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A novel energy storage mode based on the vehicle-to-grid (V2G) and vehicle-to-vehicle (V2V) concept will be greatly researched and applied as a new green solution to energy and environmental problems. However, the existing research on battery capacity decline in V2G applications has mainly focused on modeling the battery capacity to investigate its decline during vehicle charging and discharging, in order to reduce the battery capacity decline and evaluate its economics. A car-following model with the acceleration generalized force coupled with external resistance is proposed in the paper. A linear stability analysis was used to analyze the stability of the model. The stability of the traffic flow was improved when the value of the resistance coefficient increases. Then, the currents of different vehicles were also calculated according to the velocities. Moreover, the effect of different physical characteristics of driving on the decline of distributed energy storage batteries in the Internet of Vehicles (IoV) was investigated. The results suggest that in different road types and road slopes, vehicles which are at the end of the platoon position have less battery capacity degradation and better battery condition. It provides a reference for subsequent research related to V2G energy storage in the context of vehicle networking.

Rice disease has serious negative effects on crop yield, and the correct diagnosis of rice diseases is the key to avoid these effects. However, the existing disease diagnosis methods for rice are neither accurate nor efficient, and special equipment is often required. In this study, an automatic diagnosis method was developed and implemented in a smartphone app. The method was developed using deep learning based on a large dataset that contained 33,026 images of six types of rice diseases: leaf blast, false smut, neck blast, sheath blight, bacterial stripe disease, and brown spot. The core of the method was the Ensemble Model in which submodels were integrated. Finally, the Ensemble Model was validated using a separate set of images. Results showed that the three best submodels were DenseNet-121, SE-ResNet-50, and ResNeSt-50, in terms of several attributes, such as, learning rate, precision, recall, and disease recognition accuracy. Therefore, these three submodels were selected and integrated in the Ensemble Model. The Ensemble Model minimized confusion among the different types of disease, reducing misdiagnosis of the disease. Using the Ensemble Model to diagnose six types of rice diseases, an overall accuracy of 91% was achieved, which is considered to be reasonably good, considering the appearance similarities in some types of rice disease. The smartphone app allowed the client to use the Ensemble Model on the web server through a network, which was convenient and efficient for the field diagnosis of rice leaf blast, false smut, neck blast, sheath blight, bacterial stripe disease, and brown spot.

Esophageal cancer (EC) is a common malignant tumor with poor prognosis, and current treatments for patients with advanced EC remain unsatisfactory. Recently, immunotherapy has been recognized as a new and promising approach for various tumors. EC cells present a high tumor mutation burden and harbor abundant tumor antigens, including tumor-associated antigens and tumor-specific antigens. The latter, also referred to as neoantigens, are immunogenic mutated peptides presented by major histocompatibility complex class I molecules. While current genomics and bioinformatics technologies have greatly facilitated the identification of tumor neoantigens, identifying individual neoantigens systematically for successful therapies remains a challenging problem. Owing to the initiation of strong, specific tumor-killing cytotoxic T cell responses, neoantigens are emerging as promising targets to develop personalized treatment and have triggered the development of cancer vaccines, adoptive T cell therapies, and combination therapies. This review aims to give a current understanding of the clinical application of neoantigens in EC and provide direction for future investigation.

In order to improve the sowing performance of air-pressure maize dense planting high-speed precision seed-metering device and reduce the occurrence of multiple and missed seeds phenomenon, a seed-cleaning mechanism with progressive seed scraper was designed. The structure and working principle of the seed- metering device and seed-cleaning mechanism are described, the mechanical model before and after the excess seed enters the seed cleaning area is established, and the design parameters of the key components of the seed-cleaning mechanism are determined through the method of theoretical analysis. The experiments of single-factor and multi-factor are conducted with seed clearing angle, operating speed, positive pressure value of blower as influencing factors, and with qualified index, miss index, multiple index as the experimental indexes. The results show that the optimal seed-clearing performance parameter combination of the seed-cleaning mechanism is seed-clearing angle of 0.024°, operating speed of 10 km/h, positive pressure value of 6.0 kPa, verification test of the parameter combination of the qualified index of 98.11%, multiple index of 1.44%, miss index of 0.45%. In the comparative experiment, the qualified index of the device with seed-cleaning mechanism increased by about 2.3% compared to the device without seed-cleaning mechanism, and the multiple index decreased by about 2.2%. The seed-cleaning mechanism is reasonably designed to meet the seed clearing operation requirements of air-pressure maize dense planting high-speed precision seed- metering device. [ABSTRACT FROM AUTHOR]

