Research on the performance of pump-turbine during the transition process from pump mode to turbine mode

In current engineering, the transition process of pump turbines from pump to turbine mode mainly includes the shutdown process of pump operating and the startup process of turbine operating, and the switching of working conditions mostly depends on the opening and closing of the ball valve. While, this article focuses on the transitional process of pump turbine from pump to turbine condition without relying on ball valve, which will significantly reduce the response time of the unit and enable quick switching of operating conditions in emergency situations. In this study, the torque balance equation is employed to analyze the transition process of the entire flow system from pump to turbine operation. Additionally, the entropy production theory is utilized to investigate the correlation between pressure, flow state, and energy loss in the pump-turbine, shedding light on the changes in external characteristics through the evolution of internal characteristics. Furthermore, the transition process from pump mode to turbine mode is segmented into five stages based on the variations in the guide vanes (GV). The findings reveal that the rotation of GV triggers sharp fluctuations in static pressure, torque, and axial force. During stage four, the initiation of all three GV positions results in an increase in flow rate and torque, accompanied by a decrease in axial force. In stage two, the closure of GV leads to a decrease in pressure within the spiral casing (SC) and stay vanes (SV) domains, coupled with an increase in pressure in the bladeless zone, runner, and draft tube domains. Simultaneously, the pressure difference between both sides of the runner decreases significantly, directly causing a drop in torque and axial force. In stage three, GV closure interrupts the flow in the pump-turbine, resulting in significant backflow in the SC, SV, and runner domains, alongside high-speed circulation in the bladeless area. Moreover, the location of the high entropy production rate (EPR) value within the unit aligns with the reflux zone, indicating considerable energy loss attributable to reflux. The above research results will provide reference for the rapid switching of operating conditions of pump turbines in emergency situations

Pump-tailored Alternative Bell State Generation in the First-Order Hermite-Gaussian basis

We demonstrate entangled-state swapping, within the Hermite-Gaussian basis of first-order modes, directly from the process of spontaneous parametric down-conversion within a nonlinear crystal. The method works by explicitly tailoring the spatial structure of the pump photon such that it resembles the product of the desired entangled spatial modes exiting the crystal. Importantly, the result is an entangled state of balanced HG modes, which may be beneficial in applications that depend on symmetric accumulations of geometric phase through optics or in applications of quantum sensing and imaging with azimuthal sensitivity. Furthermore, the methods are readily adaptable to other spatial mode bases

Anatomy-based prediction method for determining ipsilateral lung doses in postoperative breast radiation therapy assisted by diagnostic computed tomography images

Background: This study aimed to investigate whether ipsilateral lung doses (ILDs) could be predicted by anatomical indexes measured using diagnostic computed tomography (CT) prior to the planning stage of breast radiation therapy (RT). Materials and methods: The thoracic diameters and the length of lines drawn manually were measured on diagnostic CT images. The parameters of interest were the skin maximum lung distance (sMLD), central lung distance (CLD), Haller index (HI), and body mass index (BMI). Lung dose-volume histograms were created with conformal planning, and the lung volumes receiving 5–40 Gy (V5–V40) were calculated. Linear regression models were used to investigate the correlations between the anatomical indexes and dose differences and to estimate the slope and 95% confidence intervals (CIs). Results: A total of 160 patients who had undergone three-dimensional conformal RT after breast-conserving surgery were included. Univariable analysis revealed that the sMLD (p < 0.001), CLD (p < 0.001), HI (p = 0.002), and BMI (p < 0.001) were significantly correlated with the V20. However, multivariable analysis revealed that only the sMLD (slope: 0.147, p = 0.001, 95% CI: 0.162–0.306) and CLD (0.157, p = 0.005, 0.048–0.266) were strongly correlated with the V20. The p-value for the sMLD was the lowest among the p-values for all indexes, thereby indicating that the sMLD had the best predictive power for ILD. Conclusions: sMLD and CLD are anatomical markers that can be used to predict ILD in whole breast RT. An sMLD > 20.5 mm or a CLD > 24.3 mm positively correlated with a high ILD.

