With the rapid growth of the Internet and social media, information is widely disseminated in multimodal forms, such as text and images, where discriminatory content can manifest in various ways. Discrimination detect...With the rapid growth of the Internet and social media, information is widely disseminated in multimodal forms, such as text and images, where discriminatory content can manifest in various ways. Discrimination detection techniques for multilingual and multimodal data can identify potential discriminatory behavior and help foster a more equitable and inclusive cyberspace. However, existing methods often struggle in complex contexts and multilingual environments. To address these challenges, this paper proposes an innovative detection method, using image and multilingual text encoders to separately extract features from different modalities. It continuously updates a historical feature memory bank, aggregates the Top-K most similar samples, and utilizes a Gated Recurrent Unit (GRU) to integrate current and historical features, generating enhanced feature representations with stronger semantic expressiveness to improve the model’s ability to capture discriminatory signals. Experimental results demonstrate that the proposed method exhibits superior discriminative power and detection accuracy in multilingual and multimodal contexts, offering a reliable and effective solution for identifying discriminatory content.展开更多
Background:Following the short-term outbreak of coronavirus disease 2019(COVID-19)in December 2022 in China,clinical data on kidney transplant recipients(KTRs)with COVID-19 are lacking.Methods:We conducted a single-ce...Background:Following the short-term outbreak of coronavirus disease 2019(COVID-19)in December 2022 in China,clinical data on kidney transplant recipients(KTRs)with COVID-19 are lacking.Methods:We conducted a single-center retrospective study to describe the clinical features,complications,and mortality rates of hospitalized KTRs infected with COVID-19 between Dec.16,2022 and Jan.31,2023.The patients were followed up until Mar.31,2023.Results:A total of 324 KTRs with COVID-19 were included.The median age was 49 years.The median time between the onset of symptoms and admission was 13 d.Molnupiravir,azvudine,and nirmatrelvir/ritonavir were administered to 67(20.7%),11(3.4%),and 148(45.7%)patients,respectively.Twenty-nine(9.0%)patients were treated with more than one antiviral agent.Forty-eight(14.8%)patients were treated with tocilizumab and 53(16.4%)patients received baricitinib therapy.The acute kidney injury(AKI)occurred in 81(25.0%)patients and 39(12.0%)patients were admitted to intensive care units.Fungal infections were observed in 55(17.0%)patients.Fifty(15.4%)patients lost their graft.The 28-d mortality rate of patients was 9.0%and 42(13.0%)patients died by the end of follow-up.Multivariate Cox regression analysis identified that cerebrovascular disease,AKI incidence,interleukin(IL)-6 level of>6.8 pg/mL,daily dose of corticosteroids of>50 mg,and fungal infection were all associated with an increased risk of death for hospitalized patients.Conclusions:Our findings demonstrate that hospitalized KTRs with COVID-19 are at high risk of mortality.The administration of immunomodulators or the late application of antiviral drugs does not improve patient survival,while higher doses of corticosteroids may increase the death risk.展开更多
Background: Social media platforms are popular among children and often feature challenges that become viral. Notably, the Tide Pod® and Benadryl® challenges encouraged viewers to ingest these substances for...Background: Social media platforms are popular among children and often feature challenges that become viral. Notably, the Tide Pod® and Benadryl® challenges encouraged viewers to ingest these substances for their visual appeal and hallucinogenic effects, respectively. This study aimed to assess the clinical impact and outcomes of single-use detergent sacs (SUDS) and diphenhydramine challenges on pediatric ingestions reported to United States (U.S.) Poison Control Centers (PCCs). Methods: We conducted a retrospective review of pediatric exposures reported to U.S. PCCs using data from the National Poison Data System (NPDS). The study included intentional single-substance ingestions of both brand-name and generic forms of SUDS and diphenhydramine among children ≤ 19 years. We compared the number of calls, clinical effects, disposition, and management strategies for SUDS (pre: 01/01/17 to 12/31/17 vs. post: 01/01/18 to 12/31/18) and diphenhydramine (pre: 08/01/19 to 07/31/20 vs. post: 08/01/20 to 07/31/21) ingestions 12 months before and after the introduction of the respective social media challenges. Differences in proportions were compared using the Chi-square test. Results: During the study period, 469 ingestions of SUDS and 5,702 ingestions of diphenhydramine were reported. Post-challenge periods saw an increase in both SUDS (pre: 82 vs. post: 387;372% increase) and diphenhydramine ingestions (pre: 2,672 vs. post: 3,030;13% increase). While there were no significant changes in moderate or major clinical outcomes, hospitalizations increased post-challenge for both SUDS [pre: 4 (4.9%) vs. post: 33 (8.5%);p = 0.25] and diphenhydramine [pre: n = 904 (33.8%) vs. post: 1,190 (39.3%);p Conclusion: Pediatric ingestions reported to U.S. PCCs and hospitalizations increased coinciding with the introduction of Tide Pod® and Benadryl® challenges. While causality cannot be definitively established, it is essential for pediatricians and parents to be aware of these challenges and educate vulnerable children about the harmful effects of participation in such challenges.展开更多
