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Background Rapid diagnosis of microbes in the burn wound is a big challenge in the medical field. Traditional biochemical detection techniques take hours or days to identify the species of contaminating and drug-resistant microbes. Near-infrared spectroscopy (NIRS) is evaluated to address the need for a fast and sensitive method for the detection of bacterial contamination in liquids. Methods Herin, we developed a novel technique which by using NIRS together with supporting vector machine (SVM), to identify the microbial species and drug-resistant microbes in LB medium, and to diagnose the wound colonization and wound infection models of pigs. Results The device could recognize 100% of seven kinds of microbes and 99.47% of the multi-drug resistant Staphylococcus aureus (S. aureus), with a concentration of 109 cfu ml−1 in LB medium. The accuracy of the microbial identification in colonized and infected wounds in-situ was 100%. The detection limit of NIRS with SVM for the detection of S. aureus and Escherichia coli (E. coli) was 101 cfu ml−1 in LB medium. Identification time was less than 5 s. Conclusion Our findings validate for the first time a novel technique aimed at the rapid, noncontacted, highly sensitive, and specific recognition of several microbial species including drug-resistant ones. This technique could represent a promising approach to identify diverse microbial species and a potential bedside device to rapidly diagnose infected wounds.

Objective To observe the influence of moxibustion on learning and memory ability in the rats with vascular dementia (VD) and explore the potential effect mechanism. Methods A total of 80 rats, screened by Morris water maze, were randomly divided into a sham-operation group, a model group, a neural stem cells (NSCs) group, a NSCs + piracetam group and a NSCs + moxibustion group, 16 rats in each group. After corresponding treatments, Morris water maze and immunofluorescence technique were adopted to evaluate the therapeutic effect respectively. Results Comparison among groups after modeling: compared with the sham-operation group, the escape latency was longer (P Conclusion Moxibustion improves the spatial learning and memory ability of the VD rats and promotes the reconstruction of neurogenesis and synaptic function, which may be related to the up-regulation of the expressions of hippocampus NR2B and PKMζ expressions.

With the emergence of the concept of “safe city”, security construction has gradually been valued by various cities, and video surveillance technology has also been continuously developed and applied. However, as the functional requirements of actual applications become more and more diverse, video surveillance systems also need to be more intelligent. The purpose of this article is to study methods of brute force detection and face recognition based on deep learning. Aiming at the problem of abnormal behavior detection, especially the low efficiency and low accuracy of brute force detection, a brute force detection method based on the combination of convolutional neural network and trajectory is proposed. This method uses artificial features and depth features to extract the spatiotemporal features of the video through a convolutional neural network and combines them with the trajectory features. In view of the problem that face images in surveillance video cannot be accurately recognized due to low resolution, two models are proposed: the multi-foot input CNN model and the SPP-based CNN model. By testing the performance of the brute force detection method proposed in this paper, the accuracy of the method on the Crow and Hockey datasets is as high as 92% and 97.6%, respectively. Experimental results show that the violence detection method proposed in this paper improves the accuracy of violence detection in video.

Image classification is a hot research topic in today's society and an important direction in the field of image processing research. SVM is a very powerful classification model in machine learning. CNN is a type of feedforward neural network that includes convolution calculation and has a deep structure. It is one of the representative algorithms of deep learning. Taking SVM and CNN as examples, this paper compares and analyzes the traditional machine learning and deep learning image classification algorithms. This study found that when using a large sample mnist dataset, the accuracy of SVM is 0.88 and the accuracy of CNN is 0.98; when using a small sample COREL1000 dataset, the accuracy of SVM is 0.86 and the accuracy of CNN is 0.83. The experimental results in this paper show that traditional machine learning has a better solution effect on small sample data sets, and deep learning framework has higher recognition accuracy on large sample data sets.

