Comprehensive Quality Evaluation Research Articles

Developing a novel phantom for image quality evaluation in digital radiography

Evaluation of image quality in digital radiography is important to ensure accurate diagnosis. However, to perform image quality tests accurately and effectively, complex techniques and numerous phantoms are required. The aim of the study was to develop a novel phantom to allow a comprehensive evaluation of image quality in digital radiography. High-Density Polyethylene (HDPE) was used as the main material for the phantom. Physical image quality parameters such as effective Modulation Transfer Function (eMTF), effective Normalized Noise Power Spectra (eNNPS), effective Detective Quantum Efficiency (eDQE), as well as contrast and signal-to-noise ratio (SNR) evaluations can be conducted using the phantom. Preliminary preparation work was carried out through Monte Carlo simulations. The validation of the phantom was performed by comparing with standard phantom results. Physical image quality measurements were performed using an indirect digital radiography system. It was observed that there was a good agreement between the image quality measurement results performed with the standard phantom and the developed phantom. A strong correlation was determined between integrated effective DQE (IeDQE) results (R ≥ 0.97) obtained with HDPE and PMMA phantom. Simulation results regarding the transmission factor showed that HDPE could be an alternative to Polymethyl Methacrylate (PMMA) as a phantom material.

Assessment of Soil Spatial Variability in Agricultural Ecosystems Using Multivariate Analysis, Soil Quality Index (SQI), and Geostatistical Approach: A Case Study of the Mnasra Region, Gharb Plain, Morocco

Accurate assessment of soil quality is crucial for sustainable agriculture and soil conservation. Thus, this study aimed to assess soil quality in the agricultural ecosystem of the Mnasra region within the Gharb Plain of Morocco, employing a comprehensive approach integrating multivariate analysis and geostatistical techniques. Thirty soil samples were collected from the surface layers across thirty selected sites. The results showed significant variations in soil properties across the study area, influenced by factors such as soil texture, parent material, and agricultural practices. Pearson correlation and principal component analysis (PCA) were employed to analyze the relationships among soil properties and compute the Soil Quality Index (SQI). The SQI revealed values ranging from 0.48 to 0.74, with 46.66% of sampled soils classified as “Good” and 53.33% as “Fair”. Geostatistical analysis, particularly ordinary kriging (OK) interpolation and semivariogram modeling, highlighted the spatial variability of soil properties, aiding in mapping soil quality across the landscape. The integrated approach demonstrates the importance of combining field assessments, statistical analyses, and geospatial techniques for comprehensive soil quality evaluation and informed land management decisions. These findings offer valuable insights for decision-makers in monitoring and managing agricultural land to promote sustainable development in the Gharb region of Morocco.

Air quality and public health effects of dairy digesters in California

The dairy industry in California emits large amounts of methane (CH4) that contributes significantly to the state's overall Greenhouse Gas (GHG) budget. Reducing CH4 emissions has become a key priority for dairy farms in support of California's GHG reduction goals. Anaerobic digesters designed to capture CH4 from animal manure present a practical option for reducing CH4 emissions, but a comprehensive evaluation of the local air quality impacts of this technology has not been previously undertaken. The simplest digester configurations decrease local emissions of volatile organic compounds (VOCs) but increase emissions of oxides of nitrogen (NOx), potentially changing local air quality. Here, we evaluate the air quality implications of widespread digester adoption in the year 2050 across the San Joaquin Valley (SJV) in central California, which is home to the highest concentration of dairy farms in the state. Changes to concentrations of air pollutants including ozone (O3), airborne particulate matter with diameter smaller than 2.5 μm (PM2.5), and various PM2.5 chemical components are predicted using the UCD/CIT chemical transport model at 4 km resolution. Dairy digester adoption is evaluated within two regional energy scenarios, including a business as usual (BAU) scenario and an 80% greenhouse gas reduction (GHGAi) scenario, to consider potential changes to the chemical regime that governs formation of secondary air pollution. Concentrations are evaluated across 32 randomly selected weeks over a 10-year period from the year 2046–2055 to establish a long-term average impact in the presence of El Niño Southern Oscillation (ENSO) variability. Regional weather patterns are downscaled from Global Climate Model simulations under the RCP8.5 global scenario. The results indicate that baseline dairy emissions make minor contributions to air pollutant concentrations in 2050. Under a worst-case scenario for digester adoption, PM2.5 concentrations would increase by 0.06 μg/m3 (current standard = 9 μg/m3), and maximum daily 8-h average (MDA8) O3 would change by −1.0 ppb to +0.2 ppb depending on the surrounding regional energy scenario (current standard = 70 ppb). A health impact analysis shows that the widespread use of dairy digesters would result in fewer than 0.1 additional deaths per 100,000 people due to changing air pollution. For comparison, this level of mortality change is more than 100 times smaller than the risk posed by seasonal flu. Further, Environmental Justice analysis indicates that the implementation of digesters will not influence the exposure disparities among different racial groups in either the SJV or the surrounding San Francisco Bay & Sacramento area. These findings suggest that dairy digesters can be widely adopted in central California to reduce GHG emissions with minimal effect on regional air quality and public health.

