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The thermochemical processes such as gasification and co-gasification of biomass and coal are promising route for producing hydrogen-rich syngas. However, the process is characterized with complex reactions that pose a tremendous challenge in terms of controlling the process variables. This challenge can be overcome using appropriate machine learning algorithm to model the nonlinear complex relationship between the predictors and the targeted response. Hence, this study aimed to employ various machine learning algorithms such as regression models, support vector machine regression (SVM), gaussian processing regression (GPR), and artificial neural networks (ANN) for modeling hydrogen-rich syngas production by gasification and co-gasification of biomass and coal. A total of 12 machine learning algorithms which comprises the regression models, SVM, GPR, and ANN were configured, trained using 124 datasets. The performances of the algorithms were evaluated using the coefficient of determination (R2), root mean square error (RMSE), mean square error (MSE), and mean absolute error (MAE). In all cases, the ANN algorithms offer superior performances and displayed robust predictions of the hydrogen-rich syngas from the co-gasification processes. The R2 of both the Levenberg-Marquardt- and Bayesian Regularization-trained ANN obtained from the prediction of the hydrogen-rich syngas was found to be within 0.857-0.998 with low prediction errors. The sensitivity analysis to determine the effect of the process parameters on the model output revealed that all the parameters showed a varying level of influence. In most of the processes, the gasification temperature was found to have the most significant influence on the model output.Fomesafen is an herbicide used in soybean production, and sugar beet is a sensitive crop to fomesafen. When the herbicide is sprayed in the field, it is easy to cause floating and depositing on non-target crops, resulting in crop poisoning and reducing yield. There are few on the phenomenon and mechanism of fomesafen herbicide drift on sugar beet. There are few reports on the phenomenon and mechanism of ether herbicide migration on phytotoxicity of sugar beet. Therefore, in this experiment, indoor potted plants were used to simulate the dose of fomesafen drift deposited on sugar beet in the field to study the effects of fomesafen on the growth, photosynthetic system, and physiological indexes of seedlings for sugar beet were studied. The results showed that fomesafen at the dose of 225 g a.i. ha-1 significantly inhibited the plant height, root length, and biomass of sugar beet. Compared with the control, the net photosynthetic rate, stoma conductance, transpiration rate, and total chlorophyll pigment content of leaves were reduced by 77.16%, 83.84%, 64.00%, and 28.13%, respectively. Treatment with a dose of 225 g a.i. ha-1 also damaged the photosynthetic system II of the leaves, lowering the performance index on absorption energy, maximum quantum yield and, the energy of electron transfer, causing photoinhibition and photodamage. In addition, fomesafen significantly increased the content of malondialdehyde and the activity of peroxidase in leaves of sugar beet, reducing the activities of superoxide dismutase and catalase. Overall, this study is helpful to understand the drift and deposition of fomesafen on sugar beet and to discuss the phytotoxicity risk and dose of fomesafen on the beet, as a result of controlling the dose of fomesafen sprayed in the field.Concentration data of veterinary drugs in microalgae biomass collected from photobioreactors fed with piggery wastewaters are presented for the first time in this work. To this aim, a QuEChERS methodology and an ultrasound-assisted solid-liquid extraction have been assessed as sample preparation procedures with the purpose of determining 20 veterinary drugs, mainly antibiotics of different physico-chemical properties in addition to dexamethasone, fenbendazole and progesterone. Some critical operation parameters of the QuEChERS procedure were optimized by an experimental design but tetracycline, oxytetracycline, doxycycline, marbofloxacin and ciprofloxacin were not detected by the QuEChERS sample preparation. The use of a longer and thorough approach, a solid-liquid extraction with water/methanol in presence of primary secondary amine as a clean-up agent followed by solid-phase extraction on Oasis HLB cartridges, is recommended to monitor all intended analytes. The determination in extracts is carried out by ultra-high performance liquid chromatography-tandem mass spectrometry in selected reaction monitoring mode. Limits of detection about 0.2-42 ng per g of lyophilized microalgae sample, and repeatabilities about 6-46% (n = 5, RSDs) are reached. The solid-liquid extraction method was applied to microalgae biomass samples collected from a photobioreactor. Nine drugs were detected in the samples at relatively low concentration and a proportional relationship between the found concentrations and the octanol/water partition coefficients of the drugs has been outlined. Moreover, a linear ratio between the concentrations measured in biomass and effluent has been observed for most of the drugs.
The aim of this study was to investigate the expression profiles of long noncoding RNAs (lncRNAs) in human corneal epithelial cells (HCECs) exposed to fine particulate matter (PM
) and to identify potential biological pathways involved in PM
-induced toxicity in HCECs.

Using RNA sequencing (RNA-seq) and hierarchy clustering analysis, lncRNA expression profiles in PM
-treated and untreated HCECs were examined. Gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to predict the role of altered lncRNAs in biological processes and pathways. A quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) assay was conducted to verify the RNA-seq results in HCECs and human corneal epithelial cell sheets.