Background: The global adoption of Personal Health Records (PHRs) has prompted discussions about data privacy and sharing preferences. Despite Japan’s advancing digital health initiatives, public attitudes toward hea...Background: The global adoption of Personal Health Records (PHRs) has prompted discussions about data privacy and sharing preferences. Despite Japan’s advancing digital health initiatives, public attitudes toward health data sharing remain understudied. Objectives: This study investigated the willingness to share personal health information among Fukuoka City employees as part of the “PHR Fukuoka Project.” Methods: A cross-sectional online survey was distributed to 11,604 municipal employees from February 1st - 20th, 2023. The survey assessed willingness to share personal and family health information across 36 scenarios, combining six purposes (health maintenance, medical care, emergencies, research, product development, and family sharing) with six recipient types (family, friends, healthcare providers, employers, government, and private companies). Sociodemographic factors and digital literacy were examined through logistic regression analysis. Results: Of 1241 respondents (10.6% response rate), 17.1% were willing to share personal health information, 37.3% were neutral, and 45.6% were opposed, with similar patterns for family health information (15.6%, 34.0%, 50.5%, respectively). Male gender (odds ratio [OR] 1.43, 95% confidence interval [CI] 1.12 - 1.82), smartphone use (OR 2.63, 95% CI 1.12 - 6.20), and health app usage (OR 1.41, 95% CI 1.09 - 1.83) predicted increased willingness to share. Respondents were most willing to share information for emergencies and medical care with family members and healthcare providers, while least willing to share for product development or with employers. Conclusions: While approximately half of respondents showed potential openness to sharing health information, privacy concerns persist. These findings suggest sufficient public support for digital health initiatives in Japan, though successful implementation requires careful consideration of sharing purposes and recipients, alongside robust privacy protections.展开更多
Federated learning is a machine learning framework designed to protect privacy by keeping training data on clients’devices without sharing private data.It trains a global model through collaboration between clients a...Federated learning is a machine learning framework designed to protect privacy by keeping training data on clients’devices without sharing private data.It trains a global model through collaboration between clients and the server.However,the presence of data heterogeneity can lead to inefficient model training and even reduce the final model’s accuracy and generalization capability.Meanwhile,data scarcity can result in suboptimal cluster distributions for few-shot clients in centralized clustering tasks,and standalone personalization tasks may cause severe overfitting issues.To address these limitations,we introduce a federated learning dual optimization model based on clustering and personalization strategy(FedCPS).FedCPS adopts a decentralized approach,where clients identify their cluster membership locally without relying on a centralized clustering algorithm.Building on this,FedCPS introduces personalized training tasks locally,adding a regularization term to control deviations between local and cluster models.This improves the generalization ability of the final model while mitigating overfitting.The use of weight-sharing techniques also reduces the computational cost of central machines.Experimental results on MNIST,FMNIST,CIFAR10,and CIFAR100 datasets demonstrate that our method achieves better personalization effects compared to other personalized federated learning methods,with an average test accuracy improvement of 0.81%–2.96%.Meanwhile,we adjusted the proportion of few-shot clients to evaluate the impact on accuracy across different methods.The experiments show that FedCPS reduces accuracy by only 0.2%–3.7%,compared to 2.1%–10%for existing methods.Our method demonstrates its advantages across diverse data environments.展开更多
Taking Zhejiang Province as an example,this paper explores the mechanisms and implementation pathways through which the low-altitude economy drives the transformation and upgrading of the tourism industry.It finds tha...Taking Zhejiang Province as an example,this paper explores the mechanisms and implementation pathways through which the low-altitude economy drives the transformation and upgrading of the tourism industry.It finds that the low-altitude economy can effectively promote the development of high-end and diversified tourism in Zhejiang by innovating tourism formats,optimizing resource allocation,and enhancing tourist experiences.Besides,it analyzes the current development status of the low-altitude economy in Zhejiang and its potential for integration with tourism,revealing specific enabling pathways for tourism transformation,including low-altitude sightseeing,aviation tourism,and low-altitude sports.Finally,it proposes policy recommendations such as strengthening policy support,enhancing infrastructure development,and cultivating market entities.The findings aim to provide theoretical references and practical guidance for the high-quality development of tourism in Zhejiang Province.展开更多
In the age of information explosion and artificial intelligence, sentiment analysis tailored for the tobacco industry has emerged as a pivotal avenue for cigarette manufacturers to enhance their tobacco products. Exis...In the age of information explosion and artificial intelligence, sentiment analysis tailored for the tobacco industry has emerged as a pivotal avenue for cigarette manufacturers to enhance their tobacco products. Existing solutions have primarily focused on intrinsic features within consumer reviews and achieved significant progress through deep feature extraction models. However, they still face these two key limitations: (1) neglecting the influence of fundamental tobacco information on analyzing the sentiment inclination of consumer reviews, resulting in a lack of consistent sentiment assessment criteria across thousands of tobacco brands;(2) overlooking the syntactic dependencies between Chinese word phrases and the underlying impact of sentiment scores between word phrases on sentiment inclination determination. To tackle these challenges, we propose the External Knowledge-enhanced Cross-Attention Fusion model, CITSA. Specifically, in the Cross Infusion Layer, we fuse consumer comment information and tobacco fundamental information through interactive attention mechanisms. In the Textual Attention Enhancement Layer, we introduce an emotion-oriented syntactic dependency graph and incorporate sentiment-syntactic relationships into consumer comments through a graph convolution network module. Subsequently, the Textual Attention Layer is introduced to combine these two feature representations. Additionally, we compile a Chinese-oriented tobacco sentiment analysis dataset, comprising 55,096 consumer reviews and 2074 tobacco fundamental information entries. Experimental results on our self-constructed datasets consistently demonstrate that our proposed model outperforms state-of-the-art methods in terms of accuracy, precision, recall, and F1-score.展开更多