Qualitative and quantitative analysis of major components of Qiye Shen'an tablet by UPLC Q-TOF/MS and UPLC-TQS-MS/MS

The Qiye Shen'an tablet is formulated using total saponins extracted from Notoginseng stems and leaves. At present, the study on its chemical composition remains scarce and the quality control indicators are limited, which seriously hindering the effective quality control and clinical research. Hence, this study aims to comprehensively identify and characterize the Qiye Shen'an tablet while controlling its main component contents. To achieve a comprehensive understanding of this tablet, an ultra-high performance liquid coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS/MS) method was employed for its separation and characterization. Through the analysis of 99 batches of Qiye Shen'an tablet produced by 9 enterprises, the characteristic quantitative components were further obtained. A total of 113 compounds were characterized and identified, among which 17 representative compounds were selected, and the ultra-high performance liquid-triple quadrupole tandem mass spectrometry (UPLC-TQS-MS/MS) method was established for further quantitative determination. It has been successfully applied to the content determination of 99 batches of Qiye Shen'an tablet, and a new quality control method is being formed. This study provides a new method for chemical spectrum analysis and determination of labeled compounds of Qiye Shen'an tablet, and lays a solid foundation for further study of potential active ingredients and comprehensive quality evaluation.

Impact of Ohmic Heating and Ultrasound Pretreatments on Oil Absorption and Other Quality Parameters of Fried Potato

AbstractIn this study, the effect of pretreatments ((hot water blanching (HWB), ultrasound (US) and ohmic heating (OH)) on reducing the oil absorption of potato during frying and the changes in the quality parameters of the product ((total polyphenol (TP), in vitro digestion, total flavonoid (TF), antioxidant capacity (AC), chlorogenic acid (CA), textural and sensorial properties)) were investigated. The pretreatments applied significantly affected oil absorption and quality parameters of fried potato. The oil content of fried potatoes ranged from 26.06 to 32.01% depending on the pretreatment. OH-pretreated potato had the highest content of TP (41.27 mg GAE/100 g dry matter-DM), TF (32.89 mg RE/100 g DM) and CA (1.72 mg/100 g DM). However, there was no significant difference between the pretreatments in terms of bioaccessibility of polyphenols at the end of digestion. Also, AC value of fried potato pretreated by OH (124.13 mmol AAE/100 g DM) was higher compared to that of fresh potato (83.91 mmol AAE/100 g DM), but other two pretreatments caused a decrease in AC. The highest hardness was observed in HWB-treated potato strips. OH-treated potato had the best color parameters. Sensory data indicated that US-pretreated potato had the highest sensory scores followed by OH- and HWB-pretreated ones, respectively. Consequently, based on the above comprehensive quality evaluation, it can be suggested that OH pretreatment is a better choice for preparing deep fried potato.

