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This work aims to analyze the passivation and pitting corrosion behaviors of laser beam welded R60702 zirconium alloy in neutral and acidic chloride‐containing electrolytes. Potentiodynamic polarization and electrochemical impedance spectroscopy measurements are carried out to investigate the electrochemical performance of the welding joint. Scanning electron microscope, X‐ray diffraction, and three‐dimensional profile digital microscope are utilized to reveal the microstructures and corrosion morphologies. The electrochemical results show that the heat‐affected zone (HAZ) and weld zone have nearly equal corrosion performance, and both of them are more corrosion‐resistant than the base metal. The corrosion morphologies suggest that the HAZ has the lowest sensitivity to pitting corrosion. Moreover, it is unraveled that, in chloride‐containing electrolytes, the quantity and distribution of Zr(Fe,Cr)2 particle phases are the main factors that determine the different corrosion performances of the welding joint. [ABSTRACT FROM AUTHOR]

The µW‐level power density of flexible piezoelectric energy harvesters (FPEHs) restricts their potential in applications related to high‐power multifunctional wearable devices. To overcome this challenge, a hierarchical design strategy is proposed by forming porous piezoceramics with an optimum microstructure into an ordered macroscopic array structure to enable the construction of high performance FPEHs. The porous piezoceramic elements allows optimization of the sensing and harvesting Figure of merit, and the array structure causes a high level of effective strain under a mechanical load. The introduction of a network of polymer channels between the piezoceramic array also provides increased device flexibility, thereby allowing the device to attach and conform to the curved contours of the human body. The unique hierarchical piezoceramic array architecture exhibits superior flexibility, a high open circuit voltage (618 V), high short circuit current (188 µA), and ultrahigh power density (19.1 mW cm−2). This energy density value surpasses previously reported high‐performance FPEHs. The ultrahigh power flexible harvesting can charge a 0.1 F supercapacitor at 2.5 Hz to power high‐power electronic devices. Finally, the FPEH is employed in two novel applications related to fracture healing monitoring and self‐powered wireless position tracking in extreme environments. [ABSTRACT FROM AUTHOR]

The reaction HO + SO → H + SO2 (Rt) and its reverse (R‐t) play an important role in environment and the combustion of sulfur‐containing fuels. However, their kinetics is of high uncertainty as its reaction profile is complicated with multiple deep complexes and channels. In this work, the kinetics and mechanisms of Rt and R‐t are studied comprehensively based on a newly developed full‐dimensional accurate potential energy surface (PES) with the aid of machine learning. This highly accurate PES is interfaced with the software Gaussian. Then reliable information, including the energy, structures, and vibrational frequencies of the stationary points, as well as the minimum energy path and variational analysis can be efficiently determined. The variational transition state theory (VTST) and Rice−Ramsperger−Kassel−Marcus (RRKM) theory are employed to obtain the rate coefficients of each elementary reaction. The temperature‐ and pressure‐dependent rate coefficients of Rt are derived by the RRKM‐based master equation with hindered rotor and free rotor model considered. In addition, the effect of isotope substitution for the hydrogen is investigated on the reaction kinetics. Meanwhile, the quasi‐classical trajectory (QCT) calculation is performed on the PES‐2020 to obtain the temperature‐dependent reaction kinetics. [ABSTRACT FROM AUTHOR]

With the increase of large shopping malls, there are many large parking spaces in complex environments, which increases the difficulty of finding vehicles in such environments. To upgrade the consumer's experience, some car manufacturers have proposed detecting parking space numbers in parking spaces. The detection of parking space number in parking spaces in complex environments has problems such as the diversified background of parking space numbers, tilted direction of parking space numbers, and small parking space number scale. Since no scholar has proposed a high‐performance method for such problems, a parking space number detection model based on the multi‐branch convolutional attention is presented. Firstly, using ResNet50 as the backbone network, a multi‐branch convolutional structure is proposed in the backbone network, which aims to process and fuse the feature map through three parallel branches, and enhance the network to represent ability information by convolutional attention, learn global features to selectively strengthen the features containing helpful information, and improve the ability of the model to detect the parking space number area. Secondly, a high‐level feature enhancement unit is designed to adjust the features channel by channel, obtain more spatial correlation, and reduce the loss of information in the process of feature map generation. The data results of the model on the parking space number dataset CCAG show that the precision, recall, and F‐measure are 84.8%, 84.6%, and 84.7%, respectively, which has certain advantages for parking space number detection. [ABSTRACT FROM AUTHOR]

