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Designing and fabricating a highly sensitive non-enzymatic glucose sensor is crucial for the early detection and management of diabetes. Meanwhile, the development of innovative electrode substrates has become a key focus for addressing the growing demand for constructing flexible sensors. Here, a simple one-step laser engraving method is applied for preparing laser-induced graphene (LIG) on polyimide (PI) film, which serves as the sensor substrate. NiCo-layered double hydroxides (NiCo-LDH) are synthesized on LIG as a precursor, utilizing the zeolitic imidazolate framework (ZIF-67), and then reacted with Ni(NO3)2 via solvent-thermal methods. The sensitivity of the non-enzymatic electrochemical glucose sensor is significantly improved by employing NiCo-LDH/LIG as the sensing material. The porous and interconnected structure of NiCo-LDH, derived from ZIF-67, enhances the accessibility of electrochemically active sites, while the incorporation of LIG ensures exceptional conductivity. The combination of NiCo-LDH with LIG enables efficient electron transport, leading to an increased electrochemically active surface area and enhanced catalytic efficiency. The fabricated electrode achieves a low glucose detection limit of 0.437 μM and demonstrates a high sensitivity of 1141.2 and 631.1 μA mM−2 cm−2 within the linear ranges of 0–770 μM and 770–1970 μM, respectively. Furthermore, the NiCo-LDH/LIG glucose sensor demonstrates superior reliability and little impact from other substances. A flexible integrated LIG-based non-enzymatic glucose sensor has been developed, demonstrating high sensitivity and suggesting a promising application for LIG-based chemical sensors.

With the extensive application of deep learning (DL) algorithms in recent years, e.g., for detecting Android malware or vulnerable source code, artificial intelligence (AI) and machine learning (ML) are increasingly becoming essential in the development of cybersecurity solutions. However, sharing the same fundamental limitation with other DL application domains, such as computer vision (CV) and natural language processing (NLP), AI-based cybersecurity solutions are incapable of justifying the results (ranging from detection and prediction to reasoning and decision-making) and making them understandable to humans. Consequently, explainable AI (XAI) has emerged as a paramount topic addressing the related challenges of making AI models explainable or interpretable to human users. It is particularly relevant in cybersecurity domain, in that XAI may allow security operators, who are overwhelmed with tens of thousands of security alerts per day (most of which are false positives), to better assess the potential threats and reduce alert fatigue. We conduct an extensive literature review on the intersection between XAI and cybersecurity. Particularly, we investigate the existing literature from two perspectives: the applications of XAI to cybersecurity (e.g., intrusion detection, malware classification), and the security of XAI (e.g., attacks on XAI pipelines, potential countermeasures). We characterize the security of XAI with several security properties that have been discussed in the literature. We also formulate open questions that are either unanswered or insufficiently addressed in the literature, and discuss future directions of research.

The error width and the tap-length adaptation step-size are two critical factors that affect the overall performance of the fractional variable tap-length algorithm. Some reasonably adjusted strategies can improve the performance. However, the existing strategies for adjusting these two parameters have many problems, such as overestimation, large fluctuations, underestimation, insufficient analysis of the parameter and high complexity. Therefore, this paper proposes an efficient and unified adjustment method that utilizes the accumulated and transient full-partial errors to adjust these two parameters simultaneously. The detailed parameter ranges and specific performance of the proposed algorithm were all analyzed. In the simulation, high and low noise situations, sudden environmental changes, large- and small-scale systems, continuously changing environment and key performance curves were tested. The results of theoretical analysis and experimental tests jointly confirmed that the proposed algorithm can quickly and reasonably update the tap-length and improve some performance.

