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Detection and removal of emerging contaminants from water bodies: A statistical approach 从水体中检测和去除新出现的污染物:一种统计方法
Pub Date : 2023-04-04 DOI: 10.3389/frans.2023.1115540
A. Banerjee, Surjit Singh, A. Ghosh
The integration of mathematical modelling in different scientific domains has increased dramatically in recent years. In general, modelling involves using programming languages, manipulating matrices, designing algorithms, and tracking functions and data to gain new insights and more quantitative and qualitative information about systems. These strategies have motivated researchers to investigate numerous approaches to accurately solve a variety of problems. In this direction, modelling and simulation have been used to create sensitive and focused detection methods for a variety of applications, including environmental control. New pollutants, including pesticides, heavy metals, and medications, are endangering wildlife by poisoning water supplies. As a result, numerous biosensors that use modelling for effective environmental monitoring have been documented in the literature. The most current model-inspired biosensors used for environmental monitoring will be discussed in this review study. Additionally, each analytical biosensor’s capabilities and degree of success will be discussed. Finally, present difficulties in this area will be highlighted.
近年来,数学建模在不同科学领域的整合得到了极大的发展。一般来说,建模包括使用编程语言、操作矩阵、设计算法、跟踪函数和数据,以获得关于系统的新的见解和更多的定量和定性信息。这些策略促使研究人员研究许多方法来准确地解决各种问题。在这个方向上,建模和仿真已被用于为各种应用(包括环境控制)创建敏感和集中的检测方法。新的污染物,包括杀虫剂、重金属和药物,正在毒害水源,危及野生动物。因此,文献中记录了许多使用建模进行有效环境监测的生物传感器。本文将对目前用于环境监测的基于模型的生物传感器进行综述。此外,每种分析生物传感器的能力和成功程度将被讨论。最后,将强调目前在这方面的困难。
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引用次数: 0
Mass spectrometry and machine learning in the identification of COVID-19 biomarkers 新冠肺炎生物标志物鉴定中的质谱和机器学习
Pub Date : 2023-03-31 DOI: 10.3389/frans.2023.1119438
L. C. Lázari, Gilberto Santos de Oliveira, Janaina Macedo-da-Silva, L. Rosa-Fernandes, G. Palmisano
Identifying specific diagnostic and prognostic biological markers of COVID-19 can improve disease surveillance and therapeutic opportunities. Mass spectrometry combined with machine and deep learning techniques has been used to identify pathways that could be targeted therapeutically. Moreover, circulating biomarkers have been identified to detect individuals infected with SARS-CoV-2 and at high risk of hospitalization. In this review, we have surveyed studies that have combined mass spectrometry-based omics techniques (proteomics, lipdomics, and metabolomics) and machine learning/deep learning to understand COVID-19 pathogenesis. After a literature search, we show 42 studies that applied reproducible, accurate, and sensitive mass spectrometry-based analytical techniques and machine/deep learning methods for COVID-19 biomarker discovery and validation. We also demonstrate that multiomics data results in classification models with higher performance. Furthermore, we focus on the combination of MALDI-TOF Mass Spectrometry and machine learning as a diagnostic and prognostic tool already present in the clinics. Finally, we reiterate that despite advances in this field, more optimization in the analytical and computational parts, such as sample preparation, data acquisition, and data analysis, will improve biomarkers that can be used to obtain more accurate diagnostic and prognostic tools.
识别新冠肺炎的特定诊断和预后生物标志物可以改善疾病监测和治疗机会。质谱法与机器和深度学习技术相结合,已被用于识别可作为治疗靶点的途径。此外,循环生物标志物已被确定用于检测感染严重急性呼吸系统综合征冠状病毒2型和住院风险高的个体。在这篇综述中,我们调查了基于质谱的组学技术(蛋白质组学、脂组学和代谢组学)和机器学习/深度学习相结合的研究,以了解新冠肺炎的发病机制。在文献检索后,我们展示了42项研究,这些研究应用了可重复、准确和敏感的基于质谱的分析技术和机器/深度学习方法来发现和验证新冠肺炎生物标志物。我们还证明了多组学数据产生了具有更高性能的分类模型。此外,我们将重点放在MALDI-TOF质谱法和机器学习的结合上,将其作为一种已经在临床上存在的诊断和预后工具。最后,我们重申,尽管在该领域取得了进展,但在分析和计算部分进行更多优化,如样品制备、数据采集和数据分析,将改进可用于获得更准确诊断和预后工具的生物标志物。
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引用次数: 0
What information is contained in experimentally determined lipid profiles? 实验确定的脂质图谱中包含哪些信息?
