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The rapid advancement in the modern automotive industry has put forward higher requirements for the quality of various parts. This paper explores automated dimensional measurement technique based on point cloud models and develops a novel digital inspection system to enhance measurement accuracy and efficiency. By working out specialized inspection schemes, creating local cross-sections at the corresponding inspection positions on the scanned point cloud model of the part to be measured, and adopting geometric analysis algorithms, such as random sample consensus and progressive iterative optimization, the proposed digital inspection method constructs key points for measuring dimensions. This process combines heuristic information from the design or theoretical model with local features of the actual part, enabling rapid and accurate acquisition of inspection results and errors. Besides, to meet the actual production needs for achieving efficient product inspection and quality evaluation, an open system development framework has been designed. It integrates independently developed core functionalities for collecting, sampling point cloud data, performing dimensional measurement and error analysis, with auxiliary functions developed on the basis of commercial software by applying automated scripts for the preprocessing of scanned data and visualizing dimensional measurement and error analysis results. Experimental and application results on actual components demonstrate that, compared to traditional inspection methods, the digital virtual inspection method maintains high inspection accuracy, enhances the overall intelligence level of quality evaluation, and significantly shortens measurement time. Additionally, it exhibits universality and is especially suitable for dimensional measurement where traditional methods are not applicable. [ABSTRACT FROM AUTHOR]

ABSTRACT This study presents a new framework for evaluating data asset quality using a hybrid multi‐criteria decision‐making (MCDM) approach that integrates the decision making trial and evaluation laboratory (DEMATEL), best–worst method (BWM), and fuzzy‐technique for order of preference by similarity to the ideal solution (TOPSIS) techniques. First, the framework considers data as both a product and an asset, leading to the development of quality indicators beyond the traditional dimensions. Subsequently, the interrelationships among indicators are addressed using the DEMATEL method, allowing for the identification of key indicators that significantly influence data asset quality in a given scenario. The BWM method is then employed to determine the weights of these key indicators, enabling a more precise assessment of their importance. After that, the TOPSIS method, incorporating triangular fuzzy numbers, is utilized to rank the data asset quality of different companies. Finally, the effectiveness of the framework is demonstrated by applying it to a group of companies, and the results of the company's evaluation are discussed, along with the corresponding data asset quality improvement initiatives. [ABSTRACT FROM AUTHOR]

Paying attention to cold supply chains is critical in light of rising global warming and public awareness of the issue. In addition, a lack of appropriate quality control in supply chains has resulted in significant waste in the industry. This research sought to create a three-level cold supply chain (firm, distribution center, and retailer) with a quality evaluation function. The chain has been modelled for a multiplicity of products and time periods. The parameters in this model are analyzed in three separate scenarios to reect uncertainty. The model also includes direct delivery from the firm to the store. Various factors can affect the quality evaluation variables, which in this model are assigned to two main parameters: Temperature and humidity. The quality of the products in this model is used to estimate their selling price. Due to the nonlinearity of the model, the Baron approach is applied in this work. [ABSTRACT FROM AUTHOR]

The impact of climate change on medicinal plants has significantly altered their suitable environments, thereby affecting the quality of herbal medicines. Notopterygium franchetii (N. franchetii), a medicinal plant intricately linked to its natural habitat, exhibits substantial quality variations influenced by the ecological conditions of its native region. In this study, comprehensive field surveys were conducted to gather occurrence records and samples of N. franchetii. The Maxent model and ArcGIS software were employed to predict the suitable habitats of N. franchetii during different time periods. A high-performance liquid chromatography (HPLC) method was developed to establish the chemical fingerprints of 21 sample batches. Fourteen common peaks were subjected to cluster analysis, principal component analysis, and orthogonal partial least squares-discriminant analysis. The findings revealed quality variations correlated with their geographic origins, identifying peaks 10, 1, 14, 3, and 4 as crucial for quality differentiation. The study indicates that precipitation, temperature, and altitude significantly influence the distribution of N. franchetii. Under current climate conditions, the suitable habitat area for N. franchetii is estimated to be approximately 94,637.33 km2. However, projections under three future climate scenarios suggest a declining trend in suitable habitat areas. A quality zoning map of N. franchetii was developed, integrating a correlation model between chemical composition and environmental variables with the spatial analysis and visualization capabilities of ArcGIS. The high-quality regions for N. franchetii are predominantly located in the Gannan, Linxia, Dingxi, Longnan, and Wuwei districts. These research outcomes offer a valuable reference for identifying suitable cultivation areas and assessing the quality of N. franchetii in Gansu Province. [ABSTRACT FROM AUTHOR]

Atractylodis Macrocephalae Rhizoma (AMR) is a traditional Chinese medicine used for gastrointestinal diseases. With increased demand, there are more and more places of cultivation for AMR. However, the quality of AMR varies from place to place, and there is no good way to distinguish AMR from different origins at present. In this paper, we determined the content of eight chemical components including 60% ethanol extracts, essential oil, polysaccharides, atractylenolides, and atractylone, obtained the color parameters of AMR powder by colorimetry, and odor information was captured by the electronic nose, all of which were combined with machine learning to establish a rapid origin traceability method. The results of the principal component analysis of the chemical components revealed that Zhejiang AMR has a high comprehensive score and overall better quality. The Kruskal–Wallis test demonstrated that there are varying degrees of differences in chemical composition and color parameters across the different origin. However, the accuracy of the classification model is low (less than 80%), making it difficult to distinguish between different origins of AMR. The electronic nose demonstrated excellent classification performance in the traceability of AMR from different origins, with accuracy reaching more than 90% (PLS-DA: 96.88%, BPNN: 96.88%, PSO-SVM: 100%). Overall, this study clarified the quality differences of AMR among different origins, and a rapid and precise method combining machine learning was developed to trace the origin of AMR. [ABSTRACT FROM AUTHOR]

