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Introduction: The use of a reliable scoring system for quality assessment (QA) is imperative to limit inconsistencies in measuring ultrasound acquisition skills. The current grading scale used for QA endorsed by the American College of Emergency Physicians (ACEP) is non-specific, applies irrespective of the type of study performed, and has not been rigorously validated. Our goal in this study was to determine whether a succinct, organ-specific grading scale designed for lung-specific QA would be more precise with better interobserver agreement.Methods: This was a prospective validation study of an objective QA scale for lung ultrasound (LUS) in the emergency department. We identified the first 100 LUS performed in normal clinical practice in the year 2020. Four reviewers at an urban academic center who were either emergency ultrasound fellowship-trained or current fellows with at least six months of QA experience scored each study, resulting in a total of 400. The primary outcome was the level of agreement between the reviewers. Our secondary outcome was the variability of the scores given to the studies. For the agreement between reviewers, we computed the intraclass correlation coefficient (ICC) based on a two-way random-effect model with a single rater for each grading scale. We generated 10,000 bootstrapped ICCs to construct 95% confidence intervals (CI) for both grading systems. A two-sided one-sample t-test was used to determine whether there were differences in the bootstrapped ICCs between the two grading systems.Results: The ICC between reviewers was 0.552 (95% CI 0.40–0.68) for the ACEP grading scale and 0.703 (95% CI 0.59–0.79) for the novel grading scale (P < 0.001), indicating significantly more interobserver agreement using the novel scale compared to the ACEP scale. The variance of scores was similar (0.93 and 0.92 for the novel and ACEP scales, respectively).Conclusion: We found an increased interobserver agreement between reviewers when using the novel, organ-specific scale when compared with the ACEP grading scale. Increased consistency in feedback based on objective criteria directed to the specific, targeted organ provides an opportunity to enhance learner education and satisfaction with their ultrasound education.

Existing systems for automating the assessment of risk‐of‐bias (RoB) in medical studies are supervised approaches that require substantial training data to work well. However, recent revisions to RoB guidelines have resulted in a scarcity of available training data. In this study, we investigate the effectiveness of generative large language models (LLMs) for assessing RoB. Their application requires little or no training data and, if successful, could serve as a valuable tool to assist human experts during the construction of systematic reviews. Following Cochrane's latest guidelines (RoB2) designed for human reviewers, we prepare instructions that are fed as input to LLMs, which then infer the risk associated with a trial publication. We distinguish between two modelling tasks: directly predicting RoB2 from text; and employing decomposition, in which a RoB2 decision is made after the LLM responds to a series of signalling questions. We curate new testing data sets and evaluate the performance of four general‐ and medical‐domain LLMs. The results fall short of expectations, with LLMs seldom surpassing trivial baselines. On the direct RoB2 prediction test set (n = 5993), LLMs perform akin to the baselines (F1: 0.1–0.2). In the decomposition task setup (n = 28,150), similar F1 scores are observed. Our additional comparative evaluation on RoB1 data also reveals results substantially below those of a supervised system. This testifies to the difficulty of solving this task based on (complex) instructions alone. Using LLMs as an assisting technology for assessing RoB2 thus currently seems beyond their reach. [ABSTRACT FROM AUTHOR]

The authenticity and quality of traditional Chinese medicine (TCM) directly impact clinical efficacy and safety. Quality assessment of traditional Chinese medicine (QATCM) is a global concern due to increased demand and shortage of resources. Recently, modern analytical technologies have been extensively investigated and utilized to analyze the chemical composition of TCM. However, a single analytical technique has some limitations, and judging the quality of TCM only from the characteristics of the components is not enough to reflect the overall view of TCM. Thus, the development of multi-source information fusion technology and machine learning (ML) has further improved QATCM. Data information from different analytical instruments can better understand the connection between herbal samples from multiple aspects. This review focuses on the use of data fusion (DF) and ML in QATCM, including chromatography, spectroscopy, and other electronic sensors. The common data structures and DF strategies are introduced, followed by ML methods, including fast-growing deep learning. Finally, DF strategies combined with ML methods are discussed and illustrated for research on applications such as source identification, species identification, and content prediction in TCM. This review demonstrates the validity and accuracy of QATCM-based DF and ML strategies and provides a reference for developing and applying QATCM methods. [ABSTRACT FROM AUTHOR]

The food and agriculture sector is one of the world's most critical and essential industries, as it provides the necessities of life for a growing global population. Food assessment, especially fruit, is an essential mechanism for producers and industries that can affect fruit quality assessment and export markets. However, the food industry still practices manual fruit classification and quality assessment during post-harvest handling and is prone to human error. This research aims to implement a computer-assisted and non-destructive method to classify and determine fruit quality based on colour, odour, and shape characteristics to improve the efficiency of the post-harvest handling process. Six thousand samples of mango, honeydew, chilli and tomato went through the system with data processing techniques (image and odour) and the predictive model using multimodal deep learning algorithms such as convolutional neural network (CNN), CNN-LSTM, and CNN-SVM. The predictive model extracted and concatenated odour and image features using the feature fusion level method. As a result, multimodal CNN-LSTM achieved the highest accuracy rate, such as 93.50% in fruit classification and 96.08% in fruit quality assessment. The experiments demonstrate the feasibility of the proposed multimodal deep learning method in fruit classification and quality assessment. Finally, this fruit assessment intends to provide good food quality to the customers and maintain the food quality consistently. [ABSTRACT FROM AUTHOR]

Mexico is one of the main countries in the production and exportation of bell pepper (Capsicum annuum) hence, emerging techniques to monitor and assess quality parameters postharvest is a constant topic of interest. On the other hand, color image processing is a non-invasive technique that is gaining popularity in the agro-industrial sector. Color analysis helps as an indirect or correlation measure to quantify and qualify visual quality attributes (size, shape, maturity, etc.) and even non-visual ones such as flavor. Recent techniques involve a pre-processing of the information (changing the RGB space into another) in order to obtain the chromaticity and luminescence parameters that point to the characterization of the physicochemical profile; this stage may present a loss of information. Therefore, this work presents the use of Quaternion Algebra for the management of information as a single entity, avoiding the pre-processing stage. The image is transformed into a pure quaternion; processed using the Fast Fourier Transform described in Quaternions. Image acquisition is carried out using any mobile device or low-cost sensor, which provides an advantage over other proposals. The results show that the determination of physical measurements such as length, width and thickness are characterized according to pre-established standards. In addition, we identify the state of maturity; as well as areas in which damage or injuries are found. The validation of the results obtained was done in consideration of Good Management Practices as well as, the state of the art having a high agreement with them. [ABSTRACT FROM AUTHOR]

This article explores the significance of high-quality healthcare data and the challenges involved in maintaining data quality. Healthcare data possess unique characteristics such as heterogeneity, incompleteness, timeliness, longevity, privacy, and ownership. Inaccurate data can result in financial losses, increased expenses, and can impact the performance of artificial intelligence models. The article emphasizes the necessity for tailored quality assessment indicators and methods for healthcare data, as well as the implementation of quality management measures. Additional research is required to redefine quality assessment criteria and develop quantification methods specifically for healthcare data. The authors stress the importance of interdisciplinary collaboration among experts from diverse fields to ensure effective data quality assessment. [Extracted from the article]

