Article
Engineering, Aerospace
Mingxian Wang, Hongyan Wang, Langfu Cui, Gang Xiang, Xiaoxuan Han, Qingzhen Zhang, Juan Chen
Summary: This paper predicts the remaining useful life of aero-engines by applying fuzzy clustering and time-series decomposition modeling, and uses similarity comparison to predict the RUL.
Article
Computer Science, Artificial Intelligence
Yusheng Huang, Xiaoyan Mao, Yong Deng
Summary: The degree sequence of the NVG transformation provides useful motif information for practical usage, as shown in a study on stock trend prediction. The proposed natural visibility encoding and moving window strategy have been proven effective and robust in classifying time series. Further investigation into the degree sequence of the NVG transformation is encouraged based on the success of the proposed framework.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Houtian He, Shangce Gao, Ting Jin, Syuhei Sato, Xingyi Zhang
Summary: The study introduces a novel seasonal-trend decomposition-based dendritic neuron model (STLDNM) for financial time series prediction, utilizing STL to extract seasonal and trend features and an anti-overfitting dendritic neuron model (DNM) to handle the residual component. Experimental results demonstrate the superiority of the STLDNM in predicting financial data.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Renfei He, Limao Zhang, Alvin Wei Ze Chew
Summary: This study presents a hybrid approach (STL-ML) that integrates seasonal-trend decomposition and machine learning for predicting rainfall time series. A case study using meteorological data from Cairns, Australia demonstrates the accuracy and reliability of the proposed approach, especially for sudden extreme rainfall events. Comparisons with baseline methods further support the effectiveness of the hybrid STL-ML approach.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Public, Environmental & Occupational Health
Geoffrey Chiyuzga Singini, Samuel O. M. Manda
Summary: This study estimated the contagiousness parameters of COVID-19 in eight African countries, as well as Brazil, India, and the USA. The estimates varied among countries, with higher transmission rates observed in the three heavily affected countries. The findings highlight the need for different containment measures in the region.
FRONTIERS IN PUBLIC HEALTH
(2022)
Article
Computer Science, Hardware & Architecture
Arsalan Dezhkam, Mohammad Taghi Manzuri, Ahmad Aghapour, Afshin Karimi, Ali Rabiee, Shervin Manzuri Shalmani
Summary: This paper presents a classification approach for financial time series patterns, using machine learning and deep learning models, and the performance of the algorithm is enhanced by applying Bayesian optimization technique. The results show excellent trading performance of the framework.
JOURNAL OF SUPERCOMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Xiyang Yang, Fusheng Yu, Witold Pedrycz, Zhiwei Li
Summary: This paper proposes a trend-oriented time series granulation method to transform a long numerical time series into a relatively short granular time series. The transformed granular time series captures the main characteristics of the original time series and saves calculation in time series clustering. The distance measures for unequal-size LFIGs and LFIG time series are defined, and the k-medoids method is employed to cluster datasets from UCR time-series database.
APPLIED SOFT COMPUTING
(2023)
Article
Environmental Sciences
Fabio Bovenga, Guido Pasquariello, Alberto Refice
Summary: This study introduces a method for automatically identifying relevant changes in MTInSAR displacement time series, and proposes a procedure for automatically recognizing the minimum number of parameters needed for reliable modeling of a given time series. Through the use of polynomial models, it is possible to effectively approximate the piecewise linear trends used to model warning signals preceding the failure of structures. Finally, the proposed procedure is demonstrated on displacement time series derived from processing Sentinel-1 data.
