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To enhance the precision of predicting short-term traffic volumes within urban road systems, a novel approach propelled by spatiotemporal data is introduced in this paper. Initially, the method employs grey correlation analysis to dissect intricate nonlinear relationships inherent in short-term traffic flow data across both temporal and spatial axes of urban road networks. Subsequently, the data is segmented and undergoes greyscale transformation to yield processed inputs. These inputs are then subjected to training via an Extreme Learning Machine (ELM) neural network, culminating in the derivation of predictive outcomes through the computation of optimal output weights, thus fulfilling the objective of short-term traffic flow predicting. Empirical evidence indicates that this methodology surpasses conventional techniques in terms of both predictive accuracy and expedited predicting duration. The predictions generated align closely with the observed traffic flow patterns. [ABSTRACT FROM AUTHOR]

To further enhance the accuracy and efficiency of traffic accident prediction, an improved support vector machine (SVM)-based approach is introduced. This method utilizes an encoding-decoding architecture to capture temporal data characteristics. Additionally, a spatial domain-based graph convolution operator is devised to address the issue of limited spatial connectivity between nodes, thereby extracting spatial features and furnishing reliable inputs for subsequent predictions. Leveraging the nonlinear nature of SVM models, a tailored traffic accident prediction model is constructed. To guarantee prediction precision, the ant lion algorithm is employed to refine the crucial parameters of the SVM model, bolstering its performance. The acquired time series prediction outcomes and spatial feature extractions are integrated to accomplish traffic accident prediction. The results show that the prediction time error result of the proposed method can always maintain below 0.8, the prediction position error result is less than ± 80cm, and the average prediction time is only 1.837s, which shows that the proposed method has high accuracy and efficiency of traffic accident prediction, and can provide strong support for traffic management and planning. [ABSTRACT FROM AUTHOR]

Accurate fatigue driving recognition is vital for road safety, preventing accidents caused by driver exhaustion, and protecting lives. To address the challenges of inadequate accuracy in driver feature extraction, limited precision in fatigue recognition, and prolonged processing time in conventional truck driver fatigue detection systems, the paper propose a novel fatigue driving recognition of truck drivers based on multi-feature fusion. Firstly, this scheme utilizes specialized acquisition equipment to accurately capture images of truck drivers, and corrects lighting inconsistencies through two-dimensional gamma functions; Then, the image is denoised using a dual neighborhood median filtering algorithm; Subsequently, the features extracted from the driver's eyes, mouth, and head were effectively integrated into an extreme learning machine framework to achieve accurate driver fatigue classification. Experimental results demonstrate the effectiveness of new approach, achieving a peak feature extraction accuracy of 98.74%, a maximum recognition accuracy of 98.56%, and a time efficiency ranging from 0 to 0.53 seconds. [ABSTRACT FROM AUTHOR]

The spread of antimicrobial-resistant bacteria is a significant concern, as it can lead to increased morbidity and mortality in both humans and animals. Whole-genome sequencing (WGS) is a powerful tool that can be used to conduct a comprehensive analysis of the genetic basis of antimicrobial resistance (AMR). We compared the phenotypic and genotypic AMR profiles of 97 Salmonella isolates derived from chicken and turkey diagnostic samples. We focused AMR analysis on 5 antimicrobial classes: aminoglycoside, beta-lactam, phenicol, tetracycline, and trimethoprim. The overall sensitivity and specificity of WGS in predicting phenotypic antimicrobial resistance in the Salmonella isolates were 93.4% and 99.8%, respectively. There were 16 disagreement instances, including 15 that were phenotypically resistant but genotypically susceptible; the other instance involved phenotypic susceptibility but genotypic resistance. Of the isolates examined, 67 of 97 (69%) carried at least 1 resistance gene, with 1 isolate carrying as many as 12 resistance genes. Of the 31 AMR genes analyzed, 16 were identified as aminoglycoside-resistance genes, followed by 4 beta-lactam–resistance, 3 tetracycline-resistance, 2 sulfonamide-resistance, and 1 each of fosfomycin-, quinolone-, phenicol-, trimethoprim-, bleomycin-, and colistin-resistance genes. Most of the resistance genes found were located on plasmids. [ABSTRACT FROM AUTHOR]

The Zr55Cu30Al10Ni5 amorphous alloy with thickness 0.5 mm and width of 75 mm was fabricated by twin-roll casting. Due to high rolling force, the alloy exhibited high energy state, high free volume and microstructure inhomogeneity. However, the friction property is not clear because of excellent plasticity and high free volume. The present study tested the friction property of the alloy by rotating pin-on-disk method and investigated the friction behavior and wear mechanism. Besides, the abrasive resistance was improved by subsequent annealing treatment. The results show that the wear mechanisms are mainly abrasive wear, adhesion wear, delamination wear and fatigue wear. The wear law is in accordance with the Archard's empirical wear law. The structural stability and uniformity of that cast strip can be increased by annealing the cast strip at the glass transition temperature. Meanwhile, the wear resistance of the amorphous alloy is improved, and the wear rate in the annealed state is reduced to 88.7 percent of that in the as-cast state, so that abrasive resistance is improved. This study provides a little theoretical basis for amorphous alloy as wear-resistant material and expands the application of amorphous alloy in engineering materials. [ABSTRACT FROM AUTHOR]