JUST days into the Year of the Snake,U.S.President Donald Trump signed an executive order imposing a 10 percent additional tariff on imports from China.While this may seem lower than the 25 percent tariffs levied on C...JUST days into the Year of the Snake,U.S.President Donald Trump signed an executive order imposing a 10 percent additional tariff on imports from China.While this may seem lower than the 25 percent tariffs levied on Canada and Mexico,it comes on top of previous tariffs,escalating the intensity of China-U.S.trade friction.This reckless act of economic aggression is bound to throw a wrench into China-U.S.trade,harming Chinese businesses while directly driving up consumer costs in the United States and undermining the interests of the American people.展开更多
BACKGROUND Gastric cancer remains a significant global health concern.Radical gastrectomy is the primary curative treatment.Diabetes mellitus is a common comorbidity in patients undergoing surgery for gastric cancer,i...BACKGROUND Gastric cancer remains a significant global health concern.Radical gastrectomy is the primary curative treatment.Diabetes mellitus is a common comorbidity in patients undergoing surgery for gastric cancer,including radical gastrectomy.Previous studies have suggested that diabetes can negatively affect postoperative outcomes,such as wound healing,infection rates,and overall recovery.However,the specific impact of diabetes on recovery after radical gastrectomy for gastric cancer remains poorly understood.evaluate the influence of diabetes on postope-rative recovery,including hospital stay duration,complications,and readmission rates,in patients undergoing gastrectomy for gastric cancer.Understanding these effects could help optimize perioperative management and improve patient out-comes.gastric cancer and associated postoperative outcomes.METHODS This retrospective cohort study was performed at the Endocrinology Department of Xuanwu Hospital,Capital Medical University,Beijing,China.We examined patients who underwent radical gastrectomy for cancer between January 2010 and December 2020.The patients were divided into the diabetes and non-diabetes groups.The main outcomes included length of hospital stay,postoperative com-plications,and 30-day readmission rate.Secondary outcomes included quality of life indicators.Propensity score matching was used to adjust for potential con-founding factors.RESULTS A total of 1210 patients were included in the study,with 302 diabetic patients and 908 non-diabetic patients.After propensity score matching,280 patients were included in each group.Diabetic patients demonstrated significantly longer hospital stays(mean difference 2.3 days,95%CI:1.7-2.9,P<0.001)and higher rates of postoperative complications(OR 1.68,95%CI:1.32-2.14,P<0.001).The 30-day readmission rate was also higher in the diabetic group as compared to the non-diabetic group(12.5%vs 7.8%,P=0.02).CONCLUSION Patients with diabetes mellitus undergoing radical gastrectomy for gastric cancer experience prolonged hospital stay,increased postoperative complications,and higher readmission rates,thus requiring optimized perioperative management strategies.展开更多
The rapid development of information technology in the digital era has led the development and reform in the field of education.Both the transformation and high-quality development of open universities have put forwar...The rapid development of information technology in the digital era has led the development and reform in the field of education.Both the transformation and high-quality development of open universities have put forward higher requirements for open education governance.Focusing on the important field of open education governance,this study,from the perspective of university governance,deeply explores the practical dilemmas faced by open education governance,such as unclear development positioning,difficulties in transformation and development,inadequate learning support services,insufficient depth of teaching reform,and weak professional development of teachers.In the lifelong learning education ecology of universal education,open education governance should focus on“useful and easy learning”,focus on industry-education integration,take serving society as its purpose,and promote the transformation and development of open education.Under the concept of collaboration and co-governance,a multi-subject collaborative governance mechanism should be built,and governance thinking should be actively implemented in open education and teaching affairs to accelerate the modernization of open education governance.This aims to realize the sustainable development of open education governance and provide strong theoretical support and practical guidance for building a more fair,high-quality,and flexible open education governance system.展开更多
BACKGROUND Hepatocellular carcinoma(HCC)is a major cause of cancer-related mortality worldwide,and the research landscape has rapidly evolved over the past two decades.Despite significant progress,an in-depth analysis...BACKGROUND Hepatocellular carcinoma(HCC)is a major cause of cancer-related mortality worldwide,and the research landscape has rapidly evolved over the past two decades.Despite significant progress,an in-depth analysis of global research trends,collaborative networks,and emerging themes in HCC remains limited.This study aimed to fill this gap by conducting a bibliometric analysis to map the research output,identify key contributors,and highlight future directions in HCC research.We hypothesized that the analysis would reveal a growing focus on molecular mechanisms and immunotherapy,with increasing contributions from specific countries and institutions.AIM To investigate global research trends,collaborative networks,and emerging themes in HCC from 2004 to 2023.METHODS A bibliometric analysis was performed using 93987 publications from the Science Citation Index Expanded Database of the Web of Science Core Collection.Data were analyzed using the VOSviewer software to identify publication trends,leading contributors,and research themes.Key metrics included annual publication output,country and institutional contributions,journal impact,and thematic clusters.Statistical analysis was carried out to quantify trends and collaborations.RESULTS The number of annual publications increased from 2341 in 2004 to 8756 in 2023,with 65583 papers(69.78%)published between 2014 and 2023.China,the United States,and Japan were the top contributors,constituting 58.3%of total publications.PLOS One published the most studies(n=2145),while Gastroenterology had the highest average number of citations(78.4 citations per paper).Fudan University was the most prolific institution(n=1872).Thematic analysis identified five main clusters,namely molecular mechanisms,therapeutic strategies,prognosis and immunology,risk factors,and diagnostic approaches.CONCLUSION This study highlights the growing focus on HCC research,particularly in immunotherapy and molecular mechanisms,underscoring the significance of international collaboration to advance diagnosis and treatment strategies.展开更多
