Quality Grade Research Articles

The relationship between perceptions of instruction quality, intrinsic motivation, and reading achievement: a longitudinal analysis

ABSTRACT This study including 3,089 students from 173 secondary schools explored the changes in students’ perception of classroom management and goal clarity throughout early adolescence (Grades 5 to 9) and its relationship with learning outcomes such as intrinsic motivation and school grade in reading. The results revealed: 1) Students’ perception of instruction quality, intrinsic motivation and school grade decreased over the years; 2) intrinsic motivation influenced classroom management perception, whereas the relationships between the classroom management perception and school grade were reciprocal; 3) the influence of goal clarity perception on intrinsic motivation changed over the years, and a positive influence on outcomes was only observed between Grades 8 and 9; 4) there were different results between male and female students as well as between academic and vocational tracks. The findings have implications for understanding the possible contextual factors related to the decrease in learning outcomes for reading in secondary schools.

Qingxiangxing Baijiu sensory quality grade classification by 1H NMR and GC combined with multivariate statistical analysis

The traditional uniform artificial sensory evaluation makes it difficult to standardize the classification of different sensory quality grades of Baijiu. In this study, a total of 92 authentic Qingxiangxing Baijiu samples with 3 sensory quality grades were carefully collected. Gas chromatography (GC) was used to determine 46 main flavor components and proton nuclear magnetic resonance (1H NMR) spectroscopy was employed to obtain hydrogen atom characteristic information of organic compounds. The principal component analysis (PCA), k-nearest neighbor (KNN) and linear discriminant analysis (LDA) models were conducted and fully validated by internal leave-one-out cross validation (LOOCV) and external repeated double random cross validation (RDRCV). The sensory quality grades of Qingxiangxing Baijiu were effectively classified by using GC and 1H NMR techniques coupled with PCA/KNN analysis with the averaged accuracy higher than 80%. In addition, synthetic minority oversampling technique (SMOTE) algorithm was successfully used to address the model overfitting problem caused by an unbalanced sample composition. This study demonstrated that 1H NMR and GC combined with multivariate statistical analysis were effective for sensory quality classification of Qingxiangxing Baijiu.

Automotive Grade WLCSP for Radar Applications

Wafer-Level Chip Scale Packages (WLCSPs) are becoming commonplace in the industry due to their small form factor. Applications include industrial and automotive which demand high reliability performance. Additionally, WLCSPs may be superior in some implementations to other package options for RF performance in the mmWave spectrum, which is desired for automotive radar application. In this study the industry’s first auto grade 1 capable large WLCSP package. (~ 72 mm2 body size, 18x15 BGA array, 0.5 mm pitch) will be presented. It will be demonstrated how extensive design enhancements, predictive simulations, careful package materials and process selection and assembly process optimization studies are required to develop a robust package solution. Multiple assembly process experiments and corner studies were conducted to demonstrate robustness of WLCSP package solution to meet automotive grade quality and reliability requirements. Both component/unit level and board level reliability was evaluated as per AECQ100 standards. Robustness margins were confirmed through reliability testing performed up to 2-3x reliability requirements.

Analyzing and comparising capacity of glucose- and uric acid-lowering effects of yellow tea with different varieties and grades in zebrafish model

Abstract: The glucose-lowering effects (GLE) and uric acid-lowering effects (UALE) of tea have been widely reported, but the differences in quality and activity of different varieties and grades (DVG) are still unknown. Herein, yellow tea (YT) were chosen, and in this study the effects of YT with DVG on GLE and UALE were investigated and comparised in zebrafish with diabetes and hyperuricemia, and the mechanism of action were deeply researched. Results showed that there were distinct differences in GLE and UALE of YT with DVG after zebrafish evaluation. The GLE and UALE of population cultivar with all different grades were relatively better than that of special early species. The GLE of bud tea and small tea was better than that of large tea. The UALE of small tea was better than that of large tea and then better than that of bud tea. The differences in GLE and UALE may be related to the content levels of phenols because the GLE and UALE was significantly reduced when phenols directly removed from YT solution. Regression analysis revealed that the highest GLE and UALE does not require the highest or lowest content of each phenolic substance, but depend on what components.