Target detection based on remotely sensed images, which has recently attracted much attention, is a fundamental but challenging task. In remote sensing images, the problem of difficult recognition of small targets or targets with a large aspect ratio arises because the targets have the characteristics of small proportion, dense distribution, and multidirectionality. To address the above problems, this article proposes an improved multiscale feature cross‐layer fusion remote sensing target detector based on YOLOv5. First, this method introduces the circular smooth label technique, using YOLOv5 as a rotation detector to solve the angular boundary condition and angle prediction problem for large aspect ratio targets. Second, the explicit visual centre module is introduced to solve the problem of missed detection in target‐dense distribution tasks. Finally, a multiscale feature cross‐layer fusion structure (S‐160) is proposed based on YOLOv5, which improves the detection accuracy of each scale target by fusing shallow and deep feature information and introduces new large‐scale features for small target detection to solve the problem that ultrasmall targets in remote sensing images cannot be recognised. Our experiments were conducted on three public remote sensing datasets, DOTA, DIOR‐R, and HRSC2016, and the average accuracy (mAP) on the datasets was 76.50%, 70.34%, and 97.68%, respectively, demonstrating the substantial detection performance of the proposed method. [ABSTRACT FROM AUTHOR]

Previous studies have explored effects of the conscious processing of emotional information on the interaction between emotion and executive control. However, the conscious processing of emotional information introduces "defensive responses," which might limit the emotional effect. To avoid the limitations, this study aimed to explore the effect of automatic emotional processing on response inhibition among heroin abstainers. Individuals experiencing heroin withdrawal symptoms are not entirely exempt from the influence of drugs, and it is challenging to find heroin addicts in practice. Therefore, similar to previous studies, we recruited heroin abstainers in this study. In Experiment 1, for the heroin abstainers group, 30 participants meeting the inclusion criteria were recruited from a compulsory isolated detoxification center, whereas 30 age‐ and education‐matched participants were recruited from the community as the control group. These participants completed the Go/No‐Go task by supraliminal emotional priming. In Experiment 2, the heroin abstainers group comprised 33 eligible participants and control group comprised 33 eligible participants. These participants completed the Go/No‐Go task by subliminal emotional priming. We compared the participants' rates of commission errors in the Go/No‐Go tasks. The rate of commission errors was lowest upon the activation of positive emotion. Moreover, under subliminal emotional priming, the rate of commission errors for the heroin abstainers group was significantly lower than that for the control group. However, regarding supraliminal emotional priming, there was no significant difference between the rates of commission errors for the two groups. These results suggest automatic positive emotional processing can enhance response inhibition among heroin abstainers. Moreover, under subliminal emotional priming, heroin abstainers had more enhanced response inhibition than the control groups. This study plays a significant role in understanding the effect of automatic emotional processing on response inhibition among drug addicts. This study also provides a theoretical basis for ensuring enhanced response inhibition among drug addicts. [ABSTRACT FROM AUTHOR]