An assessment of the causal treatment effect in the development and progression of certain diseases is important in clinical trials and biomedical studies. However, it is not possible to infer a causal relationship when the treatment assignment is imbalanced and confounded by other mechanisms. Specifically, when the treatment assignment is not randomized and the primary outcome is binary, a conventional logistic regression may not be valid to elucidate any causal inference. Moreover, exclusively capturing all confounders is extremely difficult and even impossible in large-scale observational studies. We propose a multiple-model-based robust (MultiMR) estimator for estimating the causal effect with a binary outcome, where multiple propensity score models and conditional mean imputation models are used to ensure estimation robustness. Furthermore, we propose an enhanced MultiMR (eMultiMR) estimator that reduces the estimation variability of MultiMR estimates by incorporating secondary outcomes that are highly correlated with the primary binary outcome. The resulting estimates are less sensitive to model mis-specification compared to those based on state-of-the-art doubly-robust methods. These estimates are verified through both theoretical and numerical assessments. The utility of (e)MultiMR estimation is illustrated using the Uniform Data Set (UDS) from the National Alzheimer's Coordinating Center with the objective of detecting the causal effect of the short-term use of antihypertensive medications on the development of dementia or mild cognitive impairment. The proposed method has been implemented in an R package and is available at. [ABSTRACT FROM AUTHOR]

There has been an increasing interest in decomposing high-dimensional multi-omics data into a product of low-rank and sparse matrices for the purpose of dimension reduction and feature engineering. Bayesian factor models achieve such low-dimensional representation of the original data through different sparsity-inducing priors. However, few of these models can efficiently incorporate the information encoded by the biological graphs, which has been already proven to be useful in many analysis tasks. In this work, we propose a Bayesian factor model with novel hierarchical priors, which incorporate the biological graph knowledge as a tool of identifying a group of genes functioning collaboratively. The proposed model therefore enables sparsity within networks by allowing each factor loading to be shrunk adaptively and by considering additional layers to relate individual shrinkage parameters to the underlying graph information, both of which yield a more accurate structure recovery of factor loadings. Further, this new priors overcome the phase transition phenomenon, in contrast to existing graph-incorporated approaches, so that it is robust to noisy edges that are inconsistent with the actual sparsity structure of the factor loadings. Finally, our model can handle both continuous and discrete data types. The proposed method is shown to outperform several existing factor analysis methods through simulation experiments and real data analyses. [ABSTRACT FROM AUTHOR]

Abstract Background The authors presented a 63-year old female synchronously complicated with a thymic tumor located at the left-side of the superior mediastinum, and a paravertebral tumor located at the right-side of the lower thorax. Conventional thoracoscopic surgical procedure using rigid instruments to simultaneously resect the two tumors via the same ports might be technically challenging. To our knowledge, the use of a surgical robot allowed the surgeon to perform precise dissection from extreme angles with the characteristic of articulating surgical instruments. Case presentation Two lesions were successfully dissected using the da Vinci Surgical System through the same four ports on the right side of the chest and two-step docking. Firstly, the patient cart came from the dorsal side of the patient and the paravertebral neoplasm was dissected. Afterwards, the patient cart was undocked and the operation table was rotated 180 degrees counterclockwise. The robot was re-introduced and the patient cart came from the ventral side of the patient and the whole thymus was resected. Conclusion This case report suggests that two-step docking via the same four ports for these two tumors located at different directions of the thorax was safe and effective, demonstrating a clear advantage of the surgical robot.