Quality assessment of ultrasound medical systems is a demanding task due to the high number of parameters to quantify their performance: in the present study, a Kiviat diagram-based integrated approach was proposed to effectively combine the contribution of some experimental parameters and quantify the overall performance of pulsed wave Doppler (PWD) systems for clinical applications. Four test parameters were defined and assessed through custom-written measurement methods based on image analysis, implemented in the MATLAB environment, and applied to spectral images of a flow phantom, i.e., average maximum velocity sensitivity (AMVS), velocity measurements accuracy (VeMeA), lowest detectable signal (LDS), and the velocity profile discrepancy index (VPDI). The parameters above were scaled in a standard range to represent the four vertices of a Kiviat plot, whose area was considered the overall quality index of the ultrasound system in PWD mode. Five brand-new ultrasound diagnostic systems, equipped with linear array probes, were tested in two different working conditions using a commercial flow phantom as a reference. The promising results confirm the robustness of AMVS, VeMeA, and LDS parameters while suggesting further investigations on the VPDI. [ABSTRACT FROM AUTHOR]

OBJECTIVES: This study aimed to systematically assess the methodological quality and key recommendations of the guidelines for the diagnosis and treatment of liver failure (LF), furnishing constructive insights for guideline developers and equipping clinicians with evidence-based information to facilitate informed decision-making. DATA SOURCES: Electronic databases and manual searches from January 2011 to August 2023. STUDY SELECTION: Two reviewers independently screened titles and abstracts, then full texts for eligibility. Fourteen guidelines were included. DATA EXTRACTION AND SYNTHESIS: Two reviewers extracted data and checked by two others. Methodological quality of the guidelines was appraised using the Appraisal of Guidelines for Research and Evaluation II tool. Of the 14 guidelines, only the guidelines established by the Society of Critical Care Medicine and the American College of Gastroenterology (2023) achieved an aggregate quality score exceeding 60%, thereby meriting clinical recommendations. It emerged that there remains ample room for enhancement in the quality of the guidelines, particularly within the domains of stakeholder engagement, rigor, and applicability. Furthermore, an in-depth scrutiny of common recommendations and supporting evidence drawn from the 10 adult LF guidelines unveiled several key issues: controversy exists in the recommendation, the absence of supporting evidence and confusing use of evidence for recommendations, and a preference in evidence selection. CONCLUSIONS: There are high differences in methodological quality and recommendations among LF guidelines. Improving these existing problems and controversies will benefit existing clinical practice and will be an effective way for developers to upgrade the guidelines. [ABSTRACT FROM AUTHOR]

Quality assessment (QA) of magnetic resonance imaging (MRI) encompasses several factors such as noise, contrast, homogeneity, and imaging artifacts. Quality evaluation is often not standardized and relies on the expertise, and vigilance of the personnel, posing limitations especially with large datasets. Machine learning based on convolutional neural networks (CNNs) is a promising approach to address these challenges by performing automated inspection of MR images. In this study, a CNN for the detection of random head motion artifacts (RHM) in T1-weighted MRI as one aspect of image quality is proposed. A two-step approach aimed to first identify images exhibiting pronounced motion artifacts, and second to evaluate the feasibility of a more detailed three-class classification. The utilized dataset consisted of 420 T1-weighted whole-brain image volumes with isotropic resolution. Human experts assigned each volume to one of three classes of artifact prominence. Results demonstrate an accuracy of 95% for the identification of images with pronounced artifact load. The addition of an intermediate class retained an accuracy of 76%. The findings highlight the potential of CNN-based approaches to increase the efficiency of post-hoc QAs in large datasets by flagging images with potentially relevant artifact loads for closer inspection. [ABSTRACT FROM AUTHOR]

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Combined with the structure from motion (SfM) technique, unmanned aerial vehicles (UAVs) are powerful tools for generating high-resolution digital elevation models (DEMs) for application in hazard assessments. During our field observations in October 2015 at Langtang Village, which was destroyed by the Gorkha earthquake in April 2015, three different UAVs with mounted cameras were operated to evaluate the volume of the avalanche deposit covering the village. This study evaluated the performance of DEMs created from the different cameras on board those UAVs. Multiple DEMs for the different cameras, including Sony-α7R (PA7), Ricoh-GR (XGR), and Canon-IXUS (EIX), were created using SfM software. All DEMs were compared with a base DEM created from differential global positioning system survey data, which was obtained simultaneously with the UAV campaigns. The results show that the elevation difference of PA7-, XGR-, and EIX-DEMs are within ±0.14 m; the standard deviations of elevation difference range from 0.33 to 0.40 m. Although there were slightly larger differences in elevation on the southwest-to-west sides of the XGR- and EIX-DEMs, which can be attributed mainly to the flight paths and ground control point network, our DEMs are still of high enough quality to be used in hazard assessments. [ABSTRACT FROM AUTHOR]

Featured Application: The proposed SMI-LE index can be used to plan healthier school lunches in line with the idea of a sustainable diet. The School Meal Index-Lunch Evaluation (SMI-LE) has been developed to assess school lunch quality. The aim of this study was to use the SMI-LE index for a comparative analysis of the quality of school meals planned in primary schools in Warsaw and Zagreb. The SMI-LE index was used to assess 4-week school meals in both cities. The collected menus were analyzed both in terms of overall quality as an average of points over 4 weeks and in terms of individual categories. According to the SMI-LE index, 4-week school lunches were rated on average 64 and 62 points out of a total of 140 points, in Warsaw and Zagreb, respectively. The majority of school lunches in Zagreb were classified as medium quality, while in Warsaw, over 50% were classified as good quality. Aspects that could be improved include an increase in vegetable availability and variety, limiting the meat dishes, and providing alternatives for children on vegetarian diets, as well as the ability to choose portion sizes. Polish schools need to change their approach to school meals. Following the example of schools in Zagreb, these could be one-course hot meals but with a wider range of raw vegetables and fruits. The current findings also highlight the importance of future research to develop standards for school food policies and investigate whether such a school food program could improve the eating habits and nutritional status of primary school children in the long term. Using the SMI-LE index to design new school meals could be a good solution to improve the quality of school meals. [ABSTRACT FROM AUTHOR]

Background: Over the past years, there has been a growing concern that a considerable amount of anti-malarial supply in the underdeveloped world particularly in the private sector, is of poor quality. The World Health Organization (WHO) has received about 1500 reports that mentions instances of substandard and falsified products since 2013. The majority of the reports concerned antibiotics and anti-malarials. The majority of reports (42%) originate from the WHO African region. Objective: This study intends to assess the quality of the most widely used anti-malarial medications [artemether-lumefantrine tablets, chloroquine phosphate tablets, primaquine phosphate tablets, artesunate, and artemether injections] in Gambella, South-West, Ethiopia. Methods: A total of 52 samples were collected on June 2022 from Gambella National Regional State, Ethiopia. Half of the districts (six) located in the four zones of the region were chosen using simple random sampling technique. All drug retail outlets available in the selected districts (locally known as woredas) were included. The samples were subjected to visual inspection with a tool adopted from the joint WHO/FIP/ USP checklist. The pharmacopeial tests for identification, uniformity of dosage forms, assay, thickness, diameter, hardness, friability, disintegration test, dissolution, and sterility tests were carried out according to the USP 44-NF 39 and International Pharmacopoeia 11th edition, 2022 monographs. Results and Discussion: Only 25% of the samples were registered on the Ethiopian Food and Drug Authority (EFDA's) electronic regulatory/ registration system (ERIS). Besides, 88.8% of artemether injection products were presented in clear glass ampoules. This might expose the products to photochemical degradation that leads to in loss of anti-plasmodial activity. In addition, 50% of the artemether products assessed were not bioequivalent with the comparator product in the in vitro dissolution comparison tests. Overall, the study findings reveal a high prevalence (58.3%) of substandard anti-malarial drugs in the region. The stated percent of the samples had failed in one or more of the quality test parameters assessed in this study. Conclusion: The study findings reveal a high prevalence (58.3%) of substandard anti-malarial drugs in the region. Only a quarter were registered and 38% of the unregistered products failed the quality tests. Hence, the national, regional medicine regulatory bodies and other stake holders should perform the required roles to circumvent presence of Substandard and Falsified (SF) anti-malarial drugs in the study sites. [ABSTRACT FROM AUTHOR]