To study the tensile strength and failure mechanisms of rock with hydro-thermal coupling damage under different loading rates, a series of static and dynamic splitting tests were conducted on thermally treated sandstone under dry and water-saturated conditions. Experimental results showed that high temperatures effectively weakened the tensile strength of sandstone specimens, and the P-wave velocity declined with increasing temperature. Overall, thermal damage of rock increased gradually with increasing temperature, but obvious negative damage appeared at the temperature of 100 °C. The water-saturated sandstone specimens had lower indirect tensile strength than the dry ones, which indicated that water−rock interaction led to secondary damage in heat-treated rock. Under both dry and water-saturated conditions, the dynamic tensile strength of sandstone increased with the increase of strain rate. The water-saturated rock specimens showed stronger rate dependence than the dry ones, but the loading rate sensitivity of thermally treated rock decreased with increasing treatment temperature. With the help of scanning electron microscopy technology, the thermal fractures of rock, caused by extreme temperature, were analyzed. Hydro-physical mechanisms of sandstone under different loading rate conditions after heat treatment were further discussed.

This study tests whether and how top executives’ preference for integrity affects product quality, using manually collected data for executive birthplace and media coverage related to food quality. We find, using ordered logistic regressions and ordinary least squares based on propensity score matching, that a preference for integrity among food industry executives has a positive effect on food quality. Further, executive power significantly regulates this effect. Valuing integrity helps top executives to overcome the temptation to misuse power. Thus, a concentration of power among executives in the Chinese food companies plays a positive role in propagating integrity within the firms they lead, further strengthening the inhibitory effect on quality failure and the positive effect on quality and safety. Finally, we find that internal control is a channel through which the top executives’ preference for integrity can positively influence product quality.

Rapid urbanization changes landscape patterns and results in frequent urban waterlogging issues, which affect citizens' daily lives and cause economic loss. Understanding the spatial patterns and impact factors associated with urban waterlogging under different rainfall intensities has significant implications for mitigating this hazard. In this study, the runoff depth calculated according to the Storm Water Management Model (SWMM) simulation results was used to investigate the spatial characteristics of urban waterlogging. Multiple scenario-based designs, a correlation analysis, and a stepwise regression model were employed to detect the relationship between surface runoff depth and landscape patterns under different rainfall intensities. The results show that when the rainfall intensity reached 12.5 mm/12 h, the conversion rate of rainfall to runoff increased significantly, indicating an increased waterlogging risk. Areas with impervious surface proportions of 25-50% and 75-100% were shown to require more attention due to the strong sensitivity of the surface runoff depth to an increase in the impervious surface. It is most cost-effective to maintain the original high-density vegetation or increase the vegetation density from 0-25% to 25-50% for urban green space. Additionally, the landscape configuration also affects the surface runoff depth. The fragmented, scattered, or regular shape of impervious surface patches can reduce surface runoff effectively; larger and less fragmented green space was also shown to have a surface runoff controlling. The adjusted R

Photoelectrochemical water splitting can convert solar energy into clean hydrogen energy for storage. It is desirable to explore non-precious electrocatalysts for practical applications of a photoelectrode in a large scale. Here, we developed a facile spin-coating and in-situ photoelectrochemical reduction method to prepare a dispersed Cu electrocatalyst on a Si photocathode, which improves the performance remarkably. We find that thiourea in the precursor solution for spin-coating plays an important role in obtaining dispersed Cu particles on the surface of a Si photoelectrode. With thiourea in the precursor, the Cu/Si photocathode shows higher performance than the one without thiourea. Moreover, the Cu/Si photocathode also indicates good stability after 16 h illumination.

The coagulation mechanism for removing particles by Al13 has been extensively investigated for water treatments. It was widely accepted that Al13 played important roles in coagulation mainly by charge neutralization and electrostatic patch. However, the discovery of Al13 aggregates (Al13agg) in flocs indicated that the real coagulation process should be different from the previous understanding, including when Al13agg were generated and how it interacted with negative particles. The aggregation process of Al13 during coagulation and its micro-interfacial effect on particle coagulation remains to be explored. In this study, to investigate the aggregation of Al13 and its effect on coagulation performance, two parallel coagulation jar tests were conducted on silica suspensions by preformed Al13agg and Al13, respectively. The results showed that optimized coagulation for particle removal by Al13 occurred from pH 7 to pH 9, which was dominated by the in-situ aggregation of Al13. The results confirmed that Al13agg were both present in flocs generated in two tests, however, the morphology and distribution of surface Al of flocs were different for two tests. The in-situ formed Al13agg covered all over the silica particles in flocs, resulting in compact structure with rough surfaces, while the preformed Al13agg mainly distributed on joint sites between particles, generating denser flocs with smooth surfaces. This difference verified that the in-situ aggregation of Al13 was the key factor to optimized particle coagulation. The overall optimized particle coagulation by Al13 should undergo the following pathway: charge neutralization - in-situ aggregation of Al13 - inter-particle bridging.