A study on the development and the application strategy of FT-MIRS-based models for the diagnosis of subclinical mastitis and milk quality classification in buffaloes

Buffalo mastitis detection and buffalo milk quality are of great importance to the world dairy industry. Somatic cell count (SCC) can be employed to assess mammary gland health and milk quality in dairy cows, but SCC detection is costly, and the detection instrument is expensive. The purpose of this study was to develop high and low SCC identification models using Fourier-transform mid-infrared spectrum (FT-MIRS), which could be used to diagnose subclinical mastitis (SCM) in buffalo and to determine the milk quality grade at a low cost. The dataset contained 899 buffalo milk samples collected from two regions in China. Firstly, the samples were divided into positive group above the threshold (SCM or unqualified milk) and negative group below the threshold (healthy or qualified milk) with SCC = 200 × 103 cells/mL (SCM in buffalo), 400 × 103 cells/mL (EU standard for raw cow milk, ES), 500 × 103 cells/mL (Indian standard for raw buffalo milk, IS), and 750 × 103 cells/mL (US standard for raw cow milk, US) as thresholds, respectively. Then, with FT-MIRS as predictive variables, predictive models were developed using Partial Least Squares Discriminant Analysis (PLSDA), Random Forest (RF), and Gradient Boosting Machine (GBM). The main results were as follows: the AUCval of the diagnostic model of SCM in buffalo using SCM criteria as a threshold was 0.84 (PLSDA). The AUCval values of the three buffalo milk quality classification models with ES, IS, and US as thresholds were 0.76 (PLSDA), 0.78 (GBM), and 0.84 (PLSDA), respectively. The predictive models established in this paper had a weak predictive ability for positive samples, and the “stepwise discriminant analysis” was recommended to improve the model application effect: The models were applied to classify samples as positive and negative, and then the samples with higher predictive probability were selected. Finally, the remaining samples were further differentiated using the reference methods of SCC detection. To conclude, FT-MIRS has the potential to predict buffalo mammary gland health status and buffalo milk quality grade, reduce the cost of SCC detection, and improve work efficiency, which will lay the foundation for rapid buffalo milk quality classification by raw milk regulatory authorities and rapid diagnosis of SCM in buffalo by farms.

Dynamic Simulation of Land Use and Habitat Quality Assessment in Baiyangdian Basin Using the SD-PLUS Coupled Model

The physical foundation and environmental assurance provided by the regional habitat are crucial for the survival and sustainable development of organisms. Land use change, as a significant manifestation of human activity, is a crucial factor in habitat quality. An SD-PLUS coupled model was developed to simulate land use change in the Baiyangdian(BYD) Basin using data on land use, socio-economic factors, and the climatic environment from 2000 to 2020. The InVEST model was employed to assess the habitat quality of the basin from 2000 to 2050. The findings indicated the following: Between 2020 and 2050, the predominant land use changes across the three scenarios involve the conversion of farmland to construction land and grassland to woodland. The magnitude of these changes steadily declines over time. The magnitude of change in land use for all kinds was greater under SSP5 compared to SSP1 and SSP2. The movement of habitat quality grades primarily occurred from higher grades to lower grades. In 2050, the habitat quality is projected to improve compared to 2020 under three different scenarios. The highest improvement is expected in SSP5 with a 0.60% increase, followed by SSP2 with a 0.42% increase and SSP1 with the smallest increase of 0.23%.

Discussion on the mechanism of Danggui Sini decoction in treating diabetic foot based on network pharmacology and molecular docking and verification of the curative effect by meta-analysis.