With the rapid development of the Artificial Intelligence of Things(AIoT),convolutional neural networks(CNNs)have demonstrated potential and remarkable performance in AIoT applications due to their excellent performan...With the rapid development of the Artificial Intelligence of Things(AIoT),convolutional neural networks(CNNs)have demonstrated potential and remarkable performance in AIoT applications due to their excellent performance in various inference tasks.However,the users have concerns about privacy leakage for the use of AI and the performance and efficiency of computing on resource-constrained IoT edge devices.Therefore,this paper proposes an efficient privacy-preserving CNN framework(i.e.,EPPA)based on the Fully Homomorphic Encryption(FHE)scheme for AIoT application scenarios.In the plaintext domain,we verify schemes with different activation structures to determine the actual activation functions applicable to the corresponding ciphertext domain.Within the encryption domain,we integrate batch normalization(BN)into the convolutional layers to simplify the computation process.For nonlinear activation functions,we use composite polynomials for approximate calculation.Regarding the noise accumulation caused by homomorphic multiplication operations,we realize the refreshment of ciphertext noise through minimal“decryption-encryption”interactions,instead of adopting bootstrapping operations.Additionally,in practical implementation,we convert three-dimensional convolution into two-dimensional convolution to reduce the amount of computation in the encryption domain.Finally,we conduct extensive experiments on four IoT datasets,different CNN architectures,and two platforms with different resource configurations to evaluate the performance of EPPA in detail.展开更多
Surgical site infections(SSIs)are the most common healthcare-related infections in patients with lung cancer.Constructing a lung cancer SSI risk prediction model requires the extraction of relevant risk factors from l...Surgical site infections(SSIs)are the most common healthcare-related infections in patients with lung cancer.Constructing a lung cancer SSI risk prediction model requires the extraction of relevant risk factors from lung cancer case texts,which involves two types of text structuring tasks:attribute discrimination and attribute extraction.This article proposes a joint model,Multi-BGLC,around these two types of tasks,using bidirectional encoder representations from transformers(BERT)as the encoder and fine-tuning the decoder composed of graph convolutional neural network(GCNN)+long short-term memory(LSTM)+conditional random field(CRF)based on cancer case data.The GCNN is used for attribute discrimination,whereas the LSTM and CRF are used for attribute extraction.The experiment verified the effectiveness and accuracy of the model compared with other baseline models.展开更多
Previous bidirectional quantum private comparison(BQPC)protocols cannot meet the requirements in some special application scenarios,where only one party needs to obtain the comparison results without a third party(TP)...Previous bidirectional quantum private comparison(BQPC)protocols cannot meet the requirements in some special application scenarios,where only one party needs to obtain the comparison results without a third party(TP),such as scenarios for authority surveys or healthcare data sharing.In addition to this,the BQPC protocol has the potential of information leakage in multiple comparisons.Therefore,we design a new unidirectional quantum private comparison(UQPC)protocol based on quantum private query(QPQ)protocols with ideal database security and zero failure probability(IDS-ZF),for the reason that they have excellent unidirectionality and security.Concretely,we design a UQPC protocol based on Wei et al.’s work[IEEE Transactions on Computers 672(2017)]and it includes an authentication process to increase the resistance to outside attacks.Moreover,we generalize the protocol and propose a general model that can transform a QPQ protocol with or without the IDS-ZF property into a secure UQPC protocol.Finally,our study shows that protocols using our model are secure,practical,and have the IDS-ZF property.展开更多
The precise mathematical method was adopted to simulate the breakdown process of 5 mm rod and plate electrode gap,which was filled with supercritical nitrogen at the condition of 127 K,4 MPa and seed electron density ...The precise mathematical method was adopted to simulate the breakdown process of 5 mm rod and plate electrode gap,which was filled with supercritical nitrogen at the condition of 127 K,4 MPa and seed electron density 1×10^(6) m^(-3) under 29 kV DC voltage.The result shows that the discharge process was completed within 11.8 ns from seed electron triggering,avalanche bulking to streamer extending until gap eventually breakdown.The entire gap breakdown process was divided into three discharge stages,namely,the initial discharge triggered(0-4 ns),avalanche(4-7 ns)and streamer phase(7-11.8 ns).At the same time,the facts were also revealed that the discharge evolution,electric field distribution,and electron density had different values,and also showed different temporal and spatial distribution characteristics along the axis of the discharge gap.Specifically,the discharge characteristics of SCN2 under 1,2,3,4,4.5,and 5 MPa at 127 K were theoretically analyzed respectively,and the microscopic mechanisms of the breakdown process were also detailed.The results indicate that the gas discharge law remained applicable within the 1-3 MPa range.However,the discharge characteristics of supercritical nitrogen at 3.4-5 MPa differed significantly from those at lower pressures,likely attributable to the unique state of matter exhibited by supercritical nitrogen.This study contributes to understanding the discharge mechanism of supercritical nitrogen and offers theoretical guidance for its practical application in the power industry.展开更多