The association between healthy eating index-2015 with anthropometric, cardiometabolic and hepatic indices among patients with non-alcoholic fatty liver disease

BackgroundObesity, cardiovascular diseases, and metabolic disorders are common problems among participants with non-alcoholic fatty liver disease (NAFLD). However, the association between these problems and the healthy eating index-2015 (HEI-2015) remains unknown. Although the HEI-2015 originated from American dietary guidelines, its comprehensive evaluation of diet quality provides valuable insights for various populations, including Iranians. Therefore, the objective of this study was to investigate the association between anthropometric, hepatic, and cardio-metabolic indices with HEI-2015 scores in participants with NAFLD.MethodsWe conducted a cross-sectional analysis of data from the Hoveyzeh Cohort Study, which included adults aged 35 to 70 years between 2016 and 2018. A total of 664 participant with NAFLD (452 females and 212 males) were included in the analysis. The HEI-2015 was assessed using the Food Frequency Questionnaire (FFQ). Various indices, including the body shape index (ABSI), atherogenic index of plasma (AIP), visceral adiposity index (VAI), lipid accumulation product (LAP), cardiometabolic index (CMI), lipoprotein combine index (LCI), AST/ALT ratio, ALD/NAFLD index, and hepatic steatosis index (HSI), were calculated.ResultsNo significant differences were observed in anthropometric, cardio-metabolic, and hepatic indices across the quartiles of HEI-2015. However, among participants with NAFLD, men had significantly higher AIP and LCI levels, while women had significantly higher BMI, ABSI, VAI, LAP, and CMI levels. Additionally, women with NAFLD exhibited higher AST/ALT and HSI levels but lower ALD/NAFLD levels compared to men with NAFLD. Linear regression analysis among men with NAFLD revealed a significant negative correlation between HEI-2015 score and HSI in both the unadjusted model (β=-0.131, SE = 0.058, p = 0.024) and the adjusted model for energy intake (β=-0.129, SE = 0.058, p = 0.028).ConclusionThe present study demonstrated a correlation between lower HEI-2015 scores and an increased risk of steatosis in men with NAFLD. Moreover, our findings highlighted gender-related differences in NAFLD and cardio-metabolic disorders.

Analysis of the spatiotemporal dynamics and driving factors of ecosystem quality in Inner Mongolia from 2005 to 2020

Enhancing ecosystem quality is a necessary part of establishing of ecological civilization. The study of ecosystem quality requires the development of comprehensive evaluation indices. The existing simple remote sensing ecological indices are insufficient for achieving a comprehensive and systematic evaluation of the ecosystem quality. Therefore, we constructed an ecosystem quality index based on the landscape pattern, ecosystem stability, and ecosystem services. The spatiotemporal dynamics of the ecosystem quality in Inner Mongolia were analyzed over the period from 2005 to 2020. Moreover, a geographically weighted regression model was used to investigate the factors influencing the spatiotemporal variations in the ecosystem quality. The main results are as follows. (1) The spatial distribution of ecosystem quality in Inner Mongolia exhibited a gradual decline from the northeast to the southwest. In contrast, temporal analysis revealed a general increase in ecosystem quality from 2005 to 2020. (2) Climate was a significant factor influencing the spatial heterogeneity and temporal variability of the ecosystem quality. Socioeconomic factors, population density and livestock numbers had notable impacts on the spatial heterogeneity and temporal variability of ecosystem quality, respectively. (3) In Inner Mongolia, temperature and ecosystem quality showed a positive correlation in the northeastern region, but a negative correlation in the central and western regions. The findings offer valuable support for local policymakers in making informed decisions regarding targeted ecosystem management. Furthermore, our results provide local governments with valuable insights for enhancing the quality of regional ecosystems by taking into account the specific conditions of the area.

Comprehensive Quality Evaluation Model of College Students Based on Deep Learning

Evaluating college students' quality in higher education institutions is significant for promoting enhancement and innovation in teaching and learning practices. Conventional evaluation strategies mainly depend on subjective evaluation, which limits their ability to capture the multifaceted characteristics of students. In this study, we developed a distinct deep learning (DL) architecture by combining the Convolutional Deep Belief Network and Red Fox Optimization (CDBN-RFO) to evaluate college students' quality. Initially, a database containing academic performance records, extracurricular activities, and other relevant information is collected and fed into the system. Then, the database was preprocessed to make it an appropriate format for subsequent analysis. Further, the proposed CDBN-RFO was created, and the CDBN was trained using the preprocessed database to understand the patterns and relations within data for evaluating college students' quality. Subsequently, the RFO approach was deployed to fine-tune the CDBN hyperparameters to their finest range, which increases the overall system performance. Subsequently, the RFO optimized the CDBN training process by fine-tuning its parameters to the optimal range, enhancing overall evaluation performance. The developed framework was modeled using Python software, and the results were analyzed, including accuracy, error, computational time, etc. Also, a comparative analysis was done with conventional algorithms, which validated that the proposed strategy outperformed them in accuracy.