Article
Computer Science, Artificial Intelligence
Zijing Yuan, Shangce Gao, Yirui Wang, Jiayi Li, Chunzhi Hou, Lijun Guo
Summary: The rapid industrial development in human society has led to air pollution, which has a serious impact on human health. One of the main factors causing air pollution is PM2.5 concentration. In order to accurately predict PM2.5 microns, a dendritic neuron model (DNM) trained by an improved state-of-matter heuristic algorithm (DSMS) based on STL-LOESS, namely DS-DNM, is proposed. Experimental results show that DS-DNM has the most competitive performance in PM2.5 concentration prediction problem among the selected training algorithms and prediction models.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Plant Sciences
Sruti Das Choudhury, Sinjoy Saha, Ashok Samal, Anastasios Mazis, Tala Awada
Summary: This paper introduces two novel algorithms for predicting and propagating drought stress in plants using image sequences captured in visible light and hyperspectral modalities. The first algorithm, VisStressPredict, analyzes image sequences captured by a visible light camera to compute holistic phenotypes and use dynamic time warping to predict the onset of drought stress. The second algorithm, HyperStressPropagateNet, leverages a deep neural network to classify reflectance spectra and determine the propagation of stress in the plant using hyperspectral imagery. Both algorithms show high correlation and can be applied to study the effect of abiotic stresses on sustainable agriculture practices.
FRONTIERS IN PLANT SCIENCE
(2023)
Article
Multidisciplinary Sciences
Grace Hui Ting Yeo, Sachit D. Saksena, David K. Gifford
Summary: This study introduces a generative framework that uses time-resolved single-cell data to model how cells change in physical time, predict cell fate biases, and simulate trajectories of perturbed cells. The approach has been validated in experiments, and is capable of accommodating complex perturbations involving multiple genes, time points, and starting cell populations.
NATURE COMMUNICATIONS
(2021)
Article
Energy & Fuels
Gurcan Kavakci, Begum Cicekdag, Seyda Ertekin
Summary: This study aims to develop a forecasting workflow that increases prediction accuracy irrespective of the machine learning method used and has minimal computational requirements. The proposed trend decomposition method incorporates irradiance and seasonal features to enhance forecasting performance by modeling both linear and non-linear components.
Article
Computer Science, Artificial Intelligence
Grzegorz Dudek
Summary: The decomposition of a time series is crucial for understanding its nature and facilitating analysis and forecasting of various components. However, existing methods neglect the variance of the time series. This work proposes a seasonal-trend-dispersion decomposition method to address heteroscedasticity and extract multiple components effectively.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2023)
Article
Energy & Fuels
Sidong Xian, Miaomiao Feng, Yue Cheng
Summary: Carbon trading is a significant tool in international politics and diplomacy, as well as having important economic value. This paper proposes innovative methods, using incremental Gaussian nonlinear trend fuzzy granulation, to predict carbon prices. The study shows that this prediction method has the smallest error in long-term prediction compared with other models, and it is validated using daily closing price datasets of carbon exchanges in Shenzhen and Beijing.
Article
Mathematics, Interdisciplinary Applications
Qian He, Fusheng Yu
Summary: This paper proposes a method called trend fuzzy granular recurrence plot (TFGRP) that effectively addresses noise and trend confusion in time series classification. By combining it with support vector machine (SVM), a superior classification performance is achieved.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Biodiversity Conservation
Xiaoyuan Zhang, Kai Liu, Shudong Wang, Taixia Wu, Xueke Li, Jinnian Wang, Dacheng Wang, Haitao Zhu, Chang Tan, Yuhe Ji
Summary: This study investigates the ecological vulnerability in the Yellow River Basin during different policy periods using an evaluation index system based on exposure-sensitivity-adaptability framework and earth observation data. The results show a decreasing trend in overall ecological vulnerability levels from 2001 to 2019, despite a slight increase in 2015 due to dry climate conditions. The study also finds geographical spatial variation in vulnerability levels, with the northern areas in the upper reaches being the most vulnerable. Ecological restoration policies have had a positive impact on improving ecological vulnerability. The findings provide guidance for ecological restoration in the Yellow River Basin and have potential applicability in assessing ecological vulnerability in other regions.
ECOLOGICAL INDICATORS
(2022)
Article
Geochemistry & Geophysics
Kai Liu, Hongbo Su, Xueke Li, Shaohui Chen
Summary: This study develops a spatio-temporal regression strategy to downscale 1-km MODIS LST product to 250-m resolution and simultaneously fill in missing values. The proposed methodology creates a high-resolution LST product and accurate ET retrievals, which can benefit land surface hydrology research and water resource management.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Geosciences, Multidisciplinary
Xiaoyuan Zhang, Kai Liu, Xueke Li, Shudong Wang, Jinnian Wang
Summary: This study assessed the spatial change of ecological vulnerability in the Loess Plateau from 2001 to 2019, showing that the southeast region is more stable while the northwest region is more vulnerable. Factors such as vegetation coverage, precipitation, and slope play key roles in influencing vulnerability.