Introduction: Pediatric dentistry should rely on evidence-based clinical decisions supported by high-quality, unbiased systematic reviews (SRs). Therefore, the purpose of this study was to systematically evaluate the methodological quality and risk of bias of SRs focused on non- and micro-invasive treatment for caries lesions in primary and permanent teeth. Methods: A comprehensive search was conducted in multiple databases, including MEDLINE/PubMed, Scopus, Web of Science, EMBASE, Epistemonikos, and ProQuest, up to March 2023 to identify relevant systematic reviews (SRs) focused on non- and micro-invasive caries treatment. Two independent reviewers extracted data from the included SRs and assessed the methodological quality and risk of bias using the AMSTAR 2 and ROBIS tools, respectively. Results: A total of 39 SRs were included in the analysis. Among these, 27 SRs (69.2%) were assessed as having critically low methodological quality, 11 SRs (28.2%) were considered to have low methodological quality, and only one SR was rated as high-quality. The primary concern identified was the absence of protocol registration before commencing of the study, observed in 33 SR when using the AMSTAR 2 tool. According to the ROBIS tool, 21 studies (53.8%) were categorized as low risk of bias, 10 (25.6%) as high risk, and eight (20.5%) as unclear risk of bias. Conclusion: Our analysis revealed that SRs focused on non- and micro-invasive treatment for caries in children and adolescents had critically low methodological quality according to the AMSTAR 2 tool but demonstrated a low risk of bias based on the ROBIS tool. These findings highlight the importance of emphasizing prospective protocol registration, transparent reporting of statistical analyses, and addressing potential bias implications within this topic. By addressing these issues, we can enhance the quality of SRs and ensure that clinical decisions rely on unbiased and trustworthy evidence. [ABSTRACT FROM AUTHOR]

The effect of chitosan (CH) coating, carbon dots (CDs) and ultrasound (US) treatment on microorganisms and the physicochemical quality of fresh-cut (FC) lettuce was investigated. FC lettuces were treated by US and dipped into CD/CH coating, then packed and stored for 15 d at 4 °C. Results presented that CD/CH coating exhibited a superior effect on the depressing growth of aerobic plate count, mould and yeast, the decrease of respiratory rate, the inhibition of peroxidase and polyphenol oxidase activities, the maintenance of ascorbic acid and chlorophyll contents, the reduction of mass loss, the restriction of water distribution in US-treated FC lettuce. This exhibited that CD/CH coating effectively kept the microbial and physicochemical quality of FC lettuce. [ABSTRACT FROM AUTHOR]

Deep Learning (DL) has emerged as a pivotal modelling tool in various domains because of its proficiency in learning distributed representations. Numerous DL algorithms have recently been proposed and applied to non-destructive testing (NDT) methods in agriculture. This study aimed to review the state-of-the-art applications of DL algorithms in NDT by analysing the application of DL to specific NDT applications and highlighting their contributions and challenges. It first presents a comprehensive overview of various NDT techniques that have been combined with DL in agricultural product evaluation, and then briefly describes their applications in diverse NDT tasks, such as image classification, object detection, image retrieval, and semantic segmentation. Second, this study addresses the ongoing challenges associated with data collection and fusion, model complexity, computational requirements, and robustness. Finally, future research directions are examined, underscoring the potential of novel neural network architectures and cross-disciplinary collaborations. This review aims to provide a clear understanding of the current state of DL-based NDT in agricultural product examinations and its prospects for the future. © 2017 Elsevier Inc. All rights reserved. Detailed visual map of the survey, illustrating the depth and breadth of the research field and the survey's comprehensive approach to the topic. The central concept: deep learning-based non-destructive testing (NDT) in agriculture branches out into multiple sections. The sections represent the technical aspects, such as deep learning techniques and NDT methods, the challenges in the field, future research directions, the potential impacts on agriculture sector, and the ethical implications of AI use in agriculture. [Display omitted] • Data structures of non-destructive methods input into neural network are summarised. • Metrics for the deployment of deep learning models are discussed. • Tailored DL architectures and cross-disciplinary collaboration are key direction. • Data issues, model complexity, and model robustness are main challenges. [ABSTRACT FROM AUTHOR]

Purpose: Search Engine Optimisation (SEO) covers processes aimed at improving website quality. SEO audits can be used to conduct comparative and competitive analyses to identify good practices employed by other online platforms. The article scores selected marketplace and e-commerce websites in terms of search engine optimisation. Design/methodology/approach: We analyse the quality of selected marketplace and e-commerce websites with synthetic aggregate metrics, so-called SEO Score. The first stage involved exploratory quality tests, whereby the home page source code was analysed for every website. The second stage was algorithmic tests using selected online tools. Findings: The websites scored 2,126 out of 3,000 points in total. It is 71% of the maximum score. This means that, according to the test applications, not many attributes require SEO effort under the employed research design. Four out of the five tested websites had their names (brands) in the meta description tag. All the portals had the title tag. However, only one site had the meta keywords tag. Originality/value: The research apparatus employed is sufficient to identify basic design flaws, which makes it useful for competitive analysis. Our algorithmic analysis pinpointed differences in the quality of leading marketplace and e-commerce websites in Poland. The exploratory research revealed certain good practices regarding meta information on marketplace and e-commerce websites, which may affect SEO. [ABSTRACT FROM AUTHOR]

Fruit and vegetable quality assessment is a critical task in agricultural and food industries, impacting various stages from production to consumption. Leveraging deep learning methods, particularly through sensor fusion, offers promising avenues to enhance the accuracy and robustness of quality assessment systems by amalgamating information from diverse sensor modalities such as visual, spectral, and tactile. The review scrutinizes a plethora of sensor fusion strategies, encompassing early fusion, late fusion, and hybrid fusion approaches, each with its distinct advantages and limitations. Furthermore, it explores the utilization of various deep learning architectures, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and their combinations, tailored specifically for multimodal data fusion. Additionally, attention is paid to the challenges and considerations associated with sensor fusion in this domain, including data heterogeneity, synchronization, and feature alignment. Moreover, the review discusses the implications of dataset size, diversity, and annotation quality on the effectiveness of deep learning-based fusion models. Furthermore, it sheds light on the transferability of fusion models across different fruit and vegetable types and environmental conditions, highlighting the need for domain adaptation techniques. Moreover, the review delves into the real-world applications and commercial implementations of sensor fusion-based quality assessment systems, providing insights into their scalability, efficiency, and economic viability. [ABSTRACT FROM AUTHOR]

