Wastewater treatment process enhancement based on multi-objective optimization and interpretable machine learning.

Optimization and control of wastewater treatment process (WTP) can contribute to cost reduction and efficiency. A wastewater treatment process multi-objective optimization (WTPMO) framework is proposed in this paper to provide suggestions for decision-making in setting parameters of WTP. Firstly, the prediction models based on Extreme Gradient Boosting (XGB) with Bayesian optimization (BO) are developed for predicting effluent water quality (EQ) and energy consumption (EC) for different influent quality and process parameter settings. Then, the SHapley Additive exPlanations (SHAP) algorithm is used to complement the interpretability of machine learning to quantitatively evaluate the impact of different features on the predicted targets. Finally, the Non-dominated Sorting Genetic Algorithm II (NSGA-II) with the Technique for Ordering Preferences on Similarity of Ideal Solutions (TOPSIS) is introduced to solve and make decisions on the multi-objective optimization problem. The WTPMO applicability is validated on Benchmark Simulation Model 1 (BSM1). The results show that BOXGB achieves accurate prediction for EQ and EC with R2 values of 0.923 and 0.965, respectively, indicating that BO can effectively select the model hyperparameters in XGB. Based on SHAP supplemented the interpretability of the model to fully explain how the influent water quality and decision variables affect the EQ and EC of the WTP. In addition, the optimized process parameters are determined based on NSGA-II and TOPSIS, and the EC optimization rate is 1.552% while guaranteeing water quality compliance. Overall, this research can effectively achieve the optimization of WTP, ensure that the effluent water quality meets the standards while reducing energy consumption, assist Wastewater treatment plants (WWTPs) to achieve more intelligent and efficient operation and maintenance management, and provide strong support for environmental protection and sustainable development goals.

Methylmercury induces inflammatory response and autophagy in microglia through the activation of NLRP3 inflammasome.

Methylmercury (MeHg) is a global environmental pollutant with neurotoxicity, which can easily crosses the blood-brain barrier and cause irreversible damage to the human central nervous system (CNS). CNS inflammation and autophagy are known to be involved in the pathology of neurodegenerative diseases. Meanwhile, MeHg has the potential to induce microglia-mediated neuroinflammation as well as autophagy. This study aims to further explore the exact molecular mechanism of MeHg neurotoxicity. We conducted in vitro studies using BV2 microglial cell from the central nervous system of mice. The role of inflammation and autophagy in the damage of BV2 cells induced by MeHg was determined by detecting cell viability, cell morphology and structure, reactive oxygen species (ROS), antioxidant function, inflammatory factors, autophagosomes, inflammation and autophagy-related proteins. We further investigated the relationship between the inflammatory response and autophagy induced by MeHg by inhibiting them separately. The results indicated that MeHg could invade cells, change cell structure, activate NOD-like receptor thermal protein domain associated protein 3 (NLRP3) inflammasome and autophagosome, release a large amount of inflammatory factors and trigger the inflammatory response and autophagy. It was also found that MeHg could disrupt the antioxidant function of cells. In addition, the inhibition of NLRP3 inflammasome alleviated both cellular inflammation and autophagy, while inhibition of autophagy increased cellular inflammation. Our current research suggests that MeHg might induce BV2 cytotoxicity through inflammatory response and autophagy, which may be mediated by the NLRP3 inflammasome activated by oxidative stress.

Genomic variation in weedy and cultivated broomcorn millet accessions uncovers the genetic architecture of agronomic traits.

Large-scale genomic variations are fundamental resources for crop genetics and breeding. Here we sequenced 1,904 genomes of broomcorn millet to an average of 40× sequencing depth and constructed a comprehensive variation map of weedy and cultivated accessions. Being one of the oldest cultivated crops, broomcorn millet has extremely low nucleotide diversity and remarkably rapid decay of linkage disequilibrium. Genome-wide association studies identified 186 loci for 12 agronomic traits. Many causative candidate genes, such as PmGW8 for grain size and PmLG1 for panicle shape, showed strong selection signatures during domestication. Weedy accessions contained many beneficial variations for the grain traits that are largely lost in cultivated accessions. Weedy and cultivated broomcorn millet have adopted different loci controlling flowering time for regional adaptation in parallel. Our study uncovers the unique population genomic features of broomcorn millet and provides an agronomically important resource for cereal crops.