Eu3+/Tb3+-co-doped CaWO4 phosphors were synthesized by a simple green co-precipitation process. The structure of the samples was investigated by X-ray diffraction. The photoluminescence spectra and fluorescence decay lifetimes of the samples were measured to investigate the luminescence properties. We analyzed the energy transfer process between Eu3+- and Tb3+-doped CaWO4. As the Tb3+ to Eu3+ energy transfer process was confirmed, Eu3+- and Tb3+-co-doped CaWO4 phosphors showed a color-tunable emission from green to red under a 365-nm UV lamp. [ABSTRACT FROM AUTHOR]

In the present study, various groove casing treatments were evaluated under a high-speed subsonic axial flow compressor using experimental and numerical simulation methods. The aim of this study was to explore the effect of inclination of grooves on compressor stability and performance. The potential flow mechanisms were also evaluated. Three different inclination grooves were designed in this study: grooves with no inclination, grooves with 30 degrees upstream inclination and grooves with 30 degrees downstream inclination. Similar effect of the grooves on the compressor stability and efficiency was observed under experimental and numerical analyses. The grooves with no inclination, 30 degrees upstream inclination and 30 degrees downstream inclination enhanced stall margin by 6.08%, 8.74% and 3.03%, respectively. The peak efficiency losses of the three types of grooves were 1.62%, 0.94% and 2.33%, respectively. Tip flow field analyses demonstrated that the radial transport effect caused by grooves effectively reduced tip loads and alleviated tip blockage. This explains why the grooves enhanced the compressor stability. The radial transport effect was enhanced, and a larger stall margin improvement was obtained when grooves inclined upstream were applied. The tip flow loss was the dominant loss observed after grooves were applied on the compressor. The grooves with upstream inclination markedly reduced the tip flow loss, indicating that they exhibited the lowest effect on reducing compressor efficiency compared with the other types of grooves. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To explore the effect of polyethylene glycol loxenatide (long-acting GLP-1R agonist) on the lipid, glucose levels, and weight in type 2 diabetes mellitus patients with obesity. PATIENTS AND METHODS: A total of 40 obese patients with type 2 diabetes mellitus in our hospital from July 2019 to June 2020 were randomly divided into a control group and a study group. The study group was treated with metformin and polyethylene glycol loxenatide injection, while the control group was treated with metformin. RESULTS: Before treatment, there was no significant difference in FPG (Fasting Blood Glucose) and PPG (Post Prandial Glycaemia) levels between the study group and the control group (p>0.05). After a treatment period, the FPG and PPG levels in the study group were significantly lower than those in the control group (p<0.05). With the longer treatment time, the patient's weight and BMI were lower (p<0.05). The weight and BMI of patients changed the least after one month of treatment, and the weight and BMI changed the most after more than seven months of treatment. After a period of treatment, the levels of FPG and PPG in the blood of male patients in the study group were significantly lower than those of female patients (p<0.05). After treatment, the TG level of the study group was significantly lower than that of the control group (p<0.05). In comparison, the HDL-C level was significantly higher than that of the control group (p<0.05). CONCLUSIONS: Lipid and glucose levels of type 2 diabetes mellitus patients with obesity have decreased after 12 weeks of polyethylene glycol loxanatide use. The weight of type 2 diabetes mellitus patients with obesity has changed after using polyethylene glycol loxenatide for a period of treatment. Among them, there is a certain relationship between body weight and treatment time, gender, and original body weight, which is worthy of further research and promotion in clinical practice. [ABSTRACT FROM AUTHOR]

Wheat yellow-green mutant Jimai5265yg has a more efficient photosynthetic system and higher productivity than its wild type under N-deficient conditions. To understand the relationship between photosynthetic properties and the grain yield, we conducted a field experiment under different N application levels. Compared to wild type, the Jimai5265yg flag leaves had higher mesophyll conductance, photosynthetic N-use efficiency, and photorespiration in the field without N application. Chlorophyll a fluorescence analysis showed that PSII was more sensitive to photoinhibition due to lower nonphotochemical quenching (NPQ) and higher nonregulated heat dissipation. In N-deficient condition, the PSI acceptor side of Jimai5265yg was less reduced. We proposed that the photoinhibited PSII protected PSI from over-reduction through downregulation of electron transport. PCA analysis also indicated that PSI photoprotection and electron transport regulation were closely associated with grain yield. Our results suggested that the photoprotection mechanism of PSI independent of NPQ was critical for crop productivity. [ABSTRACT FROM AUTHOR]