Remote sensing image fusion technology integrates observational data from multiple satellite platforms to leverage the complementary advantages of the different types of remote sensing images. High-quality fused remote sensing images provide detailed information on surface radiation, climate, and environmental conditions, thereby supporting governmental policies on environmental changes. Improving the quality and quantitative accuracy of fused images is a crucial trend in remote sensing image fusion research. This study investigates the impact of atmospheric correction and five widely applied fusion techniques on remote sensing image fusion. By constructing four fusion frameworks, it evaluates how the choice of fusion method, the implementation of atmospheric correction, the synchronization of atmospheric parameters, and the timing of atmospheric correction influence the outcomes of remote sensing image fusion. Aerial flights using remote sensors were conducted to acquire atmospheric parameter distribution images that are strictly synchronous with the remote sensing images. Comprehensive and systematic evaluations of the fused remote sensing images were performed. Experiments show that for the remote sensing images used, selecting the appropriate fusion method can improve the spatial detail evaluation metrics of the fused images by up to 2.739 times, with the smallest deviation from true reflectance reaching 35.02%. Incorporating synchronous atmospheric parameter distribution images can enhance the spatial detail evaluation metrics by up to 2.03 times, with the smallest deviation from true reflectance reaching 5.4%. This indicates that choosing an appropriate fusion method and performing imaging-based synchronous atmospheric correction before fusion can maximize the enhancement of spatial details and spectral quantification in fused images. [ABSTRACT FROM AUTHOR]

Oxytocin is the principal drug and the primary choice for labor induction and postpartum hemorrhage prevention and treatment. The problems associated with oxytocin are not usually from its effectiveness, but they are from its compromised quality which may occur at the point of manufacturing, transportation, and storage. The main objective of this study was to assess the status of oxytocin injection quality and associated factors in the health facilities located in Addis Ababa city, Ethiopia. A laboratory based instrumental quality testing alongside a cross sectional study design was used to evaluate oxytocin injection quality in Addis Ababa city administration from January to June, 2022 according to United States Pharmacopeia (USP 20), and the World Health Organization guideline of post-market medicine quality assessment. Binary logistic regression and cross tabulation analysis were conducted using SPSS 26. Significance was considered at p ≤ 0.05. Out of 107 tested oxytocin injection samples, 92.5% met the limit for oxytocin content, 81.3% for sterility test, and 91.6% for pH value. Overall, quality failure rate was 23.4%, while sterility test failure rate was 18.7%. Lack of reliable refrigerated storage condition [(AOR = 5.62, 95% CI: (1.87, 16.88)], lack of effective cold chain system during distribution [(AOR = 5.5, 95% CI: (1.53, 19.74)], and weak national medicine regulatory system [(AOR = 3.23, 95% CI: (1.13, 9.23)] were among the significantly associated factors for the failure of some of the brands. The study demonstrated that oxytocin injection quality failure rate, failing to meet at least one quality test requirement, is demonstrated in the health facilities of Addis Ababa. The determinant factors for the reported failures are related to storage, distribution, and regulatory system. Hence, these should be addressed by strictly adhering in to the national regulation and providing a comprehensive health promotion on rational use of oxytocin injection should be implemented to assure its quality and safety. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Food Safety & Quality is the property of Journal of Food Safety & Quality Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Shipin Kexue/ Food Science is the property of Food Science Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

As a plant classified under the "medicine food homology" concept, garlic offers various health benefits and comes in many different varieties. In this study, the metabolite composition of different garlic varieties were analyzed using LC–MS/MS quadrupole‐Orbitrap mass spectrometry and ICP‐MS. A total of 30 chemical elements and 1256 metabolites were identified. Significant differences in chemical elements and metabolomics profiles were observed among the five garlic groups (VIP > 1.5). Compared to WG, PG contained 5 unique compounds, HG had 15 unique compounds, SCG had 18 unique compounds, and SBG had 26 unique compounds. Furthermore, the results showed that WG had smaller differences with PG and HG, but significant differences with SBG and SCG. KEGG analysis revealed metabolic pathways associated with the formation of differential metabolites. These findings uncover the differences and mechanisms in the composition of various garlic varieties, providing a theoretical foundation for distinguishing the nutritional components of different garlic types. [ABSTRACT FROM AUTHOR]

The Core Concepts of Pharmacology (CCP) initiative is developing educational resources to transform pharmacology education into a concept‐based approach. This study evaluated the quality of global educator‐created MCQs in generating items for the pharmacology concept inventory (PCI) instrument and developed as a resource for learning pharmacology fundamental concepts. A panel of 22 global pharmacology experts recruited from the CCP initiative research team participated in the MCQ pilot database design and evaluation. The quality analysis framework of the MCQs in the pilot database included four assessment tools: item writing guidelines (IWGs), Bloom's taxonomy, the CCP, and the MCQ design format. A two‐phase evaluation process was involved, including inter‐rater agreement on item quality, followed by resolving conflicts that occurred in quality assessment. The chi‐square (χ2) test of independence and Cramer's V correlation tests were utilized to measure the relationship among quality assessment attributes. About 200 MCQs were gathered and 98% underwent expert evaluation. Nearly 80% addressed one or more CCP, with 52% designed using a context‐dependent format. However, only 40% addressed higher levels of Bloom's cognitive domain and 10% adhered to all IWGs. A strong positive correlation was observed between the context‐based item format and its effectiveness in assessing the higher cognitive domain, the main CCP and improved IWGs adherence. Context‐based item construction can assess the higher cognitive skills and fundamental pharmacology concepts, showing potential for rigorous PCI development. The pilot database will store items to create the PCI, aiding the development of a concept‐based pharmacology curriculum. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Food Safety & Quality is the property of Journal of Food Safety & Quality Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Euphorbiae pekinensis Radix (EPR) is a traditional Chinese herb commonly used to treat edema, pleural effusion, and ascites. However, counterfeit and adulterated products often appear in the market because of the homonym phenomenon, similar appearance, and artificial forgery of Chinese herbs. This study comprehensively evaluated the quality of EPR using multiple methods. The DNA barcode technique was used to identify EPR, while the UPLC‐Q‐TOF‐MS technique was utilized to analyze the chemical composition of EPR. A total of 15 tannin and phenolic acid components were identified. Furthermore, UPLC fingerprints of EPR and its common counterfeit products were established, and unsupervised and supervised pattern recognition models were developed using these fingerprints. The backpropagation artificial neural network and counter‐propagation artificial neural network models accurately identified counterfeit and adulterated products, with a counterfeit ratio of more than 25%. Finally, the contents of the chemical markers 3,3′‐di‐O‐methyl ellagic acid‐4′‐O‐β‐D‐glucopyranoside, ellagic acid, 3,3′‐di‐O‐methyl ellagic acid‐4′‐O‐β‐d‐xylopyranoside, and 3,3′‐di‐O‐methyl ellagic acid were determined to range from 0.05% to 0.11%, 1.95% to 8.52%, 0.27% to 0.86%, and 0.10% to 0.42%, respectively. This proposed strategy offers a general procedure for identifying Chinese herbs and distinguishing between counterfeit and adulterated products. [ABSTRACT FROM AUTHOR]