The diversity and complexity of the user population on the campus network increase the risk of computer virus infection during terminal information interactions.Therefore,it is crucial to explore how computer viruses ...The diversity and complexity of the user population on the campus network increase the risk of computer virus infection during terminal information interactions.Therefore,it is crucial to explore how computer viruses propagate between terminals in such a network.In this study,we establish a novel computer virus spreading model based on the characteristics of the basic network structure and a classical epidemic-spreading dynamics model,adapted to real-world university scenarios.The proposed model contains six groups:susceptible,unisolated latent,isolated latent,infection,recovery,and crash.We analyze the proposed model's basic reproduction number and disease-free equilibrium point.Using real-world university terminal computer virus propagation data,a basic computer virus infection rate,a basic computer virus removal rate,and a security protection strategy deployment rate are proposed to define the conversion probability of each group and perceive each group's variation tendency.Furthermore,we analyze the spreading trend of computer viruses in the campus network in terms of the proposed computer virus spreading model.We propose specific measures to suppress the spread of computer viruses in terminals,ensuring the safe and stable operation of the campus network terminals to the greatest extent.展开更多
Using complex network methods,we construct undirected and directed heatwave networks to systematically analyze heatwave events over China from 1961 to 2023,exploring their spatiotemporal evolution patterns in differen...Using complex network methods,we construct undirected and directed heatwave networks to systematically analyze heatwave events over China from 1961 to 2023,exploring their spatiotemporal evolution patterns in different regions.The findings reveal a significant increase in heatwaves since the 2000s,with the average occurrence rising from approximately 3 to 5 times,and their duration increasing from 15 to around 30 days,nearly doubling.An increasing trend of“early onset and late withdrawal”of heatwaves has become more pronounced each year.In particular,eastern regions experience heatwaves that typically start earlier and tend to persist into September,exhibiting greater interannual variability compared to western areas.The middle and lower reaches of the Yangtze River and Xinjiang are identified as high-frequency heatwave areas.Complex network analysis reveals the dynamics of heatwave propagation,with degree centrality and synchronization distance indicating that the middle and lower reaches of the Yangtze River,Northeast China,and Xinjiang are key nodes in heatwave spread.Additionally,network divergence analysis shows that Xinjiang acts as a“source”area for heatwaves,exporting heat to surrounding regions,while the central region functions as a major“sink,”receiving more heatwave events.Further analysis from 1994 to 2023 indicates that heatwave events exhibit stronger network centrality and more complex synchronization patterns.These results suggest that complex networks provide a refined framework for depicting the spatiotemporal dynamics of heatwave propagation,offering new avenues for studying their occurrence and development patterns.展开更多
In September 2020,a pioneering observational network of three X-band phased-array radars(XPARs)was established in Xiamen,a subtropical coastal and densely populated city in southeastern China.Statistically,this study ...In September 2020,a pioneering observational network of three X-band phased-array radars(XPARs)was established in Xiamen,a subtropical coastal and densely populated city in southeastern China.Statistically,this study demonstrated that the XPAR network outperforms single S-band radar in revealing the warm-season convective storms in Xiamen in a fine-scale manner.The findings revealed that convective activity in Xiamen is most frequent in the central and northern mountainous regions,with lower frequency observed in the southern coastal areas.The diurnal pattern of convection occurrence exhibited a unimodal distribution,with a peak in the afternoon.The frequent occurrence of convective storms correlates well in both time and space with the active terrain uplift that occurs when the prevailing winds encounter mountainous areas.Notably,September stands apart with a bimodal diurnal pattern,featuring a prominent afternoon peak and a significant secondary peak before midnight.Further examination of dense rain gauge data in Xiamen indicates that high-frequency areas of short-duration heavy rainfall largely coincide with regions of active convective storms,except for a unique rainfall hotspot in southern Xiamen,where moderate convection frequency is accompanied by substantial rainfall.This anomalous rainfall,predominantly nocturnal,appears less influenced by terrain uplift and exhibits higher precipitation efficiency than daytime rainfall.These preliminary findings offer insights into the characteristics of convection occurrence in Xiamen's subtropical coastal environment and hold promise for enhancing the accuracy of convection and precipitation forecasts in similar environments.展开更多
Atmospheric de-aliasing is one of the most important background models for recovering Earth's temporal gravity field from gravity satellite missions.To meet the needs of China's gravimetric satellite platform,...Atmospheric de-aliasing is one of the most important background models for recovering Earth's temporal gravity field from gravity satellite missions.To meet the needs of China's gravimetric satellite platform,an independent atmospheric dealiasing model that relies on Chinese meteorological data needs to be developed.The release of CRA-40,as the firstgeneration Chinese atmospheric reanalysis,provides the opportunity.This study proposes a revised modeling method to calibrate CRA-40 and develops a new atmospheric de-aliasing model(HUST-CRA,2002-20).Intensive assessments are made between HUST-CRA and the latest official de-aliasing product of the international gravity satellite mission.The tidal components of the two products demonstrate high consistency,e.g.,the spatial correlation for the major tide S_1 is 0.96.The non-tidal components of the two products are also equivalent:(1)the temporal correlation of low-degree terms is higher than 0.97,except for the term of S22(0.93);(2)the spectral correlation of degree geoid height up to degree/order 100 is as high as 0.99;(3)the confidence interval of the spatial correlation(2002-20)is[0.971,0.995]at a confidence level of 95%;and(4)the difference in KBRR(K-band range rate)residuals is less than 0.08μm s^(-1),the difference in the derived temporal gravity field is less than 0.32 mm in terms of geoid height,and both are apparently beyond the ability of the current gravity satellite mission.This confirms that CRA-40 is of high quality and that the derived de-aliasing product,HUST-CRA,is accurate enough to be used in both Chinese and international gravity satellite missions.展开更多
基金funded by the Open Foundation of Key Laboratory of Cyberspace Security,Ministry of Education[KLCS20240210].
