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Inferential modeling has been of significance for modern manufacturing in estimating the quality-related process variables. As an effective inferential model, probabilistic slow feature analysis (PSFA) has gained attention in regression tasks to interpret dynamic properties with a slowness preference. However, PSFA is often challenged by the nonlinear sequential data due to its linear state-space structure. In this study, a new nonlinear extension of PSFA is proposed under the deep learning framework to enhance the dynamic feature extraction with limited labels, incorporating variational inference and Monte Carlo inference to derive the objective function. The proposed model considers the relevance of inputs with outputs as the input weights to upgrade prediction performance. The proposed model is verified through an industrial hydrocracking process to predict diesel yield with missing labels ranged from 0% to 50%, and the root mean squared error is reduced by at least 8.78% compared to PSFA.

The increasing penetration level of photovoltaic (PV) systems in low-voltage networks causes voltage regulation issues. This brief proposes a new voltage regulation strategy utilizing distributed battery energy storage systems (BESSs) while incorporating the inevitable communication delays. The proposed strategy ensures that the voltage regulation burden is appropriately shared among all involved BESSs in the network. The effects of communication delays on the performance of the proposed strategy are analyzed and an admissible delay bound is established. Case studies are conducted to verify the effectiveness of the proposed strategy.

The potential advantage of laparoscopic gastrectomy (LG) compared with open gastrectomy (OG) for serosa-invasive (pT4a) Siewert type II and III adenocarcinoma of the esophagogastric junction (AEG) remains uncertain. Thus, the purpose of this study was to investigate the short- and long-term outcomes of LG compared to OG for pT4a Siewert type II/III AEG cancers. We retrospectively evaluated 283 patients with pathological confirmed T4a Siewert type II and type III AEG who underwent LG or OG in our center between January 2004 and September 2015. The short- and long-term outcomes were compared between the groups using a 1:1 matched propensity score matching method (PSM). The LG group had a longer operation time, less estimated blood loss, less time to first flatus, less time to start liquid diet, less time to first ambulation, and shorter length of incision than the OG group. The conversion rates were 5.4% in the LG groups. There was no significant difference in the overall complication rate between the LG and OG groups. The 5-year overall survival (OS) and the 5-year disease-free survival (DFS) were comparable between the LG and OG groups (35.4% vs 32.1%, p = 0.541; 34.1% vs 31.0%, p = 0.523, respectively). There was no significant difference in the recurrence rate and pattern between the LG and OG groups. Laparoscopic gastrectomy is associated with better short-term outcomes and similar long-term outcomes for pT4a Siewert type II/III AEG. This study reveals that LG could be a safe and feasible option for pT4a Siewert type II/III AEG compared to OG.

Background. It has been shown that low-density lipoprotein receptor-related protein 1B (LRP1B) mutations correlate with tumor mutation burden (TMB) and prognosis in patients with melanoma and non-small-cell lung cancer, while the relationship between LRP1B mutations and TMB in gastric cancer needs further study. This study is aimed at exploring the relationship between LRP1B mutations and TMB in gastric cancer. Methods. Mutation frequency profiles of the genes in patients with gastric cancer in TCGA-STAD dataset were analyzed by bioinformatics analysis. The relationship among LRP1B mutations, TMB, and patient clinical features in gastric cancer was investigated by the chi-square test. The TMB prediction capacity based on LRP1B mutation status was evaluated by ROC curves. Results. LRP1B is one of the top 10 genes with high gene mutation frequency in gastric cancer. The mutation status of LRP1B in gastric cancer patients was significantly correlated with age and TP53 and MUC16 mutation status. The result of ROC curve analysis revealed that the mutation status of LRP1B could be considered as an indicator of the degree of TMB in patients with gastric cancer. Conclusion. This study presented the relationship between TMB and LRP1B mutations in gastric cancer, providing a novel perspective for gastric cancer prognosis and therapy.

Background GPRIN1 may be a novel tumor regulator, but its role and mechanism in tumors are still unclear. Methods First, a pan‐cancer correlation analysis was conducted on the expression and prognosis of GPRIN1 based on the data downloaded from The Cancer Genome Atlas (TCGA) database. Second, the Starbase database was used to predict the upstream miRNAs and lncRNAs of GPRIN1, and the expression analysis, survival analysis, and correlation analysis were performed to screen the microRNA (miRNAs)/long non‐coding RNAs (lncRNAs) that had a correlation with kidney renal papillary cell carcinoma (KIRP) or lung adenocarcinoma (LUAD). Third, the CIBERSORT algorithm was employed to calculate the proportion of various types of immune cells, and then the R packages were used for evaluating the relation between GPRIN1 expression and tumor immune cell infiltration as well as between GPRIN1 and the immune cell biomarker. Finally, the correlation analysis was made on GPRIN1 and immune checkpoints (CD274, CTLA4, and PDCD1). Results The pan‐cancer analysis suggested that GPRIN1 was up‐expressed in KIRP and LUAD, and it correlated with poor prognosis. LINC00894/MMP25‐AS1/SNHG1/LINC02298/MIR193BHG‐miR‐140‐3p was likely to be the most promising upstream regulation pathway of GPRIN1. Upexpression of LINC00894/MMP25‐AS1/SNHG1/LINC02298/MIR193BHG and downexpression of miR‐140‐3p were found relevant with poor outcomes of KIRP and LUAD. GPRIN1 expression was significantly correlated with tumor immune cell infiltration, immune cell biomarkers, and immune checkpoints. Conclusions The competitive endogenous (ceRNA) of miR‐140‐3p‐GPRIN1 axis and its upstream lncRNAs are closely related to KIRP and LUAD, and might affect the prognosis and therapeutic effect of KIRP and LUAD., GPRIN1 is an important prognostic marker for KIRP and LUAD. ncRNA (LINC00894/MMP25‐AS1/SNHG1/LINC02298/MIR193BHG)‐mediated high expression of GPRIN1 correlates with poor prognosis and tumor immune infiltration of KIPR and LUAD.

As a convenient and efficient public transport system, high speed railway (HSR) was rapidly deployed in China. Since the fifth generation (5G) mobile communication system is commercially applied, it is necessary for mobile terminals antennas to cover multiple operating bands to be compatible with various communication systems. Here a HSR-mounted broadband and high-gain monopole antenna is proposed. By using the meander technology and introducing the tapered structure, the proposed antenna operates over a bandwidth of 694-960 MHz and 1350-5975 MHz (VSWR

Objectives Acute lung injury (ALI) is a pulmonary manifestation of an acute systemic inflammatory response, which is associated with high morbidity and mortality. Accordingly, from the perspective of treating ALI, it is important to identify effective agents and elucidate the underlying modulatory mechanisms. β-Caryophyllene (BCP) is a naturally occurring bicyclic sesquiterpene that has anti-cancer and anti-inflammatory activities. However, the effects of BCP on ALI have yet to be ascertained. Methods ALI was induced intratracheally, injected with 5 mg/kg LPS and treated with BCP. The bone marrow-derived macrophages (BMDMs) were obtained and cultured then challenged with 100 ng/ml LPS for 4 h, with or without BCP pre-treatment for 30 min. Key findings BCP significantly ameliorates LPS-induced mouse ALI, which is related to an alleviation of neutrophil infiltration and reduction in cytokine production. In vitro, BCP was found to reduce the expression of interleukin-6, interleukin-1β and tumour necrosis factor-α, and suppresses the MAPK signalling pathway in BMDMs, which is associated with the inhibition of TAK1 phosphorylation and an enhancement of MKP-1 expression. Conclusions Our data indicate that BCP protects against inflammatory responses and is a potential therapeutic agent for the treatment of LPS-induced acute lung injury.

Background Total gastrectomy for carcinoma in the remnant stomach (CRS) remains a technically demanding procedure. Whether robotic surgery is superior, equal, or inferior to laparoscopic surgery in patients with CRS is unclear. This study was designed to compare the efficacy and safety of robotic total gastrectomy (RTG) and laparoscopic total gastrectomy (LTG) for the treatment of CRS. Methods In this cohort study, we retrospectively analysed the data from patients who underwent RTG or LTG for CRS at Southwest Hospital (Chongqing, China) between May 2006 and October 2019. The surgical outcomes, post-operative complications, and survival outcomes between the two groups were compared. Results Compared with LTG, RTG was associated with similar effective operation time (272.0 vs 297.9 min, P = 0.170), higher total costs (105,967.2 vs 81,629.5 RMB, P 0.05). The 3-year disease-free survival and 3-year overall survival rates were comparable between the two groups (65.5% vs 57.5%, P = 0.918; 69.0% vs 60.0%, P = 0.850, respectively). Conclusions RTG is a safe and feasible procedure for the treatment of CRS and could serve as an optimal treatment for CRS.

Background Whether laparoscopic gastrectomy is suitable for patients with serosa-invasive gastric cancer remains controversial. We performed this study to evaluate the short- and long-term outcomes after laparoscopic gastrectomy compared with after open gastrectomy. Methods We retrospectively analyzed 906 consecutive patients with serosa-invasive gastric cancer from January 2004 to December 2014 in our center, who underwent laparoscopic gastrectomy or open gastrectomy with D2 lymphadenectomy. After propensity score matching, 334 patients were included in each group. Surgical conditions and short- and long-term results were compared. Results Laparoscopic gastrectomy was associated with less estimated blood loss and longer operation time, while the number of harvested lymph nodes was not significantly different between laparoscopic gastrectomy and open gastrectomy. Patients who underwent laparoscopic gastrectomy had an earlier time to first flatus, first diet, and first ambulation and were discharged earlier. Overall and pulmonary postoperative complication rates were lower in the laparoscopic gastrectomy group. With a minimum follow-up of 60 months, the 5-year overall survival was 39.3% in the laparoscopic gastrectomy group and 34.3% in the open gastrectomy group, and the 5-year disease-free survival was 36.4% in the laparoscopic gastrectomy group and 32.7% in the open gastrectomy group. Laparoscopic gastrectomy was associated with better 5-year overall survival in patients aged ≥60 years. The overall recurrence rates and patterns were not significantly different between the 2 groups. Conclusion Laparoscopic gastrectomy is an alternative surgical approach for patients with serosa-invasive gastric cancer in terms of short-term outcomes and long-term survival, and it might be more advantageous for certain populations.

This article presents a novel target detection method, which is named as circular target feature detection framework based on a deep convolutional neural network (DCNN). The central proposition of this method uses the optimized DCNN architecture to detect the target and locate the position of the circle accurately in the image field of view. In this article, a Hough transform based on threshold processing (HTP) is embedded into the optimized DCNN architecture, which calculates the center positions and radius of all circles by training the circular samples for each detected rectangular frame. It can efficiently identify small circular target materials in the industry and screen out unqualified particles. The experimental results show that the boundary information of the circles is obtained clearly from the complex noise background images, thereby accurately determining the location of the circle. It has some advantages over only using a specific circular recognition algorithm. We proposed the new study on HTP-DCNN, which has extremely high accuracy in the field of machine vision positioning with circles for industrial applications.

Advanced model-based control methods have been widely used in industrial process control, but excellent performance requires regular maintenance of its model. Reinforcement learning can online upda...

The economic dispatch problem (EDP) is one of the fundamental and important problems in power systems. The objective of EDP is to determine the output generation of generators to minimize the total generation cost under various constraints. In this article, a finite-time consensus-based distributed optimization algorithm is proposed to solve EDP. It is only required that each device in the communication network has access to its own local generation cost function, designed virtual local demand and its neighbors’ local optimization variables. The proposed finite-time algorithm can solve EDP, if the gain parameters in the algorithm satisfy some conditions under undirected and connected time-varying graphs. Moreover, the bounded or linear increasing assumption on the gradient and subgradient of objecive functions is relaxed in this algorithm. Examples under several cases are provided to verify the effectiveness of the proposed distributed optimization algorithm.

The various optical components have wide applications in aerospace industries. In the manufacturing process of optical components that are made of optical glass materials, the main challenges still are how to ensure the high requirements in dimensional accuracy and surface quality. In this paper, the CNC polishing method with inner channel liquid supply (ICLS) is proposed to polish glass materials based on the chemical mechanical polishing mechanism. The comparative experiment with both inner and external liquid supply was designed, and it is found that the successive and steady material removal rate (MRR) can be achieved by using the proposed polishing method. Then, the effect of polishing pressure, tool rotation speed, and polishing time on polishing quality was analyzed with single-factor experiments. Finally, the optimal polishing parameters were obtained with the orthogonal experiment. The results show that the average surface roughness is reduced from 238.16 to 1.34 nm, and the nanoscale super-smooth surface is achieved, which proves the feasibility of the CNC polishing method with ICLS.

The aromatics complex is essential in the production of p-xylene and contains several distillation towers and reactors, making this process highly energy intensive. To save energy for the aromatics...

The optimization of cyclic scheduling for an ethylene cracking furnace system (ECFS) is beneficial for ethylene plants. The scheduling problem involves multiple feeds, tanks, furnaces, and differen...

Hybrid modeling, aiming to integrate the advantages of both first-principles models and data-driven models, is an important technology for refinery process simulation and optimization. The commonly...

In chemical industry, most processes face the challenge of high energy consumption. The approach presented in this study can reduce the energy footprint and increase efficiency. The energy system of a separation process in ethylene manufacturing is used to demonstrate the effectiveness of the approach. The chilling train system of the separation process in a typical ethylene plant consumes most cooling and provides appropriate feed for distillation columns. The steady state simulation of system was presented and the simulation results were proved accurate. The conventional exergy analysis identifies that Dephlegmator No.1 (a heat exchange and mass transfer device) has the highest exergy destruction (1401.28 kW). Based on advanced exergy analysis, Dephlegmator No.1 has the highest rate of avoidable exergy destruction (89.04 %). Finally, a multi-objective optimisation aiming to maximise system exergy efficiency and to minimise operational cost was performed and the Pareto frontier was obtained. The multi-objective optimized exergy efficiency is 79.53 % (improved by 0.61 %) and the operational cost is 0.02031 yuan/kg (saved by 11.19 %). This study will guide future research to reduce energy consumption in process manufacturing.

Establishing quantitative structure-property relationships for the rational design of small molecule drugs at the early discovery stage is highly desirable. Using natural language processing (NLP), we proposed a machine learning model to process the line notation of small organic molecules, allowing the prediction of their melting points. The model prediction accuracy benefits from training upon different canonicalized SMILES forms of the same molecules and does not decrease with increasing size, complexity, and structural flexibility. When a combination of two different canonicalized SMILES forms is used to train the model, the prediction accuracy improves. Largely distinguished from the previous fragment-based or descriptor-based models, the prediction accuracy of this NLP-based model does not decrease with increasing size, complexity, and structural flexibility of molecules. By representing the chemical structure as a natural language, this NLP-based model offers a potential tool for quantitative structure-property prediction for drug discovery and development.

The morbidity and mortality of life-threatening diseases such as cancers are increasing year by year in China. Although the national medical insurance has been improved a lot, it still falls short of expecting “universal medical insurance”. To help the families of patients with cancer and other serious diseases to resolve the unaffordable medical cost, several internet platforms of “Peer to Peer Medical Mutual Aid” have gradually emerged recently. In the form of low threshold insurance combined with public support, these platforms provide subsidies to families of patients suffering from serious financial burden and then partly compensate them for the limit of national medical insurance. This article summarized the characteristics of declared patients sponsored by several medical mutual aid internet platforms. The results showed that the sponsored patients were mostly cancer patients (90.1%), aged 21 - 60 (88.4%), and the average amounts of financial support had a trend to decrease with the increase of age. In particular, the reported cases of thyroid cancer were increased dramatically recently, however, with a lowest average mutual aid fund. Given these data, it is urgent to list out a detailed rule for the use of national medical insurance on the treatment of cancer, to heighten the healthcare system for the occupational population, age from 21 to 60, and to establish the credit system for Medicare and Medicaid services.

High-speed rail (HSR) systems potentially provide a more efficient way of door-to-door transportation than airplane. However, they also pose unprecedented challenges in delivering seamless Internet service for on-board passengers. In this paper, we conduct the first large-scale disconnection-centric measurement study of TCP performance over LTE on HSR. Our measurement targets the main HSR route in China operating at 300/350 km/h. We performed extensive data collection obtaining 378.3 GB data collected over 56639 km of trips. Leveraging such a unique dataset, we measure important performance metrics such as TCP goodput, latency and loss rate across different congestion control algorithm, mobile carrier, and different train speed. We further develop the LTE disconnection taxonomy, and conduct a in-depth correlation study between TCP stall and LTE disconnection. Our findings reveal the networking performance on today’s HSR environment “in the wild”, as well as identify several root causes of performance inefficiencies, which together highlight the need to develop dedicated protocol mechanisms that are friendly to extreme mobility.

This paper presents a novel approach to mitigating the effect of temperature variations on the bridges’ dynamic modal properties for more reliably detecting scour damage around bridge piles based on the vibration-based measurements. The novelty of the presented approach lies in its ability to reasonably remove the impacts on the modal properties of bridges, particularly caused by changes in material properties and structural boundary conditions due to temperature variations without explicitly modeling these complex effects. The main idea is to adopt the probabilistic-based machine learning method, Gaussian Process Model, to learn the correlation between the changes of modal properties of a monitored bridge and the corresponding temperature variations from in situ sensor measurements, and probabilistically infer the bridge scour based on the modified vibration measurements, which have mitigated the identified impacts of temperature variations, by applying Bayesian inference through the Transitional Markov Chain Monte Carlo simulation. The proposed approach and its applicability are presented and validated through the numerical simulation of a prototype bridge, demonstrating its potential for practical application for mitigating effects of temperature variations or other environmental impacts for vibration-based Structural Health Monitoring. The limitation of the presented study and future research needs are also discussed.

This article presents a secure communication scheme based on the quantized synchronization of master-slave neural networks under an event-triggered strategy. First, a dynamic event-triggered strategy is proposed based on a quantized output feedback, for which a quantized output feedback controller is formed. Second, theoretical criteria are derived to ensure the bounded synchronization of master-slave neural networks. With these criteria, an explicit upper bound is given for the synchronization error. Sufficient conditions are also provided on the existence of quantized output feedback controllers. A Chua's circuit is chosen to illustrate the effectiveness of our theoretical results. Third, a secure communication scheme is presented based on the synchronization of master-slave neural networks by combining the basic principle of cryptology. Then, a secure image communication is studied to verify the feasibility and security performance of the proposed secure communication scheme. The impact of the quantization level and the event-triggered control (ETC) on image decryption is investigated through experiments.

BackgroundIt is unclear whether the dissection of pyloric lymph nodes (PLNs, No. 5 and No. 6 lymph nodes) is necessary for adenocarcinoma of the esophagogastric junction (AEG) with a tumor diameter >4 cm based on current guidelines. This study aimed at evaluating whether pyloric node lymphadenectomy is essential for patients with Siewert type II/III AEG according to different tumor diameters.MethodsThis study included 300 patients on whom transabdominal total gastrectomy was performed for Siewert type II/III AEG at a high-volume center in China from January 2006 to December 2015. The index of estimated benefit from lymph node dissection (IEBLD) was used to analyze the priority of pyloric lymphadenectomy.ResultsIn Siewert type II AEG, the 5-year overall survival (OS) and the 5-year disease-free survival (DFS) were similar between patients with PLN-positive cancer and patients of stage III AEG without PLN metastasis (23.1% vs. 30.6%, p = 0.505; 23.1% vs. 27.1%, p = 0.678). However, in Siewert type III AEG, the OS and the DFS of patients with PLN-positive cancer were significantly lower than that of patients with stage III without PLN metastasis (7.9% vs. 27.8%, p = 0.021; 0 vs. 26.8%, p = 0.005). According to the IEBLD, the dissection of PLNs did not appear to be beneficial in either Siewert type II AEG or type III AEG, whereas a stratified analysis revealed that PLN dissection yielded a high therapeutic benefit for Siewert type II AEG with tumor diameters >4 cm.ConclusionWe recommended that the PLNs be dissected in Siewert type II AEG when a tumor diameter is >4 cm. Total gastrectomy should be optional for Siewert type II AEG with a tumor diameter >4 cm and Siewert type III AEG.

Background From November 2014 to May 2016, 57 local health departments in New York State (NYS) excluding New York City were offered a performance incentive (PI) to promote adherence to federally recommended treatment guidelines for gonorrhea. The rationale of the PI was to delay antibiotic resistance and disrupt transmission through attaining a high percentage of treatment adherence. Methods Surveillance data from the NYS Communicable Disease Electronic Surveillance System were used for analysis. We evaluated adherence per Centers for Disease Control and Prevention sexually transmitted diseases treatment guidelines for persons 12 years and older reported with uncomplicated gonorrhea during 4 time frames: Pre-PI, PI One, PI Two, and Post-PI. We measured adherence per the Centers for Disease Control and Prevention sexually transmitted disease treatment guidelines during each respective time frame and conducted χ tests to test for the association between treatment adequacy and time frame. Results During the Pre-PI, treatment was adequate in 82.0% of persons diagnosed with gonorrhea. After program implementation, treatment adequacy increased significantly (92.1% of diagnosed persons during PI One, 90.4% during PI Two, and 90.5% during the Post-PI; P ≤ 0.0001). The most common reason for inadequate or missing treatment was patient lost to follow-up. Conclusions Public health intervention by the NYS Department of Health improved local health department adherence to federally recommended gonorrhea treatment guidelines, and improvements were maintained after the completion of the PI.

Background Few studies have been designed to evaluate the short-term outcomes between robotic-assisted total gastrectomy (RATG) and laparoscopy-assisted total gastrectomy (LATG) for advanced gastric cancer (AGC). The purpose of this study was to assess the short-term outcomes of RATG compared with LATG for AGC. Methods We retrospectively evaluated 126 and 257 patients who underwent RATG or LATG, respectively. In addition, we performed propensity score matching (PSM) analysis between RATG and LATG for clinicopathological characteristics to reduce bias and compared short-term surgical outcomes. Results After PSM, the RATG group had a longer mean operation time (291.14 ± 59.18 vs. 270.34 ± 52.22 min, p = 0.003), less intraoperative bleeding (154.37 ± 89.68 vs. 183.77 ± 95.39 ml, p = 0.004) and more N2 tier RLNs (9.07 ± 5.34 vs. 7.56 ± 4.50, p = 0.016) than the LATG group. Additionally, the total RLNs of the RATG group were almost significantly different compared to that of the LATG group (34.90 ± 13.05 vs. 31.91 ± 12.46, p = 0.065). Moreover, no significant differences were found between the two groups in terms of the length of incision, proximal resection margin, distal resection margin, residual disease and postoperative hospital stay. There was no significant difference in the overall complication rate between the RATG and LATG groups after PSM (23.8% vs. 28.6%, p = 0.390). Grade II complications accounted for most of the complications in the two cohorts after PSM. The conversion rates were 4.55 and 8.54% in the RATG and LATG groups, respectively, with no significant difference (p = 0.145), and the ratio of splenectomy were 1.59 and 0.39% (p = 0.253). The mortality rates were 0.8 and 0.4% for the RATG and LATG groups, respectively (p = 1.000). Conclusion This study demonstrates that RATG is comparable to LATG in terms of short-term surgical outcomes.

Recent years have witnessed the rapid growth of mobile virtual network operators (MVNOs), which operate on top of existing cellular infrastructures of base carriers, while offering cheaper or more flexible data plans compared to those of the base carriers. In this paper, we present a two-year measurement study towards understanding various fundamental aspects of today’s MVNO ecosystem, including its architecture, customers, performance, economics, and the complex interplay with the base carrier. Our study focuses on a large commercial MVNO with one million customers, operating atop a nation-wide base carrier. Our measurements clarify several key concerns raised by MVNO customers, such as inaccurate billing and potential performance discrimination with the base carrier. We also leverage big data analytics, statistical modeling, and machine learning to address the MVNO’s key concerns with regard to data usage prediction, data plan reselling, customer churn mitigation, and billing delay reduction. Our proposed techniques can help achieve higher revenues and improved services for commercial MVNOs.