Introduction: Quality evaluation of Huang‐qin is significant to ensure its clinical efficacy. Objective: This study aims to establish an accurate, rapid and comprehensive Huang‐qin quality evaluation method to overcome the time‐consuming and laborious shortcomings of traditional herbal medicine quality assessment methods. Methods: The contents of baicalin, baicalein and scutellarin in Huang‐qin from five different origins were analyzed by FT‐IR and NIR spectra combined with multivariate data technology. The quality of Huang‐qin from different origins was evaluated by TOPSIS and consistency analysis based on the content of three active ingredients. The correlation between ecological factors and the accumulation of active ingredients was explored. Results: Satisfactory prediction results of PLS models were obtained. Relatively, the model based on FT‐IR combined with the PLS regression method has higher R2 and smaller RMSE than the NIR combined with the PLS method. TOPSIS and consistency analysis results showed that the quality of Huang‐qin from different geographical origins was significantly different. The results showed that the quality of Huang‐qin produced in Shanxi Province was the best among the five origins studied. The results also found that the quality of Huang‐qin in different growing areas of the same origin was not completely consistent. The correlation study showed that altitude, sunshine duration and rainfall were the main factors that caused the quality difference of medicinal materials in different geographical origins. Conclusion: This study provides a reference for the rapid quantitative analysis of the active components of herbal medicine and the quality evaluation of them. The contents of baicalin, baicalein, and scutellarin in Huang‐qin from five different origins were analyzed by FT‐IR and NIR spectra combined with multivariate data technology. The quality of Huang‐qin from different origins was evaluated by TOPSIS and consistency analysis based on the content of three active ingredients. The correlation between ecological factors and the accumulation of active ingredients was explored. [ABSTRACT FROM AUTHOR]

Wine experts' ratings provide quality information and reduce the information asymmetry for the consumer. We hypothesize that consumers' ratings will come to dominate expert ratings in the wine expertise market. We employ a hedonic regression framework on the attributes of 36,970 French red wines to determine the relative impacts of expert and Vivino community ratings on wine prices. Average consumer ratings are found to have a larger effect on price than expert scores. These results are found to be robust to outliers and the general conclusion that peers matter more than experts holds when we exclude the top-end wines. [ABSTRACT FROM AUTHOR]

Exploring the data quality problems in the context of federated cooperation and adopting corresponding governance countermeasures can facilitate the smooth progress of federated cooperation and obtain high-performance models. However, previous studies have rarely focused on quality issues in federated cooperation. To this end, this paper analyzes the quality problems in the federated cooperation scenario and innovatively proposes a "Two-stage" data quality governance framework for the federated collaboration scenarios. The first stage is mainly local data quality assessment and optimization, and the evaluation is performed by constructing a metrics scoring formula, and corresponding optimization measures are taken at the same time. In the second stage, the outlier processing mechanism is introduced, and the Data Quality Federated Averaging (Abbreviation DQ-FedAvg) aggregation method for model quality problems is proposed, so as to train high-quality global models and their own excellent local models. Finally, experiments are conducted in real datasets to compare the model performance changes before and after quality governance, and to validate the advantages of the data quality governance framework in a federated learning scenario, so that it can be widely applied to various domains. The governance framework is used to check and govern the quality problems in the federated learning process, and the accuracy of the model is improved. [ABSTRACT FROM AUTHOR]

Through the investigation of Mytilaria laosensis light matrix container seedlings, the maximum eigenvector value was obtained by principal component analysis method, and the standard deviation method was used to determine the key indicators for evaluating quality of the seedlings are height and ground diameter, including grade I seedlings: seedling height> 105 cm, ground diameter> 0. 7 cm; grade Ⅱ seedling: 65 - 105 cm, ground diameter 0. 4 - 0. 7 cm. [ABSTRACT FROM AUTHOR]

[Objective) The flue-cured tobacco and other crops planted in the northern central subtropical climate region showed the overlapping planting areas. The study aimed to clarify the spatial variation characteristics of fertility in soil of tobacco planting areas and provide technical support for crop nutrient management and soil fertility regulation in this climatic region. (Method) Taking 2548 soil samples from tobacco planting area in the main climate types of northern central subtropical region in Yunnan province in 2019 as the research object, the membership function method of fuzzy mathematical model was used to comprehensively evaluate the soil fertility quality. The principal component analysis method was used to determine the weight of each index and the main controlling factors causing fertility differences. GIS spatial interpolation was used to determine the spatial distribution characteristics of soil fertility quality index. (Result) The average quality index of soil fertility in tobacco-planting areas in the main climate types of northern central subtropical region of Yunnan province was 0.65, which was at a relatively high level. The variation coefficients of SOM, TN, AP and AK in soil were 46.84%,48.69%,75.64% and 52.33%, respectively, all of which belonged to moderate variability intensity and their contents were relatively rich. Soil AP was the main limiting factor affecting soil fertility. The quality index of soil fertility in tobacco-planting areas in the main climate types of northern central subtropical region in Yunnan province showed a distribution pattern of high in the central region, low in some areas of the eastern or western regions, with scattered distribution in some areas. [Conclusion】 The soil from tobacco planting area in the main climate types of northern central subtropical region in Yunnan province is more suitable for tobacco growth. Balancing fertilization should control nitrogen, increase the application of organic fertilizer and phosphorus and potassium fertilizers, effectively balance and coordinate soil nutrients, and improve soil fertility and tobacco leaf quality in tobacco-planting areas. [ABSTRACT FROM AUTHOR]

Objective To simultaneously determine of shikimic acid, catechin, quercetin, kaempferol, isorhamnetin, 3'-hydroxypuerarin, puerarin, 3'-methoxypuerarin, daidzin and genistein in Songling Xuemaikang Capsules by quantitative analysis of multi-components by single-marker (QAMS), and to establish fusion model of weighted technique for order preference by similarity to an ideal solution (TOPSIS) and grey relational analysis (GRA) for evaluating the quality of 15 batches of samples. Methods HPLC method was used to calculate the relative correction factor and content of each component, using kaempferol as internal reference. The feasibility of QAMS method was verified by comparing with the measured value of external standard method. The content results were analyzed by chemo metrics to explore the quality difference markers of Songling Xuemaikang Capsules. Taking the VIP value of each component as the weight, we performed differential analysis on sample quality through fusion model of weighted TOPSIS and GRA. Results There was no significant difference between the results of QAMS and external standard method. The 15 batches of samples were clustered into three categories. Puerarin, 3'-hydroxypuerarin, quercetin, 3'-methoxypuerarin and shikimic acid were the quality difference markers of Songling Xuemaikang Capsules. The results of fusion model of weighted TOPSIS and GRA showed that there were some quality differences in Songling Xuemaikang Capsules produced at different times. Conclusion The hybrid model combining QAMS, weighted TOPSIS and GRA can be used for the comprehensive evaluation of the quality of Songling Xuemaikang Capsules. [ABSTRACT FROM AUTHOR]