Pub Date : 2023-03-23 DOI: 10.3389/frans.2023.1157582
D. Schwudke
Hundreds of molecular species make up the cellular lipidome. In this minireview, considerations for interpreting membrane and storage lipid profile changes that are often the focal point of lipidomic studies are discussed. In addition, insights how the most conserved molecular patterns are formed in eukaryotic systems and the consequences for the perturbation of lipid homeostasis are addressed. The implications of lipid identification specificity and experimental variability on modeling membrane structure and systemic responses are also discussed. The profile changes of membrane and storage lipids are bound to the kinetics of the metabolic system, and experimental design and functional interpretation in lipidomic research should be adapted accordingly.
数百种分子组成了细胞脂质圆顶。在这篇小型综述中,讨论了解释膜和储存脂质分布变化的注意事项,这些变化通常是脂质组学研究的焦点。此外,还讨论了在真核生物系统中如何形成最保守的分子模式以及脂质稳态扰动的后果。还讨论了脂质鉴定特异性和实验变异性对膜结构和系统反应建模的影响。膜和储存脂质的分布变化与代谢系统的动力学有关,脂质组学研究中的实验设计和功能解释应相应调整。
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引用次数: 0
Investigating metformin-active substances from different manufacturing sources by NIR, NMR, high-resolution LC-MS, and chemometric analysis for the prospective classification of legal medicines 通过近红外、核磁共振、高分辨率LC-MS和化学计量分析研究不同生产来源的二甲双胍活性物质,以对合法药物进行前瞻性分类
Pub Date : 2023-03-07 DOI: 10.3389/frans.2023.1091764
M. Raimondo, Francesca Prestinaci, F. Aureli, Giulia D’Ettorre, M. Gaudiano
Introduction: The characterisation of active substances is an essential tool to ensure the traceability and authenticity of legal medicines. Metformin is a well-established biguanide derivative recommended in oral formulations as a first-line treatment for type 2 diabetes. With its increasing demand, metformin is likely to be an attractive target for falsification and substandard production, thus posing health risks to consumers. Methods that are able to identify even small differences in active pharmaceutical ingredients (APIs) are deemed necessary. The detection of fraudulent practices in APIs is not straightforward, and a single technique that can provide sufficient information to unambiguously address this issue is still not available. Methods: This study investigated an integrated analytical platform based on NIR, 1H-NMR, 13C-NMR, and high-resolution LC-MS combined with chemometrics to profile 32 metformin hydrochloride samples originating from several global authorised manufacturers. The study's aim was to explore differences in the chemical characteristics of metformin hydrochloride APIs to identify or predict a possible classification for each manufacturer in view of prospective authenticity studies. Different pre-processing methods were applied; bucket tables for 1H- and 13C-NMR were obtained, while mass spectrometry data were processed in targeted and untargeted modes. Datasets were individually analysed and merged by a multivariate unsupervised method and performing principal component analysis (PCA). Results and Discussion: The results evidenced differences in cluster behaviour, depending on manufacturers. Each technique has shown a specific clustering tendency, highlighting how different analytical approaches are able to characterise metformin APIs. Some manufacturers’ samples, however, showed similar behaviour independently of the techniques. NIR and 1H-NMR were confirmed as the more predictive techniques if taken individually; 1H-NMR, in particular, achieved good separation between the samples of the two most representative manufacturers. For LC-MS, the targeted approach resulted in a separation in groups clearer than that of the untargeted approach. Nevertheless, the untargeted LC-MS approaches presented in this paper could be a possible alternative to obtaining different information for drug substances, with several different and complex synthetic pathways leading to several unknown impurities. Further grouping of manufacturers emerged by data fusion, highlighting its potential in the traceability of metformin.