In total, 65 lncRNAs were altered in the PM
-treated HCECs, including 41 upregulated and 24 downregulated lncRNAs. The results of the qRT-PCR assay were consistent with those of the RNA-seq analysis. The expression of two significantly upregulated lncRNAs was confirmed in human corneal epithelial cell sheets. The GO analysis demonstrated that altered lncRNAs in the PM
-treated HCECs were significantly enriched in three domains cellular component, molecular function, and biological process. The KEGG pathway analysis revealed enriched pathways of lncRNA co-expressed mRNAs, including cancer, RNA transport, and Rap1 signaling.

Our results suggest that lncRNAs are involved in the pathogenesis of PM
-induced ocular diseases, exerting their effects through biological processes and pathogenic pathways. Among the altered lncRNAs, RP3-406P24.3 and RP11-285E9.5 may play significant roles in PM
-induced ocular surface injury.
Our results suggest that lncRNAs are involved in the pathogenesis of PM2.5-induced ocular diseases, exerting their effects through biological processes and pathogenic pathways. Among the altered lncRNAs, RP3-406P24.3 and RP11-285E9.5 may play significant roles in PM2.5-induced ocular surface injury.Exposure to dust particles enriched with arsenic (As) is a significant health threat for populations living in Southeast Asian megacities. The mineralogical composition of dust particles is the key factor that controls the retention and release of As. This study investigated the degree of metal(oid)s pollution (As, Ca, Fe, K, Ga, Rb, Sr, Ti, V, Y, and Zr) in road dust of Dhaka city, Bangladesh. Enrichment factor and geoaccumulation index suggested that the road dust was heavily enriched with As, which triggers a comprehensive investigation of its controlling mechanisms and potential health risks by combining physicochemical and mineralogical information with multivariate analysis and a simulated probabilistic risk estimation model. Alkaline road dust (pH15 ranges from 8.02 to 10.34) in Dhaka city was found to have significant enrichment of As. Dust alkalinity was possibly controlled by the presence of carbonate minerals, such as calcite. Quartz was identified as the dominant mineral phase followed by magnesium carbon arsenide (MgCAs2). Carbonate mineral driven alkaline pH conditions in road dust would potentially trigger the release and mobilization of As to the environment. However, organic complexation can stabilize As on particle surfaces. Monte Carlo simulation-based health risk forecast suggested that the probability of As associated cancer risk has greatly exceeded the threshold value of 1E-4 for adults and children, and children are more vulnerable than adults. According to sensitivity analysis, the concentration of As and exposure duration (ED) posed the most significant impact (>58%) on risk estimation.In this work, a novel sludge biochar/Zn-Al layered double hydroxide composite (SL) was synthesized in a facile co-precipitation method, and it was used to simultaneously remove benzotriazole (BTA) and lead ion (Pb(II)). Batch adsorption experiments demonstrated that composites with sludge content of 1.0 g (SL-1.0) had a great adsorption performance for BTA and Pb(II). The maximum adsorption capacities of SL-1.0 for BTA and Pb(II) were 239.6 and 226.1 mg g-1, respectively. There was preferential adsorption of BTA in BTA and Pb(II) binary system. Ertugliflozin The adsorption mechanism analysis indicated that the BTA and Pb(II) adsorption involved electrostatic attraction and chemical bonding with surface functional groups on SL-1.0. Specifically, hydrogen bonding and π-π interaction were mainly ascribed to BTA adsorption, while complexation with surface function groups dominated Pb(II) adsorption. With the advantages of facile synthesis and excellent adsorption capacity, SL-1.0 possesses great potential for simultaneously removing of BTA and Pb(II) from wastewaters.Millions of passengers wait for buses at Integrated Transport Hubs (ITH) daily in metropolitan cities. Environmental exposure and associated risk for passengers is of great public concern. In this study, eight volatile organic compounds (VOCs) and the 16 EPA priority polycyclic aromatic hydrocarbons (PAHs) were analyzed in airborne samples collected from indoor waiting areas (Indoor) and bus parks of nine Singapore ITH, which comprises of two types of architectural structure (i.e., fully sheltered and open/partially enclosed). The median concentrations of total VOCs (TVOCs), total gaseous PAHs (TgPAHs) and total airborne particles-adsorbed PAH (TpPAHs) concentrations in Indoor were 30.42 μg/m3, 18.99 ng/m3 and 1.38 ng/m3; respectively. A strong correlation (r ≥ 0.75, p less then 0.001) was observed between Indoor and bus parks air compounds. The "Indoor" to bus park pollutant concentration ratio (I/B ratio) showed lower values in the bus interchanges with fully sheltered bus parks (TVOCs 0.98; TgPAHs 0.76; TpPAHs 0.71) than those with open/partially enclosed ones (TVOCs 1.28; TgPAHs 1.31; TpPAHs 0.90). This result suggests that fully sheltered structure may cause the accumulation of air pollutants. The daily VOC and PAH exposure for commuters were further estimated by considering inhalation and dermal doses using Monte Carlo simulation (n = 100,000). Overall, the result showed that the risk is still within international guideline values. In sum, the effect of architecture structure on the migration of air pollutants should be taken into consideration in future transport hub design to reduce pollutant exposure to commuters.
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