The quality evaluation of normal education is a crucial guide for the high-quality development of normal education in China, and a crucial instrument for building a great education country and a high-quality education system. Since the founding of People's Republic of China, China's quality evaluation of normal education has undergone stages of emergence, formation, and innovation, achieving great progress in terms of institutional and practical innovations. However, it still faces severe challenges such as weakened organizational mechanism and lack of regulatory mechanisms, outdated category structures and unclear type characteristics, weakened practical ability and traditional technical means, and weak governance empowerment and insufficient think tank functions. To develop a world-class normal education quality evaluation system with Chinese characteristics, it is necessary to improve the competence of evaluation organizations, regulate the operation of normal evaluation market, construct the category of three-dimensional evaluation practice, highlight the characteristics of normal evaluation types, develop categorized evaluation practice models, innovate the digital and intelligent evaluation of normal education, and enhance the governance functions of evaluation conclusions, promoting the improvement of normal education quality. [ABSTRACT FROM AUTHOR]

Metal additive manufacturing (MAM) technology provides a direct and efficient way for large-scale, integrated, and sophisticated engineering components in the aerospace field. Non-destructive testing (NDT) technique has been proven to be a significant method for quality evaluation of MAM components without destructing the integrity and performance of the components. However, it is still a challenging task that how to accurately and efficiently achieve the quality evaluation of large-scale and complex MAM engineering components using NDT technique. Nowadays, most studies mainly focus on the quality evaluation of small specimens or simple structure components, with comparatively less on the assessment of large-scale or complex engineering components. Thus, this review briefly introduced three urgent demands for quality evaluation of as-fabricated large or complex structure components and eight conventional NDT techniques possibly used for the quality detection of MAM. Four main challenges and future development trends in NDT technique are discussed in detail according to testing ability, data processing ability, and test standards. Among the future development trends, the application of machine learning and digital twins in NDT technique are the most promising method for intelligent detection and quality prediction of components. This work aims to provide a insight to enlarge the application of engineering components fabricated by MAM. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the quality of ChatGPT responses to common issues in obstetrics and assess its ability to provide reliable responses to pregnant individuals. The study aimed to examine the responses based on expert opinions using predetermined criteria, including "accuracy," "completeness," and "safety." Methods: We curated 15 common and potentially clinically significant questions that pregnant women are asking. Two native English‐speaking women were asked to reframe the questions in their own words, and we employed the ChatGPT language model to generate responses to the questions. To evaluate the accuracy, completeness, and safety of the ChatGPT's generated responses, we developed a questionnaire with a scale of 1 to 5 that obstetrics and gynecology experts from different countries were invited to rate accordingly. The ratings were analyzed to evaluate the average level of agreement and percentage of positive ratings (≥4) for each criterion. Results: Of the 42 experts invited, 20 responded to the questionnaire. The combined score for all responses yielded a mean rating of 4, with 75% of responses receiving a positive rating (≥4). While examining specific criteria, the ChatGPT responses were better for the accuracy criterion, with a mean rating of 4.2 and 80% of the questions received a positive rating. The responses scored less for the completeness criterion, with a mean rating of 3.8 and 46.7% of questions received a positive rating. For safety, the mean rating was 3.9 and 53.3% of questions received a positive rating. There was no response with an average negative rating below three. Conclusion: This study demonstrates promising results regarding potential use of ChatGPT's in providing accurate responses to obstetric clinical questions posed by pregnant women. However, it is crucial to exercise caution when addressing inquiries concerning the safety of the fetus or the mother. Synopsis: ChatGPT demonstrated the ability to provide accurate and comprehensive responses to common obstetric questions. [ABSTRACT FROM AUTHOR]

Coffee quality and varieties matter for its ultimate flavor. As multiple factors influence taste during coffee production, hyperspectral imaging (HSI) stands out with great potential for quality assessment, defect supervision, and character identification. With a relatively comprehensive summary of current HSI-based research in coffee, this literature review critically reveals HSI's competence and present shortcomings in practical applications within the coffee industry. Sequentially, potential applications of HSI technology in coffee component analysis and flavor estimation, blemish diagnosis, and origins or attributes identification are illustrated. Finally, several key challenges and future perspectives of HSI are indicated from a practical and sustainable perspective, with digitalization as a major goal in the coffee industry. [ABSTRACT FROM AUTHOR]

The ecological environment is an important influencing factor that leads to differences in the quality of forestland ginseng and farmland ginseng. The content of ginsenosides in forestland ginseng and farmland ginseng was used as an indicator to analyze their quality differences, determined the physicochemical properties of rhizosphere soil, and conducted correlation, multiple stepwise regression, coefficient of variation, partial least squares discriminant analysis, and analytic hierarchy process comprehensive evaluation analysis on the measurement results. The results showed that there were significant differences in ginsenoside content and soil physicochemical properties between forestland ginseng and farmland ginseng. Analysis of coefficient of variation showed that the coefficient of variation of most ecological factor indicators in farmland ginseng was greater than that in forestland ginseng. The results of correlation, multiple stepwise regression, and partial least squares discriminant analysis showed a significant correlation between soil factors such as the highest temperature, the lowest temperature, pH, alkaline nitrogen, and available phosphorus with ginsenosides. The results of the analytic hierarchy process showed significant differences in soil quality among different cultivation modes. Multiple statistical results showed that the highest temperature, the lowest temperature, and pH were the main factors affecting the content of ginsenosides, while alkaline nitrogen, available phosphorus, and soil moisture were secondary factors. Above results indicated that the highest temperature, the lowest temperature, pH, alkaline nitrogen, available phosphorus, and soil moisture were important factors affecting the quality differences between forestland ginseng and farmland ginseng. The results provided a theoretical basis for analyzing the formation of ginseng quality and planting production. [ABSTRACT FROM AUTHOR]