Assessing groundwater quality in semi-arid conditions: a geographic information systems-integrated approach using water quality index

Meeting freshwater demands in water-scarce regions is imperative, given challenges like hydric stress, urbanization, aridity, and population growth. This study focuses on the Tebessa aquifer system, a critical water source facing escalating demands. A primary objective is to identify actionable management strategies to improve groundwater quality dynamics in semi-arid regions. The methodology involves a comprehensive assessment of groundwater health using the Water Quality Index (WQI) approach. This method integrates diverse parameters influenced by intensive agricultural and industrial activities. Additionally, spatial relationship analysis, facilitated by Geographic Information System (GIS) technology, is employed to gain insights into complex hydrogeological processes. The multi-parameter strategy implemented results in water quality maps that highlight various ions, revealing spatial disparities and assigning quality priority classes from 'Good' to 'Poor' across the groundwater. The research, conducted in the semi-arid Tebessa-Morsott Plain, encompasses field and laboratory investigations to delineate hydrochemical traits, including alkalinity, salinity, and heightened ion concentrations. The results of the study contribute to scientific understanding by uncovering interrelationships and spatial intricacies, offering valuable insights for water resource governance. The effectiveness of the methodology, incorporating WQI and GIS, is demonstrated in the comprehensive evaluation of groundwater quality. Ultimately, this research provides a foundation for informed decision-making and sustainable management of groundwater resources in semi-arid regions.

Retinal OCT biomarkers associated with reading performance in patients with persistent vs. resolved diabetic macular edema.

Recent advancements in imaging technologies, particularly structural optical coherence tomography (OCT), have improved the understanding of diabetic macular edema (DME) pathophysiology and provided valuable biomarkers for disease progression and visual outcomes. This prospective study aimed to investigate the association between specific retinal biomarkers identified through OCT imaging and reading performance metrics in patients with previously treated persistent versus resolved DME and good visual acuity. Forty-nine eyes from 35 patients with a history of DME were enrolled. Reading performance was assessed using the Radner reading charts, which include standardized sentences with geometrically progressing print sizes. Structural alterations in the inner and outer retina, as well as the retinal pigment epithelium (RPE), were graded based on OCT images. Reading performance, measured as maximum reading speed, was associated with specific retinal biomarkers. The disruption of the ellipsoid zone (EZ) in the parafoveal region and the presence of disorganization of the inner retinal layers (DRIL) in the parafovea were correlated with reduced reading speed. These associations were independent of the presence of intraretinal or subretinal fluid. Understanding the relationship between retinal biomarkers and reading performance could contribute to a comprehensive evaluation of visual function and quality of life in patients with DME, leading to better management strategies and treatment outcomes.

Virtual Reality Technology and Artificial Intelligence for Television and Film Animation

Artificial intelligence technology has transformed television content and production methods and resulted in the development of a new generation of artificially intelligent Television. Popularising artificial intelligence technology improves television programme content, categories, cost, and efficiency. Virtual reality (VR) technology has been widely used in scientific study and everyday life; thus, its use in film and television animation (FTA) teaching has been researched to promote FTA learning. First, learning design uses dynamic environment modelling, real-time 3D graphic production, stereoscopic displays, sensors, and other VR technologies. These four issues were researched due to the present FTA primary teaching method. VR technology enhances FTA's basic training teaching, and the 3D animation course and VR technology increase professional skill course teaching. The application effect compares and analyses classroom satisfaction, comprehensive quality evaluation, and professional core curriculum effect. The VR technology group's thorough quality evaluation is significantly improved, and students' satisfaction with classroom atmosphere, teaching style, and teaching facilities is 85%, 78%, and 97.34%, respectively. This group can incorporate the new design process into animation modelling and finish the course design work well. Compared to traditional instruction, pupils are happier and harvest more. Thus, VR technology in FTA instruction can increase student engagement, efficiency, and professional knowledge and abilities. After analysing its application mode and effects, VR technology can be used in FTA teaching.