Proposed in the late 1980s, cumulative absolute velocity (CAV) is a new intensity measure for earthquake ground motion characterizations, followed by studies and applications such as CAV ground motion prediction equations (GMPEs). In this study, two new CAV GMPEs were developed with 24,667 strong-motion records from Taiwan, and the first CAV seismic hazard assessment for Taipei (the most important city in Taiwan) was then conducted using the local CAV models. It shows that the annual rate for the study area to encounter a ground motion with CAV >0.97 g-sec is 0.002 per year, corresponding to a 10% occurrence probability in 50 years. By contrast, the deterministic scenario-based analysis shows that the CAV seismic hazard is about 0.60 g-sec for the study area. Future studies are worth conducting to develop more sophisticated, local CAV GPMEs and to explore more applications of such CAV prediction models, such as the developments of PGA-CAV joint probability distributions for conducting PGA-CAV joint seismic hazard assessments.

Cellular senescence is a mechanism by which cells permanently withdraw from the cell cycle in response to stresses including telomere shortening, DNA damage, or oncogenic signaling. Senescent cells contribute to both age-related degeneration and hyperplastic pathologies, including cancer. In culture, normal human epithelial cells enter senescence after a limited number of cell divisions, known as replicative senescence. Here, to investigate how metabolic pathways regulate replicative senescence, we used LC-MS–based metabolomics to analyze senescent primary human mammary epithelial cells (HMECs). We did not observe significant changes in glucose uptake or lactate secretion in senescent HMECs. However, analysis of intracellular metabolite pool sizes indicated that senescent cells exhibit depletion of metabolites from nucleotide synthesis pathways. Furthermore, stable isotope tracing with13C-labeled glucose or glutamine revealed a dramatic blockage of flux of these two metabolites into nucleotide synthesis pathways in senescent HMECs. To test whether cellular immortalization would reverse these observations, we expressed telomerase in HMECs. In addition to preventing senescence, telomerase expression maintained metabolic flux from glucose into nucleotide synthesis pathways. Finally, we investigated whether inhibition of nucleotide synthesis in proliferating HMECs is sufficient to induce senescence. In proliferating HMECs, both pharmacological and genetic inhibition of ribonucleotide reductase regulatory subunit M2 (RRM2), a rate-limiting enzyme in dNTP synthesis, induced premature senescence with concomitantly decreased metabolic flux from glucose into nucleotide synthesis. Taken together, our results suggest that nucleotide synthesis inhibition plays a causative role in the establishment of replicative senescence in HMECs.

Background & Aims Advanced liver disease, which includes fibrosis and cirrhosis, has been reported to be more prevalent in Hispanics patients at the time of diagnosis of chronic hepatitis C virus (HCV) infection than non-Hispanic black or non-Hispanic white patients. We performed a propensity score-matched analysis to determine whether metabolic risk factors contribute to this disparity. Methods We collected data from persons with 748 HCV infection (22% Hispanic, 53% non-Hispanic black, and 26% non-Hispanic white; 23% with advanced liver disease), born from 1945 through 1965, diagnosed at 6 health care systems in Texas. Advanced liver disease was defined as a FIB-4 index score above 3.25. We examined the association between advanced liver disease and race or ethnicity, metabolic risk (based on diabetes mellitus and body mass index [BMI]) and heavy alcohol use in propensity score-matched analyses. Results In propensity-score matched models, among those who were obese (BMI ≥30) with a diagnosis of diabetes, the adjusted odds ratio of advanced liver disease for Hispanics vs non-Hispanic black was 7.89 (95% CI, 3.66–17.01) and adjusted odds ratio = 12.49 (95% CI, 3.24–48.18) for Hispanic vs non-Hispanic white patients (both P Conclusions HCV-infected Hispanics with obesity and diabetes have a far higher risk for advanced liver disease than other racial or ethnic groups. These findings highlight the need for HCV treatment and management of probable concurrent fatty liver disease. Even after we accounted for metabolic risk factors, Hispanics were still at higher risk for advanced liver disease, indicating the potential involvement of other factors such as genetic variants.