De novo gastric cancer (GC) is uncommon in clinic after liver transplantation. Until now, only a few cases have been reported, and radical resection combined with comprehensive treatment remains the major therapeutic method. Two patients with De novo GC after liver transplantation were successfully treated with D2 lymphadenectomy using da Vinci robotic surgery system at our Hospital. Both operations were successful, and the duration of case 1 and 2 was 315 and 275 minutes respectively, with the estimated blood loss of 145 and 125 mL. The patients were discharged on day 7 and 9 after surgery, and no complications occurred. Postoperative pathological stages were pT4aN3aM0, stage III B and pT4aN2M0, stage III A respectively. Case 2 developed gastric retention 3 weeks after operation, and gastroscopy revealed edema within anastomotic stoma. Conservative treatment using feeding jejunal tube was performed. After 2 weeks, normal diet was gradually restored. Patients were treated with SOX regimen 3 weeks and 2 months post operation. During follow-up period, patients were in good health without long-term complications. Therefore, GC surgery using Da Vinci robot surgery system after liver transplantation is safe and feasible.

Halide perovskite semiconductors exhibit ultralow thermal conductivities, making them potentially suitable for thermoelectric applications. Nevertheless, the thermoelectric properties of the protot...

Little is known about whether there is an inverse relation between provider volume and long-term adverse outcomes for percutaneous coronary interventions (PCIs). For patients who underwent PCI procedures from December 2013 through November 2014 in New York, we examined a continuous relation and different annual PCI volume cut points at hospital and operator levels to investigate the relation between volume and 1-year adverse outcomes (mortality and mortality/acute myocardial infarction). There were 34,498 patients who underwent PCI procedures from 60 hospitals and 408 operators. We detected a significant continuous inverse association between 1-year mortality and annual hospital PCI volume. However, we did not find that there was a hospital volume and 1-year mortality relation for the 2013 ACCF/AHA/SCAI's hospital annual PCI volume cutoff value of 200 or a significant inverse operator volume-outcome relation using the operator annual PCI volume cutoff value of 50, or for any other practical volume cutoffs. Similar findings were obtained when we used the 1-year mortality/acute myocardial infarction outcome. We did find that providers in the highest volume quartile were associated with lower adverse outcome rates than providers in the lowest volume quartile. In conclusion, no significant volume-outcome relations were found between annual hospital or operator PCI volume and risk-adjusted 1-year outcomes for any practical volume cutoff values including 2013 Guidelines' recommended hospital/operator minimal annual PCI volumes. Providers in the highest annual volume quartile, however, were associated with lower adverse outcome rates than providers in the lowest volume quartile.

Due to their on-body and ubiquitous nature, wearables can generate a wide range of unique sensor data creating countless opportunities for deep learning tasks. We propose DeepWear, a deep learning (DL) framework for wearable devices to improve the performance and reduce the energy footprint. DeepWear strategically offloads DL tasks from a wearable device to its paired handheld device through local network connectivity such as Bluetooth. Compared to the remote-cloud-based offloading, DeepWear requires no Internet connectivity, consumes less energy, and is robust to privacy breach. DeepWear provides various novel techniques such as context-aware offloading, strategic model partition, and pipelining support to efficiently utilize the processing capacity from nearby paired handhelds. Deployed as a user-space library, DeepWear offers developer-friendly APIs that are as simple as those in traditional DL libraries such as TensorFlow. We have implemented DeepWear on the Android OS and evaluated it on COTS smartphones and smartwatches with real DL models. DeepWear brings up to 5.08X and 23.0X execution speedup, as well as 53.5 and 85.5 percent energy saving compared to wearable-only and handheld-only strategies, respectively.

In the refinery process, a vast amount of data is generated in daily production. How to make full use of these data to improve the simulation’s accuracy is crucial to enhancing the refinery operating level. In this paper, a novel deep learning framework integrating the self-organizing map (SOM) and the convolutional neural network (CNN) is developed for modeling the industrial hydrocracking process. The SOM is used to map input variables into two-dimensional maps to extract process features. Then, these maps are fed into the CNN to predict the outputs of the hydrocracking process. The SOM adopted is free of training, which reduces the computational complexity, simplifies the application, and improves the prediction accuracy. Practical guidance on the application of the proposed framework is provided by comparing and analyzing different structures and parameters. Finally, an online modeling scheme is developed and applied in an actual hydrocracking process. Experimental results demonstrate that the proposed framework has great performance in modeling the hydrocracking process and provides a good reference for process optimization.

p-p orbital interaction through Mg(ii) isovalent doping in methylammonium lead chloride perovskite significantly enhances the electronic properties while not affecting the optical bandgap. This chemical behaviour shows promising applications to optoelectronic devices.

Smart manufacturing is critical in improving the quality of the process industry. In smart manufacturing, there is a trend to incorporate different kinds of new-generation information technologies into process-safety analysis. At present, green manufacturing is facing major obstacles related to safety management, due to the usage of large amounts of hazardous chemicals, resulting in spatial inhomogeneity of chemical industrial processes and increasingly stringent safety and environmental regulations. Emerging information technologies such as artificial intelligence (AI) are quite promising as a means of overcoming these difficulties. Based on state-of-the-art AI methods and the complex safety relations in the process industry, we identify and discuss several technical challenges associated with process safety: ① knowledge acquisition with scarce labels for process safety; ② knowledge-based reasoning for process safety; ③ accurate fusion of heterogeneous data from various sources; and ④ effective learning for dynamic risk assessment and aided decision-making. Current and future works are also discussed in this context. Keywords: Process industry, Smart manufacturing, Green manufacturing, Artificial intelligence

Chemical spills on complex geometry are difficult to model due to the uneven concentration distribution caused by air flow over ground obstacles. Computational fluid dynamics (CFD) is one of the powerful tools to estimate the building-resolving wind flow as well as pollutant dispersion. However, it takes too much time and requires enormous computational power in emergency situations. As a time demanding task, the estimation of the chemical spill consequence for emergency response requires abundant wind field information. In this paper, a comprehensive wind field reconstruction framework is proposed, providing the ability of parameter tuning for best reconstruction accuracy. The core of the framework is a data regression model built on principal component analysis (PCA) and extreme learning machine (ELM). To improve the accuracy, the wind field estimation from the regression model is further revised from local wind observations. The optimal placement of anemometers is provided based on the maximum projection on minimum eigenspace (MPME) algorithm. The fire dynamic simulator (FDS) generates high-resolution data of wind flow over complex geometries for the framework to be implemented. The reconstructed wind field is evaluated against simulation data and an overall reconstruction error of 9% is achieved. When used in real case, the error increases to around 12% since no convergence check is available. With parameter tuning abilities, the proposed framework provides an efficient way of reconstructing the wind flow in congested areas.