Data driven assessment of rock mass quality in red-bed hilly area: a case study of Guang’an city, SW China

The evaluation of geological suitability for urban underground space (UUS) development is an indispensable prerequisite for its optimal utilization. As the actual carrier of underground facilities, the evaluation of rock mass quality plays a crucial role in assessing geological suitability. However, it is notable that the evaluation of rock mass quality has regrettably remained somewhat marginalized within the broader framework of the geological suitability assessment in recent years. The selection of pertinent indicators for the evaluation of rock mass quality inherently presents an appreciable degree of subjectivity. Predominantly subjective evaluation methods continue to dominate the field, while the application of objective algorithms, such as unsupervised clustering, remains in its nascent stage. Furthermore, there is a lack of comprehensive investigations into distinct combinations of attributes. This limitation confines the broader applicability of the evaluation outcomes in the context of urban underground space. Within this study, we meticulously amassed rock core test data from over 40 boreholes of engineering geological significance within the urban planning ambit of Guang'An City. Utilizing the K-means unsupervised clustering algorithm and the Principal Component Analysis (PCA) algorithm. We successfully conducted an unsupervised clustering procedure with nine distinct physical and mechanical attributes. This yielded an aggregation into five discernible clusters. Building upon the derived clustering outcomes, a stratification of rock mass quality was effectuated into three distinct tiers: Level 1 (characterized by pure sandstone), Level 2 (primarily dominated by sandstone), and Level 3 (denoting fair conditions predominantly influenced by mudstone). This structured stratification facilitates a relatively objective and comprehensive evaluation of rock mass quality within the context of the red-bed hilly terrain. In the course of this analytical trajectory, we conducted a dissection of the clustering efficacy. For strongly correlated attributes, we propose a preliminary dimensionality reduction procedure prior to the clustering endeavor. Moreover, we recommend intervals of 10 m for the stratified evaluation in red bed hilly urban terrains.

Evaluation of overall comfort based on combined thermal-acoustic effects in urban squares

Investigating the combined effects of compositive human–environmental factors and developing indices to quantitatively measure environmental quality is essential. In this study, combined thermal-acoustic effects on overall comfort were used to develop evaluation models based on the demand for environmental improvement in severe cold cities, with small-to-medium-sized squares as examples. Parameter analysis was conducted to comprehensively evaluate overall comfort in squares with different spatial forms. Results indicate that thermal and acoustic environments significantly affected the overall comfort and varied with season, accounting for 58.7%–68.2% of the variations in overall comfort. Evaluation results indicated that the distribution of overall comfort was more similar to the sound level because of the significant difference in the acoustic environment. Block orientation, surrounding roads and the length-width ratio of squares were found to have different effects on overall comfort. The results can be applied to the comprehensive evaluation of environmental quality in urban squares.

Spatiotemporal comprehensive evaluation of water quality based on enhanced variable fuzzy set theory: A case study of a landfill in karst area

Water quality assessment is a crucial step in water resource management and pollution prevention, and is essential for achieving sustainable development. Current methods for evaluating water quality often fall short of meeting the needs of water resource management due to the lacks of accuracy and applicability. In this paper, an enhanced water quality evaluation system was established by Principal Component Analysis / Factor Analysis (PCA/FA), Analytic Hierarchy Process / Entropy Weight Method / Game Theory (AHP/EWM/GT) and Variable Fuzzy Set Theory (VFST). The accuracy of this method was verified by evaluating the water quality of a landfill in a karst area and comparing with the conventional evaluation models. The results indicated that the highest influence on groundwater quality in the study area came from human factor, dissolved solid factor, biological factor, and nutritional factor. The quality of surface water and groundwater in the study area was primarily Grade Ⅱ, accounting for 62.5% and 75%, respectively. The predominant groundwater type was HCO3-Ca·Mg, which was strongly affected by karstification. The NH3-N and TP in the surface water had the highest variability, and the variation coefficients of K+, Na+, Ca2+, Cl−, NH3-N, NO3−, TDS, and TH in the groundwater were greater than 1. The surface water quality gradually improved between 2018 and 2019. Overall, the groundwater quality in the southern and central regions was inferior to that in the northern and surrounding areas. There could be a hydraulic link between the surface water and landfill in the research location, while karstification and leachate primarily impacted the groundwater. The water quality evaluation method established in this study can make a significant contribution to water resource management, which has important practical significance for environmental protection and indirect social value to the public.

