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Engineering 2024年第1期32卷 152-162页

作者： Guanyi Chen Jianyuan Li Yunan Sun Zhi Wang Gary ALeeke Christian Moretti Zhanjun Cheng Yuan Wang Ning Li Lan Mu Jinyu Li junyu tao Beibei Yan Li'an Hou Interdisciplinary Innovation Lab for Environment and Energy School of Mechanical Engineering&School of Biotechnology and Food ScienceTianjin University of CommerceTianjin 300134China School of Environmental Science and Engineering Tianjin UniversityTianjin 300350China School of Ecology and Environment Tibet UniversityLhasa 850012China Tianjin Key Laboratory of Biomass Wastes UtilizationTianjin Engineering Research Center for Organic Wastes Safe Disposal and Energy UtilizationTianjin 300072China School of Chemical Engineering University of BirminghamBirmingham B152TTUK Department of Environmental Systems Science ETH ZürichZürich CH-8092Switzerland

In recent years,a great deal of attention has been focused on the environmental impact of plastics,includ-ing the carbon emissions related to plastics,which has promoted the application of biodegradable plas-tics.Countries worldwide have shown high interest in replacing traditional plastics with biodegradable plastics.However,no systematic comparison has been conducted on the carbon emissions of biodegrad-able versus traditional plastic products.This study evaluates the carbon emissions of traditional and biodegradable plastic products(BPPs)over four stages and briefly discusses environmental and economic perspectives.Four scenarios-namely,the traditional method,chemical recycling,industrial composting,and anaerobic digestion-are considered for the disposal of waste BPPs(WBPPs).The analysis takes China as a case study.The results show that the carbon emissions of 1000traditional plastic products(plastic bags,lunch boxes,cups,etc.)were52.09-150.36 carbon emissions equivalent of per kilogram(kg CO_(2)eq),with the stage of plastic production contributing 50.71%-50.77%.In comparison,1000 similar BPPs topped out at 21.06-56.86 kg CO_(2)eq,approximately 13.53%-62.19%lower than traditional plastic prod-ucts.The difference was mainly at the stages of plastic production and waste disposal,and the BPPs showed significant carbon reduction potential at the raw material acquisition stage.Waste disposal plays an important role in environmental impact,and composting and anaerobic digestion are considered to be preferable disposal methods for WBPPs.However,the high cost of biodegradable plastics is a challenge for their widespread use.This study has important reference significance for the sustainable development of the biodegradableplastics industry.

关键词： Carbon emissions Biodegradable plastics Different disposal scenarios Daily life consumption Environmental and economic discussion

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Effect of End Shape on Flow and Heat Transfer Characteristics of Two Parallel Plates

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Journal of Thermal Science 2024年第3期33卷 815-832页

作者： ZHANG Guang HONG Tianxiao WANG Dongrui XIN Jialin tao junyu LIN Zhe Key Laboratory of Fluid Transmission Technology of Zhejiang Province Zhejiang Sci-Tech UniversityHangzhou310018China

Flow around a pair of flat plates is a basic hydrodynamics problem.In this paper,the flow and heat transfer characteristics of two parallel plates with different edge shapes are numerically calculated.Under different inclined angles,the influence of chamfered and rounded structures with different sizes at the end-edge on unsteady flow and heat transfer characteristics of two parallel plates are analyzed.It is found that the instability and unsteadiness of flow decrease with the increase of end-edge size,and the non-uniformity of wake velocity of both rounded and chamfered plates decreases gradually.The non-uniformity of wake temperature increases firstly and then decreases at a small inclined angle,and the amplitude becomes the largest when S_(rou)(S_(cha))=3,while it basically keeps monotonically increasing at a large inclined angle.Moreover,the global heat transfer performance of the flat plate is obviously affected by the end-edge modification,especially the chamfered structure.With the increase of chamfered size,the global Nusselt number basically shows the decreasing trend.This study provides a theoretical basis for the application of plate-shape structure in engineering fields.