The capability of wind turbines (WTs) to provide frequency response is crucial for future power systems with high wind power penetration. Existing strategies primarily focus on mitigating initial and secondary frequency drop (SFD), often overlooking the adverse effects of rotor speed recovery on turbine safety and sustained grid support. Moreover, the lack of a dynamic linkage between the frequency support stage (FSS) and speed recovery stage (SRS) impedes multi-objective coordination encompassing initial drop suppression, SFD mitigation, and rapid rotor speed recovery. To address these gaps, this paper proposes a two-stage coordinated control strategy. In the FSS, the frequency regulation coefficients (Kp and Kd) are adaptively adjusted based on available kinetic energy, ensuring its rational release. Subsequently, the switching timing from FSS to SRS is optimized using these coefficients to suppress the SFD and accelerate recovery. Finally, a fuzzy logic-based PI controller dynamically governs the SRS to restore rotor speed efficiently while further alleviating the SFD. Simulation results confirm the effectiveness of the proposed strategy under two wind speeds. It improves the initial frequency nadir by up to 0.197 Hz over no frequency control, reduces the secondary frequency drop by as much as 0.106 Hz compared to the stepwise method, and accelerates rotor speed recovery by over 30%, quantitatively validating its superior coordinated performance.

Orthogonal chirp division multiplexing (OCDM) offers a promising modulation technology for shallow water underwater acoustic (UWA) communication systems due to multipath fading resistance and Doppler resistance. To handle the various channel distortions and interferences, obtaining accurate channel state information is vital for robust and efficient shallow water UWA communication. In recent years, deep learning has attracted widespread attention in the communication field, providing a new way to improve the performance of physical layer communication systems. In this paper, the pilot-based channel estimation is transformed into a matrix completion problem, which is mathematically equivalent to the image super-resolution problem arising in the field of image processing. Simulation results show that the deep learning-based method can improve the channel distortion, outperforming the equalization performed by traditional estimator, the performance of Bit Error Rate is improved by 2.5 dB compared to the MMSE method in OCDM system. At the 7.5 to 20 dB region, it achieves better bit error rate performance than OFDM systems, and the bit error rate is reduced by approximately 53% compared to OFDM when the SNR value is 20, which is very useful in shallow water UWA channels with multipath extension and severe time-varying characteristics.

The influence of microstructural characteristics on the fatigue crack propagation behavior of multiphase advanced high strength steels (AHSSs) was investigated in the present study with a particular focus on the retained austenite. The steel samples with unified chemical composition were treated by various processes to obtain press-hardened (PH), dual-phase (DP), quenching and partitioning (QP), and transformation-induced plasticity (TRIP) AHSSs. The results demonstrate that an increased proportion of retained austenite correlate with the enhanced tensile elongation and a reduced fatigue crack propagation rate in these AHSSs. This effect is attributed to the retardation of fracture propagation, which occurs as result of the transformation of austenite into martensite. Furthermore, the study reveals that retained austenite with a fine block morphology and high average boundary angles contributes to sustained resistance to fatigue crack propagation. It is believed that this resistance is attributed to the deflection of crack growth through the fracture along irregular and densely distributed block boundaries.

In this study, bromelain was used to break soy protein molecules into polypeptide chains, and triglycidylamine (TGA) was added to develop a bio-adhesive. The viscosity, residual rate, functional groups, thermal behavior, and fracture surface of different adhesives were measured. A three-ply plywood was fabricated and evaluated. The results showed that using 0.1 wt% bromelain improved the soy protein isolate (SPI) content of the adhesive from 12 wt% to 18 wt%, with viscosity remaining constant, but reduced the residual rate by 9.6% and the wet shear strength of the resultant plywood by 69.8%. After the addition of 9 wt% TGA, the residual rate of the SPI/bromelain/TGA adhesive improved by 13.7%, and the wet shear strength of the resultant plywood increased by 681.3% relative to that of the SPI/bromelain adhesive. The wet shear strength was 30.2% higher than that of the SPI/TGA adhesive, which was attributed to the breakage of protein molecules into polypeptide chains. This occurrence led to (1) the formation of more interlocks with the wood surface during the curing process of the adhesive and (2) the exposure and reaction of more hydrophilic groups with TGA to produce a denser cross-linked network in the adhesive. This denser network exhibited enhanced thermal stability and created a ductile fracture surface after the enzymatic hydrolysis process.