Hi-C profiling in tissues reveals 3D chromatin-regulated breast tumor heterogeneity and tumor-specific looping-mediated biological pathways.

Current knowledge in three-dimensional (3D) chromatin regulation in normal and disease states was mostly accumulated through Hi-C profiling in in vitro cell culture system. The limitations include failing to recapitulate disease-specific physiological properties and often lacking clinically relevant disease microenvironment. In this study, we conduct tissue-specific Hi-C profiling in a pilot cohort of 12 breast tissues comprising of two normal tissues (NTs) and ten ER+ breast tumor tissues (TTs) including five primary tumors (PTs), and five tamoxifen-treated recurrent tumors (RTs). We find largely preserved compartments, highly heterogeneous topological associated domains (TADs) and intensively variable chromatin loops among breast tumors, demonstrating 3D chromatin-regulated breast tumor heterogeneity. Further cross-examination identifies RT-specific looping-mediated biological pathways and suggests CA2, an enhancer-promoter looping (EPL)-mediated target gene within the bicarbonate transport metabolism pathway, might play a role in driving the tamoxifen resistance. Remarkably, the inhibition of CA2 not only impedes tumor growth both in vitro and in vivo , but also reverses chromatin looping. Our study thus yields significant mechanistic insights into the role and clinical relevance of 3D chromatin architecture in breast cancer endocrine resistance.

Maternal nitric oxide homeostasis impacts female gametophyte development under optimal and stress conditions.

In adverse environments, the number of fertilizable female gametophytes (FGs) in plants is reduced, leading to increased survival of the remaining offspring. How the maternal plant perceives internal growth cues and external stress conditions to alter FG development remains largely unknown. We report that homeostasis of the stress signaling molecule nitric oxide (NO) plays a key role in controlling FG development under both optimal and stress conditions. NO homeostasis is precisely regulated by S-nitrosoglutathione reductase (GSNOR). Prior to fertilization, GSNOR protein is exclusively accumulated in sporophytic tissues and indirectly controls FG development in Arabidopsis (Arabidopsis thaliana). In GSNOR null mutants, NO species accumulated in the degenerating sporophytic nucellus, and auxin efflux into the developing FG was restricted, which inhibited FG development, resulting in reduced fertility. Importantly, restoring GSNOR expression in maternal, but not gametophytic tissues, or increasing auxin efflux substrate significantly increased the proportion of normal FGs and fertility. Furthermore, GSNOR overexpression or added auxin efflux substrate increased fertility under drought and salt stress. These data indicate that NO homeostasis is critical to normal auxin transport and maternal control of FG development, which in turn determine seed yield. Understanding this aspect of fertility control could contribute to mediating yield loss under adverse conditions.

The role of DRP1 mediated mitophagy in HT22 cells apoptosis induced by silica nanoparticles.

