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Cracks pose a critical challenge in the preservation of historical buildings worldwide, particularly in fair-faced walls, where timely and accurate detection is essential to prevent further degradation. Traditional image processing methods have proven inadequate for effectively detecting building cracks. Despite global advancements in deep learning, crack detection under diverse environmental and lighting conditions remains a significant technical hurdle, as highlighted by recent international studies. To address this challenge, we propose an enhanced crack detection algorithm, CL-YOLOv8 (ConvNeXt V2-LSKA-YOLOv8). By integrating the well-established ConvNeXt V2 model as the backbone network into YOLOv8, the algorithm benefits from advanced feature extraction techniques, leading to a superior detection accuracy. This choice leverages ConvNeXt V2’s recognized strengths, providing a robust foundation for improving the overall model performance. Additionally, by introducing the LSKA (Large Separable Kernel Attention) mechanism into the SPPF structure, the feature receptive field is enlarged and feature correlations are strengthened, further enhancing crack detection accuracy in diverse environments. This study also contributes to the field by significantly expanding the dataset for fair-faced wall crack detection, increasing its size sevenfold through data augmentation and the inclusion of additional data. Our experimental results demonstrate that CL-YOLOv8 outperforms mainstream algorithms such as Faster R-CNN, YOLOv5s, YOLOv7-tiny, SSD, and various YOLOv8n/s/m/l/x models. CL-YOLOv8 achieves an accuracy of 85.3%, a recall rate of 83.2%, and a mean average precision (mAP) of 83.7%. Compared to the YOLOv8n base model, CL-YOLOv8 shows improvements of 0.9%, 2.3%, and 3.9% in accuracy, recall rate, and mAP, respectively. These results underscore the effectiveness and superiority of CL-YOLOv8 in crack detection, positioning it as a valuable tool in the global effort to preserve architectural heritage.

Background and aimsFew studies have examined the relationship between daytime napping and risk of kidney diseases. We aimed to investigate the association of daytime napping with the incidence of chronic kidney disease (CKD) and end-stage kidney disease (ESKD). We also examined whether sleep duration modified the association of nap with CKD or ESKD.MethodsWe recruited 460,571 European middle- to older-aged adults without prior CKD or ESKD between March 13, 2006, and October 1, 2010, in the UK Biobank. Sleep behavior data were obtained through questionnaires administered during recruitment. The analysis of the relationship between napping and the occurrence of CKD and ESKD utilized Cox proportional hazards regression models. The modification role of sleep duration on the effect of nap on CKD and ESKD was also examined.ResultsAfter a mean follow-up of 11.1 (standard deviation 2.2) years, we observed 28,330 incident CKD cases and 927 ESKD cases. The daytime napping was associated with incident CKD (P for trend = .004). After fully adjusted, when compared with participants who did not take nap, those in sometimes and usually nap groups had higher risk of CKD. Nevertheless, the available evidence did not support a link between daytime napping and ESKD (P for trend = .06). Simultaneously, there was insufficient evidence suggesting that sleeping duration modified the association of daytime napping with incident CKD or ESKD.ConclusionDaytime napping was associated with an increased risk of CKD. However, the absence of conclusive evidence did not indicate a connection between daytime napping and ESKD.

Three nonlinear fractional models, videlicet, the space-time fractional 1+1 Boussinesq equation, 2+1-dimensional breaking soliton equations, and SRLW equation, are the important mathematical approaches to elucidate the gravitational water wave mechanics, the fractional quantum mechanics, the theoretical Huygens’ principle, the movement of turbulent flows, the ion osculate waves in plasma physics, the wave of leading fluid flow, etc. This paper is devoted to studying the dynamics of the traveling wave with fractional conformable nonlinear evaluation equations (NLEEs) arising in nonlinear wave mechanics. By utilizing the oncoming exp−Θq-expansion technique, a series of novel exact solutions in terms of rational, periodic, and hyperbolic functions for the fractional cases are derived. These types of long-wave propagation phenomena played a dynamic role to interpret the water waves as well as mathematical physics. Here, the form of the accomplished solutions containing the hyperbolic, rational, and trigonometric functions is obtained. It is demonstrated that our proposed method is further efficient, general, succinct, powerful, and straightforward and can be asserted to install the new exact solutions of different kinds of fractional equations in engineering and nonlinear dynamics.

In temporal lobe epilepsy (TLE), the epileptogenic zones, such as the temporal lobe structure, could generate pathological high-frequency oscillations (pHFOs, 250–500 Hz) before the ictal period. These pHFOs have also been observed during the process of seizures in both TLE patients and animals, exhibiting a critical role as promising biomarkers for TLE seizures. TLE seizures could be modulated via regulating the neural excitability in epileptogenic zones, for that TLE is primarily associated with the excitation-inhibition imbalance. However, whether these kinds of modulations could also impact the pHFOs characteristics during TLE seizures is still unclear. For this purpose, we pharmaco-genetically inhibited the principal cells (PCs) in the mouse CA3 region and tracked the difference in the behavioral and electrophysiological features during LiCl-pilocarpine-induced TLE seizure between the hM4Di+CNO (experimental) mice and mCherry+CNO (control) mice. Delayed latency, decreased averaged duration, and reduced counts of the generalized seizure were observed in the experimental mice. Besides, the electrophysiological characteristics, such as the firing rate of PCs and the count of pHFO, exhibited significant decline in the CA3 and CA1 regions. During TLE seizure, there existed strong phase-coupling between pHFO and PCs spike timing in the control mice, while it was abolished in the experimental mice. In addition, we also found that the counts of pHFO were significantly associated with the behavioral features, indicating the close relationships within them. Collectively, our findings suggested that alterations in pHFO and the retardation of seizures may be attributed to disruptions in neuronal excitability, and the variations of electrophysiological features were related to seizure severity during TLE seizures. These results provide valuable insights into the role of pHFOs in TLE and shed light on the underlying mechanisms involved.

