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Heterogeneous CuS QDs/BiVO4@Y2O2S Nanoreactor for Monitorable Photocatalysis

SMALL 2024年第36期20卷 e2401335页

作者： Guo, Da Jiang, shuwen Shen, Lifan Pun, Edwin Yue Bun lin, Hai Dalian Polytech Univ Sch Text & Mat Engn Dalian 116034 Peoples R China Beijing Univ Technol Coll Microelect Beijing 100124 Peoples R China Beijing Univ Technol Fac Informat Technol Key Lab Optoelect Technol Beijing 100124 Peoples R China City Univ Hong Kong Dept Elect Engn Hong Kong 999077 Peoples R China City Univ Hong Kong State Key Lab Terahertz & Millimeter Waves Hong Kong 999077 Peoples R China

Exploration of multifunctional integrated catalysts is of great significance for photocatalysis toward practical application. Herein, a 1D confined nanoreactor with a heterogeneous core-shell structure is designed for synergies of efficient catalysis and temperature monitoring by custom encapsulation of Z-scheme heterojunction CuS quantum dots/BiVO4 (CuS QDs/BiVO4) and Y2O2S-Er, Yb. The dispersed active sites created by the QDs with high surface energy improve the mass transfer efficiency, and the efficient electron transport channels at the heterogeneous interface extend the carrier lifetime, which endows the nanoreactor with excellent catalytic performance. Meanwhile, real-time temperature monitoring is realized based on the thermally coupled levels H-2(11/2)/S-4(3/2)-> I-4(15/2) of Er3+ using fluorescence intensity ratio, which enables the monitorable photocatalysis. Furthermore, the nanoreactor with a multidimensional structure increases effective intermolecular collisions to facilitate the catalytic process by restricting the reaction within distinct enclosed spaces and circumvents potential unknown interaction effects. The design of multi-space nanoconfined reactors opens up a new avenue to modulate catalyst function, providing a unique perspective for photocatalytic applications in the mineralization of organic pollutants, hydrogen production, and nitrogen fixation.

关键词： coaxial electrospinning core-shell structure multifunctional nanoreactor temperature sensing Z-scheme heterojunction

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Enhancing perovskite solar cell performance: The role of polymer-assisted hole transport layers in hot carrier dynamics

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CHEMICAL ENGINEERING JOURNAL 2024年 489卷

作者： Xu, Min Wang, Peng Qi, shuwen Zhao, Rongjun Xie, lin Hua, Yong Yunnan Univ Sch Mat & Energy Kunming 650091 Peoples R China Yunnan Univ Ctr Optoelect Engn Res Dept Phys Kunming 650091 Peoples R China

Enhancing the efficiency and stability is very critical for perovskite solar cells (PSCs) commercialization. Herein, we report an effective approach to enable highly efficient and stable PSCs by incorporating a polymer material, poly[N, N ' -bis(2-octyldodecyl)-naphthalene-1,4,5,8-bis(dicarboximide)-2,6-diyl]-alt-5,5 ' -(2,2 ' -bithiophene) (named P(NDI2OD-T2)), into hole transport layer (HTL). Our research results exhibit that the addition of P (NDI2OD-T2) not only effectively improves the hole mobility and conductivity of HTL, but also makes its energy level more alignment with perovskite. More importantly, ultrafast carrier results demonstrate that the introduction of P(NDI2OD-T2) into Spiro-OMeTAD HTL can effectively improve the extraction and transfer of hot carriers from perovskite layer to HTL, and consequently reduce the recombination of charge carriers in the device. As a result, PSCs based on Spiro + P(NDI2OD-T2) as a HTL shows an enhanced power conversion efficiency (PCE) of 24.20 %, which is much higher than that of control device without P(NDI2OD-T2) (21.94 %). Furthermore, the un-encapsulated P(NDI2OD-T2)-treated PSCs exhibit excellent humidity, thermal and light stabilities, with the devices maintaining 94 % of its initial efficiency after 3000 h at approximate to 40 % humidity, 95 % of its initial efficiency after storage at 65 degrees C and 85 degrees C for 600 h, and 90 % of its initial efficiency after 600 h under one sun light irradiation, respectively. This work provides an effective strategy for improving the device efficiency and long-term stability of PSCs.

关键词： Spiro-OMeTAD Perovskite solar cell Additive Hot carriers Polymer

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Recent advances in the interfacial engineering of MOF-based mixed matrix membranes for gas separation

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NANOSCALE 2024年第16期16卷 7716-7733页

作者： Yu, shuwen Li, Conger Zhao, Shuke Chai, Milton Hou, Jingwei lin, Rijia Suzhou Univ Sch Chem & Chem Engn Suzhou 234000 Peoples R China Univ Queensland Sch Chem Engn St Lucia Qld 4072 Australia Shanghai Tech Univ Sch Phys Sci & Technol Shanghai 201210 Peoples R China

The membrane process stands as a promising and transformative technology for efficient gas separation due to its high energy efficiency, operational simplicity, low environmental impact, and easy up-and-down scaling. Metal-organic framework (MOF)-polymer mixed matrix membranes (MMMs) combine MOFs' superior gas-separation performance with polymers' processing versatility, offering the opportunity to address the limitations of pure polymer or inorganic membranes for large-scale integration. However, the incompatibility between the rigid MOFs and flexible polymer chains poses a challenge in MOF MMM fabrication, which can cause issues such as MOF agglomeration, sedimentation, and interfacial defects, substantially weakening membrane separation efficiency and mechanical properties, particularly gas separation. This review focuses on engineering MMMs' interfaces, detailing recent strategies for reducing interfacial defects, improving MOF dispersion, and enhancing MOF loading. Advanced characterisation techniques for understanding membrane properties, specifically the MOF-polymer interface, are outlined. Lastly, it explores the remaining challenges in MMM research and outlines potential future research directions. This is a comprehensive review for resolving compatibility challenges in fabricating practical metal-organic framework composite membranes for gas separation.

关键词： Defects

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Fire spread prediction model based on multi-scale convolutional neural network

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Multimedia Tools and Applications 2025年 1-22页

作者： Liu, shuwen Cao, lin lin, Chuanying Dai, Yuxuan Li, Xingdong Li, Sanping Sun, Shufa Li, Dandan College of Mechanical and Electrical Engineering Northeast Forestry University Harbin China Shandong Nuclear POWER Equipment Manufacturing Co. Ltd. Yantai China College of Engineering and Technology Northeast Forestry University Harbin China

Forest fire spread prediction is a very tricky problem, and commonly used models are difficult to apply to real forest fire cases due to their low prediction accuracy. This paper presents a method for estimating the time-resolved spatial evolution of forest fires using an optimized multi-scale convolutional neural network(OMS-CNN), whose hyperparameters are processed using the particle swarm algorithm. The multi-scale convolutional structure can extract both the global and local characteristics of the fire scene. The particle swarm algorithm can select the appropriate hyperparameters to maximize the model performance and minimize the loss value. The OMS-CNN model was trained and tested in order to cope with the spread of forest fires under field conditions. Outdoor burning experiments were designed and dataset used for training, validation and testing was recorded by a UAV equipped with an infrared camera. The comparison of the OMS-CNN model with the two degenerate models and three advanced wildfire models in terms of Kappa and Hausdorff distance values demonstrates that the OMS-CNN model achieves higher predictive accuracy. Furthermore, the input variable ablation experiments confirm the model's practical value in real-world scenarios. The model can be applied in forest fire managing and fighting system, which has extremely important theoretical significance and practical application value. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Convolutional neural networks

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Risk Factors for Prognosis of Lung Cancer Patients Receiving Anlotinib Treatment: A Retrospective Cohort Study

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ClinICAL RESPIRATORY JOURNAL 2025年第2期19卷 e70051页

作者： Xie, Congyi Chen, Jinzhan Yang, shuwen Ye, Feiyang lin, Zhenyang Xu, Yijiao Yang, Yimin Tong, lin Fudan Univ Zhongshan Hosp Xiamen Dept Pulm Med Xiamen Fujian Peoples R China Xiamen Clin Res Ctr Canc Therapy Xiamen Fujian Peoples R China Fuzhou Univ Coll Comp & Data Sci Fuzhou Fujian Peoples R China Fudan Univ Zhongshan Hosp Xiamen Dept Thorac Surg Xiamen Fujian Peoples R China Fudan Univ Zhongshan Hosp Dept Vasc Surg Shanghai Peoples R China Fudan Univ Zhongshan Hosp Dept Pulm & Crit Care Med Shanghai Peoples R China

PurposeAnlotinib is widely used in the treatment of lung cancer. However, there remains a lack of predictive biomarkers to effectively gauge the response to anlotinib therapy. We conducted a retrospective study to preliminarily explore potential risk factors that might predict outcomes in lung cancer patients undergoing anlotinib treatment. Patients and MethodsWe retrospectively analyzed lung cancer patients treated with anlotinib at our hospital between 1 June 2018 and 1 June 2021. Data were gathered from electronic medical records. Demographic and clinical characteristics of patients, progression-free survival (PFS), and overall survival (OS) were described. Predictive factors related to treatment efficacy were preliminarily analyzed using Cox regression and Kaplan-Meier survival analyses. ResultsAfter adjusting for potential confounders, clinical stage IV (hazard ratio [HR] = 2.52, 95% confidence interval [CI], 1.09-5.82, p = 0.0311), N-terminal fragment brain natriuretic peptides (NT-pro-BNP) > 300 pg/mL (HR = 2.54, 95% CI, 1.17-5.52, p = 0.0183), and neuron-specific enolase (NSE) > 16.3 ng/mL (HR = 1.70, 95% CI, 1.03-2.81, p = 0.0389) were associated with shorter OS, whereas age (HR = 0.96, 95% CI, 0.94-0.99, p = 0.0055) was associated with a longer PFS in fully adjusted model. Kaplan-Meier analyses of cumulative risk factors (clinical stage IV, NT-pro-BNP > 300 pg/mL, and NSE > 16.3 ng/mL) indicated that patients with a greater number of coexisting risk factors had significantly shorter OS (p < 0.0001). ConclusionClinical stage IV, NT-pro-BNP level, and NSE level were identified as independent prognostic factors for lung cancer patients undergoing anlotinib treatment. Patients with multiple high-risk factors may derive limited benefit from anlotinib.

关键词： anlotinib lung cancer survival

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Household catastrophic health expenditure and depressive mood among Chinese adults, children, and adolescents: a population-based panel study

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BMC PSYCHIATRY 2025年第1期25卷 1-12页

作者： Li, shuwen Fang, Kailu Zhang, Yu lin, Yushi Zheng, Luyan Wu, Jie Zhejiang Univ State Key Lab Diag & Treatment Infect Dis Natl Clin Res Ctr Infect DisAffiliated Hosp 1Col Collaborat Innovat Ctr Diag & Treatment Infect Dis Hangzhou 310003 Peoples R China Zhejiang Univ Sch Med Affiliated Hosp 2 Dept Infect Dis Hangzhou Peoples R China

BackgroundNumerous studies have suggested that catastrophic health expenditure (CHE) is associated with depressive mood. However, most published studies have examined the relationship between CHE and depressive mood only among middle-aged and older people who are already susceptible to depressive mood. The objective of our analysis was to determine the associations between household CHE and depressive mood among adults and children/*** study population consisted of Chinese residents who participated in the 2016 CFPS, 2018 CFPS, and 2020 CFPS. Our analytical sample was restricted to children/adolescents aged 10-17 years and adults aged 18 years and older. We utilized multilevel random effects multivariate logistic regression models to investigate the associations between CHE and depressive mood among both adults and children/*** study revealed that 15% of adults and 12.61% of children/adolescents had experienced CHE and that CHE was positively associated with depressive mood among adults (OR = 1.34, 95% CI: 1.21, 1.50) and among children/adolescents (OR = 1.48, 95% CI: 1.12, 1.96) after adjustment for potential confounding factors. This positive association persisted in different subgroup analyses. In addition, we found that being insured with either urban or rural health insurance was associated with decreased odds of depressive *** study indicated that CHE is common in Chinese families and may increase the risk of depressive mood for both adults and children/adolescents. These findings emphasize the need to focus on expanding health insurance coverage, as well as implementing family-based mental health resources and financial literacy programs to reduce the psychological impact of CHE across all age groups.

