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A thin, lightweight and flexible electromagnetic interference (EMI) shielding paper composite is an urgent need for modern military confrontations. Herein, a sandwich-structured EMI shielding paper composite with an easy pavement consisting of a filter paper layer, middle AgNWs/MXene layer, and polyvinyl butyral (PVB) layer was constructed by vacuum-assisted filtration, spraying and air-drying. The middle AgNWs/MXene compound endowed the filter paper with excellent electrical conductivity (166 S cm−1) and the fabricated filter paper–AgNWs/MXene–PVB composite exhibits superior EMI shielding (30 dB) with a 141 μm thickness. Remarkably, the specific EMI shielding effectiveness (SSE/t) of the filter paper–AgNWs/MXene–PVB composite reached 13,000 dB cm2 g−1 within the X-band frequency range. This value represents one of the highest reported for cellulose-based EMI shielding materials. Therefore, our sandwich-structured filter paper composite with superior EMI shielding performance can be used in the medical and military fields. [ABSTRACT FROM AUTHOR]

The accurate identification of drug-target affinity (DTA) is crucial for advancements in drug discovery and development. Many deep learning-based approaches have been devised to predict drug-target binding affinity accurately, exhibiting notable improvements in performance. However, the existing prediction methods often fall short of capturing the global features of proteins. In this study, we proposed a novel model called ETransDTA, specifically designed for predicting drug-target binding affinity. ETransDTA combines convolutional layers and transformer, allowing for the simultaneous extraction of both global and local features of target proteins. Additionally, we have integrated a new graph pooling mechanism into the topology adaptive graph convolutional network (TAGCN) to enhance its capacity for learning feature representations of chemical compounds. The proposed ETransDTA model has been evaluated using the Davis and Kinase Inhibitor BioActivity (KIBA) datasets, consistently outperforming other baseline methods. The evaluation results on the KIBA dataset reveal that our model achieves the lowest mean square error (MSE) of 0.125, representing a 0.6% reduction compared to the lowest-performing baseline method. Furthermore, the incorporation of queries, keys and values produced by the stacked convolutional neural network (CNN) enables our model to better integrate the local and global context of protein representation, leading to further improvements in the accuracy of DTA prediction. [ABSTRACT FROM AUTHOR]

Recently, there has been a growing demand for ultra‐thin carbonized wood films (CWF) with high shielding efficiency (SE) to replace non‐renewable alternatives. Researchers aim to enhance electromagnetic (EM) wave absorption and improve electromagnetic interference (EMI) SE in CWF materials to reduce secondary pollution from reflected EM waves. In this work, the carbonized wood composite film (CWF/EP/Co) with a thickness of 120 µm through the process of hot‐pressing and carbonizing wood soaked in a mixed solution of water‐borne epoxy (EP) and Co/Zn‐MOF (ZIF‐67/8) is obtained. The CWF/EP/Co film exhibits excellent conductivity (105 S cm−1) and demonstrates an excellent EMI SE (73 dB) at a 200 µm thickness. Remarkably, the specific EMI shielding effectiveness (SSE/t) of CWF/EP/Co films reached 15833.3 dB·cm2·g−1 in the X‐band, making it the highest reported value among all wood‐derived EMI shielding materials. CWF/EP/Co films have a high absorption coefficient (A) of 0.4, indicating their effectiveness in absorbing EM waves. Furthermore, the EMI shielding effect of the large‐scale wallpaper (170 mm×170 mm) is confirmed by finite element analysis. Additionally, the CWF/EP/Co film exhibits good mechanical properties and effective Joule heating performance. This shielding film shows promise in applications such as buildings and smart homes, providing EMI shielding and warming effects. [ABSTRACT FROM AUTHOR]

The predominant adhesives currently utilized in the wood sector are sourced from petroleum. However, it is crucial to acknowledge that fossil resources possess a limited supply, and their extraction procedures can lead to adverse effects on the ecosystem. Renewable biomass resources have important application prospects in wood adhesives. This paper reviews the recent research progress on utilizing biomass to replace or modify conventional petroleum-based adhesives, focusing on the application of tannin, lignin, protein, starch, and cellulose in urea–formaldehyde (UF), melamine, phenol–formaldehyde (PF), epoxy (EP), and polyurethane (PU) resin adhesives. The symbiosis of renewable biomass with conventional petroleum-based adhesives portends substantial advancements for the wood adhesive industry. This review evaluates the substitution capacity and modification effect of biomass, discusses its application prospects in the wood-based panel industry, and predicts the future direction of biomass in wood adhesives, providing new inspirations for the development of novel green adhesives. [ABSTRACT FROM AUTHOR]

In the implementation of robot motion control, complex kinematic computations consume too much central processing unit (CPU) time and affect the responsiveness of robot motion. To solve this problem, this paper proposes a parallel method for solving kinematic equations of articulated robots based on the coordinate rotation digital computer (CORDIC) algorithm. The method completes the fast calculation of the transcendental function based on the CORDIC algorithm, adopts the tree structure method to optimize the key computational paths of forward and inverse solutions, and designs a parallel pipeline to realize the low latency and high throughput of the kinematic equations. The experiments of the proposed method are validated based on the field-programmable gate array (FPGA) hardware experimental platform, and the experimental results demonstrate that the computational time to complete the entire kinematic equations is 4.68 μs, of which the computational time for the kinematic positive solution is 0.52 μs and the computational time for the kinematic inverse solution is 4.16 μs. [ABSTRACT FROM AUTHOR]

The titanium carbide nanosheets (MXene) hold great potential for fabricating high‐performance electronics due to their two‐dimensional layered structure, high electrical conductivity, and versatile surface chemistry. However, assembling the small MXene nanosheets into flexible macroscopic films for wearable electronics still remains a challenge. Herein, we report the hierarchical assembling of MXene nanosheets and cellulose nanofibers into high‐performance composite films via an electrostatic self‐assembly strategy induced by polyethyleneimine. Benefited from the nacre‐like microstructure of MXene "bricks" and cellulose nanofibers "mortars" interlocked by polyethyleneimine via hydrogen bonding and electrostatic interaction, composite films possess integrated superior flexibility, high tensile strength, and stable electrical conductivity, which are advantageous for wearable electronic applications. To provide a proof‐of‐concept design, a symmetric quasi‐solid‐state supercapacitor with the as‐prepared composite film as electrode is fabricated, which exhibits a specific capacitance of 93.9 mF cm−2 at a current density of 0.1 mA cm−2 and almost constant capacitive behavior under different bending states. In addition, the composite film possesses capacities of electrothermal conversion and complete degradation in a hydrogen peroxide solution. These results demonstrate that the electrostatically self‐assembled composite films hold great promise in the development of highly flexible, mechanically robust, and environmentally friendly energy storage and conversion devices. [ABSTRACT FROM AUTHOR]