The traditional alkaline peeling method generates high‐salinity wastewater, posing significant environmental risks. To avoid water waste and chemical use, a dry method using high‐temperature thermal radiation was explored for removing walnut skins. The mechanism of the high‐temperature thermal radiation dry method for removing walnut skins was revealed by studying the physical properties of walnut kernels. Research on the performance of the peeling device identified the optimal parameters: an infrared emitter surface temperature of 600°C, a radiation time of 20.7 seconds, and a distance of 129.46 mm between emitters, achieving a 95.18% skin removal rate with only 0.8% moisture loss and a quality score of 96.82. Raman spectroscopy showed that this method increased the unsaturated fatty acid content of walnut kernels by 27.26%, greatly enhancing their quality. SEM analysis revealed different microstructural changes between skins removed by infrared and alkaline methods, revealing the differences in their peeling mechanisms. These findings provide a scientific foundation for developing thermal radiation dry peeling technology and devices. Practical applications: The removal of walnut skins is an essential process for enhancing the added value of products. However, current industrial peeling methods such as hot alkaline peeling and steam peeling are water and energy‐intensive industries, generating large amounts of wastewater that negatively impact the environment. There is an urgent need to develop an efficient, green, and environmentally friendly dry peeling technology for walnut kernels in the food industry to replace traditional chemical peeling methods. The high‐temperature thermal radiation dry peeling technology provides a new approach that avoids the use of water and chemical reagents while maintaining high product quality after peeling. Research focuses on the theoretical study and several key points of dry peeling technology for achieving walnut kernel peeling. The research results provide scientific basis for the replacement of traditional alkaline peeling with high‐temperature thermal radiation dry peeling technology and offer theoretical support and reference for the development and optimization of related equipment. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Shenyang Pharmaceutical University is the property of Shenyang Pharmaceutical University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Light penetration depth, as a characteristic parameter reflecting light attenuation and transmission in biological tissues, has been applied in nondestructive detection of fruits and vegetables. Recently, with emergence of new optical detection technologies, researchers have begun to explore methods evaluating optical properties of double-layer or even multilayer fruit and vegetable tissues due to the differences between peel and pulp in the chemical composition and physical properties, which has gradually promoted studies on light penetration depth. A series of demonstrated research on light penetration depth could ensure the accuracy of the optical information obtained from each layer of tissue, which is beneficial to enhance detection accuracy for quality assessment of fruits and vegetables. Therefore, the aim of this review is to give detailed outlines about the theory and principle of light penetration depth based on several emerging optical detection technologies and to focus primarily on its applications in the field of quality evaluation of fruits and vegetables, its future applicability in fruits and vegetables and the challenges it may face in the future. [ABSTRACT FROM AUTHOR]

Abstract To address the need for automated sorting of synthetic diamonds based on quality in manufacturing enterprises, this study developed a dedicated dataset and an enhanced YOLOv8n model for synthetic diamonds detection and quality evaluation, named YOLOv8n-adamas. We redesigned the backbone network to improve feature extraction capabilities and introduced a dynamic detection head based on attention mechanisms to further enhance model performance. Experimental results show that on synthetic diamonds dataset, YOLOv8n-adamas achieved a 4.0% improvement in precision (P), a 2.7% increase in recall (R), and improvements of 1.5% and 1.3% in mean average precisions at 50% and 95% Intersection over Union (IoU) thresholds (mAP50 and mAP95) compared to YOLOv8. Furthermore, YOLOv8n-adamas also outperforms other commonly used, high-performing models in various metrics on this dataset, offering effective technical support for the automated quality-based sorting of synthetic diamonds.

Abstract The impact of climate change on medicinal plants has significantly altered their suitable environments, thereby affecting the quality of herbal medicines. Notopterygium franchetii (N. franchetii), a medicinal plant intricately linked to its natural habitat, exhibits substantial quality variations influenced by the ecological conditions of its native region. In this study, comprehensive field surveys were conducted to gather occurrence records and samples of N. franchetii. The Maxent model and ArcGIS software were employed to predict the suitable habitats of N. franchetii during different time periods. A high-performance liquid chromatography (HPLC) method was developed to establish the chemical fingerprints of 21 sample batches. Fourteen common peaks were subjected to cluster analysis, principal component analysis, and orthogonal partial least squares-discriminant analysis. The findings revealed quality variations correlated with their geographic origins, identifying peaks 10, 1, 14, 3, and 4 as crucial for quality differentiation. The study indicates that precipitation, temperature, and altitude significantly influence the distribution of N. franchetii. Under current climate conditions, the suitable habitat area for N. franchetii is estimated to be approximately 94,637.33 km2. However, projections under three future climate scenarios suggest a declining trend in suitable habitat areas. A quality zoning map of N. franchetii was developed, integrating a correlation model between chemical composition and environmental variables with the spatial analysis and visualization capabilities of ArcGIS. The high-quality regions for N. franchetii are predominantly located in the Gannan, Linxia, Dingxi, Longnan, and Wuwei districts. These research outcomes offer a valuable reference for identifying suitable cultivation areas and assessing the quality of N. franchetii in Gansu Province.

This study was carried out in order to investigate the differences in quality between Dictyophora rubrovolvata and Phallus dongsun from Guizhou. A total of 34 nutritional components in the two edible mushroom species were quantitatively analyzed, and differential metabolites between them were identified by non-targeted metabolomics based on ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). The results showed that the contents of L-ergothioneine, ergosterol, total dietary fiber and iron in D. rubrovolvata were higher, and the content of essential amino acids in proteins was 342.2 mg/g, which was closer to the Food and Agriculture Organization of the United Nations/World Health Organization reference pattern. The contents of soluble sugars, calcium and protein in P. dongsun were higher, and the total content of four soluble sugars including trehalose, mannitol, mannose, and glucose in D. rubrovolvata (450.8 mg/g) was much higher than that in P. dongsun (114.7 mg/g). A total of 388 significantly differential metabolites were selected by multivariate statistical analysis, mainly including 145 lipids, 38 amino acids and derivatives and 17 carbohydrates. Among these, 126 metabolites were down-regulated and 262 metabolites were up-regulated in P. dongsun compared with those in D. rubrovolvata. Most of them were flavor precursors or flavor substances in D. rubrovolvata and P. dongsun, which were closely related to their flavor. The results of this study provide basic data for the quality evaluation and functional composition analysis of D. rubrovolvata and P. dongsun.

