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Yanfeng Zhang

Kunming University of Science and Technology

Publishes on Single-cell and spatial transcriptomics, 2D Materials and Applications, Photonic and Optical Devices. 22 papers and 135 citations.

22Publications
135Total Citations

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Top publicationsby citations

Effect of Boiling Time on the Color, Water, Protein Secondary Structure, and Volatile Compounds of Beef
Liqin You, Yanfeng Zhang, Yingjuan Ma et al.|Foods|2025
Cited by 13Open Access

The influence of boiling time on the persistent changes in the surface color, water content and distribution, protein secondary structure, and the concentration of volatile compounds in beef were studied, in order to obtain quality short-term boiled beef slices. The results show that the water content of beef samples significantly decreased and migration occurred between the high-freedom water and the low-freedom water. On average, boiling for 1 min was a key point in the changes of color parameters (L*, a*, b*, w, ΔE, and BI) and partial protein secondary structure because of the change in the ambient temperature around beef. In six samples, 29 volatile compounds were confirmed by GC–MS, and 13 compounds were regarded as the potential key volatile compounds, including 1-heptanol, 1-octen-3-ol, octanal, hexanal, decanal, heptanal, nonanal, (E, E)-2,4-decadienal, (E, E)-2,4-nonadienal, dodecanal, (E)-2-undecenal, 2,3-octanedione, and 2-pentylfuran. The color, water, and protein secondary structure were closely correlated with some potential key volatile compounds. The results could be used to guide the consumers to better grasp the quality of hot-pot meat during gatherings and have a comfortable consumer experience.

A revised AdaBoost algorithm: FM-AdaBoost
Cited by 9

In view of ensemble equivalence, this paper proposes a revised AdaBoost algorithm: FM-AdaBoost. It can ensure the ensemble error rates are the least by F-module, which filter classifiers after all of the iteration finish. At the same time, with the optional M-module it can ensure the training error rates decreases monotonously, which improves the training velocity effectively. In the end, simulation results show the algorithm is valid.

Carbon footprint impact of waste sorting on the municipal household waste treatment system: A community case study of Hangzhou
Jun Yin, Min Wang, Xiaoqin Yu et al.|Circular Economy|2024
Cited by 9Open Access

Considering the pressing need to reduce carbon emissions, the environmental impacts of waste sorting and its influencing factors remain unverified across many practical scenarios. This study focused on separating perishable and residual waste in a community in Hangzhou, China, examining how waste sorting behavior affects the carbon footprint of subsequent waste treatment systems through a randomized tracking survey and life cycle assessment (LCA) method. The results indicated that the sorted waste treatment system could achieve net carbon emissions ranging from −139.92 to −254.03 kg CO 2 eq per day by integrating the anaerobic digestion of sorted perishable waste with the incineration of residual waste. In comparison to the conventional mixed incineration system, which had net carbon emissions between −56.37 and −115.46 kg CO 2 eq per day and generated 383 kWh/t of power, the carbon reduction benefits of the sorted system were considerably greater, by a factor of 2.2–2.5. Additionally, the average amount of recovered electrical energy (993 kWh/t) was also higher by a factor of 2.6. Therefore, source separation of waste significantly enhances energy recovery and carbon reduction in household waste treatment systems. In this research system, incineration power generation and oil recovery serve as the primary units for reducing carbon emissions, and the proportion of residual waste generated greatly influences the total carbon emissions of the sorted waste treatment system (p < 0.05). Consequently, increasing the percentage of classified residual waste and optimizing machine efficiency will increase the carbon reduction benefits of waste sorting and treatment systems. These findings provide crucial references and guidance for advancing carbon reduction and waste classification in municipal solid waste (MSW) management systems.

Association between herpes zoster and Parkinson’s disease and dementia: a systematic review and meta-analysis
Yanfeng Zhang, Weiping Liu, Xu Yang|Frontiers in Neurology|2024
Cited by 6Open Access

Objectives This meta-analysis investigated the relationship between herpes zoster and the risk of dementia or Parkinson’s disease by analyzing published clinical studies. Methods We systematically searched PubMed, Cochrane, Embase, and Web of Science Core Collection databases on April 25, 2024. Hazard ratios (HR) were used for statistical analyses. Random-effects models were applied, and heterogeneity was assessed using the I 2 statistic. Results Herpes zoster was associated with a non-significant trend toward increased dementia risk (HR = 1.11, 95% CI 0.99–1.24, p = 0.07) but significantly increased Parkinson’s disease risk (HR = 1.15, 95% CI 1.03–1.30, p = 0.02). Subgroup analyses revealed that herpes zoster significantly elevated the risk of the prospective study subgroup (HR = 1.08, 95% CI 1.02–1.13, p = 0.004) and vascular dementia subgroup (HR = 1.17, 95% CI 1.00–1.37, p = 0.05). Significant heterogeneity was observed for both outcomes (dementia: I 2 = 98%, p &amp;lt; 0.00001; Parkinson’s disease: I 2 = 94%, p &amp;lt; 0.00001). Conclusion Herpes zoster raises the risk of Parkinson’s disease and vascular dementia, with a potential causal link to dementia. Early vaccination against herpes zoster is recommended over post-infection antiviral treatment to mitigate risks. Systematic review registration https://www.crd.york.ac.uk/PROSPERO/ and our registration number is CRD42024555620.