引言:活性物质的表征是确保合法药品可追溯性和真实性的重要工具。二甲双胍是一种完善的双胍衍生物,推荐作为2型糖尿病的一线治疗口服配方。随着需求的增加,二甲双胍很可能成为伪造和不合格生产的诱人目标,从而对消费者构成健康风险。能够识别活性药物成分(api)的微小差异的方法被认为是必要的。检测api中的欺诈行为并不是直截了当的,而且还没有一种技术可以提供足够的信息来明确地解决这个问题。方法:本研究建立了一个基于NIR、1H-NMR、13C-NMR和高分辨率LC-MS结合化学计量学的集成分析平台,对来自几家全球授权制造商的32份盐酸二甲双胍样品进行了分析。该研究的目的是探讨盐酸二甲双胍原料药化学特性的差异,以确定或预测每个制造商在前瞻性真实性研究中的可能分类。采用了不同的预处理方法;获得1H-和13C-NMR桶表,质谱数据以靶向和非靶向模式进行处理。通过多元无监督方法和主成分分析(PCA)对数据集进行单独分析和合并。结果和讨论:结果证明了集群行为的差异,取决于制造商。每种技术都显示出特定的聚类趋势,突出了不同的分析方法如何能够表征二甲双胍原料药。然而,一些制造商的样品显示出与技术无关的类似行为。如果单独使用,NIR和1H-NMR被证实为更具预测性的技术;特别是1H-NMR,在两个最具代表性的制造商的样品之间实现了良好的分离。对于LC-MS,靶向方法比非靶向方法更清晰地分离各组。然而,本文提出的非靶向LC-MS方法可能是获取原料药不同信息的一种可能的替代方法,几种不同且复杂的合成途径导致几种未知杂质。数据融合产生了进一步的制造商分组,突出了其在二甲双胍可追溯性方面的潜力。
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引用次数: 0
Miniaturized NIR spectroscopy and chemometrics: A smart combination to solve food authentication challenges 小型化近红外光谱和化学计量学:解决食品认证挑战的智能组合
Pub Date : 2023-03-03 DOI: 10.3389/frans.2023.1118590
Arian Amirvaresi, H. Parastar
Over the years, technology has allowed more accurate, more effective, and prompt food integrity assessments to assure the quality and authenticity of food material. Thanks to the development of portable and hand-held near infrared (NIR) as a rapid, reliable, non-destructive, and user-friendly instrument, on-site food analysis is provided with more feasibility. However, miniaturized NIR devices have some significant challenges due to the presence of varying noise resources which can lead to misinterpretation. In this context, chemometric methods with the capability of resolution, identification, classification, and calibration play a pivotal role in achieving precise and in-depth comprehension of the data. In the present mini-review, we will discuss miniaturized NIR instrumentation, some chemometric concepts, and introduce the most popular algorithm in food authentication problem. The main feature of this review is avoiding mathematical details as much as possible to make the material accessible to a broad audience but highlighting the key features of chemometric methods with some simple illustrative examples in the scope of food authenticity.
多年来,技术已经允许更准确,更有效,更及时的食品完整性评估,以确保食品材料的质量和真实性。便携式和手持式近红外(NIR)作为一种快速、可靠、无损和用户友好的仪器,为现场食品分析提供了更多的可行性。然而,小型化的近红外器件面临着一些重大挑战,因为存在不同的噪声资源,这可能导致误解。在这种情况下,具有分辨率、识别、分类和校准能力的化学计量学方法在实现对数据的精确和深入理解方面发挥着关键作用。在本综述中,我们将讨论小型化近红外仪器,一些化学计量学的概念,并介绍在食品认证问题中最流行的算法。这篇综述的主要特点是尽可能地避免数学细节,使材料能够被广泛的受众所理解,但在食品真实性的范围内,通过一些简单的说述性例子强调化学计量方法的关键特征。
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引用次数: 2
Determination of dissociation constants via quantitative mass spectrometry 定量质谱法测定解离常数
Pub Date : 2023-02-24 DOI: 10.3389/frans.2023.1119489
Jonathan Schulte, Jan-Niklas Tants, Julian von Ehr, A. Schlundt, N. Morgner
The interplay of biomolecules governs all cellular processes. Qualitative analysis of such interactions between biomolecules as well as the quantitative assessment of their binding affinities are essential for the understanding of biochemical mechanisms. As scientific interest therefore moves beyond pure structural investigation, methods that allow for the investigation of such interactions become increasingly relevant. In this perspective we outline classical methods that are applicable for the determination of binding constants and highlight specifically mass spectrometry based methods. The use of mass spectrometry to gain quantitative information about binding affinities however is a still developing field. Here, we discuss different approaches, which emerged over the last years to determine dissociation constants (KD) with mass spectrometry based methods. Specifically, we highlight the recent development of quantitative Laser Induced Liquid Bead Ion Desorption (qLILBID) mass spectrometry for the example of double stranded deoxyribonucleic acids as well as for different RNA—RNA binding protein systems. We show that quantitative laser induced liquid bead ion desorption can successfully be used for the top down investigation of complexes and their dissociation constants values ranging from low nM to low µM affinities.