Abstract Oxytocin is the principal drug and the primary choice for labor induction and postpartum hemorrhage prevention and treatment. The problems associated with oxytocin are not usually from its effectiveness, but they are from its compromised quality which may occur at the point of manufacturing, transportation, and storage. The main objective of this study was to assess the status of oxytocin injection quality and associated factors in the health facilities located in Addis Ababa city, Ethiopia. A laboratory based instrumental quality testing alongside a cross sectional study design was used to evaluate oxytocin injection quality in Addis Ababa city administration from January to June, 2022 according to United States Pharmacopeia (USP 20), and the World Health Organization guideline of post-market medicine quality assessment. Binary logistic regression and cross tabulation analysis were conducted using SPSS 26. Significance was considered at p ≤ 0.05. Out of 107 tested oxytocin injection samples, 92.5% met the limit for oxytocin content, 81.3% for sterility test, and 91.6% for pH value. Overall, quality failure rate was 23.4%, while sterility test failure rate was 18.7%. Lack of reliable refrigerated storage condition [(AOR = 5.62, 95% CI: (1.87, 16.88)], lack of effective cold chain system during distribution [(AOR = 5.5, 95% CI: (1.53, 19.74)], and weak national medicine regulatory system [(AOR = 3.23, 95% CI: (1.13, 9.23)] were among the significantly associated factors for the failure of some of the brands. The study demonstrated that oxytocin injection quality failure rate, failing to meet at least one quality test requirement, is demonstrated in the health facilities of Addis Ababa. The determinant factors for the reported failures are related to storage, distribution, and regulatory system. Hence, these should be addressed by strictly adhering in to the national regulation and providing a comprehensive health promotion on rational use of oxytocin injection should be implemented to assure its quality and safety.

High-quality Geographic Knowledge Graphs (GeoKGs) are highly anticipated for their potential to provide reliable semantic support in geographical knowledge reasoning, training Geographic Large Language Models (Geo-LLMs), enabling geographical recommendation, and facilitating various geospatial knowledge-driven tasks. However, there is a lack of a standardized quality assessment methodology and clearly defined evaluative indicators in the field of GeoKGs research. This research uses the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to conduct a systematic review of literature and standards in the field of GeoKG in an effort to fill the gap. First, using the lifecycle theory as a guide, we outline and propose five groups including twenty assessment criteria and their accompanying calculation techniques for evaluating GeoKG quality. Then, expanding on this foundation, we present a streamlined evaluation scheme for GeoKGs that relies on just seven key measures, discussing their applicability, utility, and weight scheme in greater detail. After applying the GeoKG quality framework, we stated three key tasks emerge as priorities: the creation of specialized assessment tools, the formation of worldwide standards, and the building of large-scale, high-quality GeoKGs. We believe this thorough and systematic GeoKG quality assessment technique will help construct high-quality GeoKGs and promote GeoKGs as an engine for geo-intelligence applications including Geospatial Artificial Intelligence (GeoAI) systems, Sustainable Development Goals (SDGs) analyzers, and Virtual Geographic Environments (VGEs) models.

Landscape planning and design quality evaluation is a systematic analysis and assessment of landscape project designs. Its primary goal is to ensure functionality, aesthetics, and sustainability of the design. The evaluation covers aspects such as spatial layout, ecological conservation, plant arrangement, landscape effects, and human-centered considerations. Additionally, the evaluation considers the economic feasibility of the project, the practicality of construction, and the ease of future maintenance, ensuring that the landscape space meets diverse user needs while harmonizing with the natural environment. The landscape planning and design quality evaluation is MAGDM. The single-valued neutrosophic sets (SVNSs) are useful tools to cope with uncertain information during the landscape planning and design quality evaluation. In this paper, the single-valued neutrosophic number EDAS (SVNN-EDAS) model based on single-valued neutrosophic number cosine similarity measure (SVNNCSM) and SVNN cosine function similarity measure (SVNNCFSM) is formed to cope with the MAGDM. The CRITIC model is administrated to obtain the weight numbers in light with the SVNNCSM and SVNNCFSM under SVNSs. Finally, numerical examples and different comparative analysis for landscape planning and design quality evaluation is administrated to validate SVNN-EDAS model. [ABSTRACT FROM AUTHOR]

Zanthoxylum nitidum is a traditional Chinese herb, but limited information is available concerning its antioxidant activity of Z. nitidum. In this study, the bioactive components, content, and antioxidant activity of Z. nitidum roots from various regions in southern China were detected and evaluated. The results revealed that the highest nitidine chloride content found in S13. The S1 contained significantly higher concentrations of hesperidin, total flavonoids, and total phenols than other samples. The samples from S13, S1, and S12 had the strongest comprehensive antioxidant activity. Stoichiometric analysis revealed that samples from various regions were effectively identified and classified. This is the first study to investigate the antioxidant activity of wild-type Z. nitidum in southern China. It lays the groundwork for Z. nitidum harvesting, origin identification, sensible use, as well as the quality evaluation of Z. nitidum resources, particularly in vitro antioxidant activity assessment. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the effectiveness of ChatGPT in providing insights into common urinary incontinence concerns within urogynecology. By analyzing the model's responses against established benchmarks of accuracy, completeness, and safety, the study aimed to quantify its usefulness for informing patients and aiding healthcare providers. Methods: An expert‐driven questionnaire was developed, inviting urogynecologists worldwide to assess ChatGPT's answers to 10 carefully selected questions on urinary incontinence (UI). These assessments focused on the accuracy of the responses, their comprehensiveness, and whether they raised any safety issues. Subsequent statistical analyses determined the average consensus among experts and identified the proportion of responses receiving favorable evaluations (a score of 4 or higher). Results: Of 50 urogynecologists that were approached worldwide, 37 responded, offering insights into ChatGPT's responses on UI. The overall feedback averaged a score of 4.0, indicating a positive acceptance. Accuracy scores averaged 3.9 with 71% rated favorably, whereas comprehensiveness scored slightly higher at 4 with 74% favorable ratings. Safety assessments also averaged 4 with 74% favorable responses. Conclusion: This investigation underlines ChatGPT's favorable performance across the evaluated domains of accuracy, comprehensiveness, and safety within the context of UI queries. However, despite this broadly positive reception, the study also signals a clear avenue for improvement, particularly in the precision of the provided information. Refining ChatGPT's accuracy and ensuring the delivery of more pinpointed responses are essential steps forward, aiming to bolster its utility as a comprehensive educational resource for patients and a supportive tool for healthcare practitioners. Synopsis: ChatGPT demonstrated the ability to provide accurate and comprehensive responses within the context of urinary incontinence queries. [ABSTRACT FROM AUTHOR]