PHYSICS AND CHEMISTRY OF THE EARTH
(2022)
Article
Computer Science, Information Systems
Hongyan Zhang, Shudong Wang, Kai Liu, Xueke Li, Zhengqiang Li, Xiaoyuan Zhang, Bingxuan Liu
Summary: This study proposes a new framework based on the random forest (RF) model to downscale the AMSR-E soil moisture data. The downscaled results show higher correlation and lower errors compared to in situ measurements. Furthermore, the proposed method outperforms other two methods in downscaled data comparison. The feasibility of the model is supported by importance analysis and leave-one-out analysis.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
(2022)
Article
Environmental Sciences
Yong Bo, Xueke Li, Kai Liu, Shudong Wang, Hongyan Zhang, Xiaojie Gao, Xiaoyuan Zhang
Summary: Accurate estimation of GPP is crucial for understanding plant carbon sequestration and assessing the ecological environment. This study investigates the spatial-temporal variability and trends of GPP in China from 1982 to 2015 using the LUEopt product. An ARIMA model is also employed to forecast one-year lead time of monthly GPP. The results show an overall upward trend of GPP, but with distinct heterogeneity across space and time. Climate factors and human activities both contribute to the dynamics of GPP. The ARIMA model demonstrates satisfactory predictive performance in most areas.
Article
Multidisciplinary Sciences
Amanda H. Lynch, Charles H. Norchi, Xueke Li
Summary: Sea ice in the Arctic has made maritime navigation difficult, but the reduction of ice cover due to climate change is expected to improve accessibility. Projections suggest that the retreat of sea ice from the eastern Arctic will require revisions to international maritime laws. Although the economic viability of open water routes in international waters is currently uncertain, it is predicted that these routes will become feasible by the midcentury, leading to a reduction in regulatory friction and a recalibration of legal frameworks.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Article
Environmental Sciences
Haoran Hou, Hongbo Su, Kai Liu, Xueke Li, Shaohui Chen, Weimin Wang, Jinhuang Lin
Summary: This study investigates the spatiotemporal heterogeneity of driving forces on urban heat island (UHI) behaviors. The results show that the contributions of sensible heat and latent heat to UHI intensity vary significantly between warm and cold seasons, indicating the influence of seasonality. Additionally, anthropogenic heat has a significant effect in semiarid/semihumid climate zones.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Engineering, Civil
Kai Liu, Xueke Li, Shudong Wang, Xiaoyuan Zhang
Summary: Vegetation restoration under China's Grain to Green Program has had a noticeable impact on the ecological-hydrological nexus. However, the restoration status and its effect on water availability have not been sufficiently studied. This study used satellite observations, land surface model outputs, and future projections to quantify the variations in gross primary productivity (GPP) and its effect on terrestrial water storage change (TWSC) on the Loess Plateau. The findings show an increase in GPP and a decline in TWSC, with the extent of the impact varying based on different types of vegetation coverage.
JOURNAL OF HYDROLOGY
(2023)
Article
Environmental Sciences
Dehui Li, Kai Liu, Shudong Wang, Taixia Wu, Hang Li, Yong Bo, Hongyan Zhang, Yuling Huang, Xueke Li
Summary: This study investigates the eco-hydrological regimes in the Three-North Region of China and Mongolia over the past four decades using satellite-derived vegetation variables and hydrological cycle components. The results show that vegetation productivity has increased in several regions, while precipitation and runoff have decreased. The study provides valuable reference for protecting and improving ecological-hydrological conditions in Northeast Asia.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Business, Finance
Michael A. Goldstein, Amanda H. Lynch, Xueke Li, Charles H. Norchi
Summary: This article examines the potential closure or shortening of the Northern Sea Route (NSR) due to sea ice or recent sanctions on Russia, and estimates the associated costs. The findings can be utilized by other researchers to assess potential cost savings in the future as climate change continues to impact global transportation.