生物分子的相互作用支配着所有的细胞过程。生物分子间相互作用的定性分析以及它们结合亲和力的定量评估对于理解生物化学机制至关重要。因此,随着科学兴趣超越纯粹的结构研究,允许研究这种相互作用的方法变得越来越重要。从这个角度来看,我们概述了适用于确定结合常数的经典方法,并特别强调了基于质谱的方法。然而,利用质谱法获得结合亲和力的定量信息仍是一个发展中的领域。在这里,我们讨论了不同的方法,这些方法在过去几年出现,以质谱为基础的方法来确定解离常数(KD)。具体来说,我们强调了定量激光诱导液珠离子解吸(qLILBID)质谱法的最新发展,以双链脱氧核糖核酸为例,以及不同的RNA-RNA结合蛋白系统。我们发现定量激光诱导的液珠离子解吸可以成功地用于自上而下的研究配合物及其离解常数值范围从低nM到低µM亲和。
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引用次数: 1
What clinical metabolomics will bring to the medicine of tomorrow 临床代谢组学将给明天的医学带来什么
Pub Date : 2023-02-24 DOI: 10.3389/frans.2023.1142606
A. Le Gouellec, C. Plazy, B. Toussaint
The purpose of this review is to explore how clinical metabolomics could help physicians in the future. The recent advent of medical genomics brings new and interesting technological tools to measure genetic predispositions to a disease. But metabolomics will allow us to go even further by linking the patient’s pathological phenotype with gene expression defects and metabolic disorders. It is in this context that the clinical chemist must adapt and be a force of proposal to meet these health challenges. He must help the clinician by mastering these new innovative tools, in order to participate in the implementation of clinical studies for the discovery of biomarkers, but also to propose the assays of biomarkers called “signatures,” which can be composite biomarkers or fingerprints, which will ultimately guide the clinician. He will have to propose them as clinical chemistry tests. In the first part, we will look at some concrete examples of the use of clinical metabolomics in clinical research projects that have led to the identification of a new biomarker. We will use the example of trimethylamine N-oxide (or TMAO) and review the clinical studies that have proposed TMAO as a biomarker for cardiovascular diseases. In a second part, we will see through bibliographic studies, how the metabolomic fingerprint can be useful to build a supervised model for patient stratification. In conclusion, we will discuss the limitations currently under debate.
