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Abstract Recent advancements in machine learning (ML) have revolutionized the field of high-performance materials design. However, developing robust ML models to decipher intricate structure-property relationships in materials remains challenging, primarily due to the limited availability of labeled datasets with well-characterized crystal structures. This is particularly pronounced in materials where functional properties are closely intertwined with their crystallographic symmetry. We introduce a self-supervised probabilistic model (SSPM) that autonomously learns unbiased atomic representations and the likelihood of compounds with given crystal structures, utilizing solely the existing crystal structure data from materials databases. SSPM significantly enhances the performance of downstream ML models by efficient atomic representations and accurately captures the probabilistic relationships between composition and crystal structure. We showcase SSPM’s capability by discovering shape memory alloys (SMAs). Amongst the top 50 predictions, 23 have been confirmed as SMAs either experimentally or theoretically, and a previously unknown SMA candidate, MgAu, has been identified.

Objective The vaginal flora has been reported to be associated with human papillomavirus (HPV) infection. The purpose of this study was to investigate the characteristics of the cervical microbiota in patients with HPV infection and to analyse the changes in the vaginal flora and enzyme profiles in females with HPV infection.Methods We conducted a cross-sectional study involving 206 participants who underwent HPV genotyping, sexually transmitted diseases pathogen testing, cytology examination, and microbiome analysis. Additionally, we collected 115 HPV-negative samples and 48 HPV-positive samples for 16S rRNA amplicon sequencing. The vaginal microbial communities of both groups were analysed for diversity and differences to explore their association with HPV infection.Results The abundance of Lactobacillus was found to be reduced, while Gardnerella vaginalis was significantly more prevalent in the HPV + group. In terms of alpha diversity indices, the Shannon index (P = .0036) and Simpson index (P = .02) were higher in the HPV + group compared to the HPV − group, indicating greater community diversity in the HPV + group. Among the 10 sexually transmitted diseases pathogens analysed, Uup3 and Uup6 were significantly associated with HPV infection. Statistically significant differences were observed in Nugent scores and bacterial vaginosis between the two groups (P

Abstract The chemical recycling of polyester wastes is of great significance for sustainable development, which also provides an opportunity to access various oxygen-containing chemicals, but generally suffers from low efficiency or separation difficulty. Herein, we report anatase TiO2 supported Ru and Mo dual-atom catalysts, which achieve transformation of various polyesters into corresponding diols in 100% selectivity via hydrolysis and subsequent hydrogenation in water under mild conditions (e.g., 160 °C, 4 MPa). Compelling evidence is provided for the coexistence of Ru single-atom and O-bridged Ru and Mo dual-atom sites within this kind of catalysts. It is verified that the Ru single-atom sites activate H2 for hydrogenation of carboxylic acid derived from polyester hydrolysis, and the O-bridged Ru and Mo dual-atom sites suppress hydrodeoxygenation of the resultant alcohols due to a high reaction energy barrier. Notably, this kind of dual-atom catalysts can be regenerated with high activity and stability. This work presents an effective way to reconstruct polyester wastes into valuable diols, which may have promising application potential.

Quantum discord goes beyond entanglement and exists in a wide range of quantum states that may be separable, playing a crucial role in quantum information tasks. In this paper, we firstly proposed a zero-discord criterion for two-qubit system based on the partial transposition of density matrix, and then extended it to the qubit–qudit system. By detailed examples we demonstrate the effectiveness of these criteria in detecting discord. Moreover, we provide an analytical lower bound of geometric quantum discord(GQD) using eigenvalue vectors of density matrix. Finally, we presented a one-way work deficit lower bound based on our lower bound of GQD.

Abstract Background Although it is traditionally believed that ATP binding cassette subfamily C member 2 (ABCC2) is a multidrug resistance‐associated protein correlated with a worse prognosis, our previous and several other studies demonstrated the contrary to be true in gastric cancer (GC). We aim to explore the underlying mechanism of this discovery. Methods Our study utilized whole‐exome sequencing (WES), RNA sequencing, and droplet digital PCR (ddPCR) analysis of 80 gastric cancer samples, along with comprehensive immunohistochemical (IHC) analysis of 1044 human GC tissue samples.By utilizing CRISPRCas9 to genetically modify cell lines with the ABCC2‐24C > T (rs717620) point mutation and conducting dual‐luciferase reporter assays, we identified that transcription factors SOX9 and ETS1 serve as negative regulators of ABCC2 expression. Seahorse assay and mass spectrometry were used to discover altered metabolic patterns. Gain and loss‐of‐function experiments in GC cell lines and preclinical models were carried out to validate ABCC2 biological function. Results ABCC2 high expression correlated with better prognosis, and rs717620 can influence ABCC2 expression by disrupting the binding of ETS1 and SOX9. Gain and loss‐of‐function experiments in GC cell lines demonstrated amino acid deprivation reduces proliferation, migration, and drug resistance in ABCC2‐high GC cells. ABCC2 leads to reduced intracellular amino acid pools and disruption of cellular energy metabolism. This phenomenon depended on ABCC2‐mediated GSH extrusion, resulting in alterations in redox status, thereby increasing the cell's susceptibility to ferroptosis. Furthermore, patient‐derived organoids and patient‐derived tumor‐like cell clusters were used to observe impact of ABCC2 on therapeutic effect. In the xenograft model with high ABCC2 expression, we observed that constricting amino acid intake in conjunction with GPX4 inactivation resulted in notable tumor regression. Conclusions Our findings demonstrate a significant role of ABCC2 in amino acid metabolism and ferroptosis by mediating GSH efflux in GC. This discovery underlines the potential of combining multiple ferroptosis targets as a promising therapeutic strategy for GC with high ABCC2 expression. Highlights ABCC2 plays a crucial role in inducing metabolic vulnerability and ferroptosis in gastric cancer through enhanced glutathione efflux. The ABCC2 24C > T polymorphism is a key factor influencing its expression. These results highlight the potential of ABCC2 as a predictive biomarker and therapeutic target in gastric cancer.

Abstract Background In China, the world’s largest developing country, low back pain (LBP) is a common public health issue affecting workability. This meta-analysis aimed to systematically assess the risk factors of LBP in the Chinese population. Methods Four English language and four Chinese databases were searched, and cross-sectional studies on the risk factors for LBP in Chinese populations were identified and collected. The search timeframe covered the period from the establishment of the database to November 2023. Two researchers independently reviewed the literature, extracted the data, and evaluated the risk of bias. Begg’s and Egger’s tests were used to evaluate publication bias. Results Fifteen cross-sectional studies involving 86,575 people were included. Seven risk factors for LBP were identified. Six risk factors were statistically significant: Cigarette smoking (odds ratio [OR] = 1.55; 95% confidence interval [CI]: 1.15, 2.08, P = 0.004, I2 = 72%), body mass index (BMI) ≥ 28 kg/m² (OR = 4.51; 95% CI: 3.36, 6.07, P

Abstract This letter presented a symmetric 8T2R NVSRAM with autosave function. By efficiently multiplexing the node voltages, the control of the nonvolatile memristor and the isolation of the data node from the memristor are achieved, which ensures an instantaneous transition to the memristor state. Store and restore can be achieved within 66.1ps and 2.97 ps in case of VDD is 1 V for the worst case. In addition, the 8T2R structure performs well at lower supply voltages as 243.3 mV for STORE and 411.8 mV for RESTORE. When a 10%‐dimensional error of the devices and 10% memristance mismatch are taken into account, the 8T2R still shows high stability.

