Browsing by Author "Zhang M"

Now showing 1 - 3 of 3
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    Comparative study on the rheological properties of myofibrillar proteins from different kinds of meat
    (Elsevier Ltd, 2022-01) Wang H; Yang Z; Yang H; Xue J; Li Y; Wang S; Ge L; Shen Q; Zhang M
    In this study, the gel properties of myofibrillar proteins (MPs) from four meat sources (fish, beef, sheep, and pork) were compared. Oscillatory rheology measurements including temperature sweep, frequency sweep, and strain sweep were conducted to characterise the small and large deformation rheological properties of the MPs. In addition, sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and scanning electron microscopy (SEM) were used to evaluate differences in the molecular weight distribution as well as the microstructures in gel among different MPs. Frequency sweep measurements showed that all MP gels were weak gels. MPs extracted from pork exhibited the highest gel strength and most compact gel structure, whereas those from fish exhibited the lowest gel strength and loosest gel structure. In addition, the MP extracted from pork (PSM) had the highest content of myosin heavy chain (MHC) and actin. In conclusion, the MPs extracted from fish source and mammalian sources varied significantly in terms of rheological properties and microstructural characteristics. These results provided useful information for developing mixed gel products with different gel strengths.
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    ConCS: A Continual Classifier System for Continual Learning of Multiple Boolean Problems
    (IEEE, 2023-08) Nguyen TB; Browne WN; Zhang M
    Human intelligence can simultaneously process many tasks with the ability to accumulate and reuse knowledge. Recent advances in artificial intelligence, such as transfer, multitask, and layered learning, seek to replicate these abilities. However, humans must specify the task order, which is often difficult particularly with uncertain domain knowledge. This work introduces a continual-learning system (ConCS), such that given an open-ended set of problems once each is solved its solution can contribute to solving further problems. The hypothesis is that the evolutionary computation approach of learning classifier systems (LCSs) can form this system due to its niched, cooperative rules. A collaboration of parallel LCSs identifies sets of patterns linking features to classes that can be reused in related problems automatically. Results from distinct Boolean and integer classification problems, with varying interrelations, show that by combining knowledge from simple problems, complex problems can be solved at increasing scales. 100% accuracy is achieved for the problems tested regardless of the order of task presentation. This includes intractable problems for previous approaches, e.g., n-bit Majority-on. A major contribution is that human guidance is now unnecessary to determine the task learning order. Furthermore, the system automatically generates the curricula for learning the most difficult tasks.
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    Unveiling the Effects of Phosphorus on the Mineral Nutrient Content and Quality of Alfalfa (Medicago sativa L.) in Acidic Soils
    (MDPI (Basel, Switzerland), 2024-10-02) Li Z; Hao Y; Wang X; He J; Zhao X; Chen J; Gu X; Zhang M; Yang F; Dong R; Yang J
    Alfalfa (Medicago sativa L.) grown in acidic soils is often affected by phosphorus (P) deficiency, which results in reduced mineral nutrient content and forage quality. In this context, the effects of phosphorus (P) fertiliser remain unclear. In this study, we analysed the effects of P application on mineral nutrient content and forage quality in aluminium (Al)-sensitive (Longzhong) and Al-tolerant (Trifecta) alfalfa cultivars cultivated in two acidic soil environments. Mineral nutrient content and quality were affected by genotype, soil type, and P treatment concentration (p < 0.001). In limestone soil, for Longzhong and Trifecta, the optimal potassium (K), calcium (Ca), and magnesium (Mg) contents as well as crude protein content (CP) and ether extract (EE) values were observed at 20 mg P kg−1, that of the P content was observed at 40 mg P kg−1, and the minimum neutral detergent fibre (NDF) acid detergent lignin (ADL) values were observed at 40 mg P kg−1. In yellow soil, the maximum K, Ca, Mg, and P contents in Longzhong and Trifecta were observed at 40 mg P kg−1, whereas the maximum CP, EE, and ADL values were observed at 20 mg P kg−1. Our study provides an empirically based framework for optimising alfalfa fertilisation programmes in acidic soils.