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BACKGROUND: Agaricus bisporus with a completely white appearance is popular with consumers. However, A. bisporus is susceptible to senescence and spoilage, which results in browning and oxidative tissue damage, with limited shelf life. This study investigated the effects of shortwave ultraviolet (UV‐C, 1.0 kJ m−2) irradiation on quality features, enzymatic browning, and defense properties of A. bisporus stored at 4 °C for 21 days. RESULTS: After storage, UV‐C irradiated A. bisporus had increased quality of sensory, color and hardness characteristics; it exhibited higher content of total phenolic, brown melanin precursors, including γ‐glutaminyl‐4‐hydroxybenzene, γ‐glutaminyl‐3,4‐dihydroxybenzene and tyrosine, lower accumulation of malondiadehyde, hydrogen peroxide and superoxide radical, and maintained membrane integrity in comparison to control samples. Besides, A. bisporus treated by UV‐C showed lower degree of browning and higher level of self‐defense capacity, which may be ascribed to the enhancement in activities of superoxide dismutase, catalase, phenylalanine ammonia lyase, chitinase and β‐1,3‐glucanase activity, while inhibiting polyphenol oxidase activity during storage. CONCLUSION: These results indicate that the higher self‐defense capacity with UV‐C treatment might be the mechanism associated with the delay of senescence in Agaricus bisporus. Therefore, UV‐C treatment is suggested as a potential practical application in mushrooms. © 2023 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

In this article, the authors propose a new educational grading system based on fuzzy techniques, which includes five interrelated modules. Through an example to illustrate the process of the proposed fuzzy educational grading system, we find that the proposed system meets the basic requirements of the educational grading system and can overcome the limitations of existing fuzzy educational grading systems. By comparing the proposed fuzzy educational grading system with traditional methods, we find that the proposed evaluation system can more objectively and intelligently evaluate students’ answer sheets. The aim of the proposed method is not to replace the existing fuzzy educational grading systems, but to enrich the present systems for students’ learning achievement evaluation. [ABSTRACT FROM AUTHOR]

Multi-criteria decision-making (MCDM) is a popular branch of decision theory in which many methods have been proposed to solve MCDM real-world problems. However, in spite of the multiple methods, it is common that different of them provide the same solutions. Therefore, this paper analyzes the causes of the same solutions from different MCDM methods, studies why different normalization methods can achieve the same solutions in MCDM methods through the theory of MCDM methods, and discusses the relationship between different MCDM methods by category. To achieve such goals, MCDM methods are classified into three categories according to their ranking methods. Some traditional MCDM methods are then extended by considering general normalization methods and distance measures. Finally, the characteristics of various MCDM methods are discussed by category and their evaluation indexes are also compared. The comparison results are represented by tables and flowchart models. The relationship between different categories of MCDM methods is shown through the comparison of the evaluation indexes. The aim of the proposed method is not to replace existing MCDM methods, but to fill some present research gaps about MCDM methods. • General normalization methods and distance measures are considered in MCDM methods. • The causes of the same solutions from different MCDM methods are examined. • The characteristics of various MCDM methods are discussed by category. • The relationship between different MCDM methods is summarized. [ABSTRACT FROM AUTHOR]

This paper presents an improved method for estimating the similarity between LR -type fuzzy numbers. By considering different left and right shape functions, we can conveniently compute the similarity between trapezoidal fuzzy numbers, Gaussian fuzzy numbers and normal fuzzy numbers. An algorithm for computing the proposed similarity measure between LR -type fuzzy numbers and a numerical method for approximating it are provided. Some of its properties are also examined. The performance of the proposed method is compared with some existing similarity measures through using different sets of LR -type fuzzy numbers. It is shown that the similarity between LR -type fuzzy numbers with parameters from any real number belonged to the real number set R is considered in the proposed method. The given similarity measure is scale-invariant and takes into account the shape of LR -type fuzzy numbers, which can overcome the shortcomings of existing methods. [ABSTRACT FROM AUTHOR]

Kiwifruit has a high decay rate, in part because quality changes during storage cannot be easily monitored in real time. In order to better monitor the shelf life of kiwifruit and understand the quality changing process during storage, internal quality indexes such as hardness, respiratory intensity and TSS(Total Soluble Solid) were considered into the prediction models. The prediction models were constructed based on BPNN (Back Propagation Neural Network), Random Forest (RF) and XGBoost (eXtreme Gradient Boosting) respectively. And transfer learning algorithm was used to construct the quality prediction models with BPNN, RF, and XGBoost algorithms as the base learner. In the experiments, sample data were augmented by adding Gaussian noise, which effectively prevented the model from over-fitting. The experimental results showed that the prediction accuracy of each index based on transfer learning was better than that of individual BPNN, RF and XGBoost. Moreover, the average prediction accuracy of the models based on transfer learning was 96.2%, and that of respiratory intensity was as high as 99.4%. Therefore transfer learning can be used to effectively analyze and predict changes of kiwifruit quality indexes during storage. [ABSTRACT FROM AUTHOR]