A method was developed for preparing high purity Al30O8(OH)56(H2O)2418 + (Al30) through elimination of impurities by complexation. Polyaluminum chloride II (PAC30) with Alc content of 75% was adopted as the source of Al30. The PAC30 was prepared under conditions of total aluminum concentration 0.1 mol/L and OH−/Al ratio 2.2 to obtain the highest content of Al30. A precipitation/metathesis method, organic solvent precipitation method and organic complexation method were examined to separate and purify Al30. It was found that only by the organic complexation method could high purity Al30 products be obtained in large yield economically. In the experiments, benzoic acid was used as the coordinating reagent to decompose the main impurity AlO4Al12(OH)24(H2O)127 + (Al13), and the Al30 product could be obtained by precipitation and metathesis operations. It was noteworthy that the decomposition of impurities by benzoic acid could be completed in 2 hr. The Al30 product was characterized by Ferron assay, 27Al-NMR, SEM, XRD and TGA. The results showed that the purity of the Al30 product could exceed 92%.

The binding energy of enzyme and substrate is used to lower the activation energy for the catalytic reaction. 3α-HSD/CR uses remote binding interactions to accelerate the reaction of androsterone with NAD+. Here, we examine the enthalpic and entropic components of the remote binding energy in the 3α-HSD/CR-catalyzed reaction of NAD+ with androsterone versus the substrate analogs, 2-decalol and cyclohexanol, by analyzing the temperature-dependent kinetic parameters through steady-state kinetics. The effects of temperature on kcat/Km for 3α-HSD/CR acting on androsterone, 2-decalol, and cyclohexanol show the reactions are entropically favorable but enthalpically unfavorable. Thermodynamic analysis from the temperature-dependent values of Km and kcat shows the binding of the E-NAD+ complex with either 2-decalol or cyclohexanol to form the ternary complex is endothermic and entropy-driven, and the subsequent conversion to the transition state is both enthalpically and entropically unfavorable. Hence, solvation entropy may play an important role in the binding process through both the desolvation of the solute molecules and the release of bound water molecules from the active site into bulk solvent. As compared to the thermodynamic parameters of 3α-HSD/CR acting on cyclohexanol, the hydrophobic interaction of the B-ring of steroids with the active site of 3α-HSD/CR contributes to catalysis by increasing exclusively the entropy of activation (ΔTΔS‡ = 1.8 kcal/mol), while the BCD-ring of androsterone significantly lowers ΔΔH‡ by 10.4 kcal/mol with a slight entropic penalty of −1.9 kcal/mol. Therefore, the remote non-reacting sites of androsterone may induce a conformational change of the substrate binding loop with an entropic cost for better interaction with the transition state to decrease the enthalpy of activation, significantly increasing catalytic efficiency.

In this study, a Standard Operating Procedure (SOP) for the large-scale extraction, enrichment, and separation of suffruticosol B (SB), trans-ε-Viniferin (TV), trans-gnetin H (TG) from oil tree peony seeds shell (PSS) was successfully constructed. The ultrasonic-assisted extraction (UAE), macroporous adsorption resin (MAR), and column chromatography (CC) were employed to extract, enrich and separate SB, TV and TG from PSS, and the conditions were optimized. The results implied that SB (1.6937 g), TV (0.5884 g) and TG (3.8786 g) with the purity of 99.67 %, 99.32 % and 98.54 %, respectively, were obtained after the extraction, enrichment and separation. The total yields of the SB, TV and TG were 0.61 mg/g, 0.02 mg/g and 6.64 mg/g with the total extraction rates at 70.55 %, 69.77 % and 78.36 %, respectively. This is the first report on the large-scale extraction, enrichment and separation of oligostilbenes. The SOP in this paper could produce high purity SB, TV and TG, and provide a new idea for PSS as a new oligostilbene resource. The study expands the new development and research field of PSS and provides theoretical support for the green utilization of oil tree peony.