The main active components and mechanism of Danggui Sini decoction (DSD) in treating diabetic foot (DF) were studied and verified by network pharmacology and molecular docking. Evidence-based medicine was used to prove its efficacy. The TCMSP systematic pharmacology platform screened out DSD's practical components and targets-screening disease targets in GeneCards database, using Cytoscape 3.7.2 to draw DSD-active ingredient-target network diagram, and drawing the protein interaction network diagram through STRING database. The Metascape platform was used to analyze the GO function enrichment and KEGG signal pathway. The molecular docking experiment was carried out by using Auto Dock vina 4.2. The related literature on DSD in treating DF in China Zhiwang, Wanfang, Weipu, and China Biomedical Literature Database was searched. The literature was screened, data was extracted, and quality was evaluated according to the inclusion and exclusion criteria. Then, a meta-analysis was performed using RevMan 5.3 software. A total of 256 targets of all effective components of DSD were obtained. Among 1,272 disease targets, there are 113 common targets. The GO analysis received 6,179 entries, and the KEGG pathway enrichment analysis found 251 related pathways. The molecular docking results of the main targets of diabetic foot and the active substances of DSD all showed a high docking activity. The meta-analysis included six literature, all of which were randomized controlled experiments. The quality grade of the literature was C, and the results showed that the total effective rate of clinical efficacy in the experimental group was significantly higher than that in the control group. DSD may treat DF by participating in biological processes such as cell proliferation regulation, inflammatory reaction, oxidative stress reaction, and promotion of angiogenesis. DSD treats DF through AKT1, TP53, IL6, TNF, VEGFA, and other targets. DSD plays a role in treating DF mainly through the AGE-RAGE signaling pathway and PI3K-AKT signaling pathway. The molecular docking results of AKT1, TP53, IL-6, TNF, and VEGFA with the active substances of DSD show that they all have a high docking activity; among them, VEGFA has a higher docking activity. Compared with conventional treatment, DSD has a high effective rate, short wound healing time, large wound healing area, and high ABI index.

National Beef Tenderness Survey—2022: Consumer Sensory Panel Evaluations and Warner-Bratzler Shear Force of Beef Steaks From Retail and Foodservice

Beef retail steaks from establishments across 11 US cities and beef foodservice steaks from establishments in 6 US cities were evaluated by consumer sensory evaluations and Warner-Bratzler shear (WBS) force analyses. The retail tenderloin had the lowest (P<0.05) WBS force value compared to other retail cuts. The retail steak with the greatest (P<0.05) WBS force value was the top sirloin. Foodservice ribeye and top loin steaks had greater (P<0.05) WBS force values compared to the tenderloin. All retail top blade, bone-in ribeye, Porterhouse, and tenderloin steaks were categorized as“very tender” (<31.4 N). There were no (P>0.05) differences in WBS force values among USDA quality grade groups for foodservice steaks. Retail tenderloin steaks received the highest (P<0.05) consumer rating for overall like/dislike, tenderness like/dislike,tenderness level, flavor like/dislike, and juiciness like/dislike compared to all other retail cuts. There were no (P>0.05)differences among the 4 foodservice cuts for consumer sensory ratings of overall like/dislike, tenderness like/dislike, tenderness level, flavor like/dislike, and juiciness like/dislike. There were no (P>0.05) USDA quality grade differences for ribeye, top loin, top sirloin, and tenderloin foodservice steaks for overall like/dislike, tenderness like/dislike, tenderness level, flavor like/dislike, and juiciness like/dislike. Regardless of source (foodservice or retail), USDA grade group, or beef cut, measures of tenderness in this survey reveal ratings and values that should meet most consumer expectations in the marketplace.

