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Path following is crucial for enhancing the autonomy of unmanned surface vehicles (USVs) in water monitoring missions. This paper presents an offline reinforcement learning (RL) controller for USVs. The controller employs the soft actor–critic algorithm with a diversified Q-ensemble to optimize the steering control policy using a pre-collected dataset of USV path-following trials. A Markov decision process (MDP) tailored for path following is formulated. The proposed offline RL steering controller, trained on static datasets, demonstrates improved sample efficiency and asymptotic performance due to an expanded ensemble of Q-networks. The accuracy and adaptive learning capabilities of the RL controller are validated through simulations and free-running tests.

Abstract Background Anastomotic leakage (AL) is a severe complication following esophagectomy with high mortality. Perioperative decreased serum albumin level is considered a predictive of AL, however, its impact on AL incidence in patients treated with neoadjuvant chemotherapy (NCT) followed by minimally invasive esophagectomy (MIE) is not well defined. Methods The data of 318 consecutive esophageal cancer patients who underwent MIE were collected retrospectively from January 2021 to December 2021. The perioperative level of albumin was detected and the baseline of altering levels for albumin was established. The incidence of postoperative complications and survival rate were analyzed between groups. Results After exclusion, 137 patients were enrolled and assigned to more decreased albumin (MA) and less decreased albumin (LA) groups. The levels of albumin descended significantly after MIE (p

Abstract Recent studies have reported worldwide vegetation suppression in response to increasing atmospheric vapor pressure deficit (VPD). Here, we integrate multisource datasets to show that increasing VPD caused by warming alone does not suppress vegetation growth in northern peatlands. A site-level manipulation experiment and a multiple-site synthesis find a neutral impact of rising VPD on vegetation growth; regional analysis manifests a strong declining gradient of VPD suppression impacts from sparsely distributed peatland to densely distributed peatland. The major mechanism adopted by plants in response to rising VPD is the “open” water-use strategy, where stomatal regulation is relaxed to maximize carbon uptake. These unique surface characteristics evolve in the wet soil‒air environment in the northern peatlands. The neutral VPD impacts observed in northern peatlands contrast with the vegetation suppression reported in global nonpeatland areas under rising VPD caused by concurrent warming and decreasing relative humidity, suggesting model improvement for representing VPD impacts in northern peatlands remains necessary.

Under the electricity market environment, the flexible load of power users can not only reduce the cost of power consumption by adjusting their own power consumption behaviors according to the real-time price (RTP), but also can obtain additional benefits by participating in auxiliary services. The load of commercial buildings (CBs) is concentrated and makes a greater contribution to the peak load of the power system. If the flexible load of CBs can be regulated, it has great benefits for shifting the peak load of the power system in addition to reducing the electricity cost. On the basis of analyzing the characteristics of flexible loads in CBs, a flexible load regulation model including short-time interruptible load (IL), reducible load (RL), translatable load (TL), air conditioning system (ACS) and energy storage system (ESS) is established. Considering the electrical comfort and temperature preference, the objective function is jointly constructed with the electrical cost, temperature discomfort and ancillary service income. An optimal regulation strategy for multiple types of flexible loads in CBs based on the electricity market environment to realize the economic power consumption of CBs is formulated. The simulation results show that the proposed strategy can reduce the power cost of CBs and lower the peak demand under the condition of satisfying the power consumption comfort.

In this study, ecofriendly and economic carboxy-terminated plant fibers (PFs) were used as adsorbents for the effective in-syringe solid phase extraction (IS-SPE) of fluoroquinolone (FQ) residues from water. Based on the thermal esterification and etherification reaction of cellulose hydroxy with citric acid (CA) and sodium chloroacetate in aqueous solutions, carboxy groups grafted onto cotton, cattail, and corncob fibers were fabricated. Compared with carboxy-terminated corncob and cotton, CA-modified cattail with more carboxy groups showed excellent adsorption capacity for FQs. The modified cattail fibers were reproducible and reusable with relative standard deviations of 3.2%–4.2% within 10 cycles of adsorption-desorption. A good extraction efficiency of 71.3%–80.9% was achieved after optimizing the extraction condition. Based on carboxylated cattail, IS-SPE coupled with ultra-performance liquid chromatography with a photodiode array detector was conducted to analyze FQs in environmental water samples. High sensitivity with limit of detections of 0.08–0.25 μg/L and good accuracy with recoveries of 83.8%–111.7% were obtained. Overall, the simple and environment-friendly modified waste PFs have potential applications in the effective extraction and detection of FQs in natural waters.