Raw material blending process is an essential part of the cement production process. The main purpose of the process is to guarantee a certain oxide composition for the raw meal at the outlet of the mill by regulating the four raw materials. But the chemical compositions of raw materials vary from time to time, resulting in difficulties to control the oxide compositions to a predefined value. Therefore, a novel algorithm to estimate the chemical compositions of the raw materials is developed. The paper mainly consists of two parts. In model construction part, a novel constrained least square model is proposed to overcome the deviation introduced by long-term drift of the material components, and the model parameters are estimated with an online strategy. And in validation part, the approach is implemented to two examples including datasets from simulation model and the actual industrial process. The final results show the effectiveness of the proposed method.

Vertical roller mill (VRM) is an increasingly popular comminution equipment in cement plants. Raw meal fineness at the outlet of VRM is one of the most important indicators to measure product quality. A soft sensing model developed for powder fineness in real-time could assist operators to monitor the comminution process online. However, due to frequent fluctuation of raw material properties, intrinsic nonlinearity of the process and changeable operation conditions, the data present a multimodal characteristic. Therefore, this paper proposes an indicator to measure the similarity between variables, that is, the shortest distance between nodes in the constructed weighted network. By combining the Girvan Newman (GN) algorithm, the nodes in the variable network are divided into multiple groups, and based on this, the distributed PCA (DPCA) similarity is adopted for time series segmentation (TSS). Compared with traditional similarities between samples (distance, density, etc.), the similarity between time series focuses more on the dynamic characteristics of variables. And the implementation of DPCA similarity is equivalent to increasing the sparse characteristics of principal components, which is beneficial for enhancing the generalization of the model. Support vector regression (SVR) models along with a support vector machine (SVM) based classifier are built to obtain final predictions of the powder fineness. Effectiveness of the proposed method is verified by actual industrial data. It has a root mean square error (RMSE) index of 0.3451 on the test set, which is much smaller than that of the multi-modal soft sensor based on either clustering approaches (0.6524) or PCA similarity based TSS method (0.4282).

Connected and Autonomous Vehicles (CAVs) heavily rely on 3D sensors such as LiDARs, radars, and stereo cameras. However, 3D sensors from a single vehicle suffer from two fundamental limitations: vulnerability to occlusion and loss of details on far-away objects. To overcome both limitations, in this paper, we design, implement, and evaluate EMP, a novel edge-assisted multi-vehicle perception system for CAVs. In EMP, multiple nearby CAVs share their raw sensor data with an edge server which then merges CAVs' individual views to form a more complete view with a higher resolution. The merged view can drastically enhance the perception quality of the participating CAVs. Our core methodological contribution is to make the sensor data sharing scalable, adaptive, and resource-efficient over oftentimes highly fluctuating wireless links through a series of novel algorithms, which are then integrated into a full-fledged cooperative sensing pipeline. Extensive evaluations demonstrate that EMP can achieve real-time processing at 24 FPS and end-to-end latency of 93 ms on average. EMP reduces the end-to-end latency by 49% to 65% compared to the traditional vehicle-to-vehicle (V2V) sharing approach without edge support. Our case studies show that cooperative sensing powered by EMP can detect hazards such as blind spots faster by 0.5 to 1.1 seconds, compared to a single vehicle's perception.

Background This study was designed to compare the postoperative complications after Robotic total gastrectomy (RTG) and robotic distal gastrectomy (RDG) and to systematically evaluate the safety and feasibility of RTG for the treatment of gastric cancer (GC). Methods Patients with GC who underwent RTG or RDG for curative intent between March 2010 and August 2019 were analyzed. We used propensity score matching (PSM) to reduce selection bias. The morbidity and mortality within 30 days after surgery between the RTG and the RDG groups were compared. Results According to Clavien–Dindo (C–D) classification, the morbidity and mortality of the RTG group were comparable to those of the RDG group. Subgroup analyses showed no significant difference between the RTG and RDG groups in all stratified parameters (all P > .05). Multivariate analysis revealed that age ≥70 years ( P = .002) and surgeons’ experience ≤25 cases ( P = .013) were independent risk factors for overall complication. Surgeons’ experience ≤25 cases ( P = .010) was identified as an independent risk factor for severe complication. Conclusion RTG is a safe and feasible surgical procedure for the treatment of GC with acceptable morbidity and mortality. More complications were observed for RTG, indicating that RTG is more invasive than RDG.

Carrying over 75% of the last-mile mobile Internet traffic, WiFi has inevitably become an enticing target for various security threats. In this work, we characterize a wide variety of real-world WiFi threats at an unprecedented scale, involving 19 million WiFi access points (APs) mostly located in China, by deploying a crowdsourced security checking system on 14 million mobile devices in the wild. Leveraging the collected data, we reveal the landscape of nationwide WiFi threats for the first time. We find that the prevalence, riskiness, and breakdown of WiFi threats deviate significantly from common understandings and prior studies. In particular, we detect attacks at around 4% of all WiFi APs, uncover that most WiFi attacks are driven by an underground economy, and provide strong evidence of web analytics platforms being the bottleneck of its monetization chain. Further, we provide insightful guidance for defending against WiFi attacks at scale, and some of our efforts have already yielded real-world impact---effectively disrupted the WiFi attack ecosystem.

Efavirenz (EFV) is a non-nucleoside reverse transcriptase inhibitor (NNRTI), which is widely used for anti-HIV-1. Evidences revealed that several central nervous system side effects could be observed in mice and patients with administration of EFV. However, the detailed mechanisms are still unknown. In this study, we investigated the effects of long-term EFV treatment on cognitive functions and the potential underlying mechanisms in mice. We maintained C57BL/6 mice aged 2 months with treatment containing 40 or 80 mg/kg/day EFV for 5 months, while control group treated with saline. The cognitive functions were evaluated by novel object recognition test, Barnes maze test and Morris water maze. The results showed significant short-term memory impairment in 40 and 80 mg/kg groups, and notable spatial learning and memory impairments in 80 mg/kg group, without any spontaneous activity alteration. Moreover, EFV induced impairments in dendritic integrity and synaptic plasticity in hippocampus. Furthermore, Significant increases were observed in the expression levels of pro-IL-1β, a similar tendency of TNF-α and phosphorylation of p65 of the 80 mg/kg group compared with control group. These results imply that long-term EFV treatment causes synaptic dysfunction resulting in cognitive deficits, which might be induced by the enhanced pro-inflammatory cytokines IL-1β and TNF-α via activating NF-κB pathway.

BackgroundLaparoscopic gastrectomy (LG) has been increasingly used for the treatment of locally advanced Siewert type II and III adenocarcinoma of the esophagogastric junction (AEG). However, whether LG can achieve the same short-term efficacy in the treatment of patients who receive neoadjuvant chemotherapy (NACT) remains controversial. Thus, the aim of this study was to investigate the clinical outcomes of NACT combined with LG for Siewert type II and III AEG.MethodsThis retrospective study identified patients with locally advanced Siewert type II and III AEG diagnosed between May 2011 and October 2020 using the clinical tumor-node-metastasis (cTNM) staging system. The short-term outcomes were compared between the matched groups using a 1:3 propensity score matching (PSM) method, which was performed to reduce bias in patient selection.ResultsAfter PSM, 164 patients were selected, including 41 in the NACT group and 123 in the LG group. The baseline characteristics were similar between the two groups. Compared with the LG group, the NACT group exhibit a smaller tumor size and significantly less advanced pathological tumor classification and nodal classification stages. The time to first flatus of the NACT group was significantly shorter, but the hospital stay was significantly longer than that of the LG group. The NACT group showed similar overall (29.3% vs 25.2%, P=0.683), systemic (24.4% vs 21.1%, P=0.663), local (12.2% vs 9.8%, P=0.767), minor (19.5% vs 19.5%, P=1.000) and major (9.8% vs 5.7%, P=0.470) complications as the LG group. Subgroup analyses showed no significant differences in most stratified parameters. Operation time≥ 300 minutes was identified as an independent risk factor for overall complications. Age≥ 60 years was identified as an independent risk factor for major complications.ConclusionNACT combined with LG for AEG does not increase the risk of postoperative morbidity and mortality compared with LG.

Recent measurement studies show that commercial mmWave 5G can indeed offer ultra-high bandwidth (up to 2 Gbps), capable of supporting bandwidth-intensive applications such as ultra-HD (UHD) 4K/8K and volumetric video streaming on mobile devices. However, mmWave 5G also exhibits highly variable throughput performance and incurs frequent handoffs (e.g., between 5G and 4G), due to its directional nature, signal blockage and other environmental factors, especially when the device is mobile. All these issues make it difficult for applications to achieve high Quality of Experience (QoE). In this paper, we advance several new mechanisms to tackle the challenges facing UHD video streaming applications over 5G networks, thereby making them {\em 5G-aware}. We argue for the need to employ machine learning (ML) for effective throughput prediction to aid applications in intelligent bitrate adaptation. Furthermore, we advocate {\em adaptive content bursting}, and {\em dynamic radio (band) switching} to allow the 5G radio network to fully utilize the available radio resources under good channel/beam conditions, whereas dynamically switched radio channels/bands (e.g., from 5G high-band to low-band, or 5G to 4G) to maintain session connectivity and ensure a minimal bitrate. We conduct initial evaluation using real-world 5G throughput measurement traces. Our results show these mechanisms can help minimize, if not completely eliminate, video stalls, despite wildly varying 5G throughput.

Motivated by the rapid deployment of 5G, we carry out an in-depth measurement study of the performance, power consumption, and application quality-of-experience (QoE) of commercial 5G networks in the wild. We examine different 5G carriers, deployment schemes (Non-Standalone, NSA vs. Standalone, SA), radio bands (mmWave and sub 6-GHz), protocol configurations (_e.g._ Radio Resource Control state transitions), mobility patterns (stationary, walking, driving), client devices (_i.e._ User Equipment), and upper-layer applications (file download, video streaming, and web browsing). Our findings reveal key characteristics of commercial 5G in terms of throughput, latency, handover behaviors, radio state transitions, and radio power consumption under the above diverse scenarios, with detailed comparisons to 4G/LTE networks. Furthermore, our study provides key insights into how upper-layer applications should best utilize 5G by balancing the critical tradeoff between performance and energy consumption, as well as by taking into account the availability of both network and computation resources. We have released the datasets and tools of our study at https://github.com/SIGCOMM21-5G/artifact.

Deep learning-based methods mymargin have achieved remarkable performance in 3-D sensing since they perceive environments in a biologically inspired manner. Nevertheless, the existing approaches trained by monocular sequences are still prone to fail in dynamic environments. In this work, we mitigate the negative influence of dynamic environments on the joint estimation of depth and visual odometry (VO) through hybrid masks. Since both the VO estimation and view reconstruction process in the joint estimation framework is vulnerable to dynamic environments, we propose the cover mask and the filter mask to alleviate the adverse effects, respectively. As the depth and VO estimation are tightly coupled during training, the improved VO estimation promotes depth estimation as well. Besides, a depth-pose consistency loss is proposed to overcome the scale inconsistency between different training samples of monocular sequences. Experimental results show that both our depth prediction and globally consistent VO estimation are state of the art when evaluated on the KITTI benchmark. We evaluate our depth prediction model on the Make3D dataset to prove the transferability of our method as well.