Hygiene practices are crucial for the production of fermented products, as they affect both product quality and safety. Fermented products, including dairy-based such as kefir, kombucha, and traditional ethnic drinks, rely on beneficial microbes. However, poor cleanliness might introduce dangerous microorganisms, jeopardizing customer health and product stability. This study aims to discuss the key hygiene measures required for safe and high-quality drinkable dairy-based and plant-based fermented product production and to avoid cross-contamination, fermentation vessels, utensils, and storage containers should be cleaned and sterilized regularly. Personal hygiene for workers is also critical, including adequate handwashing, the use of protective equipment, and hygiene protocol training. Another key part of industrial facility management is environmental control and furthermore, adopting Hazard Analysis and Critical Control Points (HACCP) systems allows for the systematic identification and mitigation of production-related risks. Regular microbiological examination of items and surfaces helps to ensure that hygiene methods are effective and that the products fulfill safety requirements. Therefore, strict hygiene measures must be followed when creating fermented drinks to provide safe, high-quality products. Such procedures not only protect consumer health, but also improve product shelf life and sensory properties, increasing consumer trust and satisfaction. [ABSTRACT FROM AUTHOR]

The article studies problematic aspects of expansion and development of service activities in Russia. The main purpose of the study is to analyze problematic aspects of the service sphere development and existing and most popular methods of assessing the quality of services. The relevance of the study is due to the need to expand service in the country, considering orientation on the interests of the end consumer and with simultaneous improvement of service quality. The main objectives of the study are: to identify problematic aspects of development of service activities in Russia, to identify and analyze the shortcomings of the methods used by service enterprises to assess the quality of services, and to propose options for their minimization and elimination. The article used both theoretical methods (analysis of current regulatory legal acts, as well as scientific works of researchers in this field) and empirical research methods (practical substantiation of the need to improve the quality of services provided to customers). On the basis of the analysis of the most popular and frequently used methods of service quality assessment the advantages and disadvantages of their application have been revealed. The study results are the problems identification that have a negative impact on service activities development and proposal of possible options for their solution.

Media messages are any form of communication delivered to the audience, broadcasted in written, oral or visual form. They may include TV shows, web pages, advertisements, news stories, blogs or social media posts, inter alia. At present, facts are no longer the paradigm of journalism. They are often replaced by short messages constructed on the basis of biased or emotional content. In addition, commercial value of news and digitization of resources have also changed the formation of texts and images. They are built using entries posted on Facebook or Twitter (often by fake accounts), instead of face-to-face interviews, participant observation, or citing primary sources and opinions. On the other hand, there are numerous discussions on the quality of data and information, also in the context of journalism. Although there is no agreement whatsoever as to the factors contributing to high-quality communication, the author attempts to demonstrate a new model for quality assessment of written media messages. It comprises four main groups of quality factors, namely: 1) information, 2) linguistic, 3) publishing, and 4) useability. Each group consists of specific criteria, which are analyzed with respect to different media content. Its potential of application for quality assessment of press and social media will be discussed.

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.

Abstract This study introduces a comprehensive approach for classifying individual malting barley kernels, involving dual-sided kernel imaging, a specifically designed image processing algorithm, an optimized deep neural network architecture, and a mechanical sorting system. The proposed method achieves precise classification into multiple classes, aligning with quality standards for malting material assessment. Throughout the study, various image analysis techniques were assessed, including traditional feature engineering, established transfer learning deep neural network architectures, and our custom-designed convolutional neural network tailored for barley kernel image analysis. Comparative analysis underscores the superior performance of our network model. The study reveals that our proposed deep learning network achieves a 94% accuracy in classifying barley kernel defects and varieties, outperforming well-established transfer learning models to complex architectures that attain 93% accuracy. Additionally, it surpasses the traditional machine learning approach involving feature extraction and support vector machine classifiers, which achieve accuracy below 90% in detecting defective kernels and below 70% in varietal classification. However, we also noted the traditional approach’s advantage in morphological feature recognition. This observation guides new research toward integrating morphological feature extraction techniques with modern convolutional networks. This paper presents a deep neural network designed specifically for the analysis of cereal kernel images in two applications: defect and variety classification. It emphasizes the importance of standardizing kernel orientation and merging images from both sides of the kernel, and introduces a device for image acquisition that fulfills this need.

Abstract Background Over the past years, there has been a growing concern that a considerable amount of anti-malarial supply in the underdeveloped world particularly in the private sector, is of poor quality. The World Health Organization (WHO) has received about 1500 reports that mentions instances of substandard and falsified products since 2013. The majority of the reports concerned antibiotics and anti-malarials. The majority of reports (42%) originate from the WHO African region. Objective This study intends to assess the quality of the most widely used anti-malarial medications [artemether-lumefantrine tablets, chloroquine phosphate tablets, primaquine phosphate tablets, artesunate, and artemether injections] in Gambella, South-West, Ethiopia. Methods A total of 52 samples were collected on June 2022 from Gambella National Regional State, Ethiopia. Half of the districts (six) located in the four zones of the region were chosen using simple random sampling technique. All drug retail outlets available in the selected districts (locally known as woredas) were included. The samples were subjected to visual inspection with a tool adopted from the joint WHO/FIP/ USP checklist. The pharmacopeial tests for identification, uniformity of dosage forms, assay, thickness, diameter, hardness, friability, disintegration test, dissolution, and sterility tests were carried out according to the USP 44-NF 39 and International Pharmacopoeia 11th edition, 2022 monographs. Results and Discussion Only 25% of the samples were registered on the Ethiopian Food and Drug Authority (EFDA’s) electronic regulatory/ registration system (ERIS). Besides, 88.8% of artemether injection products were presented in clear glass ampoules. This might expose the products to photochemical degradation that leads to in loss of anti-plasmodial activity. In addition, 50% of the artemether products assessed were not bioequivalent with the comparator product in the in vitro dissolution comparison tests. Overall, the study findings reveal a high prevalence (58.3%) of substandard anti-malarial drugs in the region. The stated percent of the samples had failed in one or more of the quality test parameters assessed in this study. Conclusion The study findings reveal a high prevalence (58.3%) of substandard anti-malarial drugs in the region. Only a quarter were registered and 38% of the unregistered products failed the quality tests. Hence, the national, regional medicine regulatory bodies and other stake holders should perform the required roles to circumvent presence of Substandard and Falsified (SF) anti-malarial drugs in the study sites.

Graduate higher education coverage has expanded worldwide due to globalisation, the demand for more specialised human resources and online education, exacerbated by the COVID-19 pandemic. This article validates an evaluation model of academic service quality in graduate studies that integrates HiEduQual instruments with the Kano method for graduate students at a Peruvian university. A survey was conducted among graduate students (masters programmes and continuing education) at Universidad Continental, obtaining 326 responses. The study found that the attributes that have the greatest impact on student satisfaction include the presence of foreign professors, international activities, continuous improvement of university infrastructure and constant evaluation; the dimension associated with internationalisation plays an essential role in the satisfaction of graduate students, particularly in a globalised context. [ABSTRACT FROM AUTHOR]