这篇综述的目的是探讨临床代谢组学在未来如何帮助医生。最近医学基因组学的出现带来了新的和有趣的技术工具来测量疾病的遗传倾向。但代谢组学将使我们更进一步,将患者的病理表型与基因表达缺陷和代谢紊乱联系起来。正是在这种背景下,临床化学家必须适应并成为应对这些健康挑战的建议力量。他必须通过掌握这些新的创新工具来帮助临床医生,以便参与临床研究的实施,以发现生物标志物,而且还提出了称为“签名”的生物标志物的分析,它可以是复合生物标志物或指纹,最终将指导临床医生。他将不得不提议将它们作为临床化学测试。在第一部分中,我们将看一些临床代谢组学在临床研究项目中使用的具体例子,这些项目已经导致了新的生物标志物的鉴定。我们将以三甲胺n -氧化物(或TMAO)为例,回顾提出TMAO作为心血管疾病生物标志物的临床研究。在第二部分中,我们将通过文献研究了解代谢组学指纹如何有助于建立患者分层的监督模型。最后,我们将讨论目前正在辩论的局限性。
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引用次数: 2
Development and validation of an ultraviolet-visible spectrophotometric method for quantifying oxytetracycline for veterinary use 兽药用紫外-可见分光光度法定量土霉素的建立与验证
Pub Date : 2023-02-22 DOI: 10.3389/frans.2023.1066348
Jacques Mbuyi Kaluka Tshibamba, Jocelyn Mankulu Kakumba, Timothy Mavanga Mabaya, Roland Marini Djang’ieng’a, J. M. Kindenge
Livestock breeding plays a key role in sub-Saharan Africa because it is an important source of highly valued protein in the human diet, and because it is an essential driver for socio-economic development. It represents a form of investment and is also important from a socio-cultural point of view (ceremonies, social position, etc.). Livestock is an important source of income, livelihood, nutrition, and food security. However, livestock breeding faces, among other things, major sanitary constraints. Furthermore, the circulation of non-compliant antibiotics on the market constitutes a major threat to animal health, public health, and the environment. This research aims to develop and validate a UV-vis method for quantifying pharmaceutical oxytetracycline. The method developed was validated following the total error strategy as a decision tool in the accuracy profile. After its completion, the method demonstrated good absolute and relative bias and was within a tolerable interval of [−2%, +2%]. The method was also repeatable with intermediate precision, with respectively lower values than 2% and 4%. We also assessed the recovery and accuracy of the method as fitting with the specification limits. After its validation, the method was quantified in 47 oxytetracycline injectable samples, where we obtained 28 samples complying with specifications and 19 that did not. That led us to conclude that the developed method was validated and appropriate for quantification in terms of the routine quality control of oxytetracycline injection. The method needs to be reviewed and revalidated accordingly for other pharmaceutical presentations.
畜牧业在撒哈拉以南非洲发挥着关键作用,因为它是人类饮食中高价值蛋白质的重要来源,也是社会经济发展的重要驱动力。它代表了一种投资形式,从社会文化角度(仪式、社会地位等)来看也很重要。牲畜是收入、生计、营养和粮食安全的重要来源。然而,畜牧业面临着主要的卫生限制。此外,市场上不合规抗生素的流通对动物健康、公共卫生和环境构成了重大威胁。本研究旨在开发和验证一种紫外-可见光谱法来定量药物土霉素。根据总误差策略,将所开发的方法作为精度剖面中的决策工具进行了验证。完成后,该方法显示出良好的绝对和相对偏差,并且在[-2%,+2%]的可容忍区间内。该方法也具有中等精度的可重复性,其值分别低于2%和4%。我们还评估了该方法的回收率和准确性,认为符合规格限制。在验证后,该方法在47个土霉素注射样品中进行了定量,其中我们获得了28个符合规范的样品和19个不符合规范的样本。这使我们得出结论,从土霉素注射液的常规质量控制来看,所开发的方法是有效的,适用于定量。需要对该方法进行审查,并对其进行相应的重新验证,以用于其他药物展示。
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引用次数: 0
Advances and strategies for capillary electrophoresis in the characterization of traditional Chinese medicine: A review of the past decade (2011–2021) 毛细管电泳在中药表征中的进展和策略:近十年(2011-2021)综述
Pub Date : 2023-02-22 DOI: 10.3389/frans.2023.1059884
S. Shamsi, Jalpa U. Patel
While traditional Chinese medicine (TCM) is considered a valuable resource for drug discovery and form a potential basis for drug development, they also carry substantial safety risks due to adverse drug reactions and a lack of understanding of their mechanisms of action. However, due to their highly complex composition, valid analytical methodologies for analyzing TCMs must be developed and promoted. An extensive search of published research and review of scientific papers implies that the increased efficiency and sensitivity of capillary electrophoresis (CE) has attracted much research attention. This review provides an in-depth assessment of CE applications for TCM analysis published in the open literature in the last decade (2011–2021). Our survey findings showed that capillary zone electrophoresis (CZE) with ultraviolet (UV) detection is a capillary electromigration technique frequently utilized for the efficient separation, identification, and quantitation of various active components in highly complex matrices. Different extraction methods, modifiers to the background electrolyte, preconcentration techniques, and mass spectrometry (MS) detectors are used to enhance CE separation selectivity and TCM sensitivity.