Butyrylcholinesterase (BChE) is an important biomarker in serum, and aberrant BChE activity indicates onset and progression of human diseases. The duration of serum storage at -80 °C may introduce variability into and compromise the reproducibility of BChE activity measurements.We collected serum samples from eight healthy volunteers and determined serum BChE activity in these samples using a sensitive fluorescence assay at various time points during a six-month storage period at -80 °C. Changes in averaged BChE activity over storage time were assessed by repeated measures analysis of variance (ANOVA). Sidak multiple comparisons test was also used to perform post-hoc analysis.Almost all determined BChE activity values lay within the normal physiological range of BChE activity. However, repeated measures ANOVA using mean BChE activity vs. storage time showed that BChE activity values from two time points were significantly different. Analysis by Sidak multiple comparisons test provided no substantial change of BChE activity during the first 90 days of storage, but BChE activity noticeably decreased after 90 days.Serum samples stored in -80 °C for up to 90 days can be exploited to accurately determine BChE activity.

A recent meta-analysis has shown inconclusive results on the effectiveness of traditional electroencephalography (EEG) neurofeedback training (NFT) protocols in changing EEG activity and improving sports performance. To enhance the effectiveness of EEG NFT protocols, we explored a new approach to EEG NFT, namely the functionspecific instruction (FSI) approach. The basic tenet underpinning effective verbal instruction is to induce mental states as the verbal instructions consider the meaning of the brainwave function in the target region and the EEG power magnitude. This study aimed to test whether a single session of FSI is efficacious in improving frontal midline theta (FMT) activity and putting performance. Method: Thirty-six skilled golfers with a handicap of 14.05 +/- 9.43 were recruited. A consecutive sampling method was used to form three groups: an FSI group (n = 12), a traditional instruction (TI) group (n = 12), and a sham control (SC) group (n = 12). In the pre- and posttests, each participant performed 40 putts from a distance of 3 m, and the number of holed putts was recorded. The participants were asked to perform 50 trials in a single session of NFT. Putting performance improved significantly from before to after NFT in the FSI group. Moreover, the FSI group demonstrated a significant decrease in FMT power, whereas the SC group demonstrated a significant increase in FMT power from before to after NFT. These findings suggest that the FSI approach is more effective in enhancing sustained attention and putting performance in skilled golfers than TI.

Objective: To assess the influencing factors, especially BMI level contributing to the cardiovascular benefits of more intensive LDL-C lowering strategy. Methods: We systematically searched MEDLINE, Cochrane Central Register of Controlled Trials, Web of Science, ClinicalTrials and Embase for randomized controlled trials of statins, ezetimibe, proprotein convertase subtilisin-kexin type 9 inhibitors, ATP Citrate Lyase inhibitors published before April, 2021. Results: A total of 263787 participants from 33 trials were included. BMI level, baseline LDL-C level and type of lipid-lowering agents are the main factors affecting the cardiovascular benefits from more intensive LDL-C lowering strategies. Among them, the influence of BMI is more prominent. Each 1kg/m2 increase in BMI level reduced the benefit of cardiovascular mortality by 8% (RR 1.08, 95% CI 1.03-1.13), and this effect still exists when only statins are used as the LDL-C lowering strategy. The same trend was also found in myocardial infarction (RR 1.06, 95% CI 1.01-1.11) and revascularization events (RR 1.06, 95% CI 1.02-1.10) by 6%, respectively. Compared to 44% reduction of cardiovascular mortality when the BMI level was less than 25kg/m2 (RR 0.56, 95%CI 0.36-0.86), the reduction gradually vanished as the BMI increased, no benefit of cardiovascular mortality was found when the BMI was higher than 28kg/m2, this cut point is 29kg/m2 in myocardial infarction and 30kg/m2 in revascularization events. Conclusions: With the increase of BMI level, some cardiovascular benefits of intensive LDL-C lowering strategy gradually vanished. Funding Information: This work was partially supported by the National Natural Science Foundation of China (No. 81570732, Shaohua Wang and No. 81870568, Shaohua Wang). Declaration of Interests: The authors declare that they have no competing interests.