FINANCE RESEARCH LETTERS
(2022)
Review
Multidisciplinary Sciences
Xiao Zeng, Qiong Ma, Xueke Li, Liting You, Jia Li, Xi Fu, Yifeng Ren, Fengming You
Summary: Lung cancer, the most common malignant tumor, requires personalized treatment for improved survival rate. Organoids-on-a-chip, based on microfluidics, offers precise control of environmental factors, simulation of tumor microenvironment, and improved throughput and monitoring. This technology allows for exploration of tumor-stromal cell interactions, biomarker discovery, and simplification of drug screening processes, boosting the prospects of personalized diagnosis and treatment.
CHINESE SCIENCE BULLETIN-CHINESE
(2023)
Article
Environmental Sciences
Xueke Li, Amanda H. H. Lynch
Summary: As Arctic sea ice continues to retreat, the growth of polar maritime and coastal development is expected. A new Transpolar Sea Route, in addition to the central Arctic corridor, is projected to emerge in the western Arctic by 2045. The opening of this new western route could have significant operational and strategic implications by reducing navigational and financial risks, as well as regulatory friction.
Review
Engineering, Environmental
Xueke Li, Yan Liu, Ting-an Zhang
Summary: This article discusses the methods to reduce energy consumption and solve pollution problems in the Hall-Heroult process of aluminium production. It reviews the functions of carbon anode, carbon cathode, refractory material and sidewall in aluminium electrolysis cells, outlines the process of aluminium electrolysis and ways to improve its current efficiency and reduce energy consumption. It also analyzes the causes and treatment methods of spent anodes, spent cathodes, spent refractories and spent pot liner, and reviews the research progress of waste heat recovery and aluminium electrolysis flue gas purification. Lastly, it provides future research directions for aluminium electrolysis flue gas.
WASTE MANAGEMENT & RESEARCH
(2023)
Article
Geosciences, Multidisciplinary
Kai Liu, Xueke Li, Shudong Wang, Hongyan Zhang
Summary: This study proposes a new gap-filling approach using the European Space Agency Climate Change Initiative (ESA CCI) to reconstruct soil moisture time series. The developed approach integrates satellite observations, model-driven knowledge, and a machine learning algorithm to achieve high accuracy in soil moisture reconstruction in China. The application of this method to long-term soil moisture datasets also shows promising results.
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2023)
Article
Remote Sensing
Kai Liu, Xueke Li, Shudong Wang, Xiaojie Gao
Summary: The study investigates the effects of landscape pattern on the urban thermal environment in Shijiazhuang, China using different datasets and models. The results show that there are noticeable differences in land surface temperature response to urban green landscape metrics between trees and lawns. The composition of urban green space has a substantial impact on land surface temperature throughout summer. The configurations of urban green space exhibit less impact on land surface temperature and these effects vary temporally in magnitude. The study also confirms that the impact of urban green space landscape metrics on land surface temperature is consistent at different spatial scales.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2022)
Article
Environmental Sciences
Toshimi Nakajima, Mao Kuragano, Makoto Yamada, Ryo Sugimoto
Summary: This study compared the contribution of submarine groundwater discharge (SGD) to river nutrient budgets at nearshore and embayment scales, and found that SGD-derived nutrients become more important at larger spatial scales.
SCIENCE OF THE TOTAL ENVIRONMENT
(2024)
Article
Environmental Sciences
Fan Liu, Lei Zhang, Chongyang Zhang, Ziguang Chen, Jingguang Li
Summary: NO2 emissions from wall-mounted gas stoves used for household heating have become a significant source of indoor pollution in Chinese urban areas. The high indoor concentration of NO2 poses potential health risks to residents. It is urgently necessary to establish relevant regulations and implement emission reduction technologies to reduce NO2 emissions from wall-mounted gas stoves.