Objectives: Traditional manual drilling during hip fracture fixation can easily lead to unstable fixation and vascular damage. This study aimed to investigate a safe and easy‐to‐use robot‐assisted method to automatically drill bone and distinguish critical bone drilling states with high accuracy in real‐time for the bone hole‐making process during hip fracture fixation. Methods: A bone‐drilling robotic system was designed to automatically create holes in the femoral neck. Four fresh pig femurs were drilled at the posterosuperior femoral neck using three modes: "all‐in" (AI), "in‐out‐in" (IOI), and "percutaneous fixation" (PF). A high‐frequency accelerometer captured the generated vibrations of the drill handle, which were then transferred to a personal computer using a data acquisition card. Five bone drilling states are defined, including: "drill idling," "initial drilling," "in the cancellous bone," "out the femoral neck," and "in the cortical bone." The harmonic distribution of the vibration signal was extracted by fast Fourier transform (FFT) and used as a critical feature to identify different drilling states. To prove the difference in the harmonic distribution at different drilling states, an independent sample t‐test was used to compare the percentage of the first harmonic amplitude in the first 10 harmonics at each drilling state. A neural network classifier was trained with the frequency spectrum as the input and the drilled state as the output to distinguish the critical bone drilling states with high accuracy in real‐time. The classifier was trained and tested on four specimens to ensure that the surgical robot could accurately identify the five drilling states. Results: In each specimen, the harmonic distributions of the drilling vibration at different drilling modes were significantly different (p < 0.05). The average recognition accuracies of the drilling state for the four specimens were all higher than 84%. The three defined modes were distinguished with extremely high accuracies. The recognition accuracies of "in the cancellous bone" for specimens 1 to 4 were 83.2%, 84.8%, 92.9%, and 84.7%. The recognition accuracies of "in out the femoral neck" from specimens 1 to 4 are 98.2%, 88.4%, 95.8%, and 88.8%. The recognition accuracies of "in the cortical bone" for specimens 1 to 4 were 94.6%, 80.8%, 95.5%, and 85.8%. Conclusions: The proposed robot‐assisted method can automatically distinguish five critical bone‐drilling states with high accuracy in real‐time to avoid weak fixation and damage to the lateral epiphyseal artery. [ABSTRACT FROM AUTHOR]

Strong blood adhesion to dressing may cause secondary damage to the wounds during the wound dressing replacement process. Thus, blood repellent dressings have significant potential applications in wound treatment. Herein, a hydrophobic, degradable, and antibacterial dressing is reported to reduce the blood adhesion and prevent infection around the wounds. The dressing is prepared by cross‐linked non‐woven zein nanofibers with quaternized titanium dioxide (TiO2) nanoparticles coating. The dual hydrophobic structures supported by zein nanofibers and the quaternized TiO2 nanoparticles coating provide outstanding water/blood repellency for the dressing, and efficiently prevent blood leakage. Meanwhile, the dressing also possesses appropriate moisture permeability (2194 ± 143 mL m−2 per day). In addition, the quaternized TiO2 nanoparticles coating provides excellent bactericidal activity against Gram‐negative Escherichia coli O157:H7 and Gram‐positive Staphylococcus aureus, especially under visible Xe lamp illumination. Evaluations of hemolysis and cytocompatibility confirm that the fabricated mat is biocompatible and non‐toxic to the cells. Considering the excellent degradable features, the dressing may become a promising environmentally friendly biomedical material. [ABSTRACT FROM AUTHOR]

Dynamic in‐plane compression of asymmetric metal corrugated sandwich columns is conducted analytically and numerically. The initial collapse modes of the asymmetric sandwich columns are observed and identified, i.e., elastic face wrinkling, plastic face wrinkling, macro plastic buckling, and macro elastic buckling. The collapse mechanism maps are conducted for asymmetric metal corrugated sandwich columns under the dynamic in‐plane compression. The analytical collapse mechanism map captures numerical results compressed at velocity V = 1 m s−1 reasonably. It is shown that velocity has a significant effect on the deformation mode of asymmetric metal corrugated sandwich columns under the dynamic in‐plane compression. The ratio of the thickness of top and bottom face sheets has the effect on the dominant deformation modes of the metal corrugated sandwich columns to some extent and has an insignificant effect on the collapse loads of metal corrugated sandwich columns. [ABSTRACT FROM AUTHOR]