Based on chromatographic fingerprinting combined with quantitative analysis on characteristic chemical constituents as well as hierarchical cluster analysis, an easy and sensitive approach utilizing high performance liquid chromatography (HPLC) was developed for the identification and quality evaluation of Rutongshu oral liquid (ROL). What is more, nontargeted metabolomic analysis was conducted to gain a global view in terms of its chemical profile. In this study, 16 peaks from different batches (S1–S10) of ROL samples produced by Taihe Hospital of Chinese Medicine were selected as common peaks for the evaluation of their similarity whose values of all tested 10 batches exceeded 0.90 when compared with the control fingerprints. Meanwhile, simultaneous quantification of five markers in the oral solution, including albiflorin, paeoniflorin, chlorogenic acid, quercetin and ferulic acid was performed, and standard curves established for respective reference substances showed good regression in the linear range (r 2 > 0.999) with recoveries in the range of 98.96–102.35%. The ultra-high performance liquid chromatography (UHPLC) combined with Orbitrap Exploris 120 mass spectrometer resulted in 88 identified compounds. The results of validation showed that the established method was reproducible, precise and stable. This study offers an effective, dependable and useful approach for the systematic evaluation of the hospital formulation ROL. [ABSTRACT FROM AUTHOR]

Target tracking is an important part of the anti-submarine warfare process of surface ships. In the process of target tracking, the four elements of targets are obtained through the target motion element solving, and the hit probability is calculated through the result. The solution results of the target motion elements are affected by many factors, such as battlefield situation, detection method, and solution model. In order to associate the separated factor, a quality evaluation system for solving target motion elements was constructed from the four aspects of completeness, availability, timeliness, and accuracy of the solved data. In order to minimize the total deviation, the analytic hierarchy method and entropy weight method were effectively combined to determine the index weight. The quality evaluation value of the target motion elements was obtained by weighted summation and compared with the simulation result of hit probability. The simulation results show that the error between the approximate hit probability and the actual hit probability calculated by using the solved mass is less than 9.2%. The evaluation system constructed in this paper can effectively combine all information, reasonably and fully express the hit probability, and is conducive to the decision-making of the engagement.

Abstract A prototype refrigerated unit with a capacity of 30 to 60 kg depending on bulk density was designed and developed to preserve fresh fruits and vegetables. The performance of the device was evaluated in terms of cooling time, cooling efficiency, specific energy consumption, unit device cost, and quality of stored products. Guava and cauliflower were stored in the device at 5 ± 1 °C and 6 ± 1 °C, respectively at 95 ± 2% relative humidity (RH) to evaluate the storing performance of the device. The cooling time was 2.08 ± 0.05 h at 5 °C and the device showed little fluctuation in relative humidity under load conditions compared to empty conditions at set temperatures of 5 °C and 6 °C. Notably, the cooling efficiency of the device was 93 ± 2% with specific energy consumption of 0.0524 and 0.1104 kWh/kg day for preserving guava and cauliflower, respectively. The overall preservation cost was $0.116 and $0.242 per kg per month for guava and cauliflower, respectively. The results revealed that the shelf life of guava extended for 18 days in this refrigerated device with minimal quality degradation and a weight loss of 3.78%, compared with freshly harvested guava. On the contrary, the weight loss, firmness, pH, and whiteness index for cauliflower at 18 days were 7.17%, 7.17 kg/cm2, 6.59, and 64.19, respectively. Meanwhile, the fresh cauliflower exhibited a firmness of 9.85 kg/cm2, a pH of 5.74, and a whiteness index (L*) of 65.58. The results demonstrated that the freshness of stored fruits and vegetables was preserved, meeting physiological and chemical quality standards. Therefore, the inexpensive refrigeration system, effectively maintains necessary temperature and humidity levels, offering a profitable solution for minimizing post-harvest losses at the greengrocer level. Additionally, the scientific methodology outlined can be readily applied to develop commercial-scale refrigeration units for preserving high-moisture produce.

Abstract Background In recent years, global climate change in tandem with increased human activity has resulted in habitat degradation or the migration of rare medicinal plants, potentially impacting the quality of medicinal herbs. Astragalus membranaceus var. mongholicus is a valuable bulk medicinal material in Northwest China. As the demand for this medicinal herb continues to increase in both domestic and international markets, ensuring the sustainable development of high-quality Astragali Radix is important. In this study, the maximum entropy (Maxent) model was applied, thereby incorporating 136 distribution records, along with 39 environmental factors of A. membranaceus var. mongholicus, to assess the quality zonation and potential distribution of this species in China under climate change. Results The results showed that the elevation, annual mean temperature, precipitation of wettest month, solar radiation in June, and mean temperature of warmest quarter were the critical environmental factors influencing the accumulation of astragaloside IV and Astragalus polysaccharide in A. membranaceus var. mongholicus. Among the twelve main environmental variables, annual mean temperature, elevation, precipitation of the wettest month, and solar radiation in November were the four most important factors influencing the distribution of A. membranaceus var. mongholicus. In addition, ecological niche modelling revealed that highly suitable habitats were mainly located in central and western Gansu, eastern Qinghai, northern Shaanxi, southern Ningxia, central Inner Mongolia, central Shanxi, and northern Hebei. However, the future projections under climate change suggested a contraction of these suitable areas, shifting towards northeastern high-latitude and high-elevation mountains. Conclusions The findings provide essential insights for developing adaptive strategies for A. membranaceus var. mongholicus cultivation in response to climate change and can inform future research on this species. By considering the identified environmental factors and the potential impacts of the predicted climate changes, we can visualize the regional distribution of high-quality Radix Astragali and develop conservation strategies to protect and restore its suitable habitats.

The objective of this study was to assess the differences in the quality of fried potato fries across various potato varieties (lines) in Qinghai Province, as well as to identify suitable potato varieties (lines) for the production of fried potato fries. Twenty-one representative potato varieties (lines) were selected as raw materials for the production of fried potato fries, and then their fundamental nutritional attributes and quality characteristics were evaluated. The suitability of the fried potato fries was assessed using principal component analysis, correlation analysis, and iterative clustering. The results revealed considerable differences in the nutritional indicators among different potato varieties (lines) in Qinghai Province. Principal component analysis identified five principal components, which accounted for 86.43% of the cumulative variance contribution rate. Leveraging the comprehensive scores from iterative clustering, three suitable potato varieties (lines) for processing fried potato fries were identified, namely, Qingshu 15, Qingshu 14, and Qing 11-2-9. Evaluation of their palatability characteristics demonstrated that the fried potato fries exhibited a crispy exterior and tender interior texture (sensory score of 62~73), favorable chewiness (52~53), and bright color (a* value of 4.0~6.5), aligning with practical applications. The results achieved efficient utilization of potato processing in Qinghai Province, which could meet consumer demand, and provided a theoretical basis for potato quality improvement and special variety breeding.