Morphological and functional characteristics of the meibomian gland in pediatric patients with epiblepharon

BackgroundTo observe morphologic and functional changes in meibomian glands in pediatric patients with and without lower eyelid epiblepharon.MethodsIn this prospective observation study, 55 eyes of 55 patients( 24 males, 31 females; mean age ± SD,9.82 ± 2.59 years; range 6–14 years) and 60 eyes of 60 controls ( 32 males, 28 females; mean age ± SD,10.57 ± 2.75 years; range 6–14 years) were included. The following tests were performed: eyelid margin abnormality by slit-lamp examination, measurement of noninvasive keratographic break-up time (NIKBUT), grading of absence of meibomian gland (meibography score) assessed with noncontact meibography, morphologic changes of meibomian glands (thinning, dilatation and distortion), tear production by the Schirmer 1 test, and grading of meibum quality and meibomian gland expressibility.ResultsThe morphologic changes in meibomian glands were more common in the epiblepharon group (56.36%) than in the control group (28.33%) (p = 0.002). The meibum quality was worse in the epiblepharon group than in the control group (p = 0.009), and the NIKBUT was significantly shorter in the epiblepharon group than in the control group (p = 0.012). There was no significant difference in the Schirmer 1 test, meibomian gland expressibility, eyelid margin abnormality score or total meibography score between the two groups. Morphologic changes in the meibomian glands in the upper eyelids (38.18%) were more common than those in the lower eyelids (20%) (p = 0.036) in the epiblepharon group, and the meibography score was higher in the upper eyelids than in the lower eyelids (p = 0.001).ConclusionThere are morphological and functional changes in meibomian glands in pediatric patients with lower eyelid epiblepharon. Although the inverted eyelashes were located in the lower eyelid, morphological changes in the meibomian glands were more common in the upper eyelid.

A quality grade classification method for fresh tea leaves based on an improved YOLOv8x-SPPCSPC-CBAM model

In light of the prevalent issues concerning the mechanical grading of fresh tea leaves, characterized by high damage rates and poor accuracy, as well as the limited grading precision through the integration of machine vision and machine learning (ML) algorithms, this study presents an innovative approach for classifying the quality grade of fresh tea leaves. This approach leverages an integration of image recognition and deep learning (DL) algorithm to accurately classify tea leaves’ grades by identifying distinct bud and leaf combinations. The method begins by acquiring separate images of orderly scattered and randomly stacked fresh tea leaves. These images undergo data augmentation techniques, such as rotation, flipping, and contrast adjustment, to form the scattered and stacked tea leaves datasets. Subsequently, the YOLOv8x model was enhanced by Space pyramid pooling improvements (SPPCSPC) and the concentration-based attention module (CBAM). The established YOLOv8x-SPPCSPC-CBAM model is evaluated by comparing it with popular DL models, including Faster R-CNN, YOLOv5x, and YOLOv8x. The experimental findings reveal that the YOLOv8x-SPPCSPC-CBAM model delivers the most impressive results. For the scattered tea leaves, the mean average precision, precision, recall, and number of images processed per second rates of 98.2%, 95.8%, 96.7%, and 2.77, respectively, while for stacked tea leaves, they are 99.1%, 99.1%, 97.7% and 2.35, respectively. This study provides a robust framework for accurately classifying the quality grade of fresh tea leaves.

The Quality Evaluation of Highland Barley and Its Suitability for Chinese Traditional Tsampa Processing.

The physicochemical traits of highland barley prominently affect the quality of Tsampa. To find out the relevance between the physicochemical properties of raw material and the texture parameters of processed products, twenty-five physicochemical traits and ten quality parameters for seventy-six varieties of highland barley were measured and analyzed. The results showed that there was a significant difference between the physicochemical indexes for highland barleys of various colors. The dark highland barley generally has more fat, protein, total dietary fiber, phenolic, Mg, K, Ca, and Zn and less amylose, Fe, Cu, and Mo than light colored barley. Then, these highland barleys were made into Tsampa. A comprehensive quality evaluation model based on the color and texture parameters of Tsampa was established through principal component analysis. Then, cluster analysis was used to classify the tested samples into three edible quality grades predicated on the above evaluation model. At last, the regression analysis was applied to establish a Tsampa quality predictive model according to the physicochemical traits of the raw material. The results showed that amylose, protein, β-Glucan, and a* and b* could be used to predict the comprehensive quality of Tsampa. The predicted results indicated that 11 of 14 validated samples were consistent with the actual quality, and the accuracy was above 78.57%. Our study built the approach of the appropriate processing varieties evaluation. It may provide reference for processing specific highland barley.