Silica nanoparticles (SiNPs) are widely used in the biomedical field and can enter the central nervous system through the blood-brain barrier, causing damage to hippocampal neurons. However, the specific mechanism remains unclear. In this experiment, HT22 cells were selected as the experimental model in vitro, and the survival rate of cells under the action of SiNPs was detected by MTT method, reactive oxygen species (ROS), lactate dehydrogenase (LDH), superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GSH-Px) and adenosine triphosphate (ATP) were tested by the kit, the ultrastructure of the cells was observed by transmission electron microscope, membrane potential (MMP), calcium ion (Ca2+) and apoptosis rate were measured by flow cytometry, and the expressions of mitochondrial functional protein, mitochondrial dynein, mitochondrial autophagy protein as well as apoptosis related protein were detected by Western blot. The results showed that cell survival rate, SOD, CAT, GSH-Px, ATP and MMP gradually decreased with the increase of SiNPs concentration, while intracellular ROS, Ca2+, LDH and apoptosis rate increased with the increase of SiNPs concentration. In total cellular proteins,the expressions of mitochondrial functional proteins VDAC and UCP2 gradually increased, the expression of mitochondrial dynamic related protein DRP1 increased while the expressions of OPA1 and Mfn2 decreased. The expressions of mitophagy related proteins PINK1, Parkin and LC3Ⅱ/LC3Ⅰ increased and P62 gradually decreased, as well as the expressions of apoptosis related proteins Apaf-1, Cleaved-Caspase-3, Caspase-3, Caspase-9, Bax and Cyt-C. In mitochondrial proteins, the expressions of mitochondrial dynamic related proteins DRP1 and p-DRP1 were increased, while the expressions of OPA1 and Mfn2 were decreased. Expressions of mitochondrial autophagy associated proteins PINK1, Parkin, LC3II/LC3I increased, P62 decreased gradually, as well as the expressions of apoptosis related proteins Cleaved-Caspase-3, Caspase-3, and Caspase-9 increased, and Cyt-C expressions decreased. To further demonstrate the role of ROS and DRP1 in HT22 cell apoptosis induced by SiNPs, we selected the ROS inhibitor N-Acetylcysteine (NAC) and Dynamin-related protein 1 (DRP1) inhibitor Mdivi-1. The experimental results indicated that the above effects were remarkably improved after the use of inhibitors, further confirming that SiNPs induce the production of ROS in cells, activate DRP1, cause excessive mitochondrial division, induce mitophagy, destroy mitochondrial function and eventually lead to apoptosis.

HaMYBA-HabHLH1 regulatory complex and HaMYBF fine-tune red flower coloration in the corolla of sunflower (Helianthus annuus L.).

Sunflowers are well-known ornamental plants, while sunflowers with red corolla are rare and the mechanisms underlying red coloration remain unclear. Here, a comprehensive analysis of metabolomics and transcriptomics on flavonoid pathway was performed to investigate the molecular mechanisms underlying the differential color formation between red sunflower Pc103 and two yellow sunflowers (Yr17 and Y35). Targeted metabolomic analysis revealed higher anthocyanin levels but lower flavonol content in Pc103 compared to the yellow cultivars. RNA-sequencing and phylogenetic analysis identified multiple genes involved in the flavonoid pathway, including series of structural genes and three MYB and bHLH genes. Specifically, HaMYBA and HabHLH1 were up-regulated in Pc103, whereas HaMYBF exhibited reduced expression. HaMYBA was found to interact with HabHLH1 in vivo and in vitro, while HaMYBF does not. Transient expression analysis further revealed that HabHLH1 and HaMYBA cooperatively regulate increased expression of dihydroflavonol 4-reductase (DFR), leading to anthocyanin accumulation. On the other hand, ectopic expression of HaMYBF independently modulates flavonol synthase (FLS) expression, but hindered anthocyanin production. Collectively, our findings suggest that the up-regulation of HaMYBA and HabHLH1, as well as the down-regulation of HaMYBF, contribute to the red coloration in Pc103. It offers a theoretical basis for improving sunflower color through genetic engineering.

A highly sensitive flexible capacitive pressure sensor with hierarchical pyramid micro-structured PDMS-based dielectric layer for health monitoring.

Herein, a flexible pressure sensor with high sensitivity was created using a dielectric layer featuring a hierarchical pyramid microstructure, both in simulation and fabrication. The capacitive pressure sensor comprises a hierarchically arranged dielectric layer made of polydimethylsiloxane (PDMS) with pyramid microstructures, positioned between copper electrodes at the top and bottom. The achievement of superior sensing performance is highly contingent upon the thickness of the dielectric layer, as indicated by both empirical findings and finite-element analysis. Specifically, the capacitive pressure sensor, featuring a dielectric layer thickness of 0.5 mm, exhibits a remarkable sensitivity of 0.77 kPa-1 within the pressure range below 1 kPa. It also demonstrates an impressive response time of 55 ms and recovery time of 42 ms, along with a low detection limit of 8 Pa. Furthermore, this sensor showcases exceptional stability and reproducibility with up to 1,000 cycles. Considering its exceptional achievements, the pressure sensor has been effectively utilized for monitoring physiological signals, sign language gestures, and vertical mechanical force exerted on objects. Additionally, a 5 × 5 sensor array was fabricated to accurately and precisely map the shape and position of objects. The pressure sensor with advanced performance shows broad potential in electronic skin applications.