文摘With the rapid growth of the Internet and social media, information is widely disseminated in multimodal forms, such as text and images, where discriminatory content can manifest in various ways. Discrimination detection techniques for multilingual and multimodal data can identify potential discriminatory behavior and help foster a more equitable and inclusive cyberspace. However, existing methods often struggle in complex contexts and multilingual environments. To address these challenges, this paper proposes an innovative detection method, using image and multilingual text encoders to separately extract features from different modalities. It continuously updates a historical feature memory bank, aggregates the Top-K most similar samples, and utilizes a Gated Recurrent Unit (GRU) to integrate current and historical features, generating enhanced feature representations with stronger semantic expressiveness to improve the model’s ability to capture discriminatory signals. Experimental results demonstrate that the proposed method exhibits superior discriminative power and detection accuracy in multilingual and multimodal contexts, offering a reliable and effective solution for identifying discriminatory content.
基金supported by the National Natural Science Foundation of China(No.2022YFC82200842)the Zhejiang Provincial Natural Science Foundation of China(No.LQ22H050004).
文摘Background:Following the short-term outbreak of coronavirus disease 2019(COVID-19)in December 2022 in China,clinical data on kidney transplant recipients(KTRs)with COVID-19 are lacking.Methods:We conducted a single-center retrospective study to describe the clinical features,complications,and mortality rates of hospitalized KTRs infected with COVID-19 between Dec.16,2022 and Jan.31,2023.The patients were followed up until Mar.31,2023.Results:A total of 324 KTRs with COVID-19 were included.The median age was 49 years.The median time between the onset of symptoms and admission was 13 d.Molnupiravir,azvudine,and nirmatrelvir/ritonavir were administered to 67(20.7%),11(3.4%),and 148(45.7%)patients,respectively.Twenty-nine(9.0%)patients were treated with more than one antiviral agent.Forty-eight(14.8%)patients were treated with tocilizumab and 53(16.4%)patients received baricitinib therapy.The acute kidney injury(AKI)occurred in 81(25.0%)patients and 39(12.0%)patients were admitted to intensive care units.Fungal infections were observed in 55(17.0%)patients.Fifty(15.4%)patients lost their graft.The 28-d mortality rate of patients was 9.0%and 42(13.0%)patients died by the end of follow-up.Multivariate Cox regression analysis identified that cerebrovascular disease,AKI incidence,interleukin(IL)-6 level of>6.8 pg/mL,daily dose of corticosteroids of>50 mg,and fungal infection were all associated with an increased risk of death for hospitalized patients.Conclusions:Our findings demonstrate that hospitalized KTRs with COVID-19 are at high risk of mortality.The administration of immunomodulators or the late application of antiviral drugs does not improve patient survival,while higher doses of corticosteroids may increase the death risk.
文摘Background: Social media platforms are popular among children and often feature challenges that become viral. Notably, the Tide Pod® and Benadryl® challenges encouraged viewers to ingest these substances for their visual appeal and hallucinogenic effects, respectively. This study aimed to assess the clinical impact and outcomes of single-use detergent sacs (SUDS) and diphenhydramine challenges on pediatric ingestions reported to United States (U.S.) Poison Control Centers (PCCs). Methods: We conducted a retrospective review of pediatric exposures reported to U.S. PCCs using data from the National Poison Data System (NPDS). The study included intentional single-substance ingestions of both brand-name and generic forms of SUDS and diphenhydramine among children ≤ 19 years. We compared the number of calls, clinical effects, disposition, and management strategies for SUDS (pre: 01/01/17 to 12/31/17 vs. post: 01/01/18 to 12/31/18) and diphenhydramine (pre: 08/01/19 to 07/31/20 vs. post: 08/01/20 to 07/31/21) ingestions 12 months before and after the introduction of the respective social media challenges. Differences in proportions were compared using the Chi-square test. Results: During the study period, 469 ingestions of SUDS and 5,702 ingestions of diphenhydramine were reported. Post-challenge periods saw an increase in both SUDS (pre: 82 vs. post: 387;372% increase) and diphenhydramine ingestions (pre: 2,672 vs. post: 3,030;13% increase). While there were no significant changes in moderate or major clinical outcomes, hospitalizations increased post-challenge for both SUDS [pre: 4 (4.9%) vs. post: 33 (8.5%);p = 0.25] and diphenhydramine [pre: n = 904 (33.8%) vs. post: 1,190 (39.3%);p Conclusion: Pediatric ingestions reported to U.S. PCCs and hospitalizations increased coinciding with the introduction of Tide Pod® and Benadryl® challenges. While causality cannot be definitively established, it is essential for pediatricians and parents to be aware of these challenges and educate vulnerable children about the harmful effects of participation in such challenges.