Abstract Threatened animals respond with appropriate defensive behaviors to survive. It has been accepted that midbrain periaqueductal gray (PAG) plays an essential role in the circuitry system and organizes defensive behavioral responses. However, the role and correlation of different PAG subregions in the expression of different defensive behaviors remain largely unexplored. Here, we designed and manufactured a microelectrode array (MEA) to simultaneously detect the activities of dPAG and vPAG neurons in freely behaving rats. To improve the detection performance of the MEAs, PtNP/PEDOT:PSS nanocomposites were modified onto the MEAs. Subsequently, the predator odor was used to induce the rat’s innate fear, and the changes and information transmission in neuronal activities were detected in the dPAG and vPAG. Our results showed that the dPAG and vPAG participated in innate fear, but the activation degree was distinct in different defense behaviors. During flight, neuronal responses were stronger and earlier in the dPAG than the vPAG, while vPAG neurons responded more strongly during freezing. By applying high-performance MEA, it was revealed that neural information spread from the activated dPAG to the weakly activated vPAG. Our research also revealed that dPAG and vPAG neurons exhibited different defensive discharge characteristics, and dPAG neurons participated in the regulation of defense responses with burst-firing patterns. The slow activation and continuous firing of vPAG neurons cooresponded with the regulation of long-term freezing responses. The results demonstrated the important role of PAG neuronal activities in controlling different aspects of defensive behaviors and provided novel insights for investigating defense from the electrophysiological perspective.

With the increasingly complex electromagnetic environment faced by radar, random stepped frequency (RSF) has garnered widespread attention owing to its remarkable Electronic Counter-Countermeasure (ECCM) characteristic, and it has been universally applied in inverse synthetic aperture radar (ISAR) in recent years. However, if the phase error induced by the translational motion of the target in RSF ISAR is not precisely compensated, the imaging result will be defocused. To address this challenge, a novel 2D method based on sparse Bayesian learning, denoted as 2D-autofocusing complex-value inverse-free SBL (2D-AFCIFSBL), is proposed to accomplish joint ISAR imaging and autofocusing for RSF ISAR. First of all, to integrate autofocusing into the ISAR imaging process, phase error estimation is incorporated into the imaging model. Then, we increase the speed of Bayesian inference by relaxing the evidence lower bound (ELBO) to avoid matrix inversion, and we further convert the iterative process into a matrix form to improve the computational efficiency. Finally, the 2D phase error is estimated through maximum likelihood estimation (MLE) in the image reconstruction iteration. Experimental results on both simulated and measured datasets have substantiated the effectiveness and computational efficiency of the proposed 2D joint imaging and autofocusing method.

Birth weight is an indicator linking intrauterine environmental exposures to later-life diseases, and intrauterine metal exposure may affect birth weight in a sex-specific manner. We investigated sex-specific associations between prenatal exposure to metal mixtures and birth weight in a Chinese birth cohort. The birth weight of 1296 boys and 1098 girls were recorded, and 10 metals in maternal urine samples collected during pregnancy were measured using inductively coupled plasma mass spectrometry. Bayesian Kernel Machine Regression was used to estimate the association of individual metals or metal mixtures and birth weight for gestational age (BW for GA). The model showed a sex-specific relationship between prenatal exposure to metal mixtures and BW for GA with a significant negative association in girls and a non-significant positive association in boys. Cadmium (Cd) and nickel (Ni) were positively and negatively associated with BW for GA in girls, respectively. Moreover, increasing thallium (Tl) concentration lowered the positive association between Cd and BW for GA and enhanced the negative association between Ni and BW for GA in girls. When exposure to other metals increased, the positive association with Cd diminished, whereas the negative association with Ni or Tl increased. Our findings provide evidence supporting the complex effects of intrauterine exposure to metal mixtures on the birth weight of girls and further highlight the sex heterogeneity in fetal development influenced by intrauterine environmental factors.

Abstract Grid cells with stable hexagonal firing patterns in the medial entorhinal cortex (MEC) carry the vital function of serving as a metric for the surrounding environment. Whether this mechanism processes only spatial information or involves nonspatial information remains elusive. Here, we fabricated an MEC-shaped microelectrode array (MEA) to detect the variation in neural spikes and local field potentials of the MEC when rats forage in a square enclosure with a planar, three-dimensional object and social landmarks in sequence. The results showed that grid cells exhibited rate remapping under social conditions in which spike firing fields closer to the social landmark had a higher firing rate. Furthermore, global remapping showed that hexagonal firing patterns were rotated and scaled when the planar landmark was replaced with object and social landmarks. In addition, when grid cells were activated, the local field potentials were dominated by the theta band (5–8 Hz), and spike phase locking was observed at troughs of theta oscillations. Our results suggest the pattern separation mechanism of grid cells in which the spatial firing structure and firing rate respond to spatial and social information, respectively, which may provide new insights into how the brain creates a cognitive map.

Dipole approximation is a common simplified method in magnetic field research, which is widely used in magnetic anomaly detection, control of magnetic device and magnetic field experiment. The accuracy of magnetic dipole approximation will determine the upper limit of related applications. Previous studies have shown that the dipole approximation of a typical magnetic dipole simulator (e.g., a solenoid coil) can lead to a positioning error of up to 50% in localization of magnetic object in near field. In order to solve this problem, this paper aims to design a coil structure that fits well with the standard magnetic dipole. Firstly, the structure of cylindrical solenoid with planar symmetry and rotational symmetry is optimized and analyzed. On this basis, a multi-layer solenoid structure with rotational symmetry and plane symmetry is proposed. Then, the coil structure is optimized by gradient descent method, taking the inner and outer radius, height, layer spacing and quantity of the solenoid as variables. Compared with the traditional coil, this coil structure can greatly reduce the error of dipole approximation, and has the advantages of large magnetic moment and small geometric size. Simulation results show that the positioning error percentage can be reduced to less than 0.2% when the new-type coil is tested in the same area.

The problem of a traditional waveguide plasmonic resonator sensor is that part of the near-field intensity enhanced area is confined in the waveguide dielectric layer, which decreases the interaction effect between light and analyte. In order to solve this problem, a novel mid-infrared (MIR) chalcogenide (ChG) slot waveguide plasmonic resonator (SWGPR) sensor embedded with Au nanorods was proposed, where Au nanorods were used as antenna for enhancing mode coupling with the waveguide through resonance at the absorption wavelength of the analyte. The antenna parameters were optimized to make the resonance wavelength align with the absorption wavelength of the analyte. The proposed waveguide structure provides a sufficient sensing area and increases the electric field enhancement factor to > 6400. Polymethyl methacrylate (PMMA) and styrene were adopted as the analyte for sensing performance evaluation. The normalized absorption reaches 23.31 when the maximum extinction coefficient of PMMA is 0.08, which is at least 7 times higher than other silicon-on-insulator (SOI) waveguide plasmonic resonator sensors. The proposed waveguide structure provides a new idea for the design of other waveguide plasmonic resonator sensors with high sensing performance and has the potential for biochemical sensing.

Improving the landscape- and village-integrated green governance (LVIGE) is currently a problem faced by various countries. China has also put forward the revitalization strategy of “rural development, the environment is the background color”. How to judge and evaluate the landscape- and village-integrated green governance (LVIGE) is the main research purpose of this study. This study is based on the rural data from 2012 to 2021 in China to construct an evaluation system, which mainly includes three dimensions: economic production construction, social and cultural construction, and ecological environment construction. This study uses the relevant entropy method to calculate the landscape- and village-integrated green governance (LVIGE), and the following conclusions are drawn: There is a significant difference in the data on the ecological factors among rural areas in various provinces of China, and there is a gap in green governance. Many provinces still do not pay sufficient attention to rural development, especially the problem of rural green governance. Northeast China ranks at the bottom in terms of economic production construction, social and cultural construction, and ecological environment construction with a large gap. The rapid improvement of the landscape- and village-integrated green governance (LVIGE) is inseparable from the national policies. Therefore, to improve the development of the landscape- and village-integrated green governance (LVIGE), not only national policy support is needed, but also the local government should pay full attention to the development of the rural economy, social culture, and ecology, especially the construction of an ecological environment. The construction of the evaluation system of the LVIGE not only corresponds to the national policy, but also promotes the provinces’ attention to the environment.

The neural mechanisms of torpor have essential reference significance for medical methods and long-term manned space. Changes in electrophysiology of suprachiasmatic nucleus (SCN) conduce to revealing the neural mechanisms from the torpor to arousal. Due to the lower physiology state during the torpor, it is a challenge to detect neural activities in vivo on freely behaving mice. Here, we introduced a multichannel microelectrode array (MEA) for real-time detection of local field potential (LFP) and action potential (spike) in the SCN in induced torpor mice. Meanwhile, core body temperature and behaviors of mice were recorded for further analysis. Platinum nanoparticles (PtNPs) and Nafion membrane modified MEA has a lower impedance (16.58 ± 3.93 kΩ) and higher signal-to-noise ratio (S/N = 6.1). We found that from torpor to arousal, the proportion of theta frequency bands of LFPs increased, spike firing rates rapidly increased. These results could all be characteristic information of arousal, supported by the microscopic neural activity promoting arousal in mice. MEA displayed real-time dynamic changes of neuronal activities in the SCN, which was more helpful to analyze and understand neural mechanisms of torpor and arousal. Our study provided a factual basis for the neural state in SCN of induced non-hibernating animals, which was helpful for the application of clinics and spaceflight.

Portable or even on-chip detection of methane (CH4) is significant for environmental protection and production safety. However, optical sensing systems are usually based on discrete optical elements, which makes them unsuitable for the occasions with high portability requirement. In this work, we report on-chip silicon-on-insulator (SOI) waveguide CH4 sensors at 3.291 μm based on two measurement schemes including direct absorption spectroscopy (DAS) and wavelength modulation spectroscopy (WMS). In order to suppress noise, Kalman filter was adopted in signal processing. By optimizing the waveguide cross-section structure, an etch depth of 220 nm was selected with an experimentally high power confinement factor (PCF) of 23% and a low loss of only 0.71 dB/cm. A limit of detection (LoD) of 155 parts-per-million (ppm) by DAS and 78 ppm by WMS at an averaging time of 0.2 s were obtained for a 2 cm-long waveguide sensor. Compared to the chalcogenide (ChG) waveguide CH4 sensors at the same wavelength, the reported sensor reveals the minimum waveguide loss and the lowest LoD. Therefore the SOI waveguide sensor has the potential of on-chip gas sensing in the mid-infrared (MIR) waveband.

Abstract Background In China, post-abortion care (PAC) services mainly focus on married couples, such that adolescents and unmarried young womenhave limited access to those services for contraception counseling. The provision of youth-friendly PAC services in public hospitals is a new concept in China. This study examined the magnitude of PAC services utilization as well as factors influencing it’s uptake among adolescents and young women in Guangzhou, China. Methods A cross-sectional study was performed from 1st March 2020 to 30th September 2020 using anonymous self-administered questionnaire among 688 women aged 15–24 years in Tianhe district, Guangzhou. The Multivariate logistic regression was used to determine factors that were significantly associated with the uptake of PAC services. Results The magnitude of PAC services utilization was 35.9% among adolescents and young women in Guangzhou, China. Students were 69.0% significantly less likely to use PAC services compared to women who had no job. Immigrants were 59.0% significantly less likely to use PAC services than their native counterparts. Women who had a feeling of stigma were 70.0% significantly less likely to use PAC services compared to those who did not feel stigmatized. Conclusions The study highlights the need to strengthen youth-friendly PAC services provision, and emphasizes the importance of education about both family planning and abortion services among disadvantaged sub-groups of women in the study setting.

The detection algorithm commonly misses obscured pedestrians in traffic scenes with a high pedestrian density because mutual occlusion among pedestrians reduces the prediction box score of the concealed pedestrians. The paper uses the YOLOv7 algorithm as the baseline and makes the following three improvements by investigating the variables influencing the detection method’s performance: First, the backbone network of the YOLOv7 algorithm is replaced with the lightweight feature extraction network Mobilenetv3 since the pedestrian detection algorithm frequently needs to be deployed in driverless mobile, which requires a fast operating speed of the algorithm; second, a high-resolution feature pyramid structure is suggested for the issue of missed detection of hidden pedestrians, which upscales the feature maps generated from the feature pyramid to increase the resolution of the output feature maps and introduces shallow feature maps to strengthen the distinctions between adjacent sub-features to enhance the network’s ability to extract features for the visible area of hidden pedestrians and small-sized pedestrians in order to produce deeper features with greater differentiation for pedestrians; and the third is to suggest a detection head based on an attention mechanism that is employed to lower the confidence level of target neighboring sub-features, lower the quantity of redundant detection boxes, and lower the following NMS computation. The mAP of the suggested approach in this work achieves 89.75%, which is 9.5 percentage points better than the YOLOv7 detection algorithm, according to experiments on the CrowdHuman pedestrian-intensive dataset. The algorithm proposed in this paper can considerably increase the detection performance of the detection algorithm, particularly for obscured pedestrians and small-sized pedestrians in the dataset, according to the experimental effect plots.