The development of microbial electrosynthesis (MES) for renewable electricity-driven bioutilization of CO2 has recently attracted considerable interest due to its ability to synthesize chemicals with the transition towards a circular carbon economy. However, the increase of acetate production and the decrease of energy consumption of MES using an advanced reactor design have received less attention. In this study, the total acetate production rate using novel flow-electrode MES reactors ((16 ± 1) g·m−2·d−1) was double that using reactors without powder activated carbon (PAC) amendment ((8 ± 3) g·m−2·d−1). The flow-electrode MES reactors had a Coulombic efficiency of 43.5% ± 3.1%, an energy consumption of (0.020 ± 0.005) kW·h·g−1, and an energy efficiency of 18.7% ± 1.3% during acetate production. The flow-electrode with PAC amendment could decrease the net water flux and charge transfer resistance, while had little impact on the cell voltage, rheological behavior, and acetate adsorption. In the flow-electrode MES reactors, the expression of genes involving in energy production and conversion were increased, and the increase of acetate production was found correlated with the increased abundance of Acetobacterium. The Wood–Ljungdahl pathway (WLP) and reductive citric acid cycle (rTCA) were found to be the pathways responsible for carbon fixation. The concentrations of acetate in the stacked flow-electrode MES reached 7.0 g·L−1. This study presents a new approach for the construction of scalable MES reactors with high-performance chemical generation and CO2 utilization.

Microbial electrochemical sensor has been regarded as a promising technology for water biotoxicity monitoring, while its practical application is partially restricted by the requirement of organic substrate or power supply in real time. In the present study, rechargeable microbial electrochemical sensors were constructed, with the ex-situ preparation of bioanode and the in-situ preparation of biocathode. Acetate, formate, and hydrogen were identified as the charge carriers, and a Coulombic efficiency of 38% ± 18% and an energy efficiency of 2.2% ± 0.7% were obtained. The increase of charge current could decrease the energy efficiency as well as maximum acetate accumulation, while increase the H2 component. The increase of discharge resistor could enhance the energy efficiency, while had little impact on the Coulombic efficiency. Good reusability of rechargeable biosensors was observed with an injection of formaldehyde from 0% to 0.05%, but the sensors could not be fully recovered after the injection of 0.1% formaldehyde. The exposure of formaldehyde could affect the relative abundance of Acetobacterium, Acetoanaerobium, and Geobacter. When an abiotic cathode was used, the formate and hydrogen produced during the charging process were converted into acetate as an intermediate product during the discharging process. This study demonstrates the potential of the rechargeable microbial electrochemical system as a novel sensor for water biotoxicity monitoring.

Construction workers are exposed to a range of stressors that lead to mental ill-health. In a multicultural construction workplace, the interactions between workers with different cultural backgrounds may aggravate mental health issues. Existing studies on coping typically focus on a reactive approach to managing stressors in the absence of cultural-related factors. This approach is inadequate in addressing mental health issues in a culturally diverse construction workplace. This paper presents a critical review that synthesizes and analyses theories and models of stress and coping, proactive coping, occupational stress, acculturative stress, and intercultural competence to develop a conceptual model for managing mental health in a multicultural construction workforce. The proposed model relies upon a positive coping mechanism, i.e., intercultural coping, to manage stressful events during the entire coping process in a multicultural workplace, towards achieving sustained good mental health. The proposed conceptual model contributes to the development of coping theories and positive psychology approaches and provides effective coping strategies to enhance psychological well-being in a multicultural context.

Human errors are one of the major contributors of accidents. In order to improve the safety performance, human errors have to be addressed. Human Factors Analysis and Classification System (HFACS) has been developed as an analytical framework for the investigation of the role of human errors in aviation accidents. However, the HFACS framework did not reveal the relationships describing the effect among diverse factors at different levels. Similarly, its interior structure was not exposed. As a result, it is difficult to identify critical paths and key factors. Therefore, an improved Human Factors Analysis and Classification System in the construction industry (I-HFACS) was developed in this study. An analytical I-HFACS mechanism was designed to interpret how activities and decisions made by upper management lead to operator errors and subsequent accidents. Critical paths were highlighted. Similarly, key human factors were identified, that is, “regulatory factors,” “organizational process,” “supervisory violations,” “adverse spiritual state,” “skill underutilization,” “skill-based errors,” and “violations.” Findings provided useful references for the construction industry to improve the safety performance.

Aimed at the joint vibration problem caused by the load change of humanoid flexible joint, a torque compensation control method based on state observer is proposed. By controlling the motor to output a torque increment equivalent to the disturbance torque, the joint torque can quickly balance the load torque and shorten the oscillation process of the elastic element passively adapting to the load change. A state observer for estimating load disturbance torque and motor speed is designed, whose convergence is proved by the Lyapunov function. The control structure of the drive system based on the proportional integral-intergral proportional (PI-IP) speed regulator is established, and the observer output feedforward link is added to the speed regulator to improve the anti-interference ability of the system. The simulation results show that compared with proportional integral differential (PID) control and joint force feedback proportional differential (PD) control, the proposed method can restore the motor speed to stability within 0.6 s after load change and realize joint vibration suppression within 1 s. Besides, the joint speed adjustment time is shortened by about 1.8 s and 0.9 s respectively, which effectively improves the dynamic adjustment ability of the system. Finally, the effectiveness of the proposed method was verified by experiments on an integrated flexible joint testing platform.