Monthly extended ocean predictions based on a convolutional neural network via the transfer learning method

Sea surface temperature anomalies (SSTAs) and sea surface height anomalies (SSHAs) are indispensable parts of scientific research, such as mesoscale eddy, current, ocean-atmosphere interaction and so on. Nowadays, extended-range predictions of ocean dynamics, especially in SSTA and SSHA, can provide daily prediction services in the range of 30 days, which bridges the gap between synoptic-scale weather forecasts and monthly average scale climate predictions. However, the forecast efficiency of extended range remains problematic. With the development of ocean reanalysis and satellite remote sensing products, large amounts datasets provide an unprecedented opportunity to use big data for the extended range prediction of ocean dynamics. In this study, a hybrid model, combing convolutional neural network (CNN) model with transfer learning (TL), was established to predict SSTA and SSHA at monthly scales, which makes full use of these data resources that arise from delayed gridding reanalysis products and real-time satellite remote sensing observations. The proposed model, where both ocean and atmosphere reanalysis datasets serve as the pretraining dataset and the satellite remote sensing observations are employed for fine-tuning based on the transfer learning (TL) method, can effectively capture the evolving spatial characteristics of SSTAs and SSHAs with low prediction errors over the 30 days range. When the forecast lead time is 30 days, the root means square errors for the SSTAs and SSHAs model results are 0.32°C and 0.027 m in the South China Sea, respectively, indicating that this model has not only satisfactory prediction performance but also offers great potential for practical operational applications in improving the skill of extended-range predictions

Comparison of PET/CT and MRI in the Diagnosis of Bone Metastasis in Prostate Cancer Patients: A Network Analysis of Diagnostic Studies

Background: Accurate diagnosis of bone metastasis status of prostate cancer (PCa) is becoming increasingly more important in guiding local and systemic treatment. Positron emission tomography/computed tomography (PET/CT) and magnetic resonance imaging (MRI) have increasingly been utilized globally to assess the bone metastases in PCa. Our meta-analysis was a high-volume series in which the utility of PET/CT with different radioligands was compared to MRI with different parameters in this setting. Materials and Methods: Three databases, including Medline, Embase, and Cochrane Library, were searched to retrieve original trials from their inception to August 31, 2019 according to the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) statement. The methodological quality of the included studies was assessed by two independent investigators utilizing Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). A Bayesian network meta-analysis was performed using an arm-based model. Absolute sensitivity and specificity, relative sensitivity and specificity, diagnostic odds ratio (DOR), and superiority index, and their associated 95% confidence intervals (CI) were used to assess the diagnostic value. Results: Forty-five studies with 2,843 patients and 4,263 lesions were identified. Network meta-analysis reveals that 68Ga-labeled prostate membrane antigen (68Ga-PSMA) PET/CT has the highest superiority index (7.30) with the sensitivity of 0.91 and specificity of 0.99, followed by 18F-NaF, 11C-choline, 18F-choline, 18F-fludeoxyglucose (FDG), and 18F-fluciclovine PET/CT. The use of high magnetic field strength, multisequence, diffusion-weighted imaging (DWI), and more imaging planes will increase the diagnostic value of MRI for the detection of bone metastasis in prostate cancer patients. Where available, 3.0-T high-quality MRI approaches 68Ga-PSMA PET/CT was performed in the detection of bone metastasis on patient-based level (sensitivity, 0.94 vs. 0.91; specificity, 0.94 vs. 0.96; superiority index, 4.43 vs. 4.56). Conclusions: 68Ga-PSMA PET/CT is recommended for the diagnosis of bone metastasis in prostate cancer patients. Where available, 3.0-T high-quality MRI approaches 68Ga-PSMA PET/CT should be performed in the detection of bone metastasis

Nutlin-3 overcomes arsenic trioxide resistance and tumor metastasis mediated by mutant p53 in Hepatocellular Carcinoma

Background: Arsenic trioxide has been demonstrated as an effective anti-cancer drug against leukemia and solid tumors both in vitro and in vivo. However, recent phase II trials demonstrated that single agent arsenic trioxide was poorly effective against hepatocellular carcinoma (HCC), which might be due to drug resistance. Methods: Mutation detection of p53 gene in arsenic trioxide resistant HCC cell lines was performed. The therapeutic effects of arsenic trioxide and Nutlin-3 on HCC were evaluated both in vitro and in vivo. A series of experiments including MTT, apoptosis assays, co-Immunoprecipitation, siRNA transfection, lentiviral infection, cell migration, invasion, and epithelial-mesenchy-mal transition (EMT) assays were performed to investigate the underlying mechanisms. Results: The acquisition of p53 mutation contributed to arsenic trioxide resistance and enhanced metastatic potential of HCC cells. Mutant p53 (Mutp53) silence could re-sensitize HCC resistant cells to arsenic trioxide and inhibit the metastatic activities, while mutp53 overexpression showed the opposite effects. Neither arsenic trioxide nor Nutlin-3 could exhibit obvious effects against arsenic trioxide resistant HCC cells, while combination of them showed significant effects. Nutlin-3 can not only increase the intracellular arsenicals through inhibition of p-gp but also promote the p73 activation and mutp53 degradation mediated by arsenic trioxide. In vivo experiments indicated that Nutlin-3 can potentiate the antitumor activities of arsenic trioxide in an orthotopic hepatic tumor model and inhibit the metastasis to lung. Conclusions: Acquisitions of p53 mutations contributed to the resistance of HCC to arsenic trioxide. Nutlin-3 could overcome arsenic trioxide resistance and inhibit tumor metastasis through p73 activation and promoting mutant p53 degradation mediated by arsenic trioxide