Assessing water quality in North-East Algeria: a comprehensive study using water quality index (WQI) and PCA

Abstract Ensuring high water quality in Algeria, particularly in Annaba, is crucial for the well-being of its population and the sustainable development of its diverse ecosystems. The study focuses on the Cheffia Dam, Oued El Aneb, and Treat boreholes as crucial sources of drinking water. The water quality index (WQI) is used to assess water quality based on various physico-chemical parameters. The research spans from January to December 2021, analyzing 16 parameters, such as temperature, pH, conductivity, turbidity, total hardness, calcium, magnesium, sodium, potassium, chloride, nitrate, sulfate, phosphate, and iron, this results in a total of 36 samples and 576 analyses. Principal component analysis (PCA) is employed to delve into interrelationships between variables, revealing distinct characteristics for each site. This study, the first of its kind, provides a comprehensive 1-year evaluation of water quality in Annaba. The collected data serve as a valuable resource for future water management decisions, highlighting both temporal and spatial variations. The current study indicates that the analysis of water parameters, adherence to standards, and the application of WQI reveal that the water sources are generally good quality throughout the year with excellent water quality in autumn. However, challenges such as elevated turbidity in Cheffia dam water necessitate targeted interventions.

A comprehensive evaluation of lipid profiles and nutritional quality in different animal source muscle tissues

Lipid composition is crucial for assessing the nutrition and flavor of animal-derived raw materials, a key concern for consumers. Based on high-resolution mass spectrometry and chemical pattern recognition, the intermuscular lipids fingerprint of seven types of livestock, poultry, and fish muscle were analyzed. In total, 704 lipids were detected, containing fourteen lipid molecules, with significant content differences among samples, notably triglycerides, phosphatidylcholines, phosphatidylethanolamines, diglycerides, and fatty acids. Livestock and poultry muscle had a low content of lipids with an unsaturation degree above 4 (around 10% and 25%). These unsaturated lipid molecules in fish muscle ranged from approximately 60%–75%. Rainbow trout had higher contents of triglycerides and phosphatidylcholines with chain lengths exceeding 13. Mutton had more of these lipids within the 13–18 chain length, exceeding 0.3 g/(g·protein), which may be crucial for their unique texture and flavor. The results will help the deep processing and nutritional assessment of muscle foods.

Study on enhancing groundwater quality in a coastal area of Saudi Arabia using a curved glass solar still

Due to the complex geological factors and their causes, it is essential to realize the saltiness and pollution of the groundwater in the arid shoreline aquifer. The intrusion of seawater into coastline aquifers is an increasingly significant issue due to urbanization, the exploitation of groundwater, and the global rise in temperature. The increasing salt concentration of groundwater in shoreline aquifers has emerged as a significant social and economic problem in Saudi Arabia. Consequently, groundwater alkalinity levels must be accurately determined to ensure the effective protection and preservation of water resources. A compilation of eight water samples was collected along the south-western coast of Saudi Arabia, and a comprehensive evaluation of the groundwater quality was conducted using a combination of indicators. The findings indicated that the intrusion of saltwater caused a significant increase in the salt concentration and damage to the groundwater quality near the coastline. In this work, a curved glass solar still (CGSS) has been deployed to process the groundwater, and the performance of the CGSS in improving the groundwater quality was assessed under clear sky conditions. The findings indicate that the desalination process executed using the CGSS resulted in a more substantial improvement in groundwater quality, with an average daily yield of 3513 ml/day achieved with the CGSS.