Insomnia is a common sleep disorder around the world, which is harmful to people’s health, daily life, and work. The paraventricular thalamus (PVT) plays an essential role in the sleep–wake transition. However, high temporal-spatial resolution microdevice technology is lacking for accurate detection and regulation of deep brain nuclei. The means for analyzing sleep–wake mechanisms and treating sleep disorders are limited. To detect the relationship between the PVT and insomnia, we designed and fabricated a special microelectrode array (MEA) to record electrophysiological signals of the PVT for insomnia and control rats. Platinum nanoparticles (PtNPs) were modified onto an MEA, which caused the impedance to decrease and improved the signal-to-noise ratio. We established the model of insomnia in rats and analyzed and compared the neural signals in detail before and after insomnia. In insomnia, the spike firing rate was increased from 5.48 ± 0.28 spike/s to 7.39 ± 0.65 spike/s, and the power of local field potential (LFP) decreased in the delta frequency band and increased in the beta frequency band. Furthermore, the synchronicity between PVT neurons declined, and burst-like firing was observed. Our study found neurons of the PVT were more activated in the insomnia state than in the control state. It also provided an effective MEA to detect the deep brain signals at the cellular level, which conformed with macroscopical LFP and insomnia symptoms. These results laid the foundation for studying PVT and the sleep–wake mechanism and were also helpful for treating sleep disorders.

DNA methyltransferases (DNMT) and histone deacetylases (HDAC) inhibitors are used as cancer epigenome drugs. However, these epigenetic drugs lack targeting specificity and could risk inducing genome instability and the expression of oncogenes. Therefore, there is a need to develop new therapeutic strategies where specific cancer genes can be targeted for silencing or activation. The CRISPR/dCas9 system represents a promising, powerful therapeutic tool because of its simplicity and specificity. Protamine 1 (PRM1) is exclusively expressed in sperm and has a vital role in the tight packaging of DNA, thus inducing transcriptional silencing in sperm cells. We hypothesized that the activation of the PRM1 gene in tumorigenic cells would lead to DNA condensation and reduce the proliferation of these cells. To test our hypothesis, we transfected human embryonic kidney cells 293T with a dCas9-P300 plasmid that adds acetyl groups to the promoter region of PRM1 via specific gRNAs plasmids. RNA-Seq analysis of transfected cells revealed high specificity of targeted gene activation. PRM1 expression resulted in a significant decrease in cell proliferation as measured by the BrdU ELISA assay. To confirm that the activation of PRM1 was due to acetyl groups deposited to H3K27, a ChIP-qPCR was performed. The acetylation of the PRM1 promoter region targeted by dCas9-p300 in transfected cells was higher than that of the control cells. Interestingly, the targeted promoter region for acetylation showed reduced DNA methylation. These findings demonstrate the efficacy of epigenome editing in activating PRM1 in non-expressing tumorigenic cells, which could be used as a promising therapeutic strategy in cancer treatment.

The medial amygdala (MA) plays an important role in the innate fear circuit. However, the electrophysiological mechanism of MA for processing innate fear needs to be further explored. In this study, we fabricated microelectrode arrays (MEAs) with detecting sites arranged to match the location and shape of MA in mice and detected the electrophysiology in freely behaving mice under 2-methyl-2-thiazoline (2MT)-induced fear. The detection performance of MEA is improved by modifying metal nanoparticles and conductive polymers (PtNPs/PEDOT:PSS). After modification, the impedance magnitude and phase of electrodes were decreased to 27.0 ± 2.3 kΩ and −12.30 ± 0.52°, respectively, leading to a signal-to-noise ratio of 10. Its electrochemical stability and mechanical stability were also verified by cyclic voltammetry (CV) sweeping and ultrasonic vibration. MEAs were then implanted into the MA of mice, and the electrophysiology and behavioral characteristics were synchronously recorded and analyzed. The results showed that 2MT induced strong defensive behaviors in mice, accompanied by increases in the average spike firing rate and local field potential (LFP) power of MA neurons. According to principles commonly applied to cortical extracellular recordings, the recorded neurons are divided into two classes based on waveforms. Statistics showed that about 37% of type 1 neurons (putative GABAergic neurons) and 87% of type 2 neurons (putative glutamatergic neurons) were significantly activated under innate fear. At the same time, the firing rate of some activated neurons had a good linear correlation with the freezing rate.

Aiming at solving inaccurate and incomplete extraction of road in remote sensing images, this paper proposes an automatic extraction algorithm based on Rectangle Marked Point Process (RMPP). First, the RMPP is designed to model the road surface, which aims to obtain the centerline and width of road correctly. Secondly, under the framework of Bayesian theory, the proposed road extraction model is built by combining network reconstruction model and spectral measurement model. The former is to constrain the relationships between rectangles according to the structure characteristic of the road. The latter is to constrain the consistency between rectangle and road body in image. Also, to obtain optimal results, related transfer kernels of RJMCMC (Reversible Jump Markov Chain Monte Carlo) based simulation algorithm are designed accordingly. Finally, testing of the proposed method and comparing methods are carried out with different remote sensing datasets. Experimental results from the proposed algorithm show that the completeness, correctness and quality can reach 98%, 94% and 92%, respectively. Compared with the results from the comparing method qualitatively and quantitatively, it can be verified that the proposed method can not only extract the high-quality road networks from different datasets but also can obtain the width of the road simultaneously.

In this invited paper, a compact dense-pattern multipass cell-based near-infrared sensor system was demonstrated for detection of parts-per-billion in volume (ppbv)-level methane (CH4) and ethane (C2H6). The dimension size of the fabricated gas cell is 18.5 × 8 × 9 cm3 with an absorption path length of 9.39 m. CH4 measurement was realized within a spectral range of 6,046–6,048 cm−1 and an absorption line of 6,046.95 cm−1. The spectral range for C2H6 detection is 5,951–5,953 cm−1 with an absorption line of 5,951.73 cm−1. Allan deviation analysis was used for evaluating the dual-gas sensing performance, and a detection limit of 78 ppbv for CH4 and 190 ppbv for C2H6 were achieved, respectively, with an averaging time of 0.8 s. Furthermore, CH4 measurement in the indoor and outdoor atmosphere was both performed to verify the field sensing capability of the sensor system. Compared with two separate sensor systems for CH4/C2H6 sensing, the proposed dual-gas sensor system using two near-infrared lasers and one multipass cell has the advantages of low-cost, compact-size without decreasing the selectivity and sensitivity.

There are approximately 50 million people with epilepsy worldwide, even about 25% of whom cannot be effectively controlled by drugs or surgical treatment. A wireless closed-loop system for epilepsy detection and suppression is proposed in this study. The system is composed of an implantable optrode, wireless recording, wireless energy supply, and a control module. The system can monitor brain electrical activity in real time. When seizures are recognized, the optrode will be turned on. The preset photosensitive caged compounds are activated to inhibit the seizure. When seizures are inhibited or end, the optrode is turned off. The method demonstrates a practical wireless closed-loop epilepsy therapy system.