Yi-yang Sun, Peng-fei Wang, Gui-rong Yang, Dong-qing Du, Chun-jing Li, Zi-jun Mu, Yu-xia Ma, Na Zhang Department of Acupuncture-Moxibustion and Tuina, Shandong University of Traditional Chinese Medicine, Jinan, People’s Republic of ChinaCorrespondence: Yu-xia Ma; Na Zhang, Email phdmayuxia@126.com; zhangna2008zhentui@163.comBackground: Clinical acupuncture decisions are highly operator-dependent and require physician-patient interactions. The Delphi method allows subjective factors such as expert experience and preference of patients to be taken into account in clinical decision making, which is particularly applicable to acupuncture. Currently, the Delphi method is widely used to support clinical decisions in acupuncture. Therefore, it is necessary to provide high-quality and complete descriptions of the Delphi process when making clinical decisions. This study aims to evaluate the quality of the Delphi process in acupuncture, facilitate its standardization and rigor for further clinical decision making in acupuncture.Methods: Articles sourced from six databases were searched systematically to assess the quality of the Delphi consensus process based on the standards for conducting and reporting Delphi studies (CREDES). Descriptive statistics and analysis were presented according to the percentage of each item. Five-score Likert scale was used to evaluate the reporting quality of four domains as well as each item in CREDES by two independent researchers, combined with ICC-value to assess the consistency.Results: A total of 37 qualified articles were included according to eligibility criteria. As for the low reporting rate, the item “External validation” was reported as the lowest positive rate at 32.43% and the item “Prevention of bias” was 48.65%. The item “Adequacy of conclusions”, “Definition and attainment of consensus”, and “Discussion of limitations” were reported at a positive ratio of 62.16%, 64.86%, and 67.57% individually. The average scores of the four domains based on CREDES from highest to lowest were, respectively, as follows: planning and design (68.75%), reporting (66.07%), rationale for the choice of the Delphi technique (65.54%), study conduct (45.10%).Conclusion: The reporting quality of the Delphi consensus process in acupuncture is acceptable currently, but the reporting rate on some items is still low. Further standardization, including either clearer checklists or study reports, should be developed and strengthened to guide clinical decisions in acupuncture.Keywords: delphi, consensus, acupuncture, CREDES, quality assessment

Abstract Reporting the results of quality indicators can narrow the gap in the quality of care between hospitals. While most studies rely on outcome indicators, they may not accurately measure the quality of care. Process indicators are not only strongly associated with treatment outcomes, but are also more sensitive to whether patients are treated accurately, enabling timely intervention. Our study aims to investigate whether process indicators provide a more reasonable assessment of hospital quality of care compared to outcome indicators. Data were sourced from the Specific Disease Medical Service Quality Management and Control System in China. A total of 113,942 patients with breast cancer treated in 298 hospitals between January 2019 and April 2023 were included in this retrospective study. The rankability of 11 process indicators was calculated and used as a weight to create a new composite indicator. The composite indicators and outcome measures were compared using the O/E ratio categories. Finally, in order to determine the impact of different years on the results, a sensitivity analysis was conducted using bootstrap sampling. The rankability ( $$\rho$$ ρ ) values of the eleven process indicators showed significant differences, with the highest $$\rho$$ ρ value for preoperative cytological or histological examination before surgery (0.919). The $$\rho$$ ρ value for the outcome indicator was 0.011. The rankability-weighting method yielded a comprehensive score ( $$\rho$$ ρ = 0.883). The comparison with categorical results of the outcome indicator has different performance classifications for 113 hospitals (37.92%) for composite scores and 140 (46.98%) for preoperative cytological or histological examinationbefore surgery. Process indicators are more suitable than outcome indicators for assessing the quality of breast cancer care in hospitals. Healthcare providers can use process indicators to identify specific areas for improvement, thereby driving continuous quality improvement efforts.

Abstract The use of beach-cast macroalgae as a fertilizer (F) or soil amendment (SA) is coming back into focus, due to its highly efficient transformation of CO2, nutrients, salts and minerals from its aqueous surroundings into biomass. This research studied the hydrothermal carbonization (HTC) of Fucus vesiculosus macroalgae to hydrochar and evaluated its feasibility for use in soil applications. F. vesiculosus was submitted to HTC following a full factorial design of experiments with three HTC process parameters varied to assess their impact on the hydrochars: temperature (T: 160, 190, 220 °C), solid content (%So: 20, 35%), and process water recirculation (PWrec: yes and no). In general, F. vesiculosus and its hydrochars were rich in nutrients, but also contained regulated heavy metals. Investigation of the partitioning behavior of inorganic elements between the hydrochars and process water showed that heavy metals like Cr, Pb, Co and Cu tended to accumulate in the hydrochar, unaffected by HTC conditions. Nutrients such as P, N, B, and Mn were primarily found in the hydrochar and could be partially influenced to transfer to process water by changing %So and T. The correlation between the mass fractions of 22 elements in the hydrochar and HTC process parameters was studied. T was the most influential parameter, showing a significant positive correlation for eleven elements. %So and PWrec showed inconsistent effects on different elements. When process water was recirculated, some elements decreased (Ca, Cd, Fe) while others increased (K, Na, B, N) in the hydrochar. Assessment against various regulations and standards for F and SA revealed that F. vesiculosus complied with Cd limit values for most rules including the EURF and B, and was regulated only in the RAL for SA, over the limit value. In contrast, the limit value of Cd for both F and SA applications was surpassed in the 13 hydrochars. The contents of N, P, K, S, and Na in the feedstock and hydrochars complied with European F and SA rules, while they were too high for German rules on SA. The other limits for F rules were achieved (under certain HTC process parameters) except for P (lower than the requirements in F for F. vesiculosus and its hydrochars). Graphical Abstract

The present research study explores the drinking water quality of Rawalpindi and Islamabad to identify the potent dissolved contaminants and carry out a health risk assessment as the study area houses more than 3 million people. A total of 95 drinking water samples were collected from the union councils of the selected study area and analyzed for 12 physicochemical water quality indicators. The collected datasets were interpreted using general statistics, principal component analysis and spatial analysis for knowing the variations among the collected samples. The results revealed that overall 51.57% of the drinking water samples were unsatisfactory for human consumption. The rate of physicochemical contamination was 87.27% in the rural and unauthorized housing societies. Arsenic (As) and lead (Pb) were the potent contaminants in the drinking water samples. The health risk assessment uncovered that 31.57 and 10.45% of samples had a hazard quotient (HQ) >1 for arsenic and lead, respectively. Collectively, 41 drinking water sources were identified as potential health risk sources for the residents. HIGHLIGHTS Planned sampling from 95 locations was carried out from in-use drinking water sources from the capital city Islamabad and Rawalpindi, Pakistan.; Assessment of health risks for arsenic and lead was carried out using the standard guidelines of USEPA.; The combination of spatial analysis with water quality indicators provides disseminated research findings to the general public along with scientific researchers.;

Abstract A nationwide survey of inorganic components of tap water all over Japan was conducted from 2019 to 2024. In this survey, 1564 tap water samples were collected, and an additional 194 tap water samples were collected from 33 other countries. The water samples were analyzed for 27 dissolved inorganic components, with a primary focus on the distribution of major and trace components, including Ca, Mg, K, Na, Cl−, NO3 −, SO4 2−, total-hardness, Al, Fe, Cu, Mn, and Zn. The Japanese tap water hardness was 50.5 ± 30.2 (± 1σ SD) mg/L, classified as soft water according to the World Health Organization (WHO) classification. The average content of each major component in Japanese tap water tended to be lower than those in other countries. Furthermore, Piper trilinear diagrams were used to categorize Japanese tap water types. The dominating water types were the Ca–HCO3 and mixed types, which had a nationwide distribution. Japanese tap water generally complied with Japanese and WHO drinking water criteria, with only 1% (17/1564 sites) of the samples exceeding water quality standards. Observations of water quality changes for 2 years at three household faucets revealed that fluctuations in major components and trace metals (Al, Fe, Cu, Mn, and Zn) varied in different patterns. This suggests that the behavior of trace metal elements is influenced by local infrastructure, such as supply pipes, distinct from the variability in source water quality.