Affected by environmental factors, equipment aging, operating status, etc., the parameters of photovoltaic (PV) models will deviate from the original setting parameters. In order to accurately identify the dynamic parameters of photovoltaics under the general simulation model, traditional parameter identification methods mainly use heuristic intelligent optimization algorithms for direct solution. Due to the limited data collected and the strong randomness of the algorithm, it is easy to make the identification accuracy and stability of photovoltaic parameters difficult to meet the requirements. To this end, this paper proposes an optimal identification method for PV dynamic parameters driven by data expansion. Firstly, the PV external characteristic data is fitted and generalized, which used the generalized regression neural network (GRNN). Then, the extended high-quality data can be used for dynamic parameter identification for PV cell. To confirm the performance of the proposed algorithm in this paper, this paper expands based on the actual external characteristic data of different proportions and uses the general PV simulation model to conduct comparative tests on various commonly used algorithms. The case studies under different scenarios show that the proposed algorithm can provide a more reliable and well-represented fitness function to the metaheuristic algorithms. Therefore, the optimization accuracy and stability of the proposed algorithm for dynamic PV cell parameter identification can be significantly improved simultaneously.

More and more renewable energy sources are integrated into novel power systems. The randomness and fluctuation of such renewable energy sources bring challenges to the static stability and safety analysis of novel power systems. In this work, a multilayer deep deterministic policy gradient is proposed to address the fluctuation of renewable energy sources. The proposed method is stacked with multilayer deep reinforcement learning methods that can be continuously updated online. The proposed multilayer deep deterministic policy gradient is compared with other deep learning algorithms. The feasibility, effectiveness, and superiority of the proposed method are verified by numerical simulations.

BackgroundClinical benefits of neoadjuvant Anlotinib for locally advanced esophageal squamous cell carcinoma (ESCC) remains unclear. This study evaluated the efficacy and safety of neoadjuvant Anlotinib plus chemotherapy followed by minimally invasive esophagectomy (MIE) for the treatment of patients with locally advanced ESCC.MethodsPatients with locally advanced ESCC were randomly assigned to neoadjuvant Anlotinib combined with chemotherapy (Anlotinib group) or neoadjuvant chemoradiotherapy alone (nCRT group) with an allocation ratio of 1:1. The primary endpoint was the R0 surgical resection rate. Secondary endpoints included postoperative pathologic stage, complete response (CR) rate, and safety. Safety was assessed by adverse events (AEs) and postoperative complications.ResultsFrom August 2019 to August 2021, 93 patients were assigned to the nCRT or Anlotinib group. Of the 93 patients, 79 underwent MIE and were finally included in the per-protocol set (nCRT group: n=39; Anlotinib group: n=40). The R0 resection rate was 97.4% for nCRT versus 100.0% for Anlotinib group (p>0.05). Compared with the nCRT group, patients in the Anlotinib group had shorter total operation duration (262.2 ± 39.0 vs. 200.7 ± 25.5 min, p=0.010) and less blood loss (161.3 ± 126.7 vs. 52.4 ± 39.3 mL, p0.05). Besides, the incidences of AEs (80.0% vs. 92.3%) and postoperative complications (22.5% vs. 30.8%) were similar between the two groups (all p>0.05).ConclusionsNeoadjuvant Anlotinib plus chemotherapy had a similar safety profile and pathologic response, but better surgical outcomes than nCRT for locally advanced ESCC.

The co-centered orthogonal loop and dipole (COLD) array exhibits some interesting properties, which makes it ubiquitous in the context of polarized source localization. In the literature, one can find a plethora of estimation schemes adapted to the COLD array. Nevertheless, their ultimate performance in terms the so-called threshold region of mean square error (MSE), have not been fully investigated. In order to fill this lack, we focus, in this paper, on conditional and unconditional bounds that are tighter than the well known Cramér-Rao Bound (CRB). More precisely, we give some closed form expressions of the McAulay-Hofstetter, the Hammersley-Chapman-Robbins, the McAulaySeidman bounds and the recent Todros-Tabrikian bound, for both the conditional and unconditional observation model. Finally, numerical examples are provided to corroborate the theoretical analysis and to reveal a number of insightful properties.