Fatigued driving is one of the leading causes of traffic accidents, and detecting fatigued driving effectively is critical to improving driving safety. Given the variety and individual variability of the driving surroundings, the drivers’ states of weariness, and the uncertainty of the key characteristic factors, in this paper, we propose a deep-learning-based study of the MAX-MIN driver fatigue detection algorithm. First, the ShuffleNet V2K16 neural network is used for driver face recognition, which eliminates the influence of poor environmental adaptability in fatigue detection; second, ShuffleNet V2K16 is combined with Dlib to obtain the coordinates of driver face feature points; and finally, the values of EAR and MAR are obtained by comparing the first 100 frames of images to EAR-MAX and MAR-MIN. Our proposed method achieves 98.8% precision, 90.2% recall, and 94.3% F-Score in the actual driving scenario application.

The electrophysiological activities of head direction (HD) cells under visual and vestibular input dissociation are important to understanding the formation of the sense of direction in animals. In this paper, we fabricated a PtNPs/PEDOT:PSS-modified MEA to detect changes in the discharge of HD cells under dissociated sensory conditions. The electrode shape was customized for the retrosplenial cortex (RSC) and was conducive to the sequential detection of neurons at different depths in vivo when combined with a microdriver. The recording sites of the electrode were modified with PtNPs/PEDOT:PSS to form a three-dimensional convex structure, leading to closer contact with neurons and improving the detection performance and signal-to-noise ratio of the MEA. We designed a rotating cylindrical arena to separate the visual and vestibular information of the rats and detected the changes in the directional tuning of the HD cells in the RSC. The results showed that after visual and vestibular sensory dissociation, HD cells used visual information to establish newly discharged directions which differed from the original direction. However, with the longer time required to process inconsistent sensory information, the function of the HD system gradually degraded. After recovery, the HD cells reverted to their newly established direction rather than the original direction. The research based on our MEAs revealed how HD cells process dissociated sensory information and contributes to the study of the spatial cognitive navigation mechanism.

Doxorubicin (DOX) is the most clinically important antibiotic in cancer treatment, but its severe cardiotoxicity and other side effects limit its clinical use. Therefore, monitoring DOX concentrations during therapy is essential to improve efficacy and reduce adverse effects. Here, we fabricated a sensitive electrochemical aptasensor for DOX detection. The sensor used gold wire as the working electrode and was modified with reduced graphene oxide (rGO)/gold nanoparticles (AuNPs) to improve the sensitivity. An aptamer was used as the recognition element for the DOX. The 5′ end of the aptamer was modified with a thiol group, and thus immobilized to the AuNPs, and the 3′ end was modified with methylene blue, which acts as the electron mediator. The combination between the aptamer and DOX would produce a binding-induced conformation, which changes the electron transfer rate, yielding a current change that correlates with the concentration of DOX. The aptasensor exhibited good linearity in the DOX concentration range of 0.3 μM to 6 μM, with a detection limit of 0.1 μM. In addition, the aptasensor was used for DOX detection in real samples and results, and showed good recovery. The proposed electrochemical aptasensor will provide a sensitive, fast, simple, and reliable new platform for detecting DOX.

Background and Objectives: This study aims to explore the safety of preoperative chemotherapy and clarify whether preoperative chemotherapy with oxaliplatin + S-1 (SOX) regimen and its adverse events are associated with higher risks of postoperative complications.Methods: We included consecutive patients with gastric cancer who underwent gastrectomy in our department between July 1 2018, and January 31 2020. Patients with preoperative SOX regimen chemotherapy were included in the analysis.Results: In the 343 included patients, 77 cases underwent preoperative chemotherapy. In total, surgical complications were found in 117 patients (34.1%), and there was no significant difference between the patients with and without preoperative chemotherapy before and after propensity score matching (p > 0.05, respectively). Multivariate analysis showed that preoperative comorbidities (p = 0.026) and the preoperative cT4b (p = 0.028) were independent risk factors in postoperative complications. In patients with preoperative chemotherapy, neither the occurrence of adverse events nor their severity was associated with postoperative complications (p > 0.05). However, the patients who received five to six cycles were more prone to postoperative complications than those who received three to four cycles (62.5 vs. 27.9%, OR = 4.306, 95% Cl = 1.282–14.464, p = 0.018).Conclusions: Occurrence of postoperative complications was not influenced by preoperative SOX chemotherapy. However, increased cycles of chemotherapy may lead to higher incidence of postoperative complications.

Enterotoxigenic Escherichia coli (ETEC) is an important cause of post-weaning diarrhea (PWD) worldwide, resulting in huge economic losses to the swine industry worldwide. In this study, to understand the pathogenesis, the transcriptomic analysis was performed to explore the biological processes (BP) in porcine intestinal epithelial J2 cells infected with an emerging ETEC strain isolated from weaned pigs with diarrhea. Under the criteria of |fold change| (FC) ≥ 2 and P < 0.05 with false discovery rate < 0.05, a total of 131 referenced and 19 novel differentially expressed genes (DEGs) were identified after ETEC infection, including 96 upregulated DEGs and 54 downregulated DEGs. The Gene Ontology (GO) analysis of DEGs showed that ETEC evoked BP specifically involved in response to lipopolysaccharide (LPS) and negative regulation of intracellular signal transduction. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that immune response-related pathways were mainly enriched in J2 cells after ETEC infection, in which tumor necrosis factor (TNF), interleukin 17, and mitogen-activated protein kinase (MAPK) signaling pathways possessed the highest rich factor, followed by nucleotide-binding and oligomerization domain-like receptor (NLRs), C-type lectin receptor (CLR), cytokine–cytokine receptor interaction, and Toll-like receptor (TLR), and nuclear factor kappa-B (NF-κB) signaling pathways. Furthermore, 30 of 131 referenced DEGs, especially the nuclear transcription factor AP-1 and NF-κB, participate in the immune response to infection through an integral signal cascade and can be target molecules for prevention and control of enteric ETEC infection by probiotic Lactobacillus reuteri. Our data provide a comprehensive insight into the immune response of porcine intestinal epithelial cells (IECs) to ETEC infection and advance the identification of targets for prevention and control of ETEC-related PWD.

Background: The human copper Cu proteome, also termed Cu-binding proteins (CBP), is responsible for transporting “free” Cu to the cell that is related to cuproptosis. However, their role in gastric cancer (GC) has not been reported. Methods: RNA expression data of 946 GC patients were collected. A series of machine learning and bioinformatic approaches were combined to build a CBP signature to predict survival and immune microenvironment and guide the priority treatment. Immunohistochemistry and multicolor immunofluorescence (mIF) in 1076 resection slides were used to verify immune features. Results: A CBP signature was constructed using the machine learning method from TCGA that classifies cases as CBP_low and CBP_high groups. Multivariable Cox analysis confirmed that the CBP signature was an independent prognostic factor in the training and validation cohorts. Additionally, GC patients with low CBPscores showed an increase in anti-tumor immune microenvironment, which was further verified by mIF in pathological resections following immunotherapy. Importantly, patients with low CBPscores had higher levels of TMB/MSI and responded well to immunotherapy. Conclusions: We conducted the first and comprehensive CBP analysis of GC patients and established a clinically feasible CBP signature for predicting survival and response to treatment, which will be helpful for guiding personalized medicine.