The impact of civil engineering course education on civil engineers is profound and crucial. Due to the hierarchical and ambiguous nature of quality assessment for flipped classroom teaching, there is an urgent demand for a rational and effective approach to conduct such assessments. This would enable the targeted formulation of instructional improvement methods based on assessment outcomes, ultimately elevating the quality of pedagogy. This study combines the analytic hierarchy process and fuzzy evaluation method. The fuzzy evaluation method is utilized to identify four primary evaluation factor sets, fourteen secondary judgment factor sets, and five evaluation outcome sets, with subsequent quantification of the assessment results. The analytic hierarchy process is employed to ascertain the weight coefficients of the evaluation factors. The comprehensive assessment model for flipped classroom teaching quality is established. The assessment results indicate that the overall quality of flipped classroom teaching in the civil engineering major at Anhui University of Science and Technology, conducted through the platform of Superstar Learning Hub, falls within the ‘Good’ category. The fuzzy comprehensive evaluation score for extracurricular learning quality is the lowest, and the weight proportion attributed to flipped classroom infrastructure is the highest. Consequently, several targeted improvement measures are proposed to enhance the quality of flipped classroom teaching.

Abstract The recent rise in interest in point clouds as an imaging modality has motivated standardization groups such as JPEG and MPEG to launch activities aiming at developing compression standards for point clouds. Lossy compression usually introduces visual artifacts that negatively impact the perceived quality of media, which can only be reliably measured through subjective visual quality assessment experiments. While MPEG standards have been subjectively evaluated in previous studies on multiple occasions, no work has yet assessed the performance of the recent JPEG Pleno standard in comparison to them. In this study, a comprehensive performance evaluation of JPEG and MPEG standards for point cloud compression is conducted. The impact of different configuration parameters on the performance of the codecs is first analyzed with the help of objective quality metrics. The results from this analysis are used to define three rate allocation strategies for each codec, which are employed to compress a set of point clouds at four target rates. The set of distorted point clouds is then subjectively evaluated following two subjective quality assessment protocols. Finally, the obtained results are used to compare the performance of these compression standards and draw insights about best coding practices.

Background: A type 3 medication review (MR3) is a patient-centred medication service primarily provided by pharmacists and is presently employed routinely in several countries. In this process, pharmacists interview patients and collaborate with the treating physician to optimize the patient's pharmacotherapy, taking into account the patient's medication history and other medical data including laboratory values. The need to maintain the quality of such interventions during and after their initial implementation cannot be overstated. Aim: The objective of this study was to refine and assess a scoring table to evaluate the quality of MR3 conducted in Belgian community pharmacies. Methods: The comprehensive quality of MR3s was assessed by scoring its various components using a previously developed scoring table, called BRANT-MERQS, Brussels Antwerp Medication Review Quality Score. MR3s were analysed from an implementation study with patients suffering from rheumatoid arthritis (RA, subproject 1) and type 2 diabetes mellitus (T2DM, subproject 2). Additional information was obtained during a telephone call with a subset of participating pharmacists of subproject 1 who finalized their first MR3. Results: In subproject 1, a total of 21 MR3s of patients with RA were examined. The assessment showed favourable scores for elements such as a well-organized medication schedule, treatment adherence, and the elaboration of specific interventions. However, certain other quality criteria posed challenges in the evaluation, for example, the use of simple and understandable language. Pharmacists faced time constraints, and elderly general practitioners (GPs) displayed limited enthusiasm, which were notable barriers observed for this subproject. In the context of subproject 2 that investigated 41 MR3s in patients with T2DM, the quality criteria of interaction between pharmacist and GP, and used sources and tools received high scores. However, there was still room for improvement, especially in areas such as accurate dosing, handling kidney function, QT prolongation, correctly associating laboratory values with relevant drugs and medical conditions, and optimisation of medication schedules for patients. Conclusion: This study demonstrated the feasibility of MR3 quality assessment through a scoring system. However, it also unveiled the tool's current imperfections and highlighted the ongoing need for refinement, something expected of a new service in an implementation phase. [ABSTRACT FROM AUTHOR]

The water content is an essential parameter for assessing the quality of solid biofuels. In terms of economic, technical and environmental aspects a continuous determination of the solid fuel water content is sought. This article investigates the use of microwave technology for the continuous measurement of fuel water content. For this purpose, a microwave sensor was evaluated with five different types of wood chips (forest residues, beech, pine, and ash). The results of the online measurements showed a strong correlation with the reference method r < 0.9 for most materials. This means that continuous water content determination of wood fuels using microwave technology is fundamentally possible. [ABSTRACT FROM AUTHOR]

Reporting the results of quality indicators can narrow the gap in the quality of care between hospitals. While most studies rely on outcome indicators, they may not accurately measure the quality of care. Process indicators are not only strongly associated with treatment outcomes, but are also more sensitive to whether patients are treated accurately, enabling timely intervention. Our study aims to investigate whether process indicators provide a more reasonable assessment of hospital quality of care compared to outcome indicators. Data were sourced from the Specific Disease Medical Service Quality Management and Control System in China. A total of 113,942 patients with breast cancer treated in 298 hospitals between January 2019 and April 2023 were included in this retrospective study. The rankability of 11 process indicators was calculated and used as a weight to create a new composite indicator. The composite indicators and outcome measures were compared using the O/E ratio categories. Finally, in order to determine the impact of different years on the results, a sensitivity analysis was conducted using bootstrap sampling. The rankability (ρ ) values of the eleven process indicators showed significant differences, with the highest ρ value for preoperative cytological or histological examination before surgery (0.919). The ρ value for the outcome indicator was 0.011. The rankability-weighting method yielded a comprehensive score (ρ = 0.883). The comparison with categorical results of the outcome indicator has different performance classifications for 113 hospitals (37.92%) for composite scores and 140 (46.98%) for preoperative cytological or histological examinationbefore surgery. Process indicators are more suitable than outcome indicators for assessing the quality of breast cancer care in hospitals. Healthcare providers can use process indicators to identify specific areas for improvement, thereby driving continuous quality improvement efforts. [ABSTRACT FROM AUTHOR]

Background: Fractures of the distal radius are among the most common bone injuries, and their frequency is constantly increasing, leading to an elevated need for subsequent rehabilitation. This growing need has led to the emergence of online content aimed at providing guidance on rehabilitation. Nonetheless, unreviewed online content raises concerns about its reliability; therefore, the objective of this study was to evaluate the quality, reliability, and comprehensiveness of online videos concerning rehabilitation following a distal radius fracture. Methods: A total of 240 YouTube videos were screened, identifying 33 videos that met the inclusion criteria. These selected videos were evaluated by five independent experts from various professional groups, using the Global Quality Scale, the DISCERN reliability tool, and the JAMA Benchmark Score, as well as a structured set of questions to assess their comprehensiveness and coverage of pertinent aspects. Results: The observers' assessment of the Global Quality Scale exhibited a broad spectrum of viewpoints, indicating considerable variability in evaluations. In most cases, therapy aligned well with the diagnosed condition, and most raters deemed the indication and instruction in the videos acceptable. A proportion of 87% of the videos was deemed suitable for home training by at least three raters. However, a concerning trend emerged, as potential risks and pitfalls were scarcely addressed. Conclusions: The moderate overall quality of the videos and the divergence in expert opinions highlight the need for a regulatory authority to ensure adherence to guidelines and maintain high-quality content. Additionally, our results raise concerns about the applicability of established assessment tools in this context. [ABSTRACT FROM AUTHOR]

