Migrating Knowledge between Physical Scenarios based on Artificial Neural Networks

Deep learning is known to be data-hungry, which hinders its application in many areas of science when datasets are small. Here, we propose to use transfer learning methods to migrate knowledge between different physical scenarios and significantly improve the prediction accuracy of artificial neural networks trained on a small dataset. This method can help reduce the demand for expensive data by making use of additional inexpensive data. First, we demonstrate that in predicting the transmission from multilayer photonic film, the relative error rate is reduced by 46.8% (26.5%) when the source data comes from 10-layer (8-layer) films and the target data comes from 8-layer (10-layer) films. Second, we show that the relative error rate is decreased by 22% when knowledge is transferred between two very different physical scenarios: transmission from multilayer films and scattering from multilayer nanoparticles. Finally, we propose a multi-task learning method to improve the performance of different physical scenarios simultaneously in which each task only has a small dataset

Nanococktail Based on Supramolecular Glyco-Assembly for Eradicating Tumors In Vivo

The development of robust phototherapeutic strategies for eradicating tumors remains a significant challenge in the transfer of cancer phototherapy to clinical practice. Here, a phototherapeutic nanococktail atovaquone/17-dimethylaminoethylamino-17-demethoxygeldanamycin/glyco-BODIPY (ADB) was developed to enhance photodynamic therapy (PDT) and photothermal therapy (PTT) via alleviation of hypoxia and thermal resistance that was constructed using supramolecular self-assembly of glyco-BODIPY (BODIPY-SS-LAC, BSL-1), hypoxia reliever atovaquone (ATO), and heat shock protein inhibitor 17-dimethylaminoethylamino-17-demethoxygeldanamycin (17-DMAG). Benefiting from a glyco-targeting and glutathione (GSH) responsive units BSL-1, ADB can be rapidly taken up by hepatoma cells, furthermore the loaded ATO and 17-DMAG can be released in original form into the cytoplasm. Using in vitro and in vivo results, it was confirmed that ADB enhanced the synergetic PDT and PTT upon irradiation using 685 nm near-infrared light (NIR) under a hypoxic tumor microenvironment where ATO can reduce O2 consumption and 17-DMAG can down-regulate HSP90. Moreover, ADB exhibited good biosafety, and tumor eradication in vivo. Hence, this as-developed phototherapeutic nanococktail overcomes the substantial obstacles encountered by phototherapy in tumor treatment and offers a promising approach for the eradication of tumors. </p

Integrated single-cell and bulk RNA sequencing analyses reveal a prognostic signature of cancer-associated fibroblasts in head and neck squamous cell carcinoma

Objectives: To identify a prognosis-related subtype of cancer-associated fibroblasts (CAFs) in head and neck squamous cell carcinoma (HNSCC) and comprehend its contributions to molecular characteristics, immune characteristics, and their potential benefits in immunotherapy and chemotherapy for HNSCC.Materials and Methods: We performed single-cell RNA sequencing (scRNA-seq) analysis of CAFs from the samples of HNSCC patients derived from Gene Expression Omnibus (GEO), to identify the prognosis-related subtype of CAFs. CAFs were clustered into five subtypes, and a prognosis-related subtype was identified. Univariate and multivariate cox regression analyses were performed on the cohort selected from The Cancer Genome Atlas (TCGA) to determine signature construction, which was validated in GSE65858 and GSE42743. A prognostic signature based on 4 genes was constructed, which were derived from prognosis-related CAFs. The molecular characteristics, immune characteristics as well as the predicted chemosensitivity and immunotherapeutic response in the signature-defined subgroups were analyzed subsequently.Results: The patients with higher CAF scores correlated with poor survival outcomes. Additionally, a high CAF score correlated with lower infiltration levels of many immune cells including M1 macrophages, CD8+ T cells, follicular T helper cells, monocytes, and naïve B cells. High CAF score also demonstrated different enrichment pathways, mutation genes and copy number variated genes. Furthermore, patients with high CAF scores showed lower sensitivity for chemotherapy and immunotherapy than those with low CAF scores.Conclusion: The results of our study indicate the potential of the CAF signature as a biomarker for the prognosis of HNSCC patients. Furthermore, the signature could be a prospective therapeutic target in HNSCC

Probability of Premature Mortality Caused by Major Non-communicable Diseases in Pudong New Area of Shanghai，2002—2020