SCIENCE OF THE TOTAL ENVIRONMENT
(2024)
Letter
Environmental Sciences
Hans Peter H. Arp, Raoul Wolf, Sarah E. Hale, Sivani Baskaran, Juliane Gluege, Martin Scheringer, Xenia Trier, Ian T. Cousins, Harrie Timmer, Roberta Hofman-Caris, Anna Lennquist, Andre D. Bannink, Gerard J. Stroomberg, Rosa M. A. Sjerps, Rosa Montes, Rosario Rodil, Jose Benito Quintana, Daniel Zahn, Herve Gallard, Tobias Mohr, Ivo Schliebner, Michael Neumann
SCIENCE OF THE TOTAL ENVIRONMENT
(2024)
Article
Environmental Sciences
Philomina Onyedikachi Peter, Binessi Edouard Ifon, Francois Nkinahamira, Kayode Hassan Lasisi, Jiangwei Li, Anyi Hu, Chang-Ping Yu
Summary: This study investigates the relationship between dissolved organic matter (DOM) and Rare Earth Elements (REEs) in sediments from Yundang Lagoon, China. The results show four distinct fluorescent components, with protein-like substances being the most prevalent. Additionally, the total fluorescence intensity and LREE concentrations exhibit a synchronized increase from Outer to Inner to Songbai Lake core sediments. The findings demonstrate a strong correlation between DOM content and pollution levels.
SCIENCE OF THE TOTAL ENVIRONMENT
(2024)
Article
Environmental Sciences
Surya Gupta, Pasquale Borrelli, Panos Panagos, Christine Alewell
Summary: The objective of this study is to incorporate soil hydraulic properties into the erodibility factor (K) of USLE-type models. By modifying and improving the existing equations for soil texture and permeability, the study successfully included information on saturated hydraulic conductivity (Ksat) into the calculation of K factor. Using the Random Forest machine learning algorithm, two independent K factor maps with different spatial resolutions were generated. The results show that the decrease in K factor values has a positive impact on the modeling of soil erosion rates.
SCIENCE OF THE TOTAL ENVIRONMENT
(2024)
Article
Environmental Sciences
Jesmin Akter, Wendy J. M. Smith, Yawen Liu, Ilho Kim, Stuart L. Simpson, Phong Thai, Asja Korajkic, Warish Ahmed
Summary: The choice of workflow in wastewater surveillance has a significant impact on SARS-CoV-2 concentrations, while having minimal effects on HF183 and no effect on HAdV 40/41 concentrations. Certain components in the workflow can be interchangeable, but factors such as buffer type, chloroform, and homogenization speed can affect the recovery of viruses and bacteria.
SCIENCE OF THE TOTAL ENVIRONMENT
(2024)
Article
Environmental Sciences
Yu Luo, Xueting Yang, Diwei Wang, Hongmei Xu, Hongai Zhang, Shasha Huang, Qiyuan Wang, Ningning Zhang, Junji Cao, Zhenxing Shen
Summary: Atmospheric PM2.5, which can generate reactive oxygen species (ROS), is associated with cardiorespiratory morbidity and mortality. The study found that both the mass concentration of PM2.5 and the DTT activity were higher during the heating season than during the nonheating season. Combustion sources were the primary contributors to DTT activity during the heating season, while secondary formation dominated during the nonheating season. The study also revealed that biomass burning had the highest inherent oxidation potential among all sources investigated.
SCIENCE OF THE TOTAL ENVIRONMENT
(2024)
Article
Environmental Sciences
Erin L. Murphy, Leah R. Gerber, Chelsea M. Rochman, Beth Polidoro
Summary: Plastic pollution has devastating consequences for marine organisms. This study uses a trait-based framework to develop a vulnerability index for marine mammals, seabirds, and sea turtles in Hawai'i. The index ranks 63 study species based on their vulnerability to macroplastic pollution, providing valuable information for species monitoring and management priorities.
SCIENCE OF THE TOTAL ENVIRONMENT
(2024)
Article
Environmental Sciences
Kenji Maurice, Amelia Bourceret, Sami Youssef, Stephane Boivin, Liam Laurent-Webb, Coraline Damasio, Hassan Boukcim, Marc-Andre Selosse, Marc Ducousso
Summary: Growing pressure from climate change and agricultural land use is destabilizing soil microbial community interactions. Little is known about microbial community resistance and adaptation to disturbances, hindering our understanding of recovery latency and implications for ecosystem functioning. This study found that anthropic disturbance and natural disturbance have different effects on the topology and stability of soil microbial networks.