关键词： two parallel plates end shape flow characteristic heat transfer numerical simulation

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Emerging roles of circular RNAs in cancer:a narrative review

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Journal of Pancreatology 2022年第1期5卷 41-48页

作者： Shixiang Guo Junfeng Zhang junyu tao Jinfeng Zhu Ruixin Zheng Huaizhi Wang Department of Hepatopancreatobiliary Surgery Chongqing General HospitalChongqing Chongqing School University of Chinese Academy SciencesChongqingChina

Circular RNAs (circRNAs) constitute a novel class of endogenous noncoding RNAs characterized by a covalently closed structure and involved in multiple biological processes. The main biological functions and properties of circRNAs can be defined by five features: a "sponging" effect on other RNA species, post-transcriptional regulation, rolling circle translation, generation of pseudogenes, and splicing interference. Although circRNAs were first detected decades ago, the role of circRNAs and the mechanisms underlying their actions remain incompletely characterized. Recently, circRNAs were reported to play indispensable roles in regulating metabolic and signal transduction events controlling the proliferation, migration, and survival of cells. Importantly, many studies demonstrated that dysregulated circRNA expression is associated with the development of multiple diseases, including cancer. In this review, we summarize current knowledge on the roles and mechanisms of circRNAs in cancer and discuss their functions as oncogenes or tumor suppressors in different tumor types.

关键词： Cancer circRNA Oncogene Review Tumor suppressor

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State-of-the-art applications of machine learning in the life cycle of solid waste management

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Frontiers of Environmental Science & Engineering 2023年第4期17卷 53-69页

作者： Rui Liang Chao Chen Akash Kumar junyu tao Yan Kang Dong Han Xianjia Jiang Pei Tang Beibei Yan Guanyi Chen School of Environmental Science and Engineering Tianjin UniversityTianjin 300350China School of Mechanical Engineering Tianjin University of CommerceTianjin 300134China Tianjin Key Laboratory of Biomass Wastes Utilization/Tianjin Engineering Research Center of Bio Gas/Oil Technology Tianjin 300072China School of Science Tibet UniversityLhasa 850012China

Due to the superiority of machine learning(ML)data processing,it is widely used in research of solid waste(SW).This study analyzed the research and developmental progress of the applications of ML in the life cycle of SW.Statistical analyses were undertaken on the literature published between 1985 and 2021 in the Science Citation Index Expanded and Social Sciences Citation Index to provide an overview of the progress.Based on the articles considered,a rapid upward trend from 1985 to 2021 was found and international cooperatives were found to have strengthened.The three topics of ML,namely,SW categories,ML algorithms,and specific applications,as applied to the life cycle of SW were discussed.ML has been applied during the entire SW process,thereby affecting its life cycle.ML was used to predict the generation and characteristics of SW,optimize its collection and transportation,and model the processing of its energy utilization.Finally,the current challenges of applying ML to SW and future perspectives were discussed.The goal is to achieve high economic and environmental benefits and carbon reduction during the life cycle of SW.ML plays an important role in the modernization and intellectualization of SW management.It is hoped that this work would be helpful to provide a constructive overview towards the state-of-the-art development of SW disposal.

关键词： Machine learning(ML) Solid waste(SW) Bibliometrics SW management Energy utilization Life cycle

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Prediction of high-density polyethylene pyrolysis using kinetic parameters based on thermogravimetric and artificial neural networks

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Frontiers of Environmental Science & Engineering 2023年第1期17卷 63-74页

作者： Xiaoxiao Yin junyu tao Guanyi Chen Xilei Yao Pengpeng Luan Zhanjun Cheng Ning Li Zhongyue Zhou Beibei Yan School of Mechanical Engineering Tianjin University of CommerceTianjin 300134China School of Environmental Science and Engineering Tianjin UniversityTianjin 300350China Key Laboratory for Power Machinery and Engineering of Ministry of Education Shanghai Jiao Tong UniversityShanghai 200240China