文摘Background: The global adoption of Personal Health Records (PHRs) has prompted discussions about data privacy and sharing preferences. Despite Japan’s advancing digital health initiatives, public attitudes toward health data sharing remain understudied. Objectives: This study investigated the willingness to share personal health information among Fukuoka City employees as part of the “PHR Fukuoka Project.” Methods: A cross-sectional online survey was distributed to 11,604 municipal employees from February 1st - 20th, 2023. The survey assessed willingness to share personal and family health information across 36 scenarios, combining six purposes (health maintenance, medical care, emergencies, research, product development, and family sharing) with six recipient types (family, friends, healthcare providers, employers, government, and private companies). Sociodemographic factors and digital literacy were examined through logistic regression analysis. Results: Of 1241 respondents (10.6% response rate), 17.1% were willing to share personal health information, 37.3% were neutral, and 45.6% were opposed, with similar patterns for family health information (15.6%, 34.0%, 50.5%, respectively). Male gender (odds ratio [OR] 1.43, 95% confidence interval [CI] 1.12 - 1.82), smartphone use (OR 2.63, 95% CI 1.12 - 6.20), and health app usage (OR 1.41, 95% CI 1.09 - 1.83) predicted increased willingness to share. Respondents were most willing to share information for emergencies and medical care with family members and healthcare providers, while least willing to share for product development or with employers. Conclusions: While approximately half of respondents showed potential openness to sharing health information, privacy concerns persist. These findings suggest sufficient public support for digital health initiatives in Japan, though successful implementation requires careful consideration of sharing purposes and recipients, alongside robust privacy protections.
基金supported by the Foundation of President of Hebei University(XZJJ202303).
文摘Federated learning is a machine learning framework designed to protect privacy by keeping training data on clients’devices without sharing private data.It trains a global model through collaboration between clients and the server.However,the presence of data heterogeneity can lead to inefficient model training and even reduce the final model’s accuracy and generalization capability.Meanwhile,data scarcity can result in suboptimal cluster distributions for few-shot clients in centralized clustering tasks,and standalone personalization tasks may cause severe overfitting issues.To address these limitations,we introduce a federated learning dual optimization model based on clustering and personalization strategy(FedCPS).FedCPS adopts a decentralized approach,where clients identify their cluster membership locally without relying on a centralized clustering algorithm.Building on this,FedCPS introduces personalized training tasks locally,adding a regularization term to control deviations between local and cluster models.This improves the generalization ability of the final model while mitigating overfitting.The use of weight-sharing techniques also reduces the computational cost of central machines.Experimental results on MNIST,FMNIST,CIFAR10,and CIFAR100 datasets demonstrate that our method achieves better personalization effects compared to other personalized federated learning methods,with an average test accuracy improvement of 0.81%–2.96%.Meanwhile,we adjusted the proportion of few-shot clients to evaluate the impact on accuracy across different methods.The experiments show that FedCPS reduces accuracy by only 0.2%–3.7%,compared to 2.1%–10%for existing methods.Our method demonstrates its advantages across diverse data environments.
文摘Taking Zhejiang Province as an example,this paper explores the mechanisms and implementation pathways through which the low-altitude economy drives the transformation and upgrading of the tourism industry.It finds that the low-altitude economy can effectively promote the development of high-end and diversified tourism in Zhejiang by innovating tourism formats,optimizing resource allocation,and enhancing tourist experiences.Besides,it analyzes the current development status of the low-altitude economy in Zhejiang and its potential for integration with tourism,revealing specific enabling pathways for tourism transformation,including low-altitude sightseeing,aviation tourism,and low-altitude sports.Finally,it proposes policy recommendations such as strengthening policy support,enhancing infrastructure development,and cultivating market entities.The findings aim to provide theoretical references and practical guidance for the high-quality development of tourism in Zhejiang Province.
基金supported by the Global Research and Innovation Platform Fund for Scientific Big Data Transmission(Grant No.241711KYSB20180002)National Key Research and Development Project of China(Grant No.2019YFB1405801).
文摘In the age of information explosion and artificial intelligence, sentiment analysis tailored for the tobacco industry has emerged as a pivotal avenue for cigarette manufacturers to enhance their tobacco products. Existing solutions have primarily focused on intrinsic features within consumer reviews and achieved significant progress through deep feature extraction models. However, they still face these two key limitations: (1) neglecting the influence of fundamental tobacco information on analyzing the sentiment inclination of consumer reviews, resulting in a lack of consistent sentiment assessment criteria across thousands of tobacco brands;(2) overlooking the syntactic dependencies between Chinese word phrases and the underlying impact of sentiment scores between word phrases on sentiment inclination determination. To tackle these challenges, we propose the External Knowledge-enhanced Cross-Attention Fusion model, CITSA. Specifically, in the Cross Infusion Layer, we fuse consumer comment information and tobacco fundamental information through interactive attention mechanisms. In the Textual Attention Enhancement Layer, we introduce an emotion-oriented syntactic dependency graph and incorporate sentiment-syntactic relationships into consumer comments through a graph convolution network module. Subsequently, the Textual Attention Layer is introduced to combine these two feature representations. Additionally, we compile a Chinese-oriented tobacco sentiment analysis dataset, comprising 55,096 consumer reviews and 2074 tobacco fundamental information entries. Experimental results on our self-constructed datasets consistently demonstrate that our proposed model outperforms state-of-the-art methods in terms of accuracy, precision, recall, and F1-score.
文摘JUST days into the Year of the Snake,U.S.President Donald Trump signed an executive order imposing a 10 percent additional tariff on imports from China.While this may seem lower than the 25 percent tariffs levied on Canada and Mexico,it comes on top of previous tariffs,escalating the intensity of China-U.S.trade friction.This reckless act of economic aggression is bound to throw a wrench into China-U.S.trade,harming Chinese businesses while directly driving up consumer costs in the United States and undermining the interests of the American people.