Evaluation of blastocyst re-expansion, quality in relation to storage temperature, and sexing using blastocoel fluid after manual perforation with a hand-held needle involving in vivo produced equine embryos

The present study was designed to evaluate equine blastocyst re-expansion rate, quality, and sex following perforation of the blastocoel, collection of blastocoel fluid (BF), and PCR amplification of free DNA. Experiment 1 tested the feasibility of the BF sample collection with a hand-held, small-gauged needle (26g) and subsequent PCR amplification of the TSP-Y gene for males and AMEL-Y gene for males and AMEL-X gene for females. Experiment 2 tested the application of the technique. Equine embryos were collected via uterine flushes 8d after ovulation. Thereafter, embryos (n = 19) were initially assessed and transferred to a 50 μL droplet of holding medium in which the blastocoel was manually perforated as in Experiment 1. Within 1 min of detecting a diameter decrease or collapse, the entire volume of each droplet of medium was collected and stored at −20 °C until PCR. In Experiment 1, amplification of the TSP-Y gene was positive for males at 60% (9/15) and negative for females at 40% (6/15). In Experiment 2, a total of 42 embryos were randomly assigned to a collapsed embryo (CE) or intact embryo (IE) groups and stored at room temperature (RT, 25 °C) or cold temperature (CT, 5 °C) for 24h as follows: 1) CERT, n = 11; 2) CECT n = 11; 3) IERT, n = 10; and 4) IECT, n = 10. After 24h, embryo diameter and quality were reassessed. For all collapsed embryos (n = 19), blastocoel fluid was subjected to double PCR amplification of the TSPY gene with blood from adult male and female horses as controls. Positive gene amplification indicated 57.9% (11/19) of embryos were male and negative amplification indicated 31.6% (6/19) of embryos were female. Relative to the least diameter (0%) after perforation of collapsed embryos or fullest diameter (100%) of intact embryos at T0, percentage change in diameter and quality Grade 1 or 2 embryos after 24h of storage for all groups were, respectively: 31.2% and 54% for CERT group, 28.2% and 0% for CECT group, 25.9% and 100% for IERT group, 4.3% and 80% for IECT group, respectively. Thus, needle-induced leakage and collapse of the blastocoel at T0 resulted in a high rate of blastocyst re-expansion (69%) with many embryos (54%) achieving good quality at T24 with potential for transfer as either male or female embryos. For both collapsed and intact embryos, it was observed that storage for 24h at room temperature (25 °C) was associated with improved embryo growth and morphological quality compared to storage at cold temperature (5 °C).

Cai’s prescription inhibits granulosa cell apoptosis through ARHGAP4 on poor ovarian responders

PurposePoor ovarian response (POR) is a big challenge for in vitro fertilization. The traditional Chinese medicine, Cai’s Prescription of Tonifying Kidney and Strengthening Vitals (Cai’s Prescription) has yielded satisfactory results for POR treatment clinically, but systematic scientific research of Cai’s Prescription is not well reported. This study aimed to investigate the clinical effect of Cai’s Prescription on poor ovarian responders and its biological mechanism.MethodsSerum was collected from poor ovarian responders, and IL-1β, INFγ, FSH, E2 and AMH levels were analyzed by ELISA. Ovarian antral follicles were identified and counted using transvaginal ultrasound. The embryo quality grading were done on day 3 after retrieval. We used high-throughput sequencing of granulosa cells to investigate the gene transcription patterns of ovarian granulosa cells in poor ovarian responders after Cai’s Prescription pretreatment. The expression level of ARHGAP4 was analyzed by quantitative real-time PCR and western blot. The effects of ARHGAP4 for granulosa cells were analyzed by CCK-8 assay, annexin-V and PI staining, ELISA and western blot. The effects of Cai’s Prescription on the expression of PI3K-Akt pathway and apoptosis were analyzed by western blot.ResultsIn this study, we found that Cai’s Prescription pretreatment had the tendency to improve the ovarian reserve function and could increase the number of high quality embryos for poor ovarian responders. Through high-throughput sequencing of mRNA in granulosa cells, we discovered ARHGAP4, which is a member of GTPase-activating proteins (GAPs) may be a candidate target for POR treatment. ARHGAP4 was significantly increased in poor ovarian responders and can be recovered after Cai’s Prescription pretreatment. Mechanically, combining the cell line model and clinical tissue samples, we found that ARHGAP4 can accelerate cell apoptosis and inflammation response in granulosa cells via PI3K-Akt signaling pathway. In addition, Cai’s Prescription pretreatment for three months significantly reduced the high level of ARHGAP4 in poor ovarian responders.ConclusionThis study shows that the traditional Chinese medicine, Cai’s Prescription yielded satisfactory results for poor ovarian responders clinically and ARHGAP4 may be a candidate target for POR treatment.