Combining Vis-NIR and NIR Spectral Imaging Techniques with Data Fusion for Rapid and Nondestructive Multi-Quality Detection of Cherry Tomatoes.

Firmness, soluble solid content (SSC) and titratable acidity (TA) are characteristic substances for evaluating the quality of cherry tomatoes. In this paper, a hyper spectral imaging (HSI) system using visible/near-infrared (Vis-NIR) and near-infrared (NIR) was proposed to detect the key qualities of cherry tomatoes. The effects of individual spectral information and fused spectral information in the detection of different qualities were compared for firmness, SSC and TA of cherry tomatoes. Data layer fusion combined with multiple machine learning methods including principal component regression (PCR), partial least squares regression (PLSR), support vector regression (SVR) and back propagation neural network (BP) is used for model training. The results show that for firmness, SSC and TA, the determination coefficient R2 of the multi-quality prediction model established by Vis-NIR spectra is higher than that of NIR spectra. The R2 of the best model obtained by SSC and TA fusion band is greater than 0.9, and that of the best model obtained by the firmness fusion band is greater than 0.85. It is better to use the spectral bands after information fusion for nondestructive quality detection of cherry tomatoes. This study shows that hyperspectral imaging technology can be used for the nondestructive detection of multiple qualities of cherry tomatoes, and the method based on the fusion of two spectra has a better prediction effect for the rapid detection of multiple qualities of cherry tomatoes compared with a single spectrum. This study can provide certain technical support for the rapid nondestructive detection of multiple qualities in other melons and fruits.

Light-Induced TaHY5-7A and TaBBX-3B Physically Interact to Promote PURPLE PERICARP-MYB 1 Expression in Purple-Grained Wheat.

Purple-grained wheat (Triticum aestivum L.) is an important germplasm source in crop breeding. Anthocyanin biosynthesis in the pericarps of purple-grained wheat is largely light-dependent; however, the regulatory mechanisms underlying light-induced anthocyanin accumulation in the wheat pericarp remain unknown. Here we determined that anthocyanins rapidly accumulate in the pericarps of the purple-grained wheat cultivar Heixiaomai 76 (H76) at 16 days after pollination under light treatment. Using transcriptome sequencing, differential gene expression analysis, and phylogenetic analysis, we identified two key genes involved in light signaling in wheat: ELONGATED HYPOCOTYL 5-7A (TaHY5-7A) and B-BOX-3B (TaBBX-3B). TaHY5-7A and TaBBX-3B were highly expressed in purple-grained wheat pericarps. The heterologous expression of TaHY5-7A partially restored the phenotype of the Arabidopsis (Arabidopsis thaliana) hy5 mutant, resulting in increased anthocyanin accumulation and a shortened hypocotyl. The heterologous expression of TaBBX-3B in wild-type Arabidopsis had similar effects. TaHY5-7A and TaBBX-3B were nucleus-localized, consistent with a function in transcription regulation. However, TaHY5-7A, which lacks a transactivation domain, was not sufficient to activate the expression of PURPLE PERICARP-MYB 1 (TaPpm1), the key anthocyanin biosynthesis regulator in purple pericarps of wheat. TaHY5-7A physically interacted with TaBBX-3B in yeast two-hybrid and bimolecular fluorescence complementation assays. Additionally, TaHY5-7A, together with TaBBX-3B, greatly enhanced the promoter activity of TaPpm1 in a dual luciferase assay. Overall, our results suggest that TaHY5-7A and TaBBX-3B collaboratively activate TaPpm1 expression to promote light-induced anthocyanin biosynthesis in purple-pericarp wheat.

Ensemble water quality forecasting based on decomposition, sub-model selection, and adaptive interval.

The prediction of effluent quality for wastewater treatment plants (WWTPs) has caused widespread concern due to its essential role in ensuring water quality standards and reducing energy consumption. However, the complex nonlinearity of WWTPs leads to difficulties in forecasting and less attention to forecast uncertainty. A novel ensemble water quality forecasting (EWQF) system is proposed that incorporates data preprocessing, point prediction and interval prediction. The system provides an accurate prediction of effluent quality and analyses this uncertainty, for enabling feed-forward control of WWTPs. Specifically, the original water quality data is decomposed into subsequences containing more information and less noise based on improved variational modal decomposition (IVMD). The optimal sub-model for each sub-series is selected from six prediction models based on the sub-model selection strategy, and the point prediction results for water quality are obtained by combining the prediction results of the sub-models. Robust and reliable prediction interval construction based on adaptive kernel density estimation. The results demonstrate that the EWQF achieves optimal point prediction results (R2 = 0.955). The EWQF interval prediction achieves the optimal coverage width criterion (CWC) for different confidence intervals and decision objectives. These results demonstrate that EWQF systems can perform excellent point and interval prediction.

VDAC1 Protein Regulation of Oxidative Damage and Mitochondrial Dysfunction-Mediated Cytotoxicity by Silica Nanoparticles in SH-SY5Y Cells.

Silica nanoparticles (SiNPs) have been widely used in industry, electronics, and pharmaceutical industries. In addition, it is also widely used in medicine, tumor treatment and diagnosis, as well as other biomedical and biotechnology fields. The opportunities for people to contact SiNPs through iatrogenic, occupational, and environmental exposures are gradually increasing. The damage and biological effects of SiNPs on the nervous system have attracted widespread attention in the field of toxicology. Central nerve cells are rich in mitochondria. It is suggested that the effects of SiNPs on mitochondrial damage of nerve cells may involve the maintenance of neuronal membrane potential, the synthesis and operation of neurotransmitters, and the transmission of nerve pulses, and so on. We established an experimental model of SH-SY5Y cells to detect the cell survival rate, apoptosis, changes of reactive oxygen species and mitochondrial membrane potential, and the expression of mitochondrial function-related enzymes and proteins, so as to reveal the possible mechanism of SiNPs on neuronal mitochondrial damage. It was found that SiNPs could cause oxidative damage to cells and mitochondria, destroy some normal functions of mitochondria, and induce apoptosis in SH-SY5Y cells. The voltage-dependent anion channel 1(VDAC1) protein inhibitor DIDS could effectively reduce intracellular oxidative stress, such as the reduction of ROS content, and could also usefully restore some functional proteins of mitochondria to normal levels. The inhibition of VDAC1 protein may play an important role in the oxidative damage and dysfunction of neuronal mitochondria induced by SiNPs.

Modeling of and Experimenting with Concentric Tube Robots: Considering Clearance, Friction and Torsion.

Concentric tube robots (CTRs) are a promising prospect for minimally invasive surgery due to their inherent compliance and ability to navigate in constrained environments. Existing mechanics-based kinematic models typically neglect friction, clearance, and torsion between each pair of contacting tubes, leading to large positioning errors in medical applications. In this paper, an improved kinematic modeling method is developed. The effect of clearance on tip position during concentric tube assembly is compensated by the database method. The new kinematic model is mechanic-based, and the impact of friction moment and torsion on tubes is considered. Integrating the infinitesimal torsion of the concentric tube robots eliminates the errors caused by the interaction force between the tubes. A prototype is built, and several experiments with kinematic models are designed. The results indicate that the error of tube rotations is less than 2 mm. The maximum error of the feeding experiment does not exceed 0.4 mm. The error of the new modeling method is lower than that of the previous kinematic model. This paper has substantial implications for the high-precision and real-time control of concentric tube robots.