Diffusion Filters for Variational Data Assimilation of Sea Surface Temperature in an Intermediate Climate Model

Sequential, adaptive, and gradient diffusion filters are implemented into spatial multiscale three-dimensional variational data assimilation (3DVAR) as alternative schemes to model background error covariance matrix for the commonly used correction scale method, recursive filter method, and sequential 3DVAR. The gradient diffusion filter (GDF) is verified by a two-dimensional sea surface temperature (SST) assimilation experiment. Compared to the existing DF, the new GDF scheme shows a superior performance in the assimilation experiment due to its success in extracting the spatial multiscale information. The GDF can retrieve successfully the longwave information over the whole analysis domain and the shortwave information over data-dense regions. After that, a perfect twin data assimilation experiment framework is designed to study the effect of the GDF on the state estimation based on an intermediate coupled model. In this framework, the assimilation model is subject to “biased” initial fields from the “truth” model. While the GDF reduces the model bias in general, it can enhance the accuracy of the state estimation in the region that the observations are removed, especially in the South Ocean. In addition, the higher forecast skill can be obtained through the better initial state fields produced by the GDF

Prevalence of gastroparesis in diabetic patients: a systematic review and meta-analysis

Abstract Although there was no significant heterogeneity in the meta-publication, sensitivity analyses revealed significant heterogeneity. Overall, the prevalence was higher in women (N = 6, R = 4.6%, 95% CI 3.1%, 6.0%, and I2 = 99.8%) than in men (N = 6, R = 3.4%, 95% CI 2.0%, 4.7%, and I2 = 99.6the %); prevalence of type 2 diabetes (N = 9, R = 12.5%, 95% CI 7.7%, 17.3%, and I2 = 95.4%) was higher than type 1 diabetes (N = 7, R = 8.3%, 95% CI 6.4%, 10.2%, and I2 = 93.6%); the prevalence of DGP was slightly lower in DM patients aged over 60 years (N = 6, R = 5.5%, 95% CI 3.3%, 7.7%, and I2 = 99.9%) compared to patients under 60 years of age (N = 12, R = 15.8%, 95% CI 11 15.8%, 95% CI 11.4%, 20.2%, and I2 = 88.3%). In conclusion, our findings indicate that the combined estimated prevalence of gastroparesis in diabetic patients is 9.3%. However, the sensitivity of the results is high, the robustness is low, and there are significant bias factors. The subgroup analysis revealed that the prevalence of DM-DGP is associated with factors such as gender, diabetes staging, age, and study method

Adsorption Mechanism of Anionic Groups Found in Sulfonated Mulberry Stem Chemi-Mechanical Pulp (SCMP) for Removal of Methylene Blue Dye

The anionic groups (AGs) present in mulberry stem sulfonated chemi-mechanical pulp (SCMP) were studied relative to the adsorption of methylene blue (MB) dye. Adsorption isotherm experiments were carried out for the unbleached pulp, and for pulp that had been subjected to hydrogen peroxide (H2O2) bleaching. AGs present in the pulps appeared to govern the adsorption of MB. MB adsorption kinetics were evaluated for the bleached pulp. The methylene blue adsorption by SCMP, made from mulberry stems, conformed to the Langmuir adsorption model, which is consistent with a monolayer adsorption process. The adsorption thermodynamics showed that the adsorption process was spontaneous and exothermic. A pseudo-second order kinetic model described the adsorption mechanism of MB by the SCMP made from mulberry stems

The noteworthy mechanical difference and diverse substrate damage of coatings via molecular dynamics

For previous studies have neglected the effect of coating thickness and crystal plane on materials deformation during machining, this work is to investigate how coating thickness affect materials deformation with distinct crystal orientation. Using the nanoindentation technique, the mechanical response and plastic deformation of Cu substrate containing FeNiCrCoCu high-entropy alloy coating are investigated. This work provides direct evidence that coating thickness influences the deformation behavior of the workpiece at the atomic level. The results show that the crystal orientation influenced the change of the load–displacement and the deformation behavior, i.e., the mechanical feedback of different crystal planes to the nanoindentation was different, and even the opposite phenomenon occurred with the increase of coating thickness. The anisotropy of the internal phase transition patter and surface morphology deformation in different crystal planes were analyzed by the crystallographic analysis. The work offer microstructure information support for the effect of material anisotropy, coating thickness, and coating atoms on substrate defect-formation, defect/defect interactions, strengthening mechanisms upon loading

Bus Fleet Accident Prediction Based on Violation Data: Considering the Binding Nature of Safety Violations and Service Violations

The number and severity of bus traffic accidents are increasing annually. Therefore, this paper uses the historical data of Chongqing Liangjiang Public Transportation Co., Ltd. bus driver safety violations, service violations, and road traffic accidents from January to June 2022 and constructs road traffic accident prediction models using Extra Trees, BP Neural Network, Support Vector Machine, Gradient Boosting Tree, and XGBoost. The effects of safety and service violations on vehicular accidents are investigated. The quality of the prediction models is measured by five indicators: goodness of fit, mean square error, root mean square error, mean absolute error, and mean absolute percentage error. The results indicate that the XGBoost model provides the most accurate predictions. Additionally, simultaneously considering safety and service violations can improve the accuracy of the model’s predictions compared to a model that only considers safety violations. Bus safety violations, bus service violations, and bus safety operation violations significantly influence traffic accidents, which account for 27.9%, 20%, and 16.5%, respectively. In addition to safety violations, the service violation systems established by bus companies, such as bus service codes, can be an effective method of regulating the behavior of bus drivers and reducing accidents. They are improving both the safety and quality of public transportation