Effect of Lighter and Heavier Initial Weight on Growth Performance and Carcass Traits of Single-Source Beef Steers.

The objective of the study was to determine the influence that initial BW has on growth performance responses, efficiency of dietary net energy (NE) utilization, and carcass traits in feedlot steers. Charolais×Red Angus steers (n = 70) selected from a larger single-source group were used in a 209-d growing-finishing feedlot experiment. Steers were assigned to two groups based on initial BW (light initial weight, LIW = 273 ± 16.0 kg; heavy initial weight, HIW = 356 ± 14.2 kg) and allotted into 10 pens (n = 7 steers per pen; 5 pens per experimental group) the within pen standard deviation for LIW was from 14.1 kg to 20.9 kg and for HIW was from 13.7 kg to 16.0 kg. Steers were fed a common diet once daily. Experimental data were analyzed as a randomized complete block design with pen as the experimental unit. LIW steers had a greater cumulative HH change (p = 0.04). A treatment × day interaction (p = 0.05) was observed for HH with HIW steers having a greater HH at all time points. Final BW and carcass-adjusted (HCW/0.625) BW were greater for HIW steers by 13.1% and 13.4% respectively (p ≤ 0.01). HIW steers had a greater DMI (p = 0.01) compared to LIW. Cumulative ADG was greater for HIW by 3% (p = 0.04). LIW steers had better feed conversion (p = 0.01). HIW steers had greater (p ≤ 0.05) HCW, marbling scores, and yield grade (YG), with decreased REA/HCW (p = 0.01) compared to LIW. The distribution of USDA Yield Grade was altered by initial BW (p = 0.04). No differences were detected (p ≥ 0.22) for the distribution of Quality grade nor liver abscess prevalence and severity. Regression coefficients did not differ between LIW and HIW for urea space calculations of empty body water, fat, or protein (p ≥ 0.70). A quadratic response was noted for empty body fat (EBF), empty body water (EBH20), and carcass protein (CP). In conclusion, HIW steers had greater growth, but poorer feed efficiency compared to LIW steers. Steers with a HIW produced fatter carcasses with a greater degree of marbling.

Factors affecting Chinese consumers' beef purchase frequency

AbstractChina is an emerging beef market and per capita consumption of beef increased by 48% in the past decade. Given the importance of the Chinese beef market to domestic beef producers as well as foreign beef exporters, we evaluated the factors associated with how often Chinese consumers purchase beef. Using a 2021 survey of 560 beef consumers in the cities of Beijing, Shanghai, and Guangzhou, we found that nearly 50% purchased beef at least two to three times a week. Results of an ordered probit regression suggest that respondents who purchase steak, flank, shank, and brisket are more likely to purchase beef more frequently than those who do not purchase those cuts of beef. Similarly, those who purchase beef more from wet markets and supermarkets, younger shoppers, and those with higher incomes were more likely to purchase beef more frequently. Respondents who considered country of origin and hormone‐free production to be important factors purchased beef more frequently. Consumers who thought price and premium quality grades were more important purchased beef less frequently. These findings provide insights for domestic and foreign beef producers regarding the factors associated with consumer preferences and their frequency of beef purchasing in China. [EconLit Citations: EconLit Citation: Q130, Q170].

Comparison of pathologist and deep learning–based prostate cancer grading for prediction of metastatic outcomes in primary prostate cancer.

345 Background: Gleason grading is the most potent prognostic variable in primary prostate cancer, however inter-observer variability remains a major issue, particularly where subspecialty-trained pathologists are not available. Artificial intelligence algorithms for prostate cancer grading may improve health care equity by ensuring widespread access to standardized, high quality grading, however most algorithms have not been tested for performance with respect to oncologic outcomes. Here, we compared deep learning-based and pathologist-based Gleason grading for prediction of metastatic outcome in three large radical prostatectomy cohorts. Methods: Three previously published radical prostatectomy cohorts from Johns Hopkins were utilized for this study. The Natural History Cohort (n=318, PMID: 26058959) and Case-Cohort (n=231, PMID: 36006048) both utilized a case-cohort design on the outcome of metastasis, while the Race Cohort (n=335, PMID: 30851334) was designed for a grade-matched comparison of self-identified White and Black patients. For each cohort, a single representative H&E-stained slide from the dominant tumor nodule was scanned and Gleason Grade Group (GG) assessed by a modified deep learning-based grading algorithm (PMID: 35233002), or by a subspecialty-trained pathologist. Harrell’s C-indices based on unadjusted Cox models for time to metastasis were compared for the pathologist- and deep learning-assigned GG in each cohort. Results: The C-index for deep learning-assigned GG in the Natural History Cohort was 0.757 (95% confidence interval [CI]: 0.703-0.811) compared to 0.748 (95% CI: 0.692-0.804) for the pathologist-assigned GG. The C-index for deep learning-assigned GG in the Case-Cohort was 0.848 (95% CI: 0.727-0.969) compared to 0.843 (95% CI: 0.722-0.964) for the pathologist-assigned GG. The C-index for deep learning-assigned GG in the Race Cohort was 0.754 (95% CI: 0.697-0.810) compared to 0.780 (95% CI: 0.717-0.844) for the pathologist-assigned GG. In a combined analysis of all three cohorts, the C-index for the deep learning-assigned GG was 0.765 (95% CI: 0.725-0.805) compared to 0.772 (95% CI: 0.730-0.814) for the pathologist-assigned grade group. In the combined cohorts, the historical pathologist-assigned GG for the entire case had a C-index of 0.796 (95% CI: 0.757-0.836). Conclusions: Deep learning and subspecialty-trained pathologist grading were highly comparable for association with metastatic outcome across three large radical prostatectomy cohorts.

Characterization of key aroma compounds and relationship between aroma compounds and sensory attributes in different quality of high temperature Daqu

Daqu quality is determined by its aroma characteristics. In this study, molecular sensory techniques were used to investigate the sensory attributes of Jiangxiangxing high temperature Daqu, resulting in the development of a sensory wheel. A physicochemical and enzymatic analysis of different grades of Daqu revealed notable differences, especially in acidity. Furthermore, the volatile components of various grades of Daqu were investigated with HS-SPME-GC × GC-TOFMS, resulting in the identification of 524 volatile compounds belonging to 11 distinct classes within Daqu. Univariate analysis demonstrated significant differences in flavor components among Daqu samples of diverse quality grades. By employing GC-O-MS techniques and ROAV≥ 0.1, a comprehensive analysis identified a total of 29 key aroma active compounds that contribute to the overall flavor profile of Daqu. Notably, butyl acrylate and (2E)-2-octenal were found to make substantial contributions to the floral and fruity odor, as well as linalool and benzeneacetaldehyde, which were found to make substantial contributions to sweet odor. These compounds significantly enriched the aroma of Daqu and played a crucial role in enhancing the overall flavor quality of Daqu. In conclusion, these results provide a theoretical base for further investigation of different grades of Daqu, as well as the control and improvement of Daqu quality.