Natural products have provided numerous lead compounds for drug discovery. However, the traditional analytical methods cannot detect most of these active components, especially at their usual low concentrations, from complex natural products. Herein, we reviewed the recent technological advances (2015–2019) related to the separation and screening bioactive components from natural resources, especially the emerging screening methods based on the bioaffinity techniques, including biological chromatography, affinity electrophoresis, affinity mass spectroscopy, and the latest magnetic and optical methods. These screening methods are uniquely advanced compared to other traditional methods, and they can fish out the active components from complex natural products because of the affinity between target and components, without tedious separation works. Therefore, these new tools can reduce the time and cost of the drug discovery process and accelerate the development of more effective and better-targeted therapeutic agents.

PurposeTo identify the optimal number of lymph nodes dissected during esophagectomy following neoadjuvant therapy for carcinoma of the esophagus by using the Surveillance, Epidemiology and End Results Registry (SEER) database.Patients and MethodsPatients who underwent neoadjuvant Chemoradiotherapy (nCRT) plus esophagectomy with EC from 2001–2016 were analyzed retrospectively in the SEER database. We analyzed the correlation between the lymphadenectomy count and nodal stage migration and overall survival (OS) by using a binary logistic regression model and Cox proportional hazards regression. The curves of the odds ratios (ORs) of nodal stage migration and hazard ratios (HRs) of OS were smoothed using the LOWESS technique, and the cutoff points were determined by the Chow test. The OS curves were calculated with the Kaplan-Meier method.ResultsAmong the 4,710 patients analyzed in the SEER database, a median of 12 lymph nodes (IQR, 7–19) were harvested. There was a significantly proportional increase in nodal stage migration (OR, 1.017; 95% CI, 1.011 to 1.023; P

BackgroundThe prognostic benefit of extensive lymphadenectomy remains controversial in esophageal squamous cell carcinoma (ESCC). The purpose of this retrospective study was to investigate the potential effect of solitary mediastinal (SM) lymph node metastasis and solitary celiac (SC) lymph node metastasis on the short- and long-term outcomes for patients who underwent minimally invasive McKeown esophagectomy.MethodsFrom September 2009 to December 2020, a total of 934 cases were diagnosed with ESCC and underwent minimally invasive McKeown esophagectomy in our department; 223 cases met the inclusion and exclusion criteria. Propensity score matching (PSM) was utilized to contrast the postoperative results and long-term survival of Group 1 (SM) and Group 2 (SC). Univariate and multivariate Cox proportional hazards regression analyses were used on possible predictors of survival.ResultsOne hundred forty-seven patients were available for outcome comparison after PSM. The postoperative results were not significantly different between the two groups. In terms of long-term survival, the 5-year disease-free survival (DFS) was 37.6% and 57.3% (p = 0.191) and 5-year disease-specific survival (DSS) was 39.7% and 68.4% (p = 0.028) for Group 1 (SM) and Group 2 (SC), respectively. Univariate and multivariate Cox proportional hazards regression analyses showed that body mass index (BMI), pathologic stage (pStage), and SC/SM grouping had significant hazard ratios (HRs), which suggested that SC is associated with better DSS.ConclusionThis cohort study showed that SC lymph node metastasis has a better long-term survival compared with SM lymph node metastasis in esophagectomy of ESCC. The results challenge the current understanding and need confirmation in further research.

With the widespread use of electric vehicles (EVs), the charging behavior of these resources has brought a large amount of load growth to the grid, leading to a series of problems such as increased peak valley load difference and line flow violation. Non-intrusive load monitoring (NILM) is a key technology that can be employed to monitor the multi-source load data information in the power grid and support the high-proportion access of electric vehicles. However, traditional NILM approaches are designed to identify the operation of household appliances and cannot be applied at the substation level directly due to frequent and intricate switching events of electrical equipment at this stage. In this paper, a NILM algorithm that can be applied for the monitoring of the charging behavior of electric vehicles at the substation level is proposed to support the high-proportion injection of distributed energy resources. The proposed approach employs a deep learning framework and a multi-kernel convolutional neural network (multi-kernel CNN) framework is used. The performance of the proposed method is verified on the self-organized datasets based on Pecan Street data and results showed that the obtained f1 score is over 90% for both the training sets and testing sets.