Generation of Small 32P-Labeled Peptides as a Potential Approach to Colorectal Cancer Therapy

Cancers have been revealed to be extremely heterogenous in terms of the frequency and types of mutations present in cells from different malignant tumors. Thus, it is likely that uniform clinical treatment is not optimal for all patients, and that the development of individualized therapeutic regimens may be beneficial. We describe the generation of multiple, unique small peptides nine to thirty-four amino acids in length which, when labeled with the radioisotope 32P, bind with vastly differing efficiencies to cell lines derived from different colon adenocarcinomas. In addition, the most effective of these peptides permanently transfers the 32P radioisotope to colorectal cancer cellular proteins within two hours at a rate that is more than 150 times higher than in cell lines derived from other cancers or from the normal tissues tested. Currently, the only two FDA-approved radioimmunotherapeutic agents in use both employ antibodies directed against the B cell marker CD20 for the treatment of non-Hodgkin's lymphoma. By using the method described herein, large numbers of different 32P-labeled peptides can be readily produced and assayed against a broad spectrum of cancer types. This report proposes the development and use of 32P-labeled peptides as potential individualized peptide-binding therapies for the treatment of colon adenocarcinoma patients

The Coupling and Competition of Crystallization and Phase Separation, Correlating Thermodynamics and Kinetics In OPV Morphology and Performances

The active layer morphology transition of organic photovoltaics under non-equilibrium conditions are of vital importance in determining the device power conversion efficiency and stability; however, a general and unified picture on this issue has not been well addressed. Using combined in situ and ex situ morphology characterizations, morphological parameters relating to kinetics and thermodynamics of morphology evolution are extracted and studied in model systems under thermal annealing. The coupling and competition of crystallization and demixing are found to be critical in morphology evolution, phase purification and interfacial orientation. A unified model summarizing different phase diagrams and all possible kinetic routes is proposed. The current observations address the fundamental issues underlying the formation of the complex multi-length scale morphology in bulk heterojunction blends and provide useful morphology optimization guidelines for processing devices with higher efficiency and stability

Three-Tiered Risk Stratification Model to Predict Progression in Barrett's Esophagus Using Epigenetic and Clinical Features

Barrett's esophagus predisposes to esophageal adenocarcinoma. However, the value of endoscopic surveillance in Barrett's esophagus has been debated because of the low incidence of esophageal adenocarcinoma in Barrett's esophagus. Moreover, high inter-observer and sampling-dependent variation in the histologic staging of dysplasia make clinical risk assessment problematic. In this study, we developed a 3-tiered risk stratification strategy, based on systematically selected epigenetic and clinical parameters, to improve Barrett's esophagus surveillance efficiency

Novel Decapeptides that Bind Avidly and Deliver Radioisotope to Colon Cancer Cells

The rapidly growing field of targeted tumor therapy often utilizes an antibody, sometimes tagged with a tumor-ablating material such as radioisotope, directed against a specific molecule.This report describes the discovery of nine novel decapeptides which can be radioactively labeled, bind to, and deliver (32)P to colon cancer cells. The decapeptides vary from one another by one to three amino acids and demonstrate vastly different binding abilities. The most avidly binding decapeptide can permanently deliver very high levels of radioisotope to the adenocarcinoma cancer cell lines at an efficiency 35 to 150 times greater than to a variety of other cell types, including cell lines derived from other types of cancer or from normal tissue.This experimental approach represents a new example of a strategy, termed peptide binding therapy, for the potential treatment of colorectal and other adenocarcinomas

A Multicenter, Double-Blinded Validation Study of Methylation Biomarkers for Progression Prediction in Barrett's Esophagus

Esophageal adenocarcinoma risk in Barrett’s esophagus (BE) is increased 30- to 125-fold versus the general population. Among all BE patients, however, neoplastic progression occurs only once per 200 patient-years. Molecular biomarkers are therefore needed to risk-stratify patients for more efficient surveillance endoscopy and to improve the early detection of progression. We therefore performed a retrospective, multicenter, double-blinded validation study of 8 BE progression prediction methylation biomarkers. Progression or nonprogression were determined at 2 years (tier 1) and 4 years (tier 2). Methylation was assayed in 145 nonprogressors (NPs) and 50 progressors (Ps) using real-time quantitative methylation-specific PCR. Ps were significantly older than NPs (70.6 vs. 62.5 years, p < 0.001). We evaluated a linear combination of the 8 markers, using coefficients from a multivariate logistic regression analysis. Areas under the ROC curve (AUCs) were high in the 2-, 4-year and combined data models (0.843, 0.829 and 0.840; p<0.001, p<0.001 and p<0.001, respectively). In addition, even after rigorous overfitting correction, the incremental AUCs contributed by panels based on the 8 markers plus age vs. age alone were substantial (Δ-AUC = 0.152, 0.114 and 0.118, respectively) in all three models. A methylation biomarker-based panel to predict neoplastic progression in BE has potential clinical value in improving both the efficiency of surveillance endoscopy and the early detection of neoplasia

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation