OccupancyDETR: Making Semantic Scene Completion as Straightforward as Object Detection

Visual-based 3D semantic occupancy perception (also known as 3D semantic scene completion) is a new perception paradigm for robotic applications like autonomous driving. Compared with Bird's Eye View (BEV) perception, it extends the vertical dimension, significantly enhancing the ability of robots to understand their surroundings. However, due to this very reason, the computational demand for current 3D semantic occupancy perception methods generally surpasses that of BEV perception methods and 2D perception methods. We propose a novel 3D semantic occupancy perception method, OccupancyDETR, which consists of a DETR-like object detection module and a 3D occupancy decoder module. The integration of object detection simplifies our method structurally - instead of predicting the semantics of each voxels, it identifies objects in the scene and their respective 3D occupancy grids. This speeds up our method, reduces required resources, and leverages object detection algorithm, giving our approach notable performance on small objects. We demonstrate the effectiveness of our proposed method on the SemanticKITTI dataset, showcasing an mIoU of 23 and a processing speed of 6 frames per second, thereby presenting a promising solution for real-time 3D semantic scene completion

A Comparison of Postoperative Early Enteral Nutrition with Delayed Enteral Nutrition in Patients with Esophageal Cancer

We examined esophageal cancer patients who received enteral nutrition (EN) to evaluate the validity of early EN compared to delayed EN, and to determine the appropriate time to start EN. A total of 208 esophagectomy patients who received EN postoperatively were divided into three groups (Group 1, 2 and 3) based on whether they received EN within 48 h, 48 h–72 h or more than 72 h, respectively. The postoperative complications, length of hospital stay (LOH), days for first fecal passage, cost of hospitalization, and the difference in serum albumin values between pre-operation and post-operation were all recorded. The statistical analyses were performed using the t-test, the Mann-Whitney U test and the chi square test. Statistical significance was defined as p < 0.05. Group 1 had the lowest thoracic drainage volume, the earliest first fecal passage, and the lowest LOH and hospitalization expenses of the three groups. The incidence of pneumonia was by far the highest in Group 3 (p = 0.019). Finally, all the postoperative outcomes of nutritional conditions were the worst by a significant margin in Group 3. It is therefore safe and valid to start early enteral nutrition within 48 h for postoperative esophageal cancer patients

TERT mutations correlate with higher TMB value and unique tumor microenvironment and may be a potential biomarker for anti‐CTLA4 treatment

Abstract Immune checkpoint inhibitors (ICIs) have recently changed therapeutic paradigms for patients across multiple cancer types. However, current biomarkers cannot accurately predict responses to ICIs. Telomerase reverse transcriptase (TERT) mutations lead to an aberrant upregulation of TERT expression, and ultimately allow telomere maintenance, thus supporting immortalization of cancer cells. This study aimed to investigate whether the TERT mutation is a potential predictor of ICI treatment across all cancer types. TERT mutations positively correlated with a higher tumor mutational burden (TMB) value, neoantigen load, and tumor purity. Lymphocyte infiltration, macrophage regulation, interferon‐gamma (IFN‐γ) response, and transforming growth factor‐β (TGF‐β) response which was representative immune‐expression signatures, all had higher signature scores in the TERT mutation group. Activated CD4 T cell, naïve B cell, activated dendritic cell, M0 macrophage, M1 macrophage, neutrophil, resting NK cell, and plasma cells all had relatively higher immune scores in the TERT mutation group, whereas Th series cells, memory B cell, resting mast cells, monocytes, and activated NK cells had lower immune scores. Notably, in the subgroup analysis of monotherapy and combination ICI treatment, only in the anti‐cytotoxic‐T‐lymphocyte‐associated antigen 4 (anti‐CTLA4) group, patients with TERT mutations had a better prognosis, especially for melanoma. Therefore, TERT mutations were closely related to a higher TMB value and unique tumor microenvironment, which may be the reason that TERT mutations may be a potential biomarker for anti‐CTLA4 treatment

ADST: Forecasting Metro Flow Using Attention-Based Deep Spatial-Temporal Networks with Multi-Task Learning

Passenger flow prediction has drawn increasing attention in the deep learning research field due to its great importance in traffic management and public safety. The major challenge of this essential task lies in multiple spatiotemporal correlations that exhibit complex non-linear correlations. Although both the spatial and temporal perspectives have been considered in modeling, most existing works have ignored complex temporal correlations or underlying spatial similarity. In this paper, we identify the unique spatiotemporal correlation of urban metro flow, and propose an attention-based deep spatiotemporal network with multi-task learning (ADST-Net) at a citywide level to predict the future flow from historical observations. ADST-Net uses three independent channels with the same structure to model the recent, daily-periodic and weekly-periodic complicated spatiotemporal correlations, respectively. Specifically, each channel uses the framework of residual networks, the rectified block and the multi-scale convolutions to mine spatiotemporal correlations. The residual networks can effectively overcome the gradient vanishing problem. The rectified block adopts an attentional mechanism to automatically reweigh measurements at different time intervals, and the multi-scale convolutions are used to extract explicit spatial relationships. ADST-Net also introduces an external embedding mechanism to extract the influence of external factors on flow prediction, such as weather conditions. Furthermore, we enforce multi-task learning to utilize transition passenger flow volume prediction as an auxiliary task during the training process for generalization. Through this model, we can not only capture the steady trend, but also the sudden changes of passenger flow. Extensive experimental results on two real-world traffic flow datasets demonstrate the obvious improvement and superior performance of our proposed algorithm compared with state-of-the-art baselines

The changing face of hepatitis C: Recent advances on HCV inhibitors targeting NS5A

Current treatment for HCV infections consists of approved direct acting antivirals (DAAs), viz. the protease inhibitors (boceprevir, telaprevir, and simeprevir), NS5B polymerase inhibitors (sofosbuvir) and NS5A inhibitor (ledipasvir) in combination with pegylated interferon α and ribavirin). These treatments have made a great improvement in the treatment of chronic HCV infections in recent years, but their adverse side effects, emergence of resistant mutants, high cost, and increased pill burden have limited their clinical use. Recently, with the increasing knowledge in understanding the HCV life cycle, more targets have been recognized. NS5A protein plays a critical role in assembly of infectious HCV particles and offering potential for HCV therapies. Therefore, discovery and development of novel DAAs targeting NS5A with novel mechanisms of action, is of great necessity to improve the quality of existing HCV treatments. In the present review, we discuss recent advances with NS5A inhibitors with potent anti-HCV activity, and the potential for the development of HCV NS5A inhibitors to combat HCV infections.status: publishe

A 5-Gene Signature Is Closely Related to Tumor Immune Microenvironment and Predicts the Prognosis of Patients with Non-Small Cell Lung Cancer

Purpose. Establishing prognostic gene signature to predict clinical outcomes and guide individualized adjuvant therapy is necessary. Here, we aim to establish the prognostic efficacy of a gene signature that is closely related to tumor immune microenvironment (TIME). Methods and Results. There are 13,035 gene expression profiles from 130 tumor samples of the non-small cell lung cancer (NSCLC) in the data set GSE103584. A 5-gene signature was identified by using univariate survival analysis and Least Absolute Shrinkage and Selection Operator (LASSO) to build risk models. Then, we used the CIBERSORT method to quantify the relative levels of different immune cell types in complex gene expression mixtures. It was found that the ratio of dendritic cells (DCs) activated and mast cells (MCs) resting in the low-risk group was higher than that in the high-risk group, and the difference was statistically significant (P<0.001 and P=0.03). Pathway enrichment results which were obtained by performing Gene Set Variation Analysis (GSVA) showed that the high-risk group identified by the 5-gene signature had metastatic-related gene expression, resulting in lower survival rates. Kaplan–Meier survival results showed that patients of the high-risk group had shorter disease-free survival (DFS) and overall survival (OS) than those of the low-risk group in the training set (P=0.0012 and P<0.001). The sensitivity and specificity of the gene signature were better and more sensitive to prognosis than TNM (tumor/lymph node/metastasis) staging, in spite of being not statistically significant (P=0.154). Furthermore, Kaplan–Meier survival showed that patients of the high-risk group had shorter OS and PFS than those of the low-risk group (P=0.0035, P<0.001, and P<0.001) in the validating set (GSE31210, GSE41271, and TCGA). At last, univariate and multivariate Cox proportional hazard regression analyses were used to evaluate independent prognostic factors associated with survival, and the gene signature, lymphovascular invasion, pleural invasion, chemotherapy, and radiation were employed as covariates. The 5-gene signature was identified as an independent predictor of patient survival in the presence of clinical parameters in univariate and multivariate analyses (P<0.001) (hazard ratio (HR): 3.93, 95% confidence interval CI (2.17–7.1), P=0.001, (HR) 5.18, 95% CI (2.6995–9.945), P<0.001), respectively. Our 5-gene signature was also related to EGFR mutations (P=0.0111), and EGFR mutations were mainly enriched in low-risk group, indicating that EGFR mutations affect the survival rate of patients. Conclusion. The 5-gene signature is a powerful and independent predictor that could predict the prognosis of NSCLC patients. In addition, our gene signature is correlated with TIME parameters, such as DCs activated and MCs resting. Our findings suggest that the 5-gene signature closely related to TIME could predict the prognosis of NSCLC patients and provide some reference for immunotherapy

Bamboo weaving inspired design of a carbonaceous electrode with exceptionally high volumetric capacity

A highly densified electrode material is desirable to achieve large volumetric capacity. However, pores acting as ion transport channels are critical for high utilization of active material. Achieving a balance between high volume density and pore utilization remains a challenge particularly for hollow materials. Herein, capillary force is employed to convert hollow fibers to a bamboo-weaving-like flexible electrode (BWFE), in which the shrinkage of hollow space results in high compactness of the electrode. The volume of the electrode can be decreased by 96% without sacrificing the gravimetric capacity. Importantly, the conductivity of BWFE after thermal treatment can reach up to 50,500 S/m which exceeds that for most other carbon materials. Detailed mechanical analysis reveals that, due to the strong interaction between nanoribbons, Young's modulus of the electrode increases by 105 times. After SnO2 active materials is impregnated, the BWFE/SnO2 electrode exhibits an exceptionally ultrahigh volumetric capacity of 2000 mAh/cm3.Submitted/Accepted versionThis work was supported by the High-Quality Development Project of the Ministry of Industry and Information Technology of the People’s Republic of China (TC210H041), the Hundred Talents program, the National Natural Science Foundation of China (Grant No. 51872304), and the Ningbo S&T Innovation 2025 Major Special Program (2018B10024; 2019B10(17); 2020Z101)

Mitigation Mechanism of Membrane Fouling in MnFeOx Functionalized Ceramic Membrane Catalyzed Ozonation Process for Treating Natural Surface Water

In order to efficiently remove NOMs in natural surface water and alleviate membrane pollution at the same time, a flat microfiltration ceramic membrane (CM) was modified with MnFeOX (Mn-Fe-CM), and a coagulation&ndash;precipitation&ndash;sand filtration pretreatment coupled with an in situ ozonation-ceramic membrane filtration system (Pretreatment/O3/Mn-Fe-CM) was constructed for this study. The results show that the removal rates of dissolved organic carbon (DOC), specific ultraviolet absorption (SUVA) and NH4+-N by the Pretreatment/O3/Mn-Fe-CM system were 51.1%, 67.9% and 65.71%, respectively. Macromolecular organic compounds such as aromatic proteins and soluble microbial products (SMPs) were also effectively removed. The working time of the membrane was about twice that in the Pretreatment/CM system without the in situ ozone oxidation, which was measured by the change in transmembrane pressure, proving that membrane fouling was significantly reduced. Finally, based on the SEM, AFM and other characterization results, it was concluded that the main mitigation mechanisms of membrane fouling in the Pretreatment/O3/Mn-Fe-CM system was as follows: (1) pretreatment could remove part of DOC and SUVA to reduce their subsequent entrapment on a membrane surface; (2) a certain amount of shear force generated by O3 aeration can reduce the adhesion of pollutants; (3) the loaded MnFeOX with a higher catalytic ability produced a smoother active layer on the surface of the ceramic membrane, which was conducive in reducing the contact among Mn-Fe-CM, O3 and pollutants, thus increasing the proportion of reversible pollution and further reducing the adhesion of pollutants; (4) Mn-Fe-CM catalyzed O3 to produce &middot;OH to degrade the pollutants adsorbed on the membrane surface into smaller molecular organic matter, which enabled them pass through the membrane pores, reducing their accumulation on the membrane surface

Mitigation Mechanism of Membrane Fouling in MnFeOx Functionalized Ceramic Membrane Catalyzed Ozonation Process for Treating Natural Surface Water

In order to efficiently remove NOMs in natural surface water and alleviate membrane pollution at the same time, a flat microfiltration ceramic membrane (CM) was modified with MnFeOX (Mn-Fe-CM), and a coagulation–precipitation–sand filtration pretreatment coupled with an in situ ozonation-ceramic membrane filtration system (Pretreatment/O3/Mn-Fe-CM) was constructed for this study. The results show that the removal rates of dissolved organic carbon (DOC), specific ultraviolet absorption (SUVA) and NH4+-N by the Pretreatment/O3/Mn-Fe-CM system were 51.1%, 67.9% and 65.71%, respectively. Macromolecular organic compounds such as aromatic proteins and soluble microbial products (SMPs) were also effectively removed. The working time of the membrane was about twice that in the Pretreatment/CM system without the in situ ozone oxidation, which was measured by the change in transmembrane pressure, proving that membrane fouling was significantly reduced. Finally, based on the SEM, AFM and other characterization results, it was concluded that the main mitigation mechanisms of membrane fouling in the Pretreatment/O3/Mn-Fe-CM system was as follows: (1) pretreatment could remove part of DOC and SUVA to reduce their subsequent entrapment on a membrane surface; (2) a certain amount of shear force generated by O3 aeration can reduce the adhesion of pollutants; (3) the loaded MnFeOX with a higher catalytic ability produced a smoother active layer on the surface of the ceramic membrane, which was conducive in reducing the contact among Mn-Fe-CM, O3 and pollutants, thus increasing the proportion of reversible pollution and further reducing the adhesion of pollutants; (4) Mn-Fe-CM catalyzed O3 to produce ·OH to degrade the pollutants adsorbed on the membrane surface into smaller molecular organic matter, which enabled them pass through the membrane pores, reducing their accumulation on the membrane surface