Background Esophageal squamous cell carcinoma (ESCC) is one of the most aggressive and lethal cancers lacking valid prognostic biomarkers. As an essential component of a large ribonucleoprotein complex, U Three Protein 14a (UTP14a) might play important roles in human tumorigenesis. However, the clinical significance and functions of UTP14a in ESCC still remain unclear. Methods From September 2009 to August 2015, 210 patients with ESCC of the thoracic esophagus underwent thoracoscopic esophagectomy in our institute. The corresponding 210 tissue samples and 30 cancer‐distant mucosa (CDM) samples were tested for UTP14a expression by immunohistochemical staining. The long‐term survival was analyzed by the Kaplan–Meier method and Cox proportional hazards regression analyses. CCK8, cell colony formation, cell cycle, apoptosis, cell invasion, and wound healing assays were carried out with ECA109 cells to evaluate the effects of UTP14a on ESCC in vitro. Results UTP14a was positively expressed in 88.1% (185/210) of the ESCC samples. UTP14a expression in ESCC was significantly higher than in CDM, as further confirmed by Western blot analysis. High expression of UTP14a in ESCC correlated significantly with tumor invasive depth (pT stage), which predicts poor disease‐free survival and disease‐specific survival, as indicated by the log‐rank test and Cox proportional hazards regression analysis. Additionally, our in vitro experiments further demonstrated that knockdown of UTP14a inhibits cell proliferation and invasion in ECA109 cells. Conclusions Our results suggest that UTP14a is aberrantly expressed in ESCC, plays a critical role in cancer progression and could be a potential prognosis predictor of ESCC.

In this study, mulberry cultivars were found to have abundant bioactive compounds such as phenolics (100.97–586.23 mg gallic acid equivalents/100 g fresh weight), flavonoids (16.38–368.16 mg rutin equivalents/100 g fresh weight) and procyanidins (4.20–121.56 mg catechin equivalents/100 g fresh weight) after in vitro digestion. HPLC-TOF-MS analysis revealed that digested mulberry cultivars contained multiple phenolic compounds including cyanidin-3-O-glucoside and cyanidin-3-O-rutinoside. After gut microbiota fermentation, the contents of anthocyanins were increased initially, then decreased with time, and some anthocyanin metabolites (such as 3,4-Dihydroxybenzoic acid, 2,4,6-trihydroxybenzoic acid, 2,4,6-trihydroxybenzaldehyde, etc.) were detected. Our further cellular study indicated that mulberry (Hanguo) possessed reactive oxygen species scavenging capacity after gut microbiota fermentation. Our results indicated that the new cultivar Hanguo contained abundant polyphenols and exhibited potent antioxidant property after in vitro digestion and gut microbiota fermentation compared with other mulberry cultivars, which could be recommended as a dietary source of functional foods.

Liensinine, an important alkaloid in lotus seed, exhibits multiple functions such as anti-AIDS, anticancer, antidepressant, and antihypertensive properties. In this study, a highly sensitive HPLC-MS/MS method was developed and validated for the quantification of liensinine in microvolume rat plasma as low as 45 μL. Chromatographic separation was carried out using a reverse-phase Gemini-C18 column (100 mm × 3 mm i.d. × 5 μm), and mass selective detection using multiple reaction monitoring was attained using an electrospray ionization source, which operated in the positive mode. Dauricine was used as the internal standard. The precursor-to-product ion transition m/z 611.15 > 206.10 was selected for the detection of liensinine; m/z 625.25 > 206.10 was used for the detection of dauricine. The developed method is linear over the concentration range of 0.05–1000 ng/mL with an excellent coefficient of determination (R2 = 0.991). The recoveries ranged from 92.57% to 95.88% at three quality control levels. Intraday and interday precision and accuracy are less than 12.2% and 6.59%, respectively. The lower limit of quantification (LLOQ) is 0.05 ng/mL. The matrix effect was insignificant and acceptable. The validated method was successfully applied to the pharmacokinetic study of liensinine in rats. This method can be used for in vivo studies as well as quality control of traditional Chinese medicines and herbal tea containing liensinine alkaloid.