Aiming at the problems of frequent identity switches (IDs) and trajectory interruption of multi-pedestrian tracking algorithms in dense scenes, this paper proposes a multi-pedestrian tracking algorithm based on an attention mechanism and dual data association. First, the FairMOT algorithm is used as a baseline to introduce the feature pyramid network in the CenterNet detection network and up-sampling the output multi-scale fused feature maps, effectively reducing the rate of missed detection of small-sized and obscured pedestrians. The improved channel attention mechanism module is embedded in the CenterNet’s backbone network to improve detection accuracy. Then, a re-identification (ReID) branch is embedded in the head of the detection network, and the two sub-tasks of pedestrian detection and pedestrian apparent feature extraction are combined in a multi-task joint learning approach to output the pedestrian apparent feature vectors while detecting pedestrians, which improves the computational efficiency and localization accuracy of the algorithm. Finally, we propose a dual data association tracking model that tracks by associating almost every detection box instead of only the high-scoring ones. For low-scoring detection boxes, we utilize their similarities with trajectories to recover obscured pedestrians. The experiment using the MOT17 dataset shows that the tracking accuracy is improved by 0.6% compared with the baseline FairMOT algorithm, and the number of switches decreases from 3303 to 2056, which indicates that the proposed algorithm can effectively reduce the number of trajectory interruptions and identity switching.

The authors would like to correct an error in the original publication [...]

Background: Previous studies have demonstrated the embryotoxicity and fetotoxicity of thallium (Tl). However, the effects of prenatal exposure to Tl on birth weight and placental weight and the mediating role of placental weight in the association of Tl with birth weight remain unclear.Methods: We recruited 2,748 participants from the ongoing Prenatal Environment and Offspring Health Cohort (PEOH Cohort) study, which was initiated in 2016 in Guangzhou, China. The Tl concentrations in maternal urine samples collected during the first and third trimester were determined by inductively coupled plasma mass spectrometry. Birth weight and placental weight were extracted from maternal medical records.Results: Pregnant women exposed to the highest tertile of Tl in the first trimester (β = −42.7 g, 95% CI: −82.3, −3.1 g) and third trimester (β = −50.6 g, 95% CI: −99.0, −2.3 g) had babies with lower birth weights than those exposed to the lowest tertile. We also found significant negative associations of exposure to Tl concentrations in the first and third trimester with placental weight. Mediation analyses showed that 50.3% (95% CI: 15.9, 79.2%) and 33.5% (95% CI: 1.3, 80.3%) of the effects of Tl exposure in the first and third trimester on birth weight were mediated by decreased placental weight.Conclusion: Our results suggest that prenatal exposure to Tl is negatively associated with birth weight and that this association may be mediated by decreased placental weight.

Counting the number of wheat ears in images under natural light is an important way to evaluate the crop yield, thus, it is of great significance to modern intelligent agriculture. However, the distribution of wheat ears is dense, so the occlusion and overlap problem appears in almost every wheat image. It is difficult for traditional image processing methods to solve occlusion problem due to the deficiency of high-level semantic features, while existing deep learning based counting methods did not solve the occlusion efficiently. This article proposes an improved EfficientDet-D0 object detection model for wheat ear counting, and focuses on solving occlusion. First, the transfer learning method is employed in the pre-training of the model backbone network to extract the high-level semantic features of wheat ears. Secondly, an image augmentation method Random-Cutout is proposed, in which some rectangles are selected and erased according to the number and size of the wheat ears in the images to simulate occlusion in real wheat images. Finally, convolutional block attention module (CBAM) is adopted into the EfficientDet-D0 model after the backbone, which makes the model refine the features, pay more attention to the wheat ears and suppress other useless background information. Extensive experiments are done by feeding the features to detection layer, showing that the counting accuracy of the improved EfficientDet-D0 model reaches 94%, which is about 2% higher than the original model, and false detection rate is 5.8%, which is the lowest among comparative methods.

A wavelength-locked light-induced thermo-elastic spectroscopy (WL-LITES) gas sensor system was proposed for long-distance in-situ methane (CH4) detection using a fiber-coupled sensing probe. The wavelength-locked scheme was used to speed the sensor response without scanning the laser wavelength across the CH4 absorption line. A small-size piezoelectric quartz tuning fork (QTF) with a wide spectral response range was adopted to enhance the photo-thermal signal. The optical excitation parameters of the QTF were optimized based on experiment and simulation for improving the signal-to-noise ratio of the LITES technique. An Allan deviation analysis was employed to evaluate the limit of detection of the proposed sensor system. With a 0.3 s lock-in integration time and a ∼ 100 m optical fiber, the WL-LITES gas sensor system demonstrates a minimum detection limit (MDL) of ∼ 11 ppm in volume (ppmv) for CH4 detection, and the MDL can be further reduced to ∼ 1 ppmv with an averaging time of ∼ 35 s. A real-time in-situ monitoring of CH4 leakage reveals that the proposed sensor system can realize a fast response (< 12 s) for field application.

Precipitation type is a key parameter used for better retrieval of precipitation characteristics as well as to understand the cloud–convection–precipitation coupling processes. Ice crystals and water droplets inherently exhibit different characteristics in different precipitation regimes (e.g., convection, stratiform), which reflect on satellite remote sensing measurements that help us distinguish them. The Global Precipitation Measurement (GPM) Core Observatory’s microwave imager (GMI) and dual-frequency precipitation radar (DPR) together provide ample information on global precipitation characteristics. As an active sensor, the DPR provides an accurate precipitation type assignment, while passive sensors such as the GMI are traditionally only used for empirical understanding of precipitation regimes. Using collocated precipitation type flags from the DPR as the “truth”, this paper employs machine learning (ML) models to train and test the predictability and accuracy of using passive GMI-only observations together with ancillary information from a reanalysis and GMI surface emissivity retrieval products. Out of six ML models, four simple ones (support vector machine, neural network, random forest, and gradient boosting) and the 1-D convolutional neural network (CNN) model are identified to produce 90–94% prediction accuracy globally for five types of precipitation (convective, stratiform, mixture, no precipitation, and other precipitation), which is much more robust than previous similar effort. One novelty of this work is to introduce data augmentation (subsampling and bootstrapping) to handle extremely unbalanced samples in each category. A careful evaluation of the impact matrices demonstrates that the polarization difference (PD), brightness temperature (Tc) and surface emissivity at high-frequency channels dominate the decision process, which is consistent with the physical understanding of polarized microwave radiative transfer over different surface types, as well as in snow and liquid clouds with different microphysical properties. Furthermore, the view-angle dependency artifact that the DPR’s precipitation flag bears with does not propagate into the conical-viewing GMI retrievals. This work provides a new and promising way for future physics-based ML retrieval algorithm development.

