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The prevalence of extreme weather events gives rise to a significant degree of prediction bias in the forecasting of photovoltaic (PV) power. In order to enhance the precision of forecasting outcomes, this study examines the interrelationships between China's 24 conventional solar terms and extreme meteorological events. Additionally, it proposes a methodology for estimating the short-term generation of PV power based on the division of solar term time series. Firstly, given that the meteorological data from the same festival is more representative of the climate state at the current prediction moment, the sample data are grouped according to the 24 festival time nodes. Secondly, a convolutional neural network–long short-term memory (CNN-LSTM) PV power prediction model based on an Attention mechanism is proposed. This model extracts temporal change information from nonlinear sample data through LSTM, and a CNN link is added at the front end of LSTM to address the issue of LSTM being unable to obtain the spatial linkage of multiple features. Additionally, an Attention mechanism is incorporated at the back end of the CNN to obtain the feature information of crucial time steps, further reducing the multi-step prediction error. Concurrently, a PV power error prediction model is constructed to rectify the outcomes of the aforementioned prediction model. The examination of the measured data from PV power stations and the comparison and analysis with other prediction models demonstrate that the model presented in this paper can effectively enhance the accuracy of PV power predictions. [ABSTRACT FROM AUTHOR]

The short-term fluctuation of wind power can affect its prediction accuracy. Thus, a short-term segmentation prediction method of wind power based on ramp segment division is proposed. A time-series trend extraction method based on moving average iteration is proposed on the full-time period to analyze the real-time change characteristics of power time-series initially; secondly, a ramp segment extraction method based on its definition and identification technique is proposed based on the results of the trend extraction; and a segmentation prediction scheme is proposed to lean the power prediction under different time-series: the LightGBM-LSTM is proposed for the non-ramping segment using point prediction, and the CNN-BiGRU-KDE is proposed for probabilistic prediction of ramp segments. From the results, this ramp segment definition and identification technique can effectively identify the ramp process of wind power, which makes up for the misidentification and omission of the classical climbing event definition; meanwhile, the segment prediction scheme not only meets the prediction accuracy requirements of the non-ramping segment, but also provides the effective robust information for the prediction of the ramping period, which offers reliable reference information for the actual wind farms. In particular, it is well adapted to wind power prediction under extreme working conditions caused by ramping weather, which is a useful addition to short-term wind power prediction research. [ABSTRACT FROM AUTHOR]

Two types of common mode voltage (CMV) exist in medium-voltage motor drive system based on modular multilevel converter (MMC) type topology, that are, arms CMV (ACMV) and system CMV (SCMV). The former will produce circulating current between phases, and the latter will do harm to the motor. This article proposes a suppression scheme of CMV with a dual dc bus MMC-based solid-state transformer (DBM2C-SST) based drive system. The horizontal submodules (SMs) of MMC are cascaded with a quadruple-active-bridge (QAB), then a low voltage is formed. Plus the original medium voltage bus, the system is characteristic as a dual dc bus. The primary triple-active-bridge of QAB which characterized by low-impedance and synchronous-switching helps to achieve the natural suppression of the fluctuating voltage of the MMC horizontal three SMs within the entire operating frequency range under the relevant modulation strategy, thus realizing the full suppression of ACMV and low-frequency components suppression of SCMV simultaneously, and with the additional minimum method of SCMV high-frequency components, the DBM2C-SST can achieve zero CMV. As the SMs fluctuating voltage and CMV are decreased, the values of SMs capacitance and arms inductance can be significantly reduced. [ABSTRACT FROM AUTHOR]