Jujube belongs to the Rhamnaceae family and is a popular fruit worldwide. Jujube has a long history of usage as traditionally healthy food. However, jujube fruits have a short shelf-life and it can be stored for no more than ten days under non-controlled conditions. Thus, the processing of jujube to product is one of the best options for long time storage. This review aims to highlight the nutritional importance of jujube fruit and its potential application for the development of commercial food products. It also addresses the health benefits of jujube-based food products. Moreover, jujube products possess high nutritional and biological value, which can be incorporated into different food formulations to improve product quality. Therefore, jujube fruit can be a promising food ingredient for the development of functional food products to achieve high consumer acceptability and health benefits.

A robust adaptive fuzzy neural network control (RAFNNC) algorithm is proposed based on a generalized dynamic fuzzy neural network (GDFNN), proportion-integral-differential (PID), and improved bacterial foraging optimization (BFO) algorithm, for heading the control of the unmanned marine vehicle (UMV) in the presence of a complex environment disturbance. First, the inverse dynamic model of the motion control of UMV is established based on the GDFNN for the uncertain disturbance caused by the complex environment disturbance. Then, the adaptive rate of the fuzzy neural network is designed based on the error between the real UMV heading angle and designed reference heading angle, so as to further adjust the weight parameter of the GDFNN, and then, the output control value of the neural network is obtained. In order to further reduce the computation amount and computation time of the RAFNNC, the parameters of the PID control algorithm were optimized in advance by using the improved BFO algorithm. The fractal dimension step size and the intelligent probe operation are integrated into the BFO algorithm, in order to optimize the operation time and accuracy of the algorithm. Stability of the designed RAFNNC algorithm for the heading control of the UMV in the presence of complex marine environment disturbance is proved by the Lyapunov stability theory, and the effectiveness and accuracy of the control algorithm proposed are verified by semi-physical simulation experiment carried out in our laboratory.

Abstract Summertime ecosystem respiration (ER) rates through seven sites were measured at an upland tundra on Fildes Peninsula in maritime Antarctica to investigate effects of topographic gradient, vegetation types and climatic factors on tundra ER rates. Overall the highest ER rates occurred at the tundra top, followed at the middle slope, and the lowest rates at the lower slope. The daily highest ER rates occurred at noon whereas the lowest at 6 am. There was a significant positive correlation (P

The present study aimed to establish a simple and rapid method for the preparation of pure delphinidin-3-O-sambubioside (D3S) from Roselle and then investigate its antioxidant and hypoglycemic activity. According to our results, 60 mg of D3S with the purity of 96.1% was finally isolated from 500 g of Roselle by combination of macroporous resins and C18 Sep-Pak cartridge techniques. Further studies revealed that D3S could significantly attenuate H2O2-induced oxidative stress by inhibiting H2O2-induced ROS overproduction, GSH depletion, mitochondrial membrane potential decrease and mitochondrial membrane peroxidation. In addition, we also found that D3S at the concentrations of 20 μg/mL and 40 μg/mL are able to promote glucose consumption and increase glycogen content in human liver HepG2 cells. These results indicated that D3S possesses potent antioxidant activity and hypoglycemic activity. Overall, our studies suggest that D3S could be a valuable material for designing functional foods against oxidative stress-related diseases and diabetes.

Emerging evidence suggests that anthocyanins prevent type 2 diabetes (T2D), however, its mechanisms remain elusive. Herein, we sought to elucidate the antihyperglycemic mechanism of pelargonidin-3-O-glucoside (Pg3G) extracted from wild raspberry based on RNA-sequence. Our study showed that Pg3G ameliorated glucose intolerance and insulin resistance in db/db mice. Besides, Pg3G improved serum lipid profiles and attenuated hepatic dysfunction. RNA-sequence analysis showed that Pg3G contributed to 301 genes upregulated and 269 genes downregulated. Further GO, KEGG and GSEA analysis indicated that Pg3G led to differential gene expressions enriched in glucose and lipid metabolism by upregulation of Elovl7, C1ql3, Cybb, Cytip, Src, Pdk4 and downregulation of Fasn, Aacs, Srebp1c, Mlxipl, Sorbs3, Gck, Slc2a4. RT-PCR validation of selected genes exhibited a positive correlation between RNA-sequence and RT-PCR results. Taken together, this study demonstrated that Pg3G attenuated T2D by regulating glucose and lipid metabolism, which implicates the potential for T2D therapeutics.