SCIENCE OF THE TOTAL ENVIRONMENT
(2024)
Article
Environmental Sciences
Yunhao Li, Yali Feng, Haoran Li, Yisong Yao, Chenglong Xu, Jinrong Ju, Ruiyu Ma, Haoyu Wang, Shiwei Jiang
Summary: Deep-sea mining poses a serious threat to marine ecosystems and human health by disturbing sediment and transmitting metal ions through the food chain. This study developed a new regenerative adsorption material, OMN@SA, which effectively removes metal ions. The adsorption mechanism and performance of the material for metal ion fixation were investigated.
SCIENCE OF THE TOTAL ENVIRONMENT
(2024)
Article
Environmental Sciences
Antonio Medici, Margherita Lavorgna, Marina Isidori, Chiara Russo, Elena Orlo, Giovanni Luongo, Giovanni Di Fabio, Armando Zarrelli
Summary: Valsartan, a widely used antihypertensive drug, has been detected in high concentrations in surface waters due to its unchanged excretion and incomplete degradation in wastewater treatment plants. This study investigated the degradation of valsartan and identified 14 degradation byproducts. The acute and chronic toxicity of these byproducts were evaluated in key organisms in the freshwater trophic chain.
SCIENCE OF THE TOTAL ENVIRONMENT
(2024)
Article
Environmental Sciences
Jiang Lin, Lianbao Chi, Qing Yuan, Busu Li, Mingbao Feng
Summary: This study investigated the photodegradation behavior and product formation of two representative pharmaceuticals in simulated estuary water. The study found that the formed transformation products of these pharmaceuticals have potential toxicity on marine organisms, including oxidative stress and damage to cellular components.
SCIENCE OF THE TOTAL ENVIRONMENT
(2024)
Article
Environmental Sciences
Hua Fang, Dongdong Jiang, Ye He, Siyi Wu, Yuehong Li, Ziqi Zhang, Haoting Chen, Zixin Zheng, Yan Sun, Wenxiang Wang
Summary: This study revealed that exposure to lower levels of air pollutants led to decreased pregnancy rates, with PM10, NO2, SO2, and CO emerging as the four most prominent pollutants. Individuals aged 35 and above exhibited heightened susceptibility to pollutants.
SCIENCE OF THE TOTAL ENVIRONMENT
(2024)
Article
Environmental Sciences
Ali Shaan Manzoor Ghumman, Rashid Shamsuddin, Amin Abbasi, Mohaira Ahmad, Yoshiaki Yoshida, Abdul Sami, Hamad Almohamadi
Summary: In this study, inverse vulcanized polysulfides (IVP) were synthesized by reacting molten sulfur with 4-vinyl benzyl chloride, and then functionalized using N-methyl D-glucamine (NMDG). The functionalized IVP showed a high mercury adsorption capacity and a machine learning model was developed to predict the amount of mercury removed. Furthermore, the functionalized IVP can be regenerated and reused, providing a sustainable and cost-effective adsorbent.
SCIENCE OF THE TOTAL ENVIRONMENT
(2024)
Article
Environmental Sciences
Rita Bonfiglio, Renata Sisto, Stefano Casciardi, Valeria Palumbo, Maria Paola Scioli, Erica Giacobbi, Francesca Servadei, Gerry Melino, Alessandro Mauriello, Manuel Scimeca
Summary: This study investigated the presence of aluminum in human colon cancer samples and its potential association with biological processes involved in cancer progression. Aluminum was found in tumor areas of 24% of patients and was associated with epithelial to mesenchymal transition (EMT) and cell death. Additional analyses revealed higher tumor mutational burden and mutations in genes related to EMT and apoptosis in aluminum-positive colon cancers. Understanding the molecular mechanisms of aluminum toxicity may improve strategies for the management of colon cancer patients.
SCIENCE OF THE TOTAL ENVIRONMENT
(2024)