Pyrolysis is considered an attractive option and a promising way to dispose waste plastics.The thermogravimetric experiments of high-density polyethylene(HDPE)were conducted from 105℃ to 900℃ at different heating rates(10℃/min,20℃/min,and 30℃/min)to investigate their thermal pyrolysis behavior.We investigated four methods including three model-free methods and one modelfitting method to estimate dynamic parameters.Additionally,an artificial neural network model was developed by providing the heating rates and temperatures to predict the weight loss(wt.%)of HDPE,and optimized via assessing mean squared error and determination coefficient on the test set.The optimal MSE(2.6297×10^(−2))and R^(2) value(R^(2)>0.999)were obtained.Activation energy and preexponential factor obtained from four different models achieves the acceptable value between experimental and predicted results.The relative error of the model increased from 2.4%to 6.8%when the sampling frequency changed from 50 s to 60 s,but showed no significant difference when the sampling frequency was below 50 s.This result provides a promising approach to simplify the further modelling work and to reduce the required data storage space.This study revealed the possibility of simulating the HDPE pyrolysis process via machine learning with no significant accuracy loss of the kinetic parameters.It is hoped that this work could potentially benefit to the development of pyrolysis process modelling of HDPE and the other plastics.

关键词： HDPE Pyrolysis Kinetics Thermogravimetric ANOVA Artificial neural network

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机器学习在建筑垃圾处理领域的应用与现状

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环境卫生工程 2024年第2期32卷 10-19页

作者：许亚如陶俊宇梁蕊程占军颜蓓蓓陈冠益天津商业大学机械工程学院天津300134 天津大学环境科学与工程学院天津300072 天津市生物质废弃物利用重点实验室天津市生物气/油技术工程研究中心天津300072

建筑垃圾产生量巨大,成分复杂,如果不能妥善处理,其中的沥青、石膏、重金属、油漆等物质会与周围空气、土壤、水体反应并产生有害物质,严重危害人类的生存环境。我国“无废城市”的建设要求明确提出要建设固体废物综合管理体系以提升废... 详细信息

建筑垃圾产生量巨大,成分复杂,如果不能妥善处理,其中的沥青、石膏、重金属、油漆等物质会与周围空气、土壤、水体反应并产生有害物质,严重危害人类的生存环境。我国“无废城市”的建设要求明确提出要建设固体废物综合管理体系以提升废弃物的资源利用率的策略。建筑垃圾作为我国体量最大的城市固体废物,已成为被重点关注的对象,实现建筑垃圾资源化利用迫在眉睫。传统的建筑垃圾资源化处置通过人工、机械将建筑垃圾分类后再对建筑垃圾进行资源化利用,过程中存在管理难度大、效率低、成本过高等问题。机器学习作为人工智能的核心,已经逐渐应用到建筑垃圾处理的各个环节中,能有效提高建筑垃圾的资源化利用率。对建筑垃圾和机器学习的基本情况进行描述,介绍了建筑垃圾处理的过程,对机器学习在建筑垃圾处理领域的研究进展进行综述。最后结合我国国情,针对建筑垃圾处理领域提出几点建议,以期为实现建筑垃圾处理领域的自动化、智能化提供参考。

关键词：机器学习建筑垃圾人工智能资源化利用

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树鼩源碳青霉烯耐药性铜绿假单胞菌的分离鉴定及生物学特性研究

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中国畜牧兽医 2024年第4期51卷 1717-1728页

作者：穆政融程晴晴张东洁翟珊珊李竹欣陶俊宇冷静广西医科大学基础医学院南宁530021 广西中医药大学南宁530200 广西高发传染病中西医结合转化医学重点实验室南宁530200 广西特色实验动物病证模型重点实验室南宁530200 南宁市中医医院南宁530001