Fruits tend to possess different nutritional values among different cultivars of same family. Therefore, in this study, the composition and antioxidant activity of some new and common bayberry cultivars were evaluated. Significant amounts of phenolics (0.47 to 2.31 g gallic acid equivalents/kg), flavonoids (0.34 to 2.08 g rutin equivalents/kg) and procyanidins (0.24 to 1.99 g catechin equivalents/kg) were found in all tested bayberry varieties. Anthocyanin cyanidin-3-glucoside and flavonol myricetin was detected in almost all cultivars, however, cyanidin-3-glucoside was not detected in new cultivar Xishanbai. Antioxidant activity of bayberry was highly correlated with contents of phenolics, including flavonoids. However, no positive correlation was observed between cellular reactive oxygen species scavenging ability and bioactive compounds. The new cultivar Yingsi was found to have higher levels of nutritional components and potent antioxidant activity among all tested cultivars.

Mulberry is a delicious fruit with high nutritional value. However, there are significant differences in the nutritional values among different mulberry cultivars. Therefore, in this study, the composition of some new and common mulberry cultivars was compared and their potential antioxidant activity evaluated. HPLC and LC–MS analyses revealed that mulberry fruits are rich in polyphenols such as cyanidin-3-O-glucoside (1.25–3.35 g/kg), cyanidin-3-O-rutinoside (0.25–1.50 g/kg), rutin (0.01–0.12 g/kg) and quercetin (0.0068–0.0081 g/kg). Correlation studies explained that the antioxidant activity of mulberry cultivars was closely associated with phenolics, including flavonoids. However, weak correlation was observed between cellular reactive oxygen species (ROS) scavenging ability and bioactive components. Besides, principal component analysis was employed to compare the differences between mulberry cultivars. Concerning high content of nutritional components and antioxidant activity, Hanguo variety was found to be the most beneficial and commercial cultivar among all the tested varieties.

Let be a sequence of positive independent and identically distributed random variables with common Pareto-type distribution function as , where represents a slowly varying function at infinity. In this note we study the strong convergence bound of a kind of right censored Pareto index estimator under second-order regularly varying conditions.

Background: Neutrophil-to-lymphocyte ratio (NLR) is a promising prognostic marker for patients undergoing hepatectomy for colorectal liver metastases (CRLM). However, its prognostic value in patients receiving neoadjuvant therapy (NAT) has not been sufficiently addressed. Methods: From 2013 to 2023, a cohort of 692 patients with CRLM receiving hepatectomy were enrolled in five centers. Clinicopathological characteristics were obtained from a prospectively maintained multi-center database. The effect of NLR (> 2 versus ≤ 2) on overall survival (OS) and recurrence-free survival was estimated by Kaplan–Meier analysis. Univariable and multivariable Cox regression analysis was applied to investigate the influence of individual clinicopathological parameters on OS. Results: In the entire cohort, the median NLR level was 2.11 (0.30–16.33). There were 307 (44.4%) patients receiving NAT followed by hepatectomy, while 385 (55.6%) patients undergoing upfront surgery. Notably, patients in the NAT group showed significantly lower NLR level than those in the upfront surgery group (1.83 versus 2.32, P < 0.001). In the upfront surgery group, high NLR was significantly associated with worse OS, independent of other factors (HR = 1.49, 95% CI 1.08–2.05, P = 0.02). In the NAT group, there was no significant difference in OS between the high NLR and low NLR group. Conclusion: The prognostic value of NLR in surgically resected CRLM is potentially influenced by NAT in the modern era. [ABSTRACT FROM AUTHOR]

The stability problem of power grids has become increasingly serious in recent years as the size of novel power systems increases. In order to improve and ensure the stable operation of the novel power system, this study proposes an artificial emotional lazy Q-learning method, which combines artificial emotion, lazy learning, and reinforcement learning for static security and stability analysis of power systems. Moreover, this study compares the analysis results of the proposed method with those of the small disturbance method for a stand-alone power system and verifies that the proposed lazy Q-learning method is able to effectively screen useful data for learning, and improve the static security stability of the new type of power system more effectively than the traditional proportional-integral-differential control and Q-learning methods. [ABSTRACT FROM AUTHOR]