This study investigated the impact of the depulping of cocoa beans after pod opening, as well as the influences of pod storage (PS) and fermentation time on the fermentation dynamics and the overall quality of beans and liquors made thereof. Twelve variations were conducted in three experimental runs (with/without depulping; 1-/3-day PS; and fermentation times of 3, 4, 5, 6 or 7 days). Fermentation dynamics (e.g., temperature and pH) and the quality of dried beans (e.g., cut-test and fermentation index) and liquors (sensory assessment, quantification of cocoa key-odorants and tastants) were investigated. It was demonstrated that 17–20% of cocoa pulp, relative to the total bean-pulp-mass weight, could be mechanically removed without negatively affecting the bean quality. No significant differences were found in the percentages of well-fermented beans after 5–6 days fermentation with 1-day PS, resulting in 49 ± 9% with, and 48 ± 12% without depulping. There were no significant differences in key tastants present in the liquors; however, significantly less volatile acids and esters were found when liquors were produced from 5–6 day-fermented depulped beans, with 1-day PS, without negatively affecting the sensory profiles. This strategy allows producers to maximize the cacao fruit's value by integrating part of the pulp into the cocoa value chain. [ABSTRACT FROM AUTHOR]

The study aims to explore the impact of different material to water ratios on the quality of corn husk during mixed microbial fermentation. The experiment used a solid-state fermentation process, setting up four groups with material to water ratios of 30% (Group Ⅰ), 40% (Group Ⅱ), 50% (Group Ⅲ), and 60% (Group Ⅳ), with four replicates for each group. Corn husk, rice bran, and soybean meal were mixed evenly in a ratio of 20∶3∶3, then mixed with a microbial solution containing Bacillus coagulans, Lactobacillus crispatus, and Bacillus subtilis (1∶1∶1) at a seeding rate of 7%, and fermented for five days to investigate the effect of different material to water ratios on the fermentation effect of feed. The results showed that under the condition of a 50% material to water ratio, the total viable count was 3.5×108 CFU/g, which is 58 times that before fermentation. The contents of vomitoxin and dry matter (DM) in Group Ⅲ were significantly lower than those in Group Ⅰ, Group Ⅱ and Group Ⅳ (P<0.05), the content of neutral detergent fiber (NDF) in Group Ⅲ was significantly lower than that in Group Ⅰ and Group Ⅱ (P<0.05), and the pH value of Group Ⅲ was 4.18. The study indicates that the optimal material to water ratio for solid-state fermentation of corn husk by mixed microbial cultures is 50%. Under this condition, the fermented feed has a uniform and loose texture with a rich aroma. [ABSTRACT FROM AUTHOR]

Introduction: Efforts toward reducing stroke burden have been an immense challenge. One important reasons could be the scope and quality of clinical practice guidelines (CPGs) developed for stroke rehabilitation in low- and middle-income countries (LMICs), restricting its translation to clinical practice. This systematic review aimed to assess the availability, scope and quality of CPGs for stroke rehabilitation in LMICs. Methods: Following PRISMA guidelines, CPGs for stroke rehabilitation in LMICs were searched across four major electronic databases (Medline, Embase, CINAHL, and PEDro). Additional studies were identified from grey literature and a hand search of key bibliographies and search engines. The availability and content of the CPGs were narratively summarized and quality of de novo CPGs was analyzed using “Appraisal of Guidelines REsearch and Evaluation” (AGREE) tools: version II & Recommendations Excellence (REX) version. Features of contextualizations/adaptations of non-de novo CPGs were narratively summarized. Results: Twelve CPGs from 10 countries were included. CPGs from Pakistan, Sri Lanka, India, and China were developed de novo. CPGs from Kenya, Philippines, South Africa, Cameroon, Mongolia, and Ukraine were contextualized/adapted based on existing guidelines from high-income countries. Most contextualized CPGs had limited stakeholder involvement, local health systems/patient pathway analyses. All ten countries included recommendations for physiotherapy, seven for communication, swallowing, and five for occupational therapy services poststroke. Quality assessment using AGREE-REX and AGREE-II for de novo guidelines was poor, especially scoring low in development and applicability. Conclusion: Contextualized CPGs for stroke rehabilitation in LMICs were scarcely available and not meeting required quality. There is a need for development of context-specific, culturally relevant CPGs for stroke rehabilitation in LMICs to improve implementation/translation into clinical practice. [ABSTRACT FROM AUTHOR]

Nano-sized titanium dioxide particles (TiO2 NPs) are a high-production volume nanomaterial widely used in the paints, cosmetics, food and photovoltaics industry. However, the potential carcinogenic effects of TiO2 NPs in the lung are still unclear despite the vast number of in vitro and in vivo studies investigating TiO2 NPs. Here, we systematically reviewed the existing in vitro and in vivo mechanistic evidence of TiO2 NP lung carcinogenicity using the ten key characteristics of carcinogens for identifying and classifying carcinogens. A total of 346 studies qualified for the quality and reliability assessment, of which 206 were considered good quality. Using a weight-of-evidence approach, these studies provided mainly moderate to high confidence for the biological endpoints regarding genotoxicity, oxidative stress and chronic inflammation. A limited number of studies investigated other endpoints important to carcinogenesis, relating to proliferation and transformation, epigenetic alterations and receptor-mediated effects. In summary, TiO2 NPs might possess the ability to induce chronic inflammation and oxidative stress, but it was challenging to compare the findings in the studies due to the wide variety of TiO2 NPs differing in their physicochemical characteristics, formulation, exposure scenarios/test systems, and experimental protocols. Given the limited number of high-quality and high-reliability studies identified within this review, there is a lack of good enough mechanistic evidence for TiO2 NP lung carcinogenicity. Future toxicology/carcinogenicity research must consider including positive controls, endotoxin testing (where necessary), statistical power analysis, and relevant biological endpoints, to improve the study quality and provide reliable data for evaluating TiO2 NP-induced lung carcinogenicity. [ABSTRACT FROM AUTHOR]

Aim: To evaluate the quantity and quality of randomized controlled trials (RCTs) in hepatobiliary surgery and for identifying gaps in current evidences. Methods: A systematic search was conducted in MEDLINE (via PubMed), Web of Science, and Cochrane Controlled Register of Trials (CENTRAL) for RCTs of hepatobiliary surgery published from inception until the end of 2023. The quality of each study was assessed using the Cochrane risk‐of‐bias (RoB) tool. The associations between risk of bias and the region and publication date were also assessed. Evidence mapping was performed to identify research gaps in the field. Results: The study included 1187 records. The number and proportion of published randomized controlled trials (RCTs) in hepatobiliary surgery increased over time, from 13 RCTs (.0005% of publications) in 1970–1979 to 201 RCTs (.003% of publications) in 2020–2023. There was a significant increase in the number of studies with a low risk of bias in RoB domains (p <.01). The proportion of RCTs with low risk of bias improved significantly after the introduction of CONSORT guidelines (p <.001). The evidence mapping revealed a significant research focus on major and minor hepatectomy and cholecystectomy. However, gaps were identified in liver cyst surgery and hepatobiliary vascular surgery. Additionally, there are gaps in the field of perioperative management and nutrition intervention. Conclusion: The quantity and quality of RCTs in hepatobiliary surgery have increased over time, but there is still room for improvement. We have identified gaps in current research that can be addressed in future studies. [ABSTRACT FROM AUTHOR]