虽然中药被认为是药物发现的宝贵资源,并构成了药物开发的潜在基础,但由于药物不良反应和对其作用机制的了解不足,它们也存在巨大的安全风险。然而,由于中药的成分非常复杂,必须开发和推广有效的分析方法。对已发表的研究和科学论文的广泛检索表明,毛细管电泳(CE)的效率和灵敏度的提高引起了人们的广泛关注。本综述对过去十年(2011-2021年)公开文献中发表的用于中药分析的CE应用进行了深入评估。我们的调查结果表明,毛细管区带电泳(CZE)与紫外(UV)检测是一种毛细管电迁移技术,经常用于高效分离,鉴定和定量各种有效成分的高度复杂的基质。采用不同的提取方法、背景电解质改性剂、预富集技术和质谱(MS)检测器来提高CE的分离选择性和TCM的灵敏度。
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引用次数: 1
Causal analysis of nitrogen oxides emissions process in coal-fired power plant with LiNGAM 燃煤电厂氮氧化物排放过程的LiNGAM原因分析
Pub Date : 2023-02-16 DOI: 10.3389/frans.2023.1045324
Tatsuki Saito, Koichi Fujiwara
Coal has been an important energy source worldwide; however, it is the largest source of nitrogen oxide (NOx) emissions because the amount of nitrogen in coal is larger than that of other fossil fuels. Precise control of NOx emissions is required in operations of coal-fired power plants from the viewpoint of air pollution control. Although theoretical analyses of NOx generation from a coal-fired power plant have been conducted, it is difficult to precisely predict NOx generation in an actual plant. NOx generation is affected by various factors, such as furnace design and operating conditions, and there are complicated relationships among them. Thus, it is necessary to identify important operating factors that affect NOx generation in actual coal-fired power plants. A linear non-Gaussian acyclic model (LiNGAM) is an exploratory causal analysis method that identifies a causal ordering of variables and their connection strengths without any prior knowledge of causal relationships among variables. In this study, we analyzed real operation data collected from a coal-fired power plant using LiNGAM to identify factors of NOx generation. The causal relationship between process variables and NOx generation was estimated by means of LiNGAM, and the connectional strengths of the variables on NOx generation were derived. The analysis results agreed with previous reports on NOx generation mechanisms, such as combustion air temperature, steam temperature on a specific side of the furnace, and air flow rate of forced draft fans. In addition, we found the steam flow rate and the furnace pressure as new candidate factors of NOx generation through causal analysis using LiNGAM, which heretofore has not been suggested. Our analysis result should contribute to reducing NOx emissions from coal-fired power plants in the future.
煤炭一直是世界范围内的重要能源;然而,它是氮氧化物(NOx)排放的最大来源,因为煤中的氮含量大于其他化石燃料。从空气污染控制的角度来看,在燃煤发电厂的运行中需要精确控制NOx排放。尽管已经对燃煤发电厂的NOx生成进行了理论分析,但很难准确预测实际发电厂中的NOx生成。NOx的产生受到多种因素的影响,如炉膛设计和运行条件,它们之间存在复杂的关系。因此,有必要确定影响实际燃煤发电厂NOx生成的重要运行因素。线性非高斯非循环模型(LiNGAM)是一种探索性的因果分析方法,它在没有任何变量之间因果关系的先验知识的情况下识别变量的因果排序及其连接强度。在本研究中,我们分析了使用LiNGAM从燃煤发电厂收集的实际运行数据,以确定NOx产生的因素。利用LiNGAM方法估算了工艺变量与NOx生成之间的因果关系,并推导了各变量对NOx生成的连接强度。分析结果与之前关于NOx生成机制的报告一致,如燃烧空气温度、炉膛特定侧的蒸汽温度和送风机的空气流速。此外,通过使用LiNGAM进行因果分析,我们发现蒸汽流速和炉膛压力是NOx产生的新的候选因素,而迄今为止尚未提出这一点。我们的分析结果将有助于减少未来燃煤发电厂的NOx排放。
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引用次数: 1
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