Spermatogenesis, sperm motility, and apoptosis are dependent on the regulation of glandular hormones and mitochondria. Natural astaxanthin (ASTA) has antioxidant, anti-inflammatory, and anti-apoptotic properties. The present study evaluates the effects of ASTA on testosterone synthesis and mitochondrial function in aging roosters. Jinghong No. 1 layer breeder roosters (n = 96, 53-week old) were fed a corn–soybean meal basal diet containing 0, 25, 50, or 100 mg/kg ASTA for 6 weeks. The levels of plasma reproductive hormones and the mRNA and protein levels of molecules related to testosterone synthesis were significantly improved (p < 0.05) in the testes of the ASTA group roosters. In addition, antioxidant activities and free radical scavenging abilities in roosters of the ASTA groups were higher than those of the control group (p < 0.05). Mitochondrial electron transport chain complexes activities and mitochondrial membrane potential in sperm increased linearly with dietary ASTA supplementation (p < 0.05). The levels of reactive oxygen species and apoptosis factors decreased in roosters of the ASTA groups (p < 0.05). Collectively, these results suggest that dietary ASTA may improve testosterone levels and reduce sperm apoptosis, which may be related to the upregulation of the testosterone synthesis pathway and the enhancement of mitochondrial function in aging roosters.

Necroptosis is a form of programmed cell death (PCD) characterized by RIP3 mediated MLKL activation and increased membrane permeability via MLKL oligomerization. Tumor cell immunogenic cell death (ICD) has been considered to be essential for the anti-tumor response, which is associated with DC recruitment, activation, and maturation. In this study, we found that P. aeruginosa showed its potential to suppress tumor growth and enable long-lasting anti-tumor immunity in vivo. What’s more, phosphorylation- RIP3 and MLKL activation induced by P. aeruginosa infection resulted in tumor cell necrotic cell death and HMGB1 production, indicating that P. aeruginosa can cause immunogenic cell death. The necrotic cell death can further drive a robust anti-tumor response via promoting tumor cell death, inhibiting tumor cell proliferation, and modulating systemic immune responses and local immune microenvironment in tumor. Moreover, dying tumor cells killed by P. aeruginosa can catalyze DC maturation, which enhanced the antigen-presenting ability of DC cells. These findings demonstrate that P. aeruginosa can induce immunogenic cell death and trigger a robust long-lasting anti-tumor response along with reshaping tumor microenvironment.

Sanggou Bay is well known as an exemplary coastal water of Integrated Multi-Trophic Aquaculture (IMTA). IMTA as practiced in China is highly ecologically efficient, through the combination of extractive and fed species. In this paper, Ecopath model was used to study the food web structure and function of Sanggou Bay ecosystem. According to the model, Sanggou Bay ecosystem ranged from 1.00–3.89 in trophic level. Sanggou Bay ecosystem was dominated by low trophic levels, of which aggregated trophic level I and II (TL I and TL II). TL I and TL II contributed 83.64 % and 16.36 % in biomass. Aquaculture species (kelp, oyster, scallop and abalone) were all in TL I and TL II, together accounted for 97.30 % in biomass of all functional groups. Kelp accounted for 81.12 % of the total biomass. Transfer efficiency of the ecosystem was 10.85 %. Aquaculture harvest had a positive influence on scallop, oyster and kelp, but had a negative influence on abalone. All functional groups in Sanggou Bay ecosystem had negative self-impacts, that could be interpreted as intraspecific competition for resources. Oyster, scallop and abalone showed negative impacts on each other. From the system properties, connectance index (CI) was 0.26 and system omnivory index (SOI) was 0.08, these suggested that Sanggou Bay was influenced by human activities. The ratio of production to respiration (P/R) was 3.57, the ecosystem production is much more than respiration. This presented that IMTA in Sanggou Bay showed a way to minimize the disturbance of aquaculture to protect the ecosystem and improve economic benefits for stakeholders. This paper may provide reference for research and management of ecosystem structure and function of aquaculture waters. Keywords: Keyword, Sanggou Bay, Integrated multi-trophic aquaculture, Ecopath, Food web structure, Ecosystem attributes

The study aims to explore the comprehensive reasons for patients' non-compliance with graded elastic compression stockings (GECS) as the treatment for lower limb varicose veins. Phenomenological analysis was applied in this qualitative study. The patients diagnosed with lower limb varicose veins and undergoing elective surgery who showed non-compliance with GECS as the treatment were invited to have semi-structured, in-depth, face-to-face interviews. Colaizzi method was employed to analyze the data for emerging themes associated with the reasons for patients' non-compliance. Four main themes and nine subthemes related to the reasons for non-compliance with GECS for lower limb varicose veins were summarized. The main themes that emerged were (1) gaps in the knowledge of GECS therapy as a treatment for lower limb varicose veins, (2) few recommendations from the doctors and nurses, (3) disadvantages of GECS, and (4) sociopsychological factors. These themes provide data for policy and planning to improve patients' compliance with GECS in China. Patients, healthcare professionals, and policy makers should share the responsibility to improve patients' compliance with GECS therapy.