BackgroundNon-communicable diseases (NCDs) pose a major threat to population health. Probability of premature mortality is an index recommended by WHO for the evaluation of the threat of NCDs.ObjectiveTo explore the mortality and probability of premature mortality caused by four major NCDs (cardiovascular and cerebrovascular diseases, cancer, diabetes and chronic respiratory disease) in Pudong New Area of Shanghai from 2002 to 2020, providing a reference for the development of measures to the target of reducing the probability of premature mortality due to these four major NCDs in the Health China 2030 plan.MethodsThis analysis was conducted in May 2021 based on data collected from Pudong New Area&apos;s Residents Death Surveillance Database, involving registered residents of Pudong New Area who died of cardiovascular and cerebrovascular diseases, cancer, diabetes and chronic respiratory disease between 2002-01-01 and 2020-12-31. Crude mortality, age-standardized mortality and probability of premature mortality were used for analyzing deaths due to the four above-mentioned NCDs. The annual percent change (APC) was adopted to analyze the temporal trend of mortality and probability of premature mortality.ResultsThe crude mortality of four major NCDs ascended from 526.82/100 000 in 2002 to 678.84/100 000 in 2020 (APC=1.56%, Z=13.715, P&lt;0.001) . The age-standardized mortality of four major NCDs decreased from 404.05/100 000 in 2002 to 260.87/100 000 in 2020 (APC=-2.09%, Z=-12.428, P&lt;0.001) . The probability of premature mortality caused by four major NCDs decreased from 13.09% in 2002 to 8.45% in 2020 (APC=-2.31%, Z=-15.847, P&lt;0.001) . The probability of premature mortality caused by cardiovascular and cerebrovascular diseases was declined from 3.57% in 2002 to 2.38% in 2020 (APC=-2.21%, Z=-9.739, P&lt;0.001) , and that caused by cancer decreased from 8.36% to 5.49% (APC=-2.24%, Z=-19.476, P&lt;0.001) , and that by chronic respiratory disease reduced from 1.08% to 0.24% (APC=-7.23%, Z=-13.326, P&lt;0.001) . No significant temporal trend for the probability of premature mortality caused by diabetes was found (Z=-0.395, P=0.698) . The probability of premature mortality caused by four major NCDs in males was higher than that in females. According to the annual increase rates during 2015 to 2020, it is estimated that the probability of premature mortality caused by these four major NCDs would be 6.67%.ConclusionThe crude mortality of the four major NCDs in Pudong New Area ascended during 2002—2020, and both the age-standardized mortality and the probability of premature mortality showed a downward tendency in the same period. Pudong New Area had achieved the goal in the Health China 2020 plan of reducing the probability of premature mortality of four NCDs in 2020. However, according to the present annual increase rates, the task of achieving the Health China 2030 target of the decent of the probability of premature mortality caused by four major NCDs would be daunting. Thus, more measures should be taken to strengthen the containment of such NCDs. Moreover, males should be treated as the key group, and more attention should be paid to the premature death caused by diabetes in males

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Building models to evaluate internal comprehensive quality of apples and predict storage time

Apple quality and customer satisfaction are significantly impacted by variations in apple quality throughout storage. In this study, the evaluation of apples' internal overall quality and the estimation of storage time were investigated. By using Pearson correlation analysis and an analytical hierarchy approach, an internal comprehensive quality index was created. A calibration model and a high-order kinetic model were created for the internal comprehensive quality index using the competitive adaptive reweighted sampling (CARS) algorithm in conjunction with partial least squares regression (PLSR) and in accordance with the results of fitting chemical kinetic reactions to variations in internal comprehensive quality with storage time. The calibration model and the high-order kinetic model were combined to create a prediction model for the storage time of apples. Results revealed that the determination coefficient of the prediction (Rp2) and root mean square error (RMSE) of the calibration model were 0.9419 and 0.0023 respectively, and a residual predictive deviation (RPD) of 5.77; the correlation coefficient (R) and RMSE of the higher-order kinetic model were 0.9620 and 0.0038 respectively; the Rp2 of the prediction model was determined as 0.8957, with a root mean square error of 4.63 d. Results show that the proposed calibration model and higher-order kinetic model are capable of evaluating the internal comprehensive quality of apples, and that the determined prediction model is capable of projecting the storage time of apples with an acceptable margin of error while still meeting the real requirements.</p

Kron reduction based on node ordering optimization for distribution network dispatching with flexible loads

Kron reduction is a general tool of network simplification for flow calculation. With a growing number of flexible loads appearing in distribution networks, traditional Kron reduction cannot be widely used in control and scheduling due to the elimination of controllable and variable load buses. Therefore, this paper proposes an improved Kron reduction based on node ordering optimization whose principles guarantee that all the boundary nodes are retained eventually after eliminating the first row and the first column in every step according to the order, thereby making it possible to take full advantage of their potential to meet different requirements in power system calculation and dispatching. The proposed method is verified via simulation models of IEEE 5-bus and 30-bus systems through illustrating the dynamic consistency of the output active power of the generator nodes and the power flow data of preserved nodes before and after reduction.Published versionThis work is funded by the National Natural Science Foundation of China (No. 61773137), the Natural Science Foundation of Shandong Province (Nos. ZR2019MF030 and ZR2018PEE018) and the China Postdoctoral Science Foundation (No. 2018M641830)