关键词： Catastrophic health expenditure Depressive mood Panel data China Multilevel model

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Controlling thermal radiation by metasurface for infrared and laser compatible stealth with radiative cooling

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OPTICS AND LASER TECHNOLOGY 2025年 189卷

作者： Chen, Xiuyu Qin, lin Huang, Jinlong Liu, Yufang Zheng, shuwen Qian, Mengdan Henan Normal Univ Sch Phys Henan Key Lab Infrared Spectrum Measures & Applica Xinxiang 453007 Henan Peoples R China Henan Acad Sci Inst Phys Zhengzhou 450046 Peoples R China

Controlling thermal radiation in the infrared (IR) spectrum is pivotal for energy management and military camouflage, sparking heightened research interest. This study introduces a wavelength-selective thermal emitter (WSTE) utilizing a metal-dielectric-metal (MDM) structure composed of an Al/Ge/Al periodic array. The WSTE exhibits low emissivity in the IR atmospheric windows (epsilon 3-5 mu m = 0.2 and epsilon 8-14 mu m = 0.2), fulfilling IR camouflage requirements while achieving high emissivity in the non-atmospheric window (epsilon 5-8 mu m = 0.6) for efficient thermal dissipation to achieve radiative cooling. Furthermore, the WSTE demonstrates strong absorption at 10.6 mu m, enhancing its laser stealth capability. Measures data substantiate the alignment between simulations and experiments, showing stable performance at temperatures up to 350 degrees C. When compared to conventional lowemissivity stealth materials (Al film), the surface temperature of the WSTE could be 18.42 degrees C lower than that of the Al film at 45 W, indicating excellent thermal management capability. The WSTE's straightforward yet robust design exhibits exceptional high-temperature resistance, ease of fabrication, and scalability for mass production, positioning it as a promising candidate for applications demanding infrared stealth and radiative cooling.

关键词： Selective emitter Infrared stealth Compatible camouflage Thermal management

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Identification of a novel macrophage-related prognostic signature in colorectal cancer

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SCIENTIFIC REPORTS 2024年第1期14卷 1-25页

作者： lin, Dongfa Zheng, Tingjin Huang, Shangyuan Liu, Rui Guan, shuwen Zhang, Zhishan Jilin Univ Sch Life Sci Key Lab Mol Enzymol & Engn Minist Educ Changchun 130012 Peoples R China Jilin Univ Engn Lab AIDS Vaccine Changchun 130012 Peoples R China Jilin Univ Sch Life Sci Changchun 130012 Peoples R China Fujian Med Univ Quanzhou Hosp 1 Dept Clin Lab 248 East St Quanzhou 362000 Fujian Peoples R China Shanghai Jiao Tong Univ Sch Life Sci & Biotechnol Sheng Yushou Ctr Cell Biol & Immunol Lab Mol NeurobiolDept Genet & Dev Biol 800 Dongchuan Rd Shanghai 200240 Peoples R China

Colorectal cancer (CRC) is one of the most prevalent and deadliest illnesses all around the world. Growing proofs demonstrate that tumor-associated macrophages (TAMs) are of critical importance in CRC pathogenesis, but their mechanisms remain yet unknown. The current research was designed to recognize underlying biomarkers associated with TAMs in CRC. We screened macrophage-related gene modules through WGCNA, selected hub genes utilizing the LASSO algorithm and COX regression, and established a model. External validation was performed by expression analysis using datasets GSE14333, GSE74602, and GSE87211. After validating the bioinformatics results using real-time quantitative reverse transcription PCR, we identified SPP1, C5AR1, MMP3, TIMP1, ADAM8 as potential biomarkers associated with macrophages in CRC.