To improve the durability of pumice lightweight aggregate concrete applied in cold and drought areas, sodium silicate-modified waste tire rubber powder is used to treat the pumice lightweight aggregate concrete. The pumice lightweight aggregate concrete studied is mainly used in river lining structures. It will be eroded by water flow and the impact of ice and other injuries, resulting in reduced durability, and the addition of modified rubber will reduce the damage. The durability, including mass loss rate and relative dynamic elastic modulus of pumice lightweight aggregate concrete with different sodium silicate dosages and rubber power particle sizes, is analyzed under freeze-thaw cycles, and the microstructure is further characterized by using microscopic test methods such as nuclear magnetic resonance tests, ultra-depth 3D microscope tests, and scanning electron microscopy tests. The results showed that the durability of pumice lightweight aggregate concrete is significantly improved by the addition of modified waste tire rubber powder, and the optimum durability is achieved when using 2 wt% sodium silicate modified rubber power with a particle size of 20, and then the mass loss rate decreased from 4.54% to 0.77% and the relative dynamic elastic modulus increased from 50.34% to 64.87% after 300 freeze-thaw cycles compared with other samples. The scanning electron microscopy test result showed that the surface of rubber power is cleaner after the modification of sodium silicate, so the bonding ability between rubber power and cement hydration products is improved, which further improved the durability of concrete under the freeze-thaw cycle. The results of the nuclear magnetic resonance test showed that the pore area increased with the number of freeze-thaw cycles, and the small pores gradually evolved into large pores. The effect of sodium silicate on the modification of rubber power with different particle sizes is different. After the treatment of 2 wt% sodium silicate, the relationship between the increased rate of pore area and the number of freezing-thawing cycles is 23.8/times for the pumice lightweight aggregate concrete containing rubber power with a particle size of 20 and 35.3/times for the pumice lightweight aggregate concrete containing a particle size of 80 rubber power, respectively. [ABSTRACT FROM AUTHOR]

Background: Hepatocellular carcinoma (HCC) is one of the most common malignancies with a high lethality rate. ZMIZ2 is a transcriptional co-activator implicated in various human diseases. However, the role and molecular mechanism of ZMIZ2 in HCC remains to be elucidated. Methods: The expression and prognostic value of ZMIZ2 in HCC was excavated from public databases and explored by bioinformatic analysis. Then the expression of ZMIZ2 and related genes was further validated by quantitative RT-PCR, western blotting, and immunohistochemistry. Loss and gain-of-function experiments were performed in vitro and in vivo to investigate the function of ZMIZ2 in HCC. In addition, transcriptome sequencing and immunoprecipitation was conducted to explore the potential molecular mechanisms of ZMIZ2. Results: ZMIZ2 was highly expressed in HCC and associated with poor prognosis. Silencing ZMIZ2 significantly inhibited HCC cell proliferation, cell cycle process, migration, and invasion in vitro, and also inhibited the progression of HCC in vivo. Additionally, ZMIZ2 expression was correlated with immune cell infiltration in HCC samples. Somatic mutation analysis showed that ZMIZ2 and TP53 mutations jointly affected the progression of HCC. Mechanistically, ZMIZ2 interacted with LEF1 to regulate malignant progression of HCC by activating the Wnt/β-catenin pathway. Conclusion: ZMIZ2 was overexpressed in HCC and associated with poor prognosis. The overexpression of ZMIZ2 was corelated with malignant phenotype, and it facilitated HCC progression via LEF1-mediated activation of the Wnt/β-catenin pathway. Furthermore, ZMIZ2 could be served as a prognostic biomarker and a new therapeutic target for HCC. [ABSTRACT FROM AUTHOR]

[Display omitted] • The static magnetic field-assisted thawing (SMAT) with 1、2、3 mT was applied to frozen beef steaks. • SMAT can shorten thawing time and maintain the quality of beef steaks. • 2 mT SMAT samples exhibited less severe protein oxidation and denaturation. This study investigated the effect of static magnetic field-assisted thawing (SMAT) at varying intensities (0, 1, 2, and 3 mT) on the quality, water status, and myofibrillar protein (MP) characteristics of frozen beef steaks. The thawing times of SMAT-1, 2, and 3 treatments could be shortened by approximately 10.9 %, 20.0 %, and 8.5 %, respectively, compared to the control. The results indicated that SMAT treatment significantly decreased thawing loss, maintained color stability, and reduced the degree of lipid oxidation in beef steaks compared to the control group (P < 0.05). Low-field nuclear magnetic resonance results confirmed that SMAT treatment enhanced the water-holding capacity of muscle. Furthermore, SMAT-2 treatment protected the muscle microstructure, decreased carbonyl content, and increased total sulfhydryl content (P < 0.05) compared to the control group. In conclusion, SMAT treatment effectively improved the beef quality and the characteristics of MP after thawing, especially in 2 mT. [ABSTRACT FROM AUTHOR]

• Various key sludge properties synergistically affect the conditioning process. • Multifactorial models based on coupling indicators help to quantify reagent demand. • Floc properties and water state affect the competitive reaction in conditioning. • Filterability of sludge is separate from the adjustability of its filtration. • A dual-system impact model characterizes the conditioning and filtration processes. The high amount of densely hydrated organic substance present in sewage sludge impedes its filterability, thus restricting sludge disposal. Although chemical conditioning can facilitate filtration, the diverse sludge properties complicate the quantitative control of conditioning process. Investigating how to accurately quantify the optimal reagent demand (ORD) based on the critical physicochemical properties of the target sludge is an effective way to address the current issue. This study focused on the sewage and stockpiled sludge with varying properties, and their ORD under different chemical conditioning. The results showed that organic content, floc size, and bound water synergistically influenced conditioning process. The quantitative models were established between their coupling indicators and ORD, with coupling indicators including the ratio of organic content to floc size, the ratio of flow viscosity to floc size, and the ratio of the product of organic content and bound water to floc size. The linear correlation of the coupling indicator with ORD was higher than that of the traditional single-factor indicator. Furthermore, the inherent filterability of the sludge was somewhat separate from the adjustability of its filtration. A "dual-system" impact model was proposed to characterized the conditioning and filtration processes. These results provide theoretical guidance for the quantitative regulation of conditioning and filtration processes of sludge with complex characteristics. [Display omitted] [ABSTRACT FROM AUTHOR]