Fertilizer discharge process is a critical part of fertilizer application, as it affects the fertilizer discharge rate and uniformity of fertilizer application. In this study, a spiral grooved-wheel fertilizer discharge device was designed to replace the conventional straight grooved-wheel. Comparisons of the fertilizer discharge performance of the two grooved-wheel types were performed through tests and simulations using the discrete element method (DEM). The discharge performance of the two discharge devices was assessed by measuring the discharge mass rate, discharge uniformity, and the falling velocity of the fertilizer particles. Results showed that under similar conditions, the fertilizer discharge mass rate of the spiral grooved-wheel was higher than that of the straight grooved-wheel. The fertilizer discharge uniformity of the spiral grooved-wheel was much better than that of the straight grooved-wheel. The average falling velocity of fertilizer particles through the discharge spout was higher under the spiral grooved-wheel. The relative errors between the test and simulation results for the discharge mass rates, discharge uniformity, and particle falling velocities of the spiral grooved-wheel were all less than 10%. The developed spiral grooved-wheel exhibited a better performance than the conventional straight grooved-wheel, in all the aspects examined. The results serve as a theoretical basis for guiding the design of high-performance fertilizer applicators.

Abstract Background We performed a meta-analysis to compare the efficacy of definitive chemoradiotherapy (dCRT) and esophagectomy as initial treatments for potentially resectable esophageal cancer. Methods To assess both strategies, the combined odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Thirteen studies (N = 2071; dCRT = 869 and surgery = 1202) were included. In all, 90.39% of the patients were diagnosed with esophageal squamous cell carcinoma (ESCC). Results The 2-year (OR = 1.199, 95% CI 0.922–1.560; P = 0.177) and 5-year overall survival (OS) rates (OR = 0.947, 95% CI 0.628–1.429; P = 0.796) were not significantly different. No significant differences were identified in the 2-year OS among patients with stage I disease (OR = 1.397, 95% CI 0.740–2.638; P = 0.303) or stage II–III (OR = 0.418, 95% CI 0.022–7.833; P = 0.560). Patients with lymph node metastases tended to have a better 5-year OS when treated with dCRT than with surgery (OR = 0.226, 95% CI 0.044–1.169; P = 0.076); however, the difference between the two methods was not significant. Western patients who received dCRT had poorer prognoses than patients who underwent surgery (OR = 1.522, 95% CI 1.035–2.238; P = 0.033). dCRT and surgery led to similar 5-year progression-free survival rates (OR = 1.06, 95% CI 0.79–1.42; P = 0.70). Conclusions dCRT and surgery are equally effective as initial treatments for potentially resectable esophageal cancer. These results apply primarily to Asian populations as they have an increased incidence of ESCC.

Abstract Background Few studies have shown nomograms that may predict disease-specific survival (DSS) probability after curative D2 gastrectomy for advanced gastric cancer (AGC), particularly among Chinese patients. This study sought to develop an elaborative nomogram that predicts long-term DSS for AGC in Chinese patients. Methods A retrospective study was conducted on 6753 AGC patients undergoing D2 gastrectomy between January 1, 2000 and December 31, 2012 from three large medical hospitals in China. We assigned patients from Sun Yat-sen University Cancer Center to the training set, and patients from the First Affiliated Hospital of China Medical University and Tianjin Medical University Cancer Hospital to two separate external validation sets. A multivariate survival analysis was performed using Cox proportional hazards regression model in a training set, and a nomogram was constructed. Harrell’s C-index was used to evaluate discrimination and calibration plots were used to validate similarities between survival probabilities predicted by the nomogram model and actual survival rates in two validation sets. Results The multivariate Cox regression model identified age, tumor size, location, Lauren classification, lymphatic/venous invasion, depth of invasion, and metastatic lymph node ratio as covariates associated with survival. In the training set, the nomogram exhibited superior discrimination power compared with the 8th American Joint Committee on Cancer TNM classification (Harrell’s C-index, 0.82 vs. 0.74; P