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A Forest Fire Susceptibility Modeling Approach Based on Light Gradient Boosting Machine Algorithm

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REMOTE SENSING 2022年第17期14卷

作者： Sun, Yanyan Zhang, Fuquan lin, Haifeng Xu, shuwen Nanjing Forestry Univ Coll Informat Sci & Technol Nanjing 210037 Peoples R China Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Peoples R China

A forest fire susceptibility map generated with the fire susceptibility model is the basis of fire prevention resource allocation. A more reliable susceptibility map helps improve the effectiveness of resource allocation. Thus, further improving the prediction accuracy is always the goal of fire susceptibility modeling. This paper developed a forest fire susceptibility model based on an ensemble learning method, namely light gradient boosting machine (LightGBM), to produce an accurate fire susceptibility map. In the modeling, a subtropical national forest park in the Jiangsu province of China was used as the case study area. We collected and selected eight variables from the fire occurrence driving factors for modeling based on correlation analysis. These variables are from topographic factors, climatic factors, human activity factors, and vegetation factors. For comparative analysis, another two popular modeling methods, namely logistic regression (LR) and random forest (RF) were also applied to construct the fire susceptibility models. The results show that temperature was the main driving factor of fire in the area. In the produced fire susceptibility map, the extremely high and high susceptibility areas that were classified by LR, RF, and LightGBM were 5.82%, 18.61%, and 19%, respectively. The F1-score of the LightGBM model is higher than the LR and RF models. The accuracy of the model of LightGBM, RF, and LR is 88.8%, 84.8%, and 82.6%, respectively. The area under the curve (AUC) of them is 0.935, 0.918, and 0.868, respectively. The introduced ensemble learning method shows better ability on performance evaluation metrics.

关键词： machine learning fire factors prediction fire susceptibility map

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Development and validation of prediction models for nosocomial infection and prognosis in hospitalized patients with cirrhosis

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ANTIMICROBIAL RESISTANCE AND INFECTION CONTROL 2024年第1期13卷 1-12页

作者： Li, shuwen Zhang, Yu lin, Yushi Zheng, Luyan Fang, Kailu Wu, Jie Zhejiang Univ Affiliated Hosp 1 Collaborat Innovat Ctr Diag & Treatment Infect Dis State Key Lab Diag & Treatment Infect DisSch Med Hangzhou 310003 Peoples R China Zhejiang Univ Affiliated Hosp 2 Sch Med Dept Infect Dis Hangzhou Peoples R China

Background Nosocomial infections (NIs) frequently occur and adversely impact prognosis for hospitalized patients with cirrhosis. This study aims to develop and validate two machine learning models for NIs and in-hospital mortality risk prediction. Methods The Prediction of Nosocomial Infection and Prognosis in Cirrhotic patients (PIPC) study included hospitalized patients with cirrhosis at the Qingchun Campus of the First Affiliated Hospital of Zhejiang University. We then assessed several machine learning algorithms to construct predictive models for NIs and prognosis. We validated the best-performing models with bootstrapping techniques and an external validation dataset. The accuracy of the predictions was evaluated through sensitivity, specificity, predictive values, and likelihood ratios, while predictive robustness was examined through subgroup analyses and comparisons between models. Results We enrolled 1,297 patients into derivation cohort and 496 patients into external validation cohort. Among the six algorithms assessed, the Random Forest algorithm performed best. For NIs, the PIPC-NI model achieved an area under the curve (AUC) of 0.784 (95% confidence interval [CI] 0.741-0.826), a sensitivity of 0.712, and a specificity of 0.702. For in-hospital mortality, the PIPC- mortality model achieved an AUC of 0.793 (95% CI 0.749-0.836), a sensitivity of 0.769, and a specificity of 0.701. Moreover, our PIPC models demonstrated superior predictive performance compared to the existing MELD, MELD-Na, and Child-Pugh scores. Conclusions The PIPC models showed good predictive power and may facilitate healthcare providers in easily assessing the risk of NIs and prognosis among hospitalized patients with cirrhosis.

关键词： Nosocomial infection Cirrhosis Machine learning In-hospital mortality

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