This paper studies the nonlinear dynamics and energy harvesting performance of a novel bi-stable piezoelectric energy harvester inspired by the rapid shape transition of the Venus flytrap leaves. The harvester is composed of a piezoelectric MFC transducer, a tip mass, and two sub-beams. The two sub-beams are akin to the bidirectionally curved Venus flytrap leaves that could rapidly snap-through from the open state to the closed state. To realize the bistability of the Venus flytrap leaves induced by the stored potential energy, an in-plane pre-displacement constraint is applied to the free ends of the sub-beams. The pre-displacement constraint leads to bending and twisting deformations and creates the potential energy in the harvester. The bio-inspired design is introduced in detail and a prototype is fabricated to validate the conceptual design. The nonlinear dynamics of the bio-inspired bi-stable piezoelectric energy harvester is investigated under base acceleration excitations. Results show that the sub-beams of the harvester experience more complicated local vibrations containing broadband high-frequency components as the snap-through motion happens. The energy harvesting performance of the harvester is evaluated at different excitation levels. The broadband energy harvesting is achieved at higher excitation levels and an average power output of 0.193 mW is attained under the excitation of 10 Hz and 4.0 g.

OBJECTIVE A large-scale multicenter retrospective cohort study was conducted to compare the short- and long-term outcomes of robotic gastrectomy (RG) and laparoscopic gastrectomy (LG) for gastric cancer. SUMMARY OF BACKGROUND DATA RG is being increasingly used worldwide, but data from large-scale multicenter studies on the short- and long-term oncologic outcomes of RG versus LG are limited. The potential benefits of RG compared with LG for gastric cancer remain controversial. METHODS Data from eligible patients who underwent RG or LG for gastric cancer of 11 experienced surgeons from 7 centers in China between March 2010 and October 2019 were collected. The RG group was matched 1:1 with the LG group by using propensity score matching (PSM). The primary outcome was postoperative complications. RESULTS After PSM, a well-balanced cohort of 3552 patients was included for further analysis. The occurrence of overall complications (12.6% vs 15.2%, P = 0.023) was lower in the RG group than in the LG group. RG was associated with less blood loss (126.8 vs 142.5 mL, P < 0.001) and more retrieved lymph nodes in total (32.5 vs 30.7, P < 0.001) and in suprapancreatic areas (13.3 vs 11.6, P < 0.001). The long-term oncological outcomes were comparable between the two groups. CONCLUSIONS The results of this multicenter study demonstrate that RG is a safe and effective treatment for gastric cancer when performed by experienced surgeons, although longer operation time and higher costs are still concerns about RG. This study provides evidence suggesting that RG may represent an alternative surgical treatment to LG.

Background Rapid laboratory detection is essential to diagnose norovirus infection. LAMP has many advantages compared with RT‐PCR for detecting norovirus, including high sensitivity, high specificity, rapidity, low cost, and intuitive results, which can be easily read with the naked eye with the help of color‐based reporters. In this study, we intend to analyze the accuracy of LAMP methods for the diagnosis of norovirus infection. Methods Two researchers independently retrieved relevant literature up to January 2021 (PubMed, Web of Science, Cochrane Library, Embase, CNKI, Wan Fang, and VIP). The researchers screened all articles and extracted their research data for meta‐analysis. QUADAS‐2 tool was used to evaluate the quality of the included studies by Review Manager 5.3. Forest plots were performed by Meta‐DiSc 1.4 to evaluate the accuracy of the test. Deeks’ funnel plot symmetry tests were conducted by Stata 15.0 to check the potential publication bias. Results Eleven sets of data extracted from the eight included studies were included for meta‐analysis. For the detection of norovirus, the pooled sensitivity, specificity, positive LR, negative LR, diagnostic OR, and their 95% CI were 0.96 (0.95–0.97), 0.99 (0.99–1.00), 91.14 (31.88–260.56), 0.06 (0.04–0.09), and 1473.68 (562.96–3857.70), respectively. Besides, AUC in the SROC curve was 0.9920. Conclusion LAMP had high sensitivity and specificity in terms of the diagnosis of norovirus infection. However, further extension of this approach should be researched to ensure the accuracy and practicability of this hopeful test in the future., The AUC was 0.9920, and Q* was 0.9636 in SROC; the curve was close to the top left corner. The results proved a higher value, suggesting a greater diagnostic potential of LAMP for norovirus infection. One may conclude that the capacity of LAMP in the early diagnosis of norovirus is considerably high. LAMP may be a practical and reliable method for detecting norovirus infection.

Schistosoma japonicum infection showed protective effects against allergic airway inflammation (AAI). However, controversial findings exist especially regarding the timing of the helminth infection and the underlying mechanisms. Most previous studies focused on understanding the preventive effect of S. japonicum infection on asthma (infection before allergen sensitization), whereas the protective effects of S. japonicum infection (allergen sensitization before infection) on asthma were rarely investigated. In this study, we investigated the protective effects of S. japonicum infection on AAI using a mouse model of OVA-induced asthma. To explore how the timing of S. japonicum infection influences its protective effect, the mice were percutaneously infected with cercaria of S. japonicum at either 1 day (infection at lung-stage during AAI) or 14 days before ovalbumin (OVA) challenge (infection at post–lung-stage during AAI). We found that lung-stage S. japonicum infection significantly ameliorated OVA-induced AAI, whereas post–lung-stage infection did not. Mechanistically, lung-stage S. japonicum infection significantly upregulated the frequency of regulatory T cells (Treg cells), especially OVA-specific Treg cells, in lung tissue, which negatively correlated with the level of OVA-specific immunoglobulin E (IgE). Depletion of Treg cells in vivo partially counteracted the protective effect of lung-stage S. japonicum infection on asthma. Furthermore, transcriptomic analysis of lung tissue showed that lung-stage S. japonicum infection during AAI shaped the microenvironment to favor Treg induction. In conclusion, our data showed that lung-stage S. japonicum infection could relieve OVA-induced asthma in a mouse model. The protective effect was mediated by the upregulated OVA-specific Treg cells, which suppressed IgE production. Our results may facilitate the discovery of a novel therapy for AAI.