Background: The tumor microenvironment (TME) has recently been proven to play a crucial role in the development and prognosis of tumors. However, the current knowledge on the potential of the TME in prostate cancer (PCa) remains scarce. Purpose: This study aims to elucidate the value of TME-related genes for PCa prognosis by integrative bioinformatics analysis. Materials and Methods: We downloaded the immune and stromal scores of PCa samples via the ESTIMATE and correlated these scores to clinicopathological characteristics and recurrence-free survival (RFS) of patients. Based on these scores, the TME-related differentially expressed genes were identified for functional enrichment analysis. Cox regression analyses were performed to identify prognostic genes and establish a predictive risk model. Moreover, gene set enrichment analysis (GSEA) was performed to evaluate the relationship between risk score and immune pathway. Results: The stromal and immune scores were associated with clinicopathological characteristics and RFS in PCa patients. In total, 238 intersecting differentially expressed genes were identified. Functional enrichment analysis further revealed that these genes dramatically participated in the immune-related pathways. The immune-related risk model was built with C-type lectin domain containing 7A (CLEC7A) and collagen type XI alpha 1 chain (COL11A1) using Cox regression analyses. Kaplan–Meier survival analysis showed that the expression levels of CLEC7A and COL11A1 were significantly associated with the RFS. Further, the RFS time in high-risk group was significantly shorter than that in low-risk group. The areas under the curve for the risk model in predicting 3- and 5-year RFS rates were 0.694 and 0.731, respectively. GSEA suggested that immunosuppression existed in high-risk PCa patients. Conclusion: CLEC7A and COL11A1 were selected to build a predictive risk model, which may help clinicians to assess the prognosis of PCa patients and select appropriate targets for immunotherapy. [ABSTRACT FROM AUTHOR]

Background: Dyslipidemia is a major health problem in China and an important modifiable cardiovascular disease (CVD) risk factor. This study aimed to describe the prevalence of dyslipidemia and low high density lipoprotein cholesterol (HDL-cholesterol) and associated risk factors among adults in rural northwest China. Methods: In a cross-sectional analyses involving 2,980 adults aged >18 years, information on the demographics, cigarette smoking, alcohol consumption, education, and medical history was collected via face-to-face interviews. Blood samples were collected to determine total cholesterol (TC), low-density lipoprotein cholesterol (LDL-cholesterol), and HDL-cholesterol, and triglycerides (TG) levels. Results: The prevalence of high TC, high LDL-cholesterol, low HDL-cholesterol, and high TG were 1.0%, 0.6%, 60.9%, and 13.7%, respectively. TC, LDL-cholesterol, and TG increased with age in females. Elevated TC was more common in females than in males. The prevalence of low HDL-cholesterol was 67.6% in males and 55.4% in females. Current smokers, those with less education, those who were overweight or obese, and those with large waist circumference were more likely to have low HDL-cholesterol (p<0.05). Multivariable regression showed that male gender showed an association with low HDL-cholesterol (OR 2.10, 95%CI 1.68–2.61), age ≥60 years (OR 0.80, 95% CI 0.64–0.99), BMI (BMI = 24–27.9, OR 1.27, 95%CI 1.04–1.54, p = 0.02 and BMI≥28, OR 1.56, 95%CI 1.10–2.20, p = 0.01) and enlarged waist circumference (OR 2.10, 95%CI 1.51–2.92). Non-alcohol drinker was associated with low HDL-cholesterol levels (OR 0.72, 95%CI 0.53–0.99, p = 0.04). Conclusions: This study found that the prevalence of low HDL-cholesterol was 67.6% and 55.4% for males and females. Male gender, non-alcohol drinker, BMI and central obesity were important risk factors for low HDL-cholesterol in Chinese adults. [ABSTRACT FROM AUTHOR]

In the process of water treatment by bipolar pulsed discharge plasma, there are not only the chemical effects such as the active species formed in the plasma channel, but also the physical effects like the ultraviolet radiation. Power energy consumed in form of optical radiation can be used by photocatalyst to improve the energy efficiency of the discharge system. Therefore, the effects of the photocatalyst on the formation of active species and degradation of the organic pollutant in the packed bed plasma reactor were studied in this paper. The nanoparticle TiO2 photocatalyst was obtained using the sol-gel method, structure and characteristics of TiO2 films were investigated via X-ray diffraction and scanning electron microscope. Formation of H2O2 and O3 under different conditions (applied voltage, air flow rate, diameter of solid packing, etc.) in the plasma and hybrid plasma–catalysis system was investigated. The experimental results proved that the combination of the pulsed discharge plasma process with TiO2 catalysis enhanced concentration of active species generated, and improved water treatment efficiency. In addition, the synergistic effect on H2O2 and O3 concentration increased with the increase of applied voltage, the gas flow rate and the amount of TiO2 photocatalyst. A small part of the TiO2 film fell off rough surface of the glass beads even after 5-h electric discharge treatment, and then remained almost constant. No obvious differences were found in the removal rate of indigo carmine after the catalyst loss. [ABSTRACT FROM PUBLISHER]