Reduced graphene oxide (rGO) exhibits mechanical, optoelectronic, and conductive properties comparable to pristine graphene, which has led to its widespread use as a method for producing graphene-like materials in bulk. This paper reviews the characteristics of graphene oxide and the evolution of traditional reduction methods, including chemical and thermal techniques. A comparative analysis reveals that these traditional methods encounter challenges, such as toxicity and high energy consumption, while plasma reduction offers advantages like enhanced controllability, the elimination of additional reducing agents, and reduced costs. However, plasma reduction is complex and significantly influenced by process parameters. This review highlights the latest advancements in plasma technology for reducing graphene oxide, examining its effectiveness across various gas environments. Inert gas plasmas, such as argon (Ar) and helium (He), demonstrate superior reduction efficiency, while mixed gases facilitate simultaneous impurity reduction. Additionally, carbon-based gases can aid in restoring defects in graphene oxide. This paper concludes by discussing the future prospects of plasma-reduced graphene and emphasizes the importance of understanding plasma parameters to manage energy and chemical footprints for effective reduction.

Gap junction intercellular communication (GJIC) between two adjacent cells involves direct exchange of cytosolic ions and small molecules via connexin gap junction channels (GJCs). Connexin GJCs have emerged as drug targets, with small molecule connexin inhibitors considered a viable therapeutic strategy in several diseases. The molecular mechanisms of GJC inhibition by known small molecule connexin inhibitors remain unknown, preventing the development of more potent and connexin-specific therapeutics. Here we show that two GJC inhibitors, mefloquine (MFQ) and 2-aminoethoxydiphenyl borate (2APB) bind to Cx32 and block dye permeation across Cx32 hemichannels (HCs) and GJCs. Cryo-EM analysis shows that 2APB binds to “site A”, close to the N-terminal gating helix of Cx32 GJC, restricting the entrance to the channel pore. In contrast, MFQ binds to a distinct “site M”, deeply buried within the pore. MFQ binding to this site modifies the electrostatic properties of Cx32 pore. Mutagenesis of V37, a key residue located in the site M, renders Cx32 HCs and GJCs insensitive to MFQ-mediated inhibition. Moreover, our cryo-EM analysis, mutagenesis and activity assays show that MFQ targets the M site in Cx43 GJC similarly to Cx32. Taken together, our results point to a conserved inhibitor binding site in connexin channels, opening a new route for development of specific drugs targeting connexins.

Background Cesarean hysterectomy as a traditional therapeutic maneuver for placenta accreta spectrum (PAS) has been associated with serious morbidity, conservative management has been used in many institutions to treat women with PAS. This systematic review aims to compare maternal outcomes according to conservative management or cesarean hysterectomy in women with placenta accreta spectrum disorders. Methods A systematic literature search was performed in MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, Web of Science, and four Chinese databases (Chinese Biomedical Literature Database, China National Knowledge Infrastructure, Chinese Wanfang database and VIP database) to May 2024. Included studies were to be retrospective or prospective in design and compare and report relevant maternal outcomes according to conservative management (the placenta left partially or totally in situ) or cesarean hysterectomy in women with PAS. A risk ratio (RR) with 95% confidence interval (95% CI) was calculated for categorical outcomes and weighted mean difference (WMD) with 95% CI for continuous outcomes. The Newcastle-Ottawa Quality Assessment Scale was used to assess the observational studies. All analyses were performed using STATA version 18.0. Results Eight studies were included in the meta-analysis. Compared with cesarean hysterectomy, PAS women undergoing conservative management showed lower estimated blood loss [WMD − 1623.83; 95% CI: -2337.87, -909.79], required fewer units of packed red blood cells [WMD − 2.37; 95% CI: -3.70, -1.04] and units of fresh frozen plasma transfused [WMD − 0.40; 95% CI: -0.62, -0.19], needed a shorter mean operating time [WMD − 73.69; 95% CI: -90.52, -56.86], and presented decreased risks of bladder injury [RR 0.24; 95% CI: 0.11, 0.50], ICU admission [RR 0.24; 95% CI: 0.11, 0.52] and coagulopathy [RR 0.20; 95% CI: 0.06, 0.74], but increased risk for endometritis [RR 10.91; 95% CI: 1.36, 87.59] and readmission [RR 8.99; 95% CI: 4.00, 12.21]. The incidence of primary or delayed hysterectomy rate was 25% (95% CI: 19–32, I 2  = 40.88%) and the use of uterine arterial embolization rate was 78% (95% CI: 65–87, I 2  = 48.79%) in conservative management. Conclusion Conservative management could be an effective alternative to cesarean hysterectomy when women with PAS desire to preserve the uterus and are informed about the limitations of conservative management. Prospero ID CRD42023484578.