【目的】确定养殖过程中死亡树鼩的致病原因并分析病原的生物学特性、致病性和耐药情况,制定防治方法。【方法】对死亡树鼩进行病理剖检,记录肺脏、肝脏、脾脏、肠道等主要脏器的病变情况,通过平板划线法从主要病变脏器中分离单个菌落,... 详细信息

【目的】确定养殖过程中死亡树鼩的致病原因并分析病原的生物学特性、致病性和耐药情况,制定防治方法。【方法】对死亡树鼩进行病理剖检,记录肺脏、肝脏、脾脏、肠道等主要脏器的病变情况,通过平板划线法从主要病变脏器中分离单个菌落,观察菌落形态并进行革兰染色镜检,通过生化试验、药敏试验、致病性试验及16S rRNA基因测序和全基因组测序等手段对分离株进行进一步分析。【结果】从死亡滇西树鼩的脾脏、肠道中分离获得1株碳青霉烯耐药性铜绿假单胞菌,分离菌株在LB琼脂培养基中呈现产绿色水溶色素的灰白色菌落,镜检为革兰阴性杆菌;生化试验进一步证实分离菌为非发酵菌;通过序列进化分析可知,分离菌与GenBank收录的土壤来源铜绿假单胞菌F4相似性高达99%。药敏试验结果显示,分离菌对亚胺培南和美罗培南等碳青霉烯类及左氧氟沙星等喹诺酮类抗菌药均具有一定的耐药性。致病性试验结果显示,该分离株对成年昆明小鼠的半数致死量(LD 50)为3.382×108 CFU,对死亡小鼠脏器组织进行病理学观察,可见肺脏、肝脏、脾脏、肠道等的炎性损伤和坏死。对各脏器再次进行细菌分离,基于16S rRNA序列分析发现铜绿假单胞菌可在死亡小鼠的脾脏、肠道、血液中存在,具有较高的致病性。全基因组测序结果证实,分离菌具有碳青霉烯耐药性相关基因,并与铜绿假单胞菌高致病参考菌株具有相似的毒力因子基因。【结论】本研究从病死滇西树鼩体内分离出碳青霉烯耐药性铜绿假单胞菌,为树鼩微生物致病研究和驯化养殖提供了新的理论依据。

关键词：树鼩铜绿假单胞菌耐药性

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酒糟厌氧发酵-气化耦合制备燃气环境影响评价

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环境工程 2024年第1期42卷 63-71页

作者：张笑颜王智李志宇李健颜蓓蓓左晓宇杨改秀陶俊宇陈冠益天津大学环境科学与工程学院天津300072 北京化工大学环境科学与工程系北京100029 中国科学院广州能源所中国科学院可再生能源重点实验室广东省新能源和可再生能源研究开发与应用重点实验室广州510640 天津商业大学机械工程学院天津300134

厌氧发酵-气化耦合技术是一种高效的生物质燃气化技术,具备显著的能源转化优势。为准确评估厌氧发酵程度对该耦合系统环境效益的影响,利用全生命周期分析方法,通过Gabi软件对所建立的不同厌氧发酵时间下酒糟厌氧发酵-气化耦合制备燃气... 详细信息

厌氧发酵-气化耦合技术是一种高效的生物质燃气化技术,具备显著的能源转化优势。为准确评估厌氧发酵程度对该耦合系统环境效益的影响,利用全生命周期分析方法,通过Gabi软件对所建立的不同厌氧发酵时间下酒糟厌氧发酵-气化耦合制备燃气模型进行环境影响评价。结果表明:厌氧发酵-气化梯度耦合反应系统基于能量流产生的环境正面影响可抵消基于物质流产生的环境负面影响,从而使系统获得正面的综合环境效益。厌氧发酵时间为8 d时系统环境影响结果最优,其环境影响潜值为-2.02×10^(-9)。对厌氧发酵-气化耦合系统的耦合程度进行控制,可在优化系统能量收益的同时产生最有利的环境影响,从而为耦合技术的应用提供理论指导。