The Fengyun-4B (FY-4B) satellite is currently the primary operational geostationary meteorological satellite in China, replacing the previous FY-4A satellite. The advanced geostationary radiation imager (AGRI) aboard the FY-4B satellite provides an operational sea surface temperature (SST) product with a high observation frequency of 15 min. This paper conducts the first data quality assessment of operational SST products from the FY-4B/AGRI using quality-controlled measured SSTs from the in situ SST quality monitor dataset and foundation SSTs produced by the operational sea surface temperature and sea ice analysis (OSTIA) system from July 2023 to January 2024. The FY-4B/AGRI SST product provides a data quality level flag on a pixel-by-pixel basis. Accuracy evaluations are conducted on the FY-4B/AGRI SST product with different data quality levels. The results indicate that the FY-4B/AGRI operational SST generally has a negative mean bias compared to in situ SST and OSTIA SST, and that the accuracy of the FY-4B/AGRI SST, with an excellent quality level, can meet the needs of practical applications. The FY-4B/AGRI SST with an excellent quality level demonstrates a strong correlation with in situ SST and OSTIA SST, with a correlation coefficient R exceeding 0.99. Compared with in situ SST, the bias, root mean square error (RMSE), and unbiased RMSE (ubRMSE) of the FY-4B/AGRI SST with an excellent quality level are −0.19, 0.66, and 0.63 °C in daytime, and −0.15, 0.70, and 0.68 °C at night, respectively. Compared with OSTIA SST, the bias, RMSE, and ubRMSE of the FY-4B/AGRI SST with an excellent data quality level are −0.10, 0.64, and 0.63 °C in daytime, and −0.13, 0.68, and 0.67 °C at night. The FY-4B/AGRI SST tends to underestimate the sea water temperature in mid–low-latitude regions, while it tends to overestimate sea water temperature in high-latitude regions and near the edges of the full disk. The time-varying validation of FY-4B/AGRI SST accuracy shows weak fluctuations with a period of 3–4 months. Hourly accuracy verification shows that the difference between the FY-4B/AGRI SST and OSTIA SST reflects a diurnal effect. However, FY-4B/AGRI SST products need to be used with caution around midnight to avoid an abnormal accuracy. This paper also discusses the relationships between the FY-4B/AGRI SST and satellite zenith angle, water vapor content, wind speed, and in situ SST, which have an undeniable impact on the underestimation of the FY-4B/AGRI operational SST. The accuracy of the FY-4B/AGRI operational SST retrieval algorithm still needs to be further improved in the future. [ABSTRACT FROM AUTHOR]

The objective of this study was to assess the quality and consistency of recommendations in clinical practice guidelines (CPGs) and expert consensus on paediatric cow's milk protein allergy (CMPA) to serve as a foundation for future revisions and enhancements of clinical guidelines and consensus documents. We conducted a comprehensive literature search across several databases, including the Chinese Biomedical Literature Database (CBM), PubMed, Embase, Web of Science, UpToDate, ClinicalKey, DynaMed Plus and BMJ Best Practice. We spanned the search period from the inception of each database through October 1, 2023. We integrated subject headings (MeSH/Emtree) and keywords into the search strategy, used the search methodologies of existing literature and developed it in collaboration with a librarian. Two trained researchers independently conducted the literature screening and data extraction. We evaluated methodological quality and recommendations by using the Appraisal of Guidelines for Research & Evaluation II (AGREE II) and AGREE-Recommendations for Excellence (AGREE-REX) tools. Moreover, we compared and summarized key recommendations from high-quality CPGs. Our study included 27 CPGs and expert consensus documents on CMPA. Only four CPGs (14.8%) achieved a high-quality AGREE II rating. The four high-quality CPGs consistently provided recommendations for CMPA. The highest scoring domains for AGREE II were 'scope and purpose' (77 ± 12%) and 'clarity of presentation' (75 ± 22%). The lowest scoring domains were 'stakeholder involvement' (49 ± 21%), 'rigor of development' (34 ± 20%) and 'applicability' (12 ± 20%). Evaluation with AGREE-REX generally demonstrated low scores across its domains. Conclusion: Recommendations within high-quality CPGs for the paediatric CMPA showed fundamental consistency. Nevertheless, the methodology and recommendation content of CPGs and the expert consensus exhibited low quality, thus indicating a substantial scope for enhancement. Guideline developers should rigorously follow the AGREE II and AGREE-REX standards in creating CPGs or expert consensuses to guarantee their clinical efficacy in managing paediatric CMPA. What is Known: • The quality of clinical practice guidelines and expert consensus on paediatric cow's milk protein allergy (CMPA) remains uncertain. • There is a lack of clarity regarding the consistency of crucial recommendations for CMPA management. What is New: • Improving the methodological quality of guidelines and consensus on CMPA requires greater emphasis on stakeholder engagement, rigorous development processes, and practical applicability. • The recommendations from four high-quality guidelines align. However, addressing clinical applicability, integrating values and preferences, and ensuring actionable implementation are critical to improving the quality of all guidelines. [ABSTRACT FROM AUTHOR]

This paper introduces a new methodology for assessing the quality of a polyherbal preparation using thin-layer chromatography (TLC) image analysis integrated with the leave-1-out method and cross-sectional study. "Phikud Navakot", a Thai polyherbal preparation for relieving circulatory disorders and dizziness, consisting of nine herbs, was used as a case study. The leave-1-out technique involves systematically excluding one herb at a time from the preparation to generate TLC profiles, which are then analyzed and compared with the original preparation. Another approach, based on a cross-sectional study of the TLC image, was employed by converting all track on the TLC image into red, green, and blue (RGB) profiles simultaneously for direct band-by-band comparison across chromatograms. The leave-1-out approach combined with image analysis enhances band detection clarity, allowing for a more precise assignment of each band to its corresponding herb. Regardless of whether the substance band in polyherbal preparation was distinctly noticeable, faint, closely adjacent, overlapping, or concealed, the approaches based on TLC image analysis integrated with the leave-1-out method and cross-sectional study were demonstrated to be effective analytical techniques for complex herbal preparations and could be applied to other herbal mixtures. [ABSTRACT FROM AUTHOR]

Purpose: To develop an inline automatic quality control to achieve consistent diagnostic image quality with subject‐specific scan time, and to demonstrate this method for 2D phase‐contrast flow MRI to reach a predetermined SNR. Methods: We designed a closed‐loop feedback framework between image reconstruction and data acquisition to intermittently check SNR (every 20 s) and automatically stop the acquisition when a target SNR is achieved. A free‐breathing 2D pseudo‐golden‐angle spiral phase‐contrast sequence was modified to listen for image‐quality messages from the reconstructions. Ten healthy volunteers and 1 patient were imaged at 0.55 T. Target SNR was selected based on retrospective analysis of cardiac output error, and performance of the automatic SNR‐driven "stop" was assessed inline. Results: SNR calculation and automated segmentation was feasible within 20 s with inline deployment. The SNR‐driven acquisition time was 2 min 39 s ± 67 s (aorta) and 3 min ± 80 s (main pulmonary artery) with a min/max acquisition time of 1 min 43 s/4 min 52 s (aorta) and 1 min 43 s/5 min 50 s (main pulmonary artery) across 6 healthy volunteers, while ensuring a diagnostic measurement with relative absolute error in quantitative flow measurement lower than 2.1% (aorta) and 6.3% (main pulmonary artery). Conclusion: The inline quality control enables subject‐specific optimized scan times while ensuring consistent diagnostic image quality. The distribution of automated stopping times across the population revealed the value of a subject‐specific scan time. [ABSTRACT FROM AUTHOR]