Multi-Attention Segmentation Networks Combined with the Sobel Operator for Medical Images.

Medical images are used as an important basis for diagnosing diseases, among which CT images are seen as an important tool for diagnosing lung lesions. However, manual segmentation of infected areas in CT images is time-consuming and laborious. With its excellent feature extraction capabilities, a deep learning-based method has been widely used for automatic lesion segmentation of COVID-19 CT images. However, the segmentation accuracy of these methods is still limited. To effectively quantify the severity of lung infections, we propose a Sobel operator combined with multi-attention networks for COVID-19 lesion segmentation (SMA-Net). In our SMA-Net method, an edge feature fusion module uses the Sobel operator to add edge detail information to the input image. To guide the network to focus on key regions, SMA-Net introduces a self-attentive channel attention mechanism and a spatial linear attention mechanism. In addition, the Tversky loss function is adopted for the segmentation network for small lesions. Comparative experiments on COVID-19 public datasets show that the average Dice similarity coefficient (DSC) and joint intersection over union (IOU) of the proposed SMA-Net model are 86.1% and 77.8%, respectively, which are better than those in most existing segmentation networks.

MicroRNA156 conditions auxin sensitivity to enable growth plasticity in response to environmental changes in Arabidopsis.

MicroRNAs (miRNAs) play diverse roles in plant development, but whether and how miRNAs participate in thermomorphogenesis remain ambiguous. Here we show that HYPONASTIC LEAVES 1 (HYL1)-a key component of miRNA biogenesis-acts downstream of the thermal regulator PHYTOCHROME INTERACTING FACTOR 4 in the temperature-dependent plasticity of hypocotyl growth in Arabidopsis. A hyl1-2 suppressor screen identified a dominant dicer-like1 allele that rescues hyl1-2's defects in miRNA biogenesis and thermoresponsive hypocotyl elongation. Genome-wide miRNA and transcriptome analysis revealed microRNA156 (miR156) and its target SQUAMOSA PROMOTER-BINDING-PROTEIN-LIKE 9 (SPL9) to be critical regulators of thermomorphogenesis. Surprisingly, perturbation of the miR156/SPL9 module disengages seedling responsiveness to warm temperatures by impeding auxin sensitivity. Moreover, miR156-dependent auxin sensitivity also operates in the shade avoidance response at lower temperatures. Thus, these results unveil the miR156/SPL9 module as a previously uncharacterized genetic circuit that enables plant growth plasticity in response to environmental temperature and light changes.

QTL Mapping for Important Agronomic Traits Using a Wheat55K SNP Array-Based Genetic Map in Tetraploid Wheat.

Wheat yield is highly correlated with plant height, heading date, spike characteristics, and kernel traits. In this study, we used the wheat55K single nucleotide polymorphism array to genotype a recombinant inbred line population of 165 lines constructed by crossing two tetraploid wheat materials, Icaro and Y4. A genetic linkage map with a total length of 6244.51 cM was constructed, covering 14 chromosomes of tetraploid wheat. QTLs for 12 important agronomic traits, including plant height (PH), heading date (HD), awn color (AC), spike-branching (SB), and related traits of spike and kernel, were mapped in multiple environments, while combined QTL-by-environment interactions and epistatic effects were analyzed for each trait. A total of 52 major or stable QTLs were identified, among which may be some novel loci controlling PH, SB, and kernel length-width ratio (LWR), etc., with LOD values ranging from 2.51 to 54.49, thereby explaining 2.40-66.27% of the phenotypic variation. Based on the 'China Spring' and durum wheat reference genome annotations, candidate genes were predicted for four stable QTLs, QPH.nwafu-2B.2 (165.67-166.99 cM), QAC.nwafu-3A.1 (419.89-420.52 cM), QAC.nwafu-4A.1 (424.31-447.4 cM), and QLWR.nwafu-7A.1 (166.66-175.46 cM). Thirty-one QTL clusters and 44 segregation distortion regions were also detected, and 38 and 18 major or stable QTLs were included in these clusters and segregation distortion regions, respectively. These results provide QTLs with breeding application potential in tetraploid wheat that broadens the genetic basis of important agronomic traits such as PH, HD, AC, SB, etc., and benefits wheat breeding.