Pathological examination of microscopic image of Pap smear slide remains the main method for cervical cancer diagnosis. The accurate segmentation and classification of images are two important phases of the analysis. Firstly, the Mean-Shift clustering algorithm is applied to obtain regions of interest (ROI) for cell nuclei segmentation. Then the flexible mathematical morphology is applied to split overlapped cell nuclei for better accuracy and robustness. For classification of the images, features based on shape, textural features based on color space and Gabor features are extracted and put together to obtain better classification performance. The optimal feature set is obtained by chain-like agent genetic algorithm (CAGA), P-value and maximum relevance-minimum multicollinearity (MRmMC). The proposed segmentation and classification methods were tested on 362 cervical Pap smear images. Experimental results showed that the cervical cell nuclei can be segmented by the proposed segmentation method with high effective segmentation results (Sensitivity: 94.25%±1.03% and Specificity 93.45%±1.14%). The feature selection method based on CAGA with Gabor features has the highest classification performance for normal, uninvolved and abnormal images (more than 96% accuracy). The proposed method can automatically and effectively segment cell nuclei of microscopic images. From the experimental results, Gabor features and feature selection based on CAGA are apparently helpful for improving the performance of classification.

Extreme cold events have always been great threats to the major rice-cultivation areas across China. The spatial pattern of rice exposure to cold stress (ECS) is critical to develop countrywide adaptation strategies. Under climate change, whether and how ECS spatial pattern has changed? These answers are urgently required for adaptation optimization, but regrettably remain unclear. Here, we examined the changes in rice-planted area exposed to cold stress across mainland China, and historical movements of the geographical centroids of rice ECS over 1980–2015. The results showed that in the single rice cultivation of northeast China and the Yunan-Guizhou plateau, the area exposed to cold stress has shrunk significantly and the centroid moved northward since the 1980s. The southern parts of the mid-lower reaches of Yangtze River witnessed a continuous decrease in the area exposed to cold stress from the 1980s to 2000s, but a large expansion over the 2010s. In south China, the areas exposed to cold stress mainly gathered in the northern parts and showed large variations since the 1980s. These two regions dominant by double rice have witnessed westward movements of ECS centroids over the past decades.

As an aspartic protease, β-site APP cleaving enzyme 1 (BACE1) can efficiently cleave amyloid precursor protein (APP) to produce amyloid beta (Aβ), a chief constituent of senile plaques in Alzheimer's disease. Thus, BACE1 inhibitor is identified as a therapeutic candidate for AD. However, recent failures of clinical trials using BACE1 inhibitors emphasized that comprehensively understanding of BACE1 function is particularly important. Kv2.1, a potassium channel, modulates potassium current in cortical neurons and potassium efflux is a requisite event in the process of cell apoptosis. Previously we showed that BACE2 cleaves Kv2.1 and reduces neuronal apoptosis. Our study here showed that BACE1 cleaves Kv2.1, and results in decreased I

This paper presents a new copula-based earthquake early warning (EEW) decision-making strategy, aiming to characterize missed-alarm and false-alarm probabilities for an on-site EEW and determine an optimum threshold at which EEW should be set off with the lowest missed-alarm and false-alarm probabilities combined. On the basis of an existing PD3-PGV (PD3: peak ground displacement within the first three seconds after P-wave arrives; PGV: peak ground velocity) on-site EEW, the analysis shows that a copula model consisting of the Lognormal distribution, Weibull distribution, and Frank copula can satisfactorily model the PD3-PGV joint probability distribution. Accordingly, the optimum PD3 triggering thresholds for different PGV warning thresholds from 5 to 35 cm/s are presented for future references in the use of the PD3-PGV on-site EEW with maximum reliability.