A laser driver which features high stability and a graphical user-interface was designed and used in trace gas sensing. The running of the laser driver was managed by an ARM processor which was embedded with a real-time operating system (RTOS). Through clicking on the touch screen that was configured with an emWin graphical user-interface (GUI), the parameters of the driving current can be graphically set and monitored. The circuit model of the distributed feedback laser diode (DFB-LD) was introduced into a TINA-SPICE simulation to evaluate the performance of the current source. Through simulation, the potential self-oscillation can be visually predicted, and the feedback loop can be appropriately compensated. To validate the applicability, the laser driver was used for driving a carefully selected DFB-LD and was employed in wavelength modulation spectroscopy (WMS) for CH4 detection at R(3) absorption line of the 2ν3 overtone. Under the conditions of room temperature, normal pressure and an effective absorption path of 15.4 cm, repetitive experiments were conducted using gas samples, with their concentrations ranging from 400 ppm to 1%, and the detection limit derived from the signal-to-noise ratio (SNR) was 7.2 ppm. The promising result indicates the high potential of this laser driver for use in absorption spectrum-based sensing applications.

Development of a methane (CH4) sensor system was reported based on a novel quartz-tuning-fork (QTF)-embedded, double-pass, off-beam quartz-enhanced photoacoustic spectroscopy (DP-OB-QEPAS). A simplified and accurate numerical model was presented to optimize the DP-OB-QEPAS spectrophone and to enhance the detection sensitivity. A compact and fiber-coupled acoustic detection module (ADM) with a volume of 3 × 2×1 cm3 and a weight of 9.7 g was fabricated. A continuous-wave distributed feedback diode laser was used to target the CH4 absorption line at 6046.95 cm−1. With the combination of wavelength modulation spectroscopy (WMS) and second harmonic (2f) detection technique, the CH4 sensor system reveals a 1σ detection limit of 8.62 parts-per-million in volume (ppmv) for a 0.3 s averaging time with an optimized modulation depth of 0.26 cm−1. The proposed CH4 sensor shows a similar or even lower level in the normalized noise equivalent absorption coefficient (NNEA) (1.8 × 10−8 cm−1∙W/√Hz), compared to previously reported QEPAS-based CH4 sensors.

Research on the intracerebral mechanism of insomnia induced by serotonin (5-HT) deficiency is indispensable. In order to explore the effect of 5-HT deficiency-induced insomnia on brain regions related to memory in rats, we designed and fabricated a microelectrode array that simultaneously detects the electrical activity of the dorsal raphe nucleus (DRN) and hippocampus in normal, insomnia and recovery rats in vivo. In the DRN and hippocampus of insomnia rats, our results showed that the spike amplitudes decreased by 40.16 and 57.92%, the spike repolarization slope decreased by 44.64 and 48.59%, and the spiking rate increased by 66.81 and 63.40%. On a mesoscopic scale, the increased firing rates of individual neurons led to an increased δ wave power. In the DRN and hippocampus of insomnia rats, the δ wave power increased by 57.57 and 67.75%. Furthermore, two segments’ δ wave slopes were also increased in two brain regions of the insomnia rats. Our findings suggest that 5-HT deficiency causes the hyperactivity of neurons in the hippocampus and DRN; the DRN’s firing rate and the hippocampal neuronal amplitude reflect insomnia in rats more effectively. Further studies on alleviating neurons affected by 5-HT deficiency and on achieving a highly effective treatment for insomnia by the microelectrode array are needed.

Defense is the basic survival mechanism of animals when facing dangers. Previous studies have shown that the midbrain periaqueduct gray (PAG) was essential for the production of defense responses. However, the correlation between the endogenous neuronal activities of the dorsal PAG (dPAG) and different defense behaviors was still unclear. In this article, we designed and manufactured microelectrode arrays (MEAs) whose detection sites were arranged to match the shape and position of dPAG in rats, and modified it with platinum-black nanoparticles to improve the detection performance. Subsequently, we successfully recorded the electrophysiological activities of dPAG neurons via designed MEAs in freely behaving rats before and after exposure to the potent analog of predator odor 2-methyl-2-thiazoline (2-MT). Results demonstrated that 2-MT could cause strong innate fear and a series of defensive behaviors, accompanied by the significantly increased average firing rate and local field potential (LFP) power of neurons in dPAG. We also observed that dPAG participated in different defense behaviors with different degrees of activation, which was significantly stronger in the flight stage. Further analysis showed that the neuronal activities of dPAG neurons were earlier than flight, and the intensity of activation was inversely proportional to the distance from predator odor. Overall, our results indicate that dPAG neuronal activities play a crucial role in controlling different types of predator odor-evoked innate fear/defensive behaviors, and provide some guidance for the prediction of defense behavior.

An electrical-domain self-adaptive mid-infrared absorption spectroscopy for methane detection based on an interband cascade laser was demonstrated. By adding noise into the laser drive signal, denoising and sensing performances were evaluated for the technique. Experiments were made to study the effects of noise level/type on sensor stability, characterized by Allan deviation. High- and low-frequency noise levels have the same functional variation trend on Allan deviation, which differs from white Gaussian noise. Within a noise level range of 0-125 mV for low- and high-frequency noise and 0-62.5 mV for white Gaussian noise in the mercury-cadmium-telluride detector's output (with a pure signal amplitude of ~300 mV), the sensor stability using self-adaptive denoising was enhanced by a factor of 1.05-20, 1.32-6.25, and 1.15-3.33 times compared to that using no filtering, for the three kinds of noise, respectively. The reported self-adaptive methane sensor system shows enhanced stability compared to the direct laser absorption spectroscopy sensor using traditional sensing architecture and classic filtering method. The sensor was further evaluated through outdoor atmospheric methane measurements using such technique. A second-order self-adaptive direct laser absorption spectroscopy technique was also proposed for noise suppression in both optical and electrical domain as an outlook of the concept of this paper.

Abstract Background Although the efficacy of tamoxifen (TAM) for breast cancer has been attributed to inducing cell cycle arrest and apoptosis by inhibiting estrogen receptor (ER) signaling, recent evidence indicates that TAM also possesses ER-independent antitumor activity through an unclear mechanism. The present study investigated the anti-tumor mechanism of TAM on mesenchymal triple-negative breast cancer (TNBC). Methods The inhibitory effect of TAM on tumor migration and metastasis was analyzed by transwell chamber in vitro and by murine xenograft model in vivo. The promoter sequence of miR-200c was predicted by an online CpG island predictor. Relative expression of miR-200c was measured by quantitative real-time PCR. Results After treatment with TAM, mesenchymal TNBC cells (MCF-7/ADR and MDA-MB-231) morphologically changed from mesenchymal to epithelial types. Meanwhile, cell migration ability was also significantly decreased in ER-positive breast cancer cells after exposure to TAM. Consistent with these in-vitro results, TAM significantly suppressed lung metastasis rate of mesenchymal TNBC cells in murine xenograft tumors. miRNA array analysis of two types of breast cancer cells showed that miR-200c expression was inhibited in mesenchymal TNBC cells, but increased after TAM treatment due to demethylation of miR-200c promoters. Conclusions Our results indicate that TAM inhibits cell migration and enhances chemosensitivity of mesenchymal TNBC cells by reversing their EMT-like property; and that this EMT-reversal effect results from upregulation of miR-200c through demethylating its promoter. To our knowledge, this is the first explanation of a non-ER-related mechanism for the effect of TAM on mesenchymal TNBC cells.