Investigating soil quality in cold highland agricultural fields with different soil types

ABSTRACT To evaluate the soil quality of alpine farmland and elucidate the key factors influencing productivity levels under the current agricultural paradigm, we conducted an extensive collection of soil samples. In total, 234 soil samples (0–20 cm) were collected from Menyuan County, the heartland of the southern slope of the Qilian Mountains. These samples represented four predominant soil types, including cold calcic soil, luvic chernozem, calcareous meadow soil, and calcareous gray cinnamon soil. Moreover, by employing principal component analysis, we established a minimum data set (MDS) that encapsulated the essential parameters for the comprehensive evaluation of the soil quality of farmland in the study area. Upon evaluating the soil quality index, the rankings were as follows: luvic chernozem (0.63) > calcareous gray cinnamon soil (0.58) > calcareous meadow soil (0.58) > cold calcic soil (0.55). Overall, the results highlighted that the significant impact of soil total nitrogen (TN), available potassium (AK), and soil water content (SWC) on soil quality within the study area. Therefore, in the context of land management practices, careful attention should be paid to the management of soil TN, AK content, and SWC to avoid the degradation of cultivated land into abandoned fields.

THUBreast: an open-source breast phantom generation software for x-ray imaging and dosimetry

Objective. Establishing realistic phantoms of human anatomy is a continuing concern within virtual clinical trials of breast x-ray imaging. However, little attention has been paid to glandular distribution within these phantoms. The principal objective of this study was to develop breast phantoms considering the clinical glandular distribution. Approach. This research introduces an innovative method for integrating glandular distribution information into breast phantoms. We have developed an open-source software, THUBreast 4 4 http://github.com/true02Hydrogen/THUBreast/ , which generates breast phantoms that accurately replicate both the structural texture and glandular distribution, two crucial elements in breast x-ray imaging and dosimetry. To validate the efficacy of THUBreast, we assembled three groups of breast phantoms (THUBreast, patient-based, homogeneous) for irradiation simulation and calculated the power-law exponents ( β ) and mean glandular dose ( Dg ), indicators of texture realism and radiation risk, respectively, utilizing MC-GPU. Main results. Upon the computation of the Dg for the THUBreast phantoms, it was found to be in agreement with that absorbed by the phantoms based on patients, with an average deviation of 4%. The estimates of average Dg thus obtained were on average 23% less than those computed for the homogeneous phantoms. It was observed that the homogeneous phantoms did overestimate the average Dg by 30% when compared to the phantoms based on patients. The mean value of β for the images of THUBreast phantoms was found to be 2.92 ± 0.08, which shows a commendable agreement with the findings of prior investigations. Significance. It is evidently clear from the results that THUBreast phantoms have a preliminary good performance in both imaging and dosimetry in terms of indicators of texture realism and glandular dose. THUBreast represents a further step towards developing a powerful toolkit for comprehensive evaluation of image quality and radiation risk.

Comprehensive evaluation of quality and bioactivity of kombucha from six major tea types in China

Kombucha is a kind of fermented tea prepared with a symbiotic culture of bacteria and yeasts (SCOBY) on the basis of sugared black tea infusion. In the current study, six major Chinese tea leaves (dark tea, black tea, oolong tea, white tea, yellow tea, and green tea) were used to prepare kombucha and their physiochemical properties, bioactivity, and sensory quality were compared. The total acidity of kombucha increased as the fermentation proceeded, decreasing the pH value from ∼6.0 to ∼2.5. Moreover, the antioxidant capacity was significantly increased after fermentation compared to fresh tea infusions and this is mostly attributed to the increased total polyphenols concentration (from 1333.25 mg/L to 1683.24 mg/L). Antimicrobial experiments showed fermentation enhanced the antimicrobial effects of kombucha, and oolong tea kombucha showed the strongest bacteriostatic capacity against Staphylococcus aureus (S. aureus) while the yellow tea kombucha showed the strongest bacteriostatic capacity against Escherichia coli (E. coli). Volatile components and sensory evaluation results revealed that the tea types remarkably influenced the flavors of kombucha. Generally, oolong tea kombucha and green tea kombucha had higher overall sensory scores than other samples. In conclusion, the types of tea significantly influenced the quality of kombucha, and fermentation favors the improvement in the anti-oxidant and antimicrobial properties of kombucha.