This paper investigates the use of an artificial neural network (ANN) model to predict dissolved organic carbon (DOC) in a river network and evaluates the impacts of watershed characteristics on stream DOC. Samples and relevant environmental variables were obtained from field sampling at 28 hydrological response units (HRUs) and a MODIS/SRTM DEM satellite image. HRUs can provide reliable spatial interpolation for filling data gaps and incorporate potential spatial correlation among observations in each ANN neuron. The process and results of neural network modeling were assessed by deterministic and statistical methods and spatial regression kriging. The spatial prediction results show that ANN, using improved back propagation algorithms of 7-15-1 architecture, was the optimal network, by which predictions maintained most of the original spatial variation and eliminated smoothing effects of RK. The sum of the relative contributions of four sensitive variables, including soil organic carbon density, geographic longitude, surface runoff and Chl a in river water, was >75 %. A minor prediction error of ~6 % was found in HRUs of open shrublands, but HRUs of urban and croplands had an error of 24-30 %. This pattern exemplifies anthropogenic impacts in urban areas on stream DOC and agricultural activities in croplands. The usefulness of ANN modeling-based GIS in this study is demonstrated by depiction of spatial variation of stream DOC and indicates the benefits of understanding sensitive factors for watershed impact assessments. [ABSTRACT FROM AUTHOR]

Background: Epithelial cell adhesion molecule (EpCAM) expression has been reported in many types of cancer, including prostate cancer (PCa). However, the role of EpCAM expression remains inconsistent. We conducted a meta-analysis to assess the clinicopathological and prognostic significance of EpCAM expression in PCa.Methods: Publications were searched online using electronic databases. The available data were obtained from The Cancer Genome Atlas (TCGA). The odds ratios (ORs) or hazard ratios (HRs) with their 95% confidence intervals (CIs) were calculated.Results: We identified seven studies in which immunohistochemistry was used and that included 871 prostatic tissue samples. EpCAM expression was significantly higher in PCa samples than in benign and normal tissue samples (OR = 77.93, P = 0.002; OR = 161.61, P <  0.001; respectively). No correlation of EpCAM overexpression with pT stage and lymph node metastasis was observed; however, EpCAM overexpression showed a significant correlation with Gleason score (OR = 0.48, P = 0.012) and bone metastasis (OR = 145.80, P <  0.001). Furthermore, TCGA data showed that EpCAM overexpression was not closely correlated with age, pT stage, lymph node metastasis, number of lymph node, prostate-specific antigen level, Gleason score, biochemical recurrence, and overall survival. Based on multivariate Cox proportional-hazards regression analysis, a significant correlation was observed between EpCAM overexpression and 5-year worse biochemical recurrence free-survival.Conclusions: EpCAM overexpression may be correlated with the development of bone metastasis and worse biochemical recurrence free-survival of PCa. Further studies are needed to verify these findings. [ABSTRACT FROM AUTHOR]

Background: The objective of this study was to examine the effectiveness and safety of lower pole (LP) approach in retroperitoneal laparoscopic radical nephrectomy (LRN). Methods: One hundred thirty-two renal cancer patients were scheduled for selective retroperitoneal LRN. The surgery parameters and outcomes were compared. Out of 132 patients, 78 (59.1%) patients underwent LRN via LP approach, while 54 (40.9%) patients underwent LRN via lateroposterior space (LPS) approach. Results: Compared to LPS group, the LP group had a higher body mass index (27.0 ± 1.7 kg/m2 vs. 24.5 ± 1.8 kg/m2, P < 0.0001) and a larger tumor size (6.9 ± 3.5 cm vs. 4.1 ± 3.3 cm, P < 0.0001). The LP approach reduced the volumes of blood loss and transfusion significantly (135.3 ± 17.2 mL vs. 219.6 ± 30.9 mL, P < 0.0001; 55.6 ± 28.3 vs. 141.1 ± 50.4 mL, P < 0.0001) as compared to the LPS approach. The LP approach also decreased the risk of conversion to open procedure (1.3 vs. 7.4%, P < 0.05). Conclusions: The LP approach is an effective and safe alternative to the LPS approach for retroperitoneal LRN and might be more suitable for patients with obesity, large tumors, tumors located at the medial part of the kidney, or renal pedicular adhesion. [ABSTRACT FROM AUTHOR]