, among others. In this paper, a more suitable microlens shape for 2 µm gallium antimonide semiconductor lasers is designed. Based on the fiber coupling efficiency model, the parameters of the designed slanting wedge-shaped microlens fiber are optimized to improve laser beam quality. The large tangent angle on both sides of the slanted, wedge-shaped microlens fiber is calculated using Snell's law, and the fiber core diameter and small wedge angle are determined through space fiber coupling experiments. After packaging the fiber coupling module with the chip, the laser output beam exhibits good overall symmetry in the spot with a uniform intensity distribution. The maximum output power is approximately 210 mW, demonstrating good power stability. [ABSTRACT FROM AUTHOR]

A pulse duration compression technique that combines stimulated Brillouin scattering (SBS) and stimulated Raman scattering (SRS) was presented in this study, achieving an output pulse duration of 48.3 ps. The feasibility of this approach has been experimentally demonstrated. To be specific, a pulse duration of 7.4 ns is compressed to 48.3 ps with an energy of 5.27 mJ, and the energy efficiency of the SRS pulse duration compression system is up to 21.84%. Moreover, this study provides a practical method for reliably generating high-energy short pulses. [ABSTRACT FROM AUTHOR]

Staphylococcus aureus stands as one of the most pervasive pathogens given its morbidity and mortality worldwide due to its roles as an infectious agent that causes a wide variety of diseases ranging from moderately severe skin infections to fatal pneumonia and sepsis. S. aureus produces a variety of exotoxins that serve as important virulence factors in S. aureus-related infectious diseases and food poisoning in both humans and animals. For example, staphylococcal enterotoxins (SEs) produced by S. aureus induce staphylococcal foodborne poisoning; toxic shock syndrome toxin-1 (TSST-1), as a typical superantigen, induces toxic shock syndrome; hemolysins induce cell damage in erythrocytes and leukocytes; and exfoliative toxin induces staphylococcal skin scalded syndrome. Recently, Panton–Valentine leucocidin, a cytotoxin produced by community-associated methicillin-resistant S. aureus (CA-MRSA), has been reported, and new types of SEs and staphylococcal enterotoxin-like toxins (SEls) were discovered and reported successively. This review addresses the progress of and novel insights into the molecular structure, biological activities, and pathogenicity of both the classic and the newly identified exotoxins produced by S. aureus. [ABSTRACT FROM AUTHOR]

This paper discusses a semantic segmentation framework and shows its application in agricultural intelligence, such as providing environmental awareness for agricultural robots to work autonomously and efficiently. We propose an ensemble framework based on the bagging strategy and the UNet network, using RGB and HSV color spaces. We evaluated the framework on our self-built dataset (Maize) and a public dataset (Sugar Beets). Then, we compared it with UNet-based methods (single RGB and single HSV), DeepLab V3+, and SegNet. Experimental results show that our ensemble framework can synthesize the advantages of each color space and obtain the best IoUs (0.8276 and 0.6972) on the datasets (Maize and Sugar Beets), respectively. In addition, including our framework, the UNet-based methods have faster speed and a smaller parameter space than DeepLab V3+ and SegNet, which are more suitable for deployment in resource-constrained environments such as mobile robots. [ABSTRACT FROM AUTHOR]

Precise recognition of maize growth stages in the field is one of the critical steps in conducting precision irrigation and crop growth evaluation. However, due to the ever-changing environmental factors and maize growth characteristics, traditional recognition methods usually suffer from limitations in recognizing different growth stages. For the purpose of tackling these issues, this study proposed an improved U-net by first using a cascade convolution-based network as the encoder with a strategy for backbone network replacement to optimize feature extraction and reuse. Secondly, three attention mechanism modules have been introduced to upgrade the decoder part of the original U-net, which highlighted critical regions and extracted more discriminative features of maize. Subsequently, a dilation path of the improved U-net was constructed by integrating dilated convolution layers using a multi-scale feature fusion approach to preserve the detailed spatial information of in-field maize. Finally, the improved U-net has been applied to recognize different growth stages of maize in the field. The results clearly demonstrated the superior ability of the improved U-net to precisely segment and recognize maize growth stage from in-field images. Specifically, the semantic segmentation network achieved a mean intersection over union (mIoU) of 94.51% and a mean pixel accuracy (mPA) of 96.93% in recognizing the maize growth stage with only 39.08 MB of parameters. In conclusion, the good trade-offs made in terms of accuracy and parameter number demonstrated that this study could lay a good foundation for implementing accurate maize growth stage recognition and long-term automatic growth monitoring. [ABSTRACT FROM AUTHOR]

The practical use of polyethylene oxide polymer electrolyte in the solid‐state sodium metallic batteries (SSMBs) suffers from the retard Na+ diffusion at the room temperature, mechanical fragility as well as the oxidation tendency at high voltages. Herein, a hetero‐layered composite polymeric electrolyte (CPE) is proposed to enable the simultaneous interfacial stability with the high voltage cathodes (till 4.2 V) and Na metallic anode. Being incorporated within the polymer matrix, the sand‐milled Na3Zr2Si2PO12 nanofillers and nanocellulose scaffold collectively endow the thin‐layer (25 µm), ultralightweight (1.65 mg cm−2) CPE formation with an order of magnitude enhancement of the mechanical strength (13.84 MPa) and ionic conductivity (1.62 × 10−4 S cm−1) as compared to the pristine polymer electrolyte, more importantly, the improved dimension stability up to 180 °C. Upon the integration of the hetero‐layered CPE with the iron hexacyanoferrate FeHCF cathode (1 mAh cm−2) and the Na foil, the cell model can achieve the room‐temperature cycling stability (93.73% capacity retention for 200 cycles) as well as the high temperature tolerance till 80 °C, which inspires a quantum leap toward the surface‐wetting‐agent‐free, energy‐dense, wide‐temperature‐range SSMB prototyping. [ABSTRACT FROM AUTHOR]