A novel deep learning ensemble model based on two-stage feature selection and intelligent optimization for water quality prediction.

Accurate prediction of effluent total nitrogen (E-TN) can assist in feed-forward control of wastewater treatment plants (WWTPs) to ensure effluent compliance with standards while reducing energy consumption. However, multivariate time series prediction of E-TN is a challenge due to the complex nonlinearity of WWTPs. This paper proposes a novel prediction framework that combines a two-stage feature selection model, the Golden Jackal Optimization (GJO) algorithm, and a hybrid deep learning model, CNN-LSTM-TCN (CLT), aiming to effectively capture the nonlinear relationships of multivariate time series in WWTPs. Specifically, convolutional neural network (CNN), long short-term memory (LSTM), and temporal convolutional network (TCN) combined to build a hybrid deep learning model CNN-LSTM-TCN (CLT). A two-stage feature selection method is utilized to determine the optimal feature subset to reduce the complexity and improve the accuracy of the prediction model, and then, the feature subset is input into the CLT. The hyperparameters of the CLT are optimized using GJO to further improve the prediction performance. Experiments indicate that the two-stage feature selection model learns the optimal feature subset to predict best, and the GJO-CLT achieves the best performance for different backtracking windows and prediction steps. These results demonstrate that the prediction system excels in the task of multivariate water quality time series prediction of WWTPs.

A bilevel data-driven method for sewer deposit prediction under uncertainty.

Deposit accumulation is one of the predominant causes of sewer blockage and overflow. Nevertheless, the traditional detection methods are costly and time-consuming, and the accuracy of the mathematical models for deposit prediction is usually affected by some uncertain factors (e.g., pipe properties and flow velocity of water). This paper proposes a framework of global sensitivity analysis (GSA) to identify the most sensitive indicators for sewer deposit prediction by (i) developing a data-driven bilevel (i.e., catchment level and segment level) model to map the relation between input and output indicators and (ii) employing three different GSA methods, namely, the Morris method, Sobol method, and Borgonovo index method to identify the indicators as important or unimportant (insensitive). The results show that the likelihood of combined sewer overflow occurrences (LCSOO), pipe age (PA), and pipe material (PM) are influential parameters for the thickness of deposits. Here, we pay close attention to the most influential parameters, which can help improve forecast prediction accuracy.

Feasibility of Enhanced Recovery After Surgery Protocols Implemented Perioperatively in Endoscopic Submucosal Dissection for Early Gastric Cancer: A Single-Center Retrospective Study.

Background: Endoscopic submucosal dissection (ESD) for early gastric cancer (EGC) has advantages over traditional radical gastrectomy. We investigated whether enhanced recovery after surgery (ERAS) protocols are appropriate in the ESD perioperative period. Materials and Methods: We screened 129 consecutive patients, and 12 were excluded. All study patients underwent ESD for EGC. Of the 117 included patients, 57 received traditional perioperative care between January 2017 and December 2018, and 60 patients received perioperative care according to ERAS protocols between January 2019 and September 2020. The primary study endpoint was ESD-related complications. Secondary endpoints included the following postoperative parameters: anal exhaust time, incidence of nausea or vomiting, length of hospitalization, fever rate, abdominal pain on the visual analog scale (VAS), and reported perioperative satisfaction. Results: Complications were comparable between the 2 groups. In the ERAS group, no patients experienced delayed bleeding or perforation. One traditional group patient bled, and one perforated. Postoperative anal exhaust time, nausea or vomiting incidence, hospitalization, fever rate, and VAS pain scores were significantly lower, and perioperative satisfaction rate was significantly higher in the ERAS group. Conclusions: ERAS protocols are both feasible and safe for patients undergoing ESD. ERAS protocols enhance the advantages of ESD for EGC without increasing complications.