The development of an efficient, portable, real-time, and high-precision ammonia (NH3) remote sensor system is of great significance for environmental protection and citizens’ health. We developed a NH3 remote sensor system based on tunable diode laser absorption spectroscopy (TDLAS) technique to measure the NH3 leakage. In order to eliminate the interference of water vapor on NH3 detection, the wavelength-locked wavelength modulation spectroscopy technique was adopted to stabilize the output wavelength of the laser at 6612.7 cm−1, which significantly increased the sampling frequency of the sensor system. To solve the problem in that the light intensity received by the detector keeps changing, the 2f/1f signal processing technique was adopted. The practical application results proved that the 2f/1f signal processing technique had a satisfactory suppression effect on the signal fluctuation caused by distance changing. Using Allan deviation analysis, we determined the stability and limit of detection (LoD). The system could reach a LoD of 16.6 ppm·m at an average time of 2.8 s, and a LoD of 0.5 ppm·m at an optimum averaging time of 778.4 s. Finally, the measurement result of simulated ammonia leakage verified that the ammonia remote sensor system could meet the need for ammonia leakage detection in the industrial production process.

Silver nanoparticles (AgNPs) were synthesized with wheat straw biomass at room temperature using light irradiation. The reaction conditions were optimized, including the light intensity, biomass concentration, NaCl addition, and reaction time. The silver nanoparticles fabricated at the optimum conditions (light intensity 60,000 lx, biomass concentration 2 mg/mL, and reaction time 90 min) were characterized by UV-Vis spectroscopy, X-ray diffraction (XRD), transmission electron microscopy (TEM), Fourier transform infrared spectroscopy (FTIR), and zeta potential. The TEM results showed that the silver nanoparticles were mostly spherical, with an average diameter of 17.2 nm. The zeta potential of AgNPs reached -21.6 mV. The XRD spectra showed that the AgNPs were highly crystalline, with four characteristic peaks. The FTIR of nanoparticles implied that alcohols and proteins may have a vital role in the formation and stability of AgNPs. The silver nanoparticles synthesized by wheat straw biomass revealed antimicrobial activity against Escherichia coli and Bacillus subtilis strains.

The detection of neuroelectrophysiology while performing optogenetic modulation can provide more reliable and useful information for neural research. In this study, an optical fiber and a microelectrode array were integrated through hot-melt adhesive bonding, which combined optogenetics and electrophysiological detection technology to achieve neuromodulation and neuronal activity recording. We carried out the experiments on the activation and electrophysiological detection of infected neurons at the depth range of 900–1250 μm in the brain which covers hippocampal CA1 and a part of the upper cortical area, analyzed a possible local inhibition circuit by combining opotogenetic modulation and electrophysiological characteristics and explored the effects of different optical patterns and light powers on the neuromodulation. It was found that optogenetics, combined with neural recording technology, could provide more information and ideas for neural circuit recognition. In this study, the optical stimulation with low frequency and large duty cycle induces more intense neuronal activity and larger light power induced more action potentials of neurons within a certain power range (1.032 mW–1.584 mW). The present study provided an efficient method for the detection and modulation of neurons in vivo and an effective tool to study neural circuit in the brain.

The largest number of cybersecurity attacks is on web applications, in which Cross-Site Scripting (XSS) is the most popular way. The code audit is the main method to avoid the damage of XSS at the source code level. However, there are numerous limits implementing manual audits and rule-based audit tools. In the age of big data, it is a new research field to assist the manual auditing through machine learning. In this paper, we propose a new way to audit the XSS vulnerability in PHP source code snippets based on a PHP code parsing tool and the machine learning algorithm. We analyzed the operation sequence of source code and built a model to acquire the information that is most closely related to the XSS attack in the data stream. The method proposed can significantly improve the recall rate of vulnerability samples. Compared with related audit methods, our method has high reusability and excellent performance. Our classification model achieved an F1 score of 0.92, a recall rate of 0.98 (vulnerable sample), and an area under curve (AUC) of 0.97 on the test dataset.

Prediction of oscillating pressure is a key technology for cavity research. Nonlinear Acoustic Solver (NLAS) is applied to analyze aeroacoustics recently. A nonlinear numerical solver is combined with the Reynolds-averaged Navier-Stokes (RANS) method. RANS is applied to solving the flow field around a cavity, and average solution of initial turbulent statistics is obtained which contains the basic characteristics of the average flow field and statistic description of turbulence fluctuation. The source of acoustic generation is reconstructed, and the spreading of oscillating pressure is simulated precisely. According to the comparison of the cavity noise calculation and experimental results under Mach numbers 0.6, 0.85, and 1.35, it indicates that NLAS is capable to predict oscillating pressure of cavity flow from subsonic to supersonic with acceptable deviation. On this basis, the contribution to oscillating pressure suppression made by passive control such as rectangular fence (RF) and square tooth spoiler (STS) is investigated. It is found that these two passive control methods can lessen the total noise.

By contrast with the widely reported traditional two mirror-based Herriott cell, a three mirror-based dense pattern gas cell was proposed, of which the modeling and design were proven to be effective through a comparison between the simulated spot pattern and effective path length and those of the experimental results. A mechanical structure was designed to adjust the position/angle of the three mirrors for aligning the optical path. The experimentally measured reflection number was 60, resulting in an optical path length of ~11 m, which agrees well with the theoretical value of 10.95 m. Combined with a near-infrared laser with a center wavenumber located at an acetylene (C2H2) absorption line of 6521.2 cm−1, a C2H2 sensor system was established to verify the feasibility of the three mirror-based gas cell. Assisted by a data acquisition (DAQ) card, a LabVIEW platform was developed to generate the drive signal of the laser and acquire the second harmonic (2f) signal from the output of the detector. Through Allan variance analysis, the limit of detection (LoD) of the sensor system is 4.36 ppm at an average time of 0.5 s; as the average time exceeds 10 s, the LoD is

In this study, a micro converter for driving a piezoelectric actuator is designed and implemented. The converter can produce 100 V, 80 Hz AC voltage from 3.7 V DC voltage. With regard to the requirements of micro mobile robots, the main contributions of this study are the design and implementation of a circuit topology supplying power for micro mobile robots at low power and the miniaturization of this topology to make it suitable for driving a centimeter-level robot. The 91 mg mass (excluding printed circuit board mass), 14 × 12 × 4 mm size, and 84.6% efficiency of the converter indicate that this circuit could be applied in micro mobile robots driven by piezoelectric actuators.