A series of silicon-containing derivatives of linear alicyclic musks comprising sila-Rosamusk ( 3b), sila-Romandolide ( 5b), sila-Applelide ( 11b), and the corresponding dehydro derivatives was synthesized from sila-analogs of Artemone and Herbac, respectively, by means of sodium borohydride reduction and subsequent esterification with the corresponding acid chlorides in the presence of triethylamine. The olfactory properties of the new sila-odorants 3b- 13b are reported in comparison with their carba-analogs 3a- 13a, and quantitative threshold data allowed the generation of an improved musk olfactophore model featuring a correlation of 80.5 % with a null-cost distance of 244. This olfactophore model shows that it is likely that linear and macrocyclic musks address the same odorant receptors, and it should facilitate the design of new musks. [ABSTRACT FROM AUTHOR]

Si-Artemone ( 4a), Si-β-Dynascone ( 5a), and Si-Herbac 6a, which are Si analogues of the commercial fragrance ingredients Artemone ( 1), β-Dynascone ( 2), and Herbac ( 3), were synthesized expediently by the insertion of terminal alkynes into silacyclobutane 7a. The sensory characterization results revealed that 4a and 6a had quite similar odor qualities compared with those of 1 and 3, whereas 5a had a totally different odor character relative to that of 2. In terms of the odor threshold values, that of 4a was slightly more substantive than that of its carbon analogue 1, 6a was less potent than its carbon analogue 3, whereas that of 5a was approximately one-sixth that of its carbon analogue 2. [ABSTRACT FROM AUTHOR]

Tobacco-specific N-nitrosamines (TSNAs), including N′-nitrosonornicotine, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone, N′-nitrosoanatabine, and N′-nitrosoanabasine, have been implicated as a source of carcinogenicity in tobacco and cigarette smoke. We present a rapid and effective method comprising SPE based on tetraazacalix[2]arene[2]triazine-modified silica as sorbent and analysis with HPLC-MS/MS for the determination of TSNAs and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), a metabolite of 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone, in rabbit plasma. The linear dynamic ranges were 10-2000 pg/mL for NNAL and 4-2000 pg/mL for the four TSNAs with good correlation coefficients (>0.9965). The LODs were in the range of 0.9-3.7 pg/mL, and the LOQs were between 2.9 and 12.3 pg/mL. The accuracies of the method were also evaluated and found to be in the range of 90.1-113.3%. This method is promising to be applied to the preconcentration and determination of TSNAs and NNAL in smoke and human body fluids. [ABSTRACT FROM AUTHOR]

It is difficult to effectively predict remaining useful life (RUL) due to limited training samples and lack of life labels in some operating conditions of practical engineering. When existing deep learning methods predict the RUL of equipment in such operating conditions using a model trained on other operating conditions, the poor generalization of the model caused by large distribution differences cannot be ignored. In this study, an RUL prediction method based on integrated dilated convolution transfer is proposed. This method jointly adjusts the model parameters by inverting the loss function of the RUL prediction module and the domain adaptive module, and then realizes the extraction of domain‐invariant features between different operating condition data through the feature extraction module, which provides support for transfer RUL prediction between different operating conditions. In the feature extraction module, a one‐dimensional convolution network with a large‐size kernel reduces noise in the original data, which reduces the erroneous effect of noise on the trending expression of the original data, and a hybrid dilated convolution network extracts the features of the different sensory fields of the noise‐reduced data, which increases the richness of the extracted features and thus improves the accuracy of the modeling. Next, the extracted features are fed into the RUL prediction module to predict RUL; into the classification model in the domain adaptation module to divide the source and target domains; and into the distribution difference measurement model in the domain adaptation module to identify the feature distribution differences between the source and target domains, and inversely adjust the model parameters by reducing the distribution differences. Furthermore, domain invariant characteristics of the features in different receptive fields under multiple operating conditions are obtained to enhance the model's generalization ability and achieve RUL prediction across various operating conditions. Monte Carlo (MC) dropout simulation technology is used to quantify the uncertainty of prediction results. Finally, the effectiveness and superiority of the proposed method are verified using the prognostics and health management (PHM) 2012 bearing dataset. [ABSTRACT FROM AUTHOR]