关键词：酒糟厌氧发酵-气化耦合生命周期评价环境影响

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Identification of three novel noncoding RNAs from Drosophila melanogaster

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Chinese Science Bulletin 2006年第22期51卷 2737-2742页

作者： HE Hualiang ZHOU Hui XIAO Zhendong ZENG Xianfen CHEN junyu ZHENG tao QU Lianghu Key Laboratory of Gene Engineering of the Ministry of Education State Key Laboratory for Biocontrol Sun Yat-sen University Guangzhou 510275 China

三新奇小非编码的 RNA 从 D 的保存 intronicregions 被识别。由使用比较基因组学方法和分子的生物学途径的 melanogaster。Oneis 以一个 combinated 方法的新奇 snoRNA，它 snoRNAfamily 显示典型地代表 C/D 盒子的结构的特征并且为在 ... 详细信息

三新奇小非编码的 RNA 从 D 的保存 intronicregions 被识别。由使用比较基因组学方法和分子的生物学途径的 melanogaster。Oneis 以一个 combinated 方法的新奇 snoRNA，它 snoRNAfamily 显示典型地代表 C/D 盒子的结构的特征并且为在 C2673 指导 D.melanogaster 28S rRNA 的 2''-O-methylation 拥有一个 10-nt-long rRNA 反感觉元素。另外的二是预言先锋采用已知的 miRNA 的 astem 环结构特征的 miRNAs。二 miRNAs 基因看起来有无所不在的表示侧面， ~ 23-nt RNA 抄本由北弄污检测了。我们的学习 revealed396 多种类 intronic 保存了与长度 from100 在 introns 嵌套到 500 bp 的序列(MCIS ) 。除了编码的小 RNA， MCIS 可能作为涉及基因抄写或 post-transcriptional 处理的 c/s-acting 元素工作。

关键词：果蝇 miRNA MCIS 分子生物学

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Interpretable machine learning assisted spectroscopy for fast characterization of biomass and waste

Interpretable machine learning assisted spectroscopy for fas...

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2023年有机固废处理与资源化利用大会

作者： Liang Rui Chen Chao tao junyu Yan Beibei Chen Guanyi School of Environmental Science and Engineering Tianjin University School of Mechanical Engineering Tianjin University of Commerce Tianjin Key Lab of Biomass Wastes Utilization/Tianjin Engineering Research Center of Bio Gas/Oil Technology School of Science Tibet University

Background,Aims and Scope.The characterization of biomass and waste(BW) is important to its downstream treatment and utilization.In order to overcome the long duration and complex procedure problems of traditional BW characterization methods,the spectroscopy and machine learning based BW fast characterization method has been developed recently,and presented satisfactory performance.However,this fast characterization process is lack of interpretability towards its chemical insights,leading to less satisfactory recognition for its reliability and difficulty in expanding the further application.Accordingly,this study proposed a hypothesis to the inner working mechanism of the spectroscopy and machine learning based BW fast characterization method:Infrared spectra have close qualitative and quantitative correlation with the functional groups' species and content.Each functional group has its specific element composition and heating value characteristics.Hence,the element composition and heating value results are obtained by processing the functional group information behind the infrared spectra.this paper aimed to verify the hypothesis.A novel dimensionality reduction method with physicochemical meanings was proposed to explain the chemical insights of the machine learning model.The high loading spectral peaks of BW,which contain the important information of the functional groups of raw materials,were selected as the results of dimensionality reduction.Then,combined with functional groups attribution of these spectral peaks,the machine learning model could provide clearer logic explanation of the input spectra and output characteristics,furthermore,provide support to the above hypothesis.This paper discussed the results of the dimensionality reduction,evaluated the characterization performance between the newly dimensionality reduction method and PCA,moreover,explored the theoretical fundamentals of the input spectra on the output characteristics.It is hoped to provide mechanism explanation and theoretical basis for

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