Honey is rich in nutrients and has a wide range of biological activities. However, due to the different botanical origins, geographical origins, entomological origins, and maturity, honey shows significant differences in their endogenous compositions and nutritional values. Volatile organic compounds (VOCs) are closely related to the characteristic properties of honey, and can be used to characterize the differences between honey. Gas chromatography-ion mobility spectroscopy (GC-IMS) is a new technology which combines gas chromatography with ion mobility spectroscopy for the determination of VOCs. In recent years, GC-IMS has been gradually applied to entomological origins identification, geographical origin tracing, botanical origin differentiation, adulteration identification and maturity evaluation of honey, and has achieved good results, showing great application potential in honey quality evaluation. In this paper, the application research progress of GC-IMS for honey quality evaluation is summarized. It is suggested that future research should be carried out from the aspects of establishing honey GC-IMS database, developing GC-IMS equipment with fusion quantitative function, developing the technical standard of quality evaluation based on GC-IMS, and using GC-IMS in combination with other detection technologies，in order to provide reference for the application of GC-IMS for honey quality control, flavor research and product development.

The intelligent university teaching detection system can effectively improve the teaching efficiency of university classrooms and improve the teaching environment. In order to improve the quality of online teaching supervision, this study combines digital monitoring technology to monitor the online teaching process in colleges and universities, and analyzes the method and process of using the equivalence line and the rotation theorem to estimate the projection angle. This work applies a projection method to digital teaching detection, improves the algorithm based on requirements, uses factor improvement methods to improve the problems in model application, uses requirement analysis methods to construct a system model, and uses experimental analysis methods to verify the effectiveness of the proposed algorithm and model. With the support of simulation platforms and mathematical statistical methods, the effectiveness of the system model is verified in this work. From the evaluation results, it can be seen that the evaluation results of the system model in this work are distributed between [84,92], indicating that the use of the system in this study is very excellent. The experimental research shows that the digital online monitoring technology proposed in this study can monitor students in real time in online teaching in colleges and universities, effectively improve the participation of students in the online teaching process, and play an important role in improving the quality of teaching.

Introduction: The quality of traditional Chinese medicine is based on the content of their secondary metabolites, which vary with habitat adaptation and ecological factors. This study focuses on Lonicera japonica Flos (LJF), a key traditional herbal medicine, and aims to evaluate how ecological factors impact its quality. Methods: We developed a new evaluation method combining high-performance liquid chromatography (HPLC) fingerprinting technology and MaxEnt models to assess the effects of ecological factors on LJF quality. The MaxEnt model was used to predict suitable habitats for current and future scenarios, while HPLC was employed to analyze the contents of key compounds. We also used ArcGIS for spatial analysis to create a quality zoning map. Results: The analysis identified 21 common chromatographic peaks, with significant variations in the contents of Hyperoside, Rutin, Chlorogenic acid, Cynaroside, and Isochlorogenic acid A across different habitats. Key environmental variables influencing LJF distribution were identified, including temperature, precipitation, and elevation. The current suitable habitats primarily include regions south of the Yangtze River. Under future climate scenarios, suitable areas are expected to shift, with notable expansions in southern Gansu, southeastern Tibet, and southern Liaoning. The spatial distribution maps revealed that high-quality LJF is predominantly found in central and southern Hebei, northern Henan, central Shandong, central Sichuan, southern Guangdong, and Taiwan. Discussion: The study indicates that suitable growth areas can promote the accumulation of certain secondary metabolites in plants, as the accumulation of these metabolites varies. The results underscore the necessity of optimizing quality based on cultivation practices. The integration of HPLC fingerprinting technology and the MaxEnt model provides valuable insights for the conservation and cultivation of herbal resources, offering a new perspective on evaluating the impact of ecological factors on the quality of traditional Chinese medicines. [ABSTRACT FROM AUTHOR]

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The experiment aimed to study the product quality of the Bacillus subtilis-fermented compound feed. The trial optimized the fermentation conditions by examining the effects of wheat bran addition, the ratio of auxiliary materials (addition of garlic peel and ginkgo leaf), and fermentation time on protease activity, and comprehensively evaluated the nutritional value and quality of the fermented feed by detecting the number of live bacteria and pH value before and after fermentation, as well as the content of conventional nutrients, peptides, soluble protein, and free amino acids, and the degree of protein hydrolysis during the fermentation process. The results showed that based on protease activity as an indicator, the optimal fermentation conditions were determined through single-factor and orthogonal tests to be 2% wheat bran, 2.5% garlic peel + 2.5% ginkgo leaf, and a fermentation time of 72 hours. Under these conditions, the protease activity was 342.36 U/g. Bacillus subtilis UL-191 grew well on the substrate, with the number of live bacteria reaching 3.5×1014 CFU/g. There were no significant changes in moisture and crude ash content before and after fermentation, while the content of crude protein and crude fat increased significantly, with large molecular proteins being degraded into proteins of smaller molecular weights. The degree of protein hydrolysis, peptide content, and free amino acid content all showed an upward trend with the extension of fermentation time. At 72 hours of fermentation, the degree of protein hydrolysis reached 25%, and the contents of peptides and free amino acids reached 182.9 and 1 006.4 μg/g, respectively. The study indicates that the quality of the experimentally prepared fermented compound feed is high and has certain market application prospects. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Food Safety & Quality is the property of Journal of Food Safety & Quality Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The diversity and dynamics of quality index information bring challenges to quality assessment of experience products. This paper proposes a three-stage quality assessment method based on grounded theory, association analysis, combined weighting, sentiment analysis and cloud model. Firstly, based on online reviews, the true quality indicators of animation are recognized by grounded theory, and the relationships among quality indicators are identified by association analysis. Secondly, by introducing the principle of gaming, the combined weighting based on network opinion leader and network opinion follower is proposed. Finally, an animation comprehensive quality evaluation model based on cloud model and sentiment analysis is proposed. The feasibility and practicability of the method are verified on multiple animation datasets, and the quality levels of different sales products are obtained, providing a direction for animation quality improvement. Meanwhile, this paper further demonstrates the method's superiority by comparing it with other methods. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Henan Agricultural Sciences is the property of Editorial Board of Journal of Henan Agricultural Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)