Agricultural development driven by the digital economy: improved EfficientNet vegetable quality grading

IntroductionThe conventional manual grading of vegetables poses challenges that necessitate innovative solutions. In this context, our paper proposes a deep learning methodology for vegetable quality grading.MethodsTo address the scarcity of vegetable datasets, we constructed a unique dataset comprising 3,600 images of diverse vegetables, including lettuce, broccoli, tomatoes, garlic, bitter melon, and Chinese cabbage. We present an improved CA-EfficientNet-CBAM model for vegetable quality grading. The CA module replaces the squeeze-and-excitation (SE) module in the MobileNet convolution (MBConv) structure of the EfficientNet model. Additionally, a channel and spatial attention module (CBAM) is integrated before the final layer, accelerating model training and emphasizing nuanced features.ResultsThe enhanced model, along with comparisons to VGGNet16, ResNet50, and DenseNet169, was subjected to ablation experiments. Our method achieved the highest classification accuracy of 95.12% on the cabbage vegetable image test set, outperforming VGGNet16, ResNet50, and DenseNet169 by 8.34%, 7%, and 4.29%, respectively. Notably, the proposed method effectively reduced the model’s parameter count.DiscussionOur experimental results highlight the effectiveness of the deep learning approach in improving vegetable quality grading accuracy. The superior performance of the enhanced EfficientNet model underscores its potential for advancing the field, achieving both high classification accuracy and parameter efficiency. We hope this aligns with your expectations. If there are further adjustments or clarifications needed, please let us know.

An automatic online optics classification method used in the final optics recycling loop strategy

The final optics recycling loop used on large laser facility is an effcient and necessary strategy to maintain the optics in intervals between long-term physical experiments, In order to avoid cross-use between optics of different quality levels, we put forward the A/B recycling loop strategy of optics refer to the strategy from NIF, which arranges optics of the same quality level working in the same beamline, and optics of large quality difference loop independently to protect high-quality optics. Additionally, in order to improve the efficiency of recycling task and the stability of classification standard, we have searched for a proper intelligence technology applying on the loop process. To solve the small sample problem under each label, we use data augmentation method to manually increase samples. Furthermore, transfer learning method based on VGG16 is also used to extract features of the target. As a result the accuracy of the learning model reaches over 90 %. From now on, the integration and data interaction with the computer centralized control system have been completed. The realization of online image automatic classification can estimate the quality grades of optics, so as to provide reference for optics maintaining and optimize the efficiency of the optics recycling loop.

Risk Factors for Atrial Fibrillation in the Dog: A Systematic Review.

Different risk factors for atrial fibrillation (AF) development have been identified in numerous studies on humans, but this information is less clearly available on the dog. The aim of this systematic review is to determine the risk factors for AF in the dog. Following the PRISMA 2020 guidelines, we conducted a comprehensive search using the Web of Science and Scopus databases for articles reporting on cases of spontaneously occurring AF in dogs. The level of evidence was assessed using the Evidence Quality Grading System of the National Institute of Health. One thousand forty-three studies were initially identified, and twenty of them were included in this systematic review involving 2,359,275 dogs, of which 4807 showed spontaneously occurring AF. Genetics, for the Irish Wolfhound, increased body weight, and left atrial enlargement were the main risk factors for the development of AF in dogs with different cardiac diseases, particularly myxomatous mitral valve disease (MMVD) and dilated cardiomyopathy (DCM). However, some differences were found between these two cardiac diseases regarding additional risk factors. In particular, the presence of congestive heart failure and echocardiographic evidence of increased left atrial pressure or the presence of right atrial enlargement emerged as risk factors in dogs with MMVD or DCM, respectively. Furthermore, significant differences in risk factors were observed between dogs and humans. In particular, advanced age and male sex are not reliable indicators of an increased risk of AF in dogs.