文摘BACKGROUND Gastric cancer remains a significant global health concern.Radical gastrectomy is the primary curative treatment.Diabetes mellitus is a common comorbidity in patients undergoing surgery for gastric cancer,including radical gastrectomy.Previous studies have suggested that diabetes can negatively affect postoperative outcomes,such as wound healing,infection rates,and overall recovery.However,the specific impact of diabetes on recovery after radical gastrectomy for gastric cancer remains poorly understood.evaluate the influence of diabetes on postope-rative recovery,including hospital stay duration,complications,and readmission rates,in patients undergoing gastrectomy for gastric cancer.Understanding these effects could help optimize perioperative management and improve patient out-comes.gastric cancer and associated postoperative outcomes.METHODS This retrospective cohort study was performed at the Endocrinology Department of Xuanwu Hospital,Capital Medical University,Beijing,China.We examined patients who underwent radical gastrectomy for cancer between January 2010 and December 2020.The patients were divided into the diabetes and non-diabetes groups.The main outcomes included length of hospital stay,postoperative com-plications,and 30-day readmission rate.Secondary outcomes included quality of life indicators.Propensity score matching was used to adjust for potential con-founding factors.RESULTS A total of 1210 patients were included in the study,with 302 diabetic patients and 908 non-diabetic patients.After propensity score matching,280 patients were included in each group.Diabetic patients demonstrated significantly longer hospital stays(mean difference 2.3 days,95%CI:1.7-2.9,P<0.001)and higher rates of postoperative complications(OR 1.68,95%CI:1.32-2.14,P<0.001).The 30-day readmission rate was also higher in the diabetic group as compared to the non-diabetic group(12.5%vs 7.8%,P=0.02).CONCLUSION Patients with diabetes mellitus undergoing radical gastrectomy for gastric cancer experience prolonged hospital stay,increased postoperative complications,and higher readmission rates,thus requiring optimized perioperative management strategies.
基金2022 Education and Teaching Research and Reform Project of Guangdong Open University System,“Practical Dilemmas and Practical Paths of Educational Governance in Open Education in the Post-Pandemic Era”(Project No.:2022TXJG35)。
文摘The rapid development of information technology in the digital era has led the development and reform in the field of education.Both the transformation and high-quality development of open universities have put forward higher requirements for open education governance.Focusing on the important field of open education governance,this study,from the perspective of university governance,deeply explores the practical dilemmas faced by open education governance,such as unclear development positioning,difficulties in transformation and development,inadequate learning support services,insufficient depth of teaching reform,and weak professional development of teachers.In the lifelong learning education ecology of universal education,open education governance should focus on“useful and easy learning”,focus on industry-education integration,take serving society as its purpose,and promote the transformation and development of open education.Under the concept of collaboration and co-governance,a multi-subject collaborative governance mechanism should be built,and governance thinking should be actively implemented in open education and teaching affairs to accelerate the modernization of open education governance.This aims to realize the sustainable development of open education governance and provide strong theoretical support and practical guidance for building a more fair,high-quality,and flexible open education governance system.
基金Supported by National Natural Science Foundation of China,No.82372070 and No.82072037。
文摘BACKGROUND Hepatocellular carcinoma(HCC)is a major cause of cancer-related mortality worldwide,and the research landscape has rapidly evolved over the past two decades.Despite significant progress,an in-depth analysis of global research trends,collaborative networks,and emerging themes in HCC remains limited.This study aimed to fill this gap by conducting a bibliometric analysis to map the research output,identify key contributors,and highlight future directions in HCC research.We hypothesized that the analysis would reveal a growing focus on molecular mechanisms and immunotherapy,with increasing contributions from specific countries and institutions.AIM To investigate global research trends,collaborative networks,and emerging themes in HCC from 2004 to 2023.METHODS A bibliometric analysis was performed using 93987 publications from the Science Citation Index Expanded Database of the Web of Science Core Collection.Data were analyzed using the VOSviewer software to identify publication trends,leading contributors,and research themes.Key metrics included annual publication output,country and institutional contributions,journal impact,and thematic clusters.Statistical analysis was carried out to quantify trends and collaborations.RESULTS The number of annual publications increased from 2341 in 2004 to 8756 in 2023,with 65583 papers(69.78%)published between 2014 and 2023.China,the United States,and Japan were the top contributors,constituting 58.3%of total publications.PLOS One published the most studies(n=2145),while Gastroenterology had the highest average number of citations(78.4 citations per paper).Fudan University was the most prolific institution(n=1872).Thematic analysis identified five main clusters,namely molecular mechanisms,therapeutic strategies,prognosis and immunology,risk factors,and diagnostic approaches.CONCLUSION This study highlights the growing focus on HCC research,particularly in immunotherapy and molecular mechanisms,underscoring the significance of international collaboration to advance diagnosis and treatment strategies.
基金supported by the Natural Science Foundation of China No.62362008the Major Scientific and Technological Special Project of Guizhou Province([2024]014).
文摘With the rapid development of the Artificial Intelligence of Things(AIoT),convolutional neural networks(CNNs)have demonstrated potential and remarkable performance in AIoT applications due to their excellent performance in various inference tasks.However,the users have concerns about privacy leakage for the use of AI and the performance and efficiency of computing on resource-constrained IoT edge devices.Therefore,this paper proposes an efficient privacy-preserving CNN framework(i.e.,EPPA)based on the Fully Homomorphic Encryption(FHE)scheme for AIoT application scenarios.In the plaintext domain,we verify schemes with different activation structures to determine the actual activation functions applicable to the corresponding ciphertext domain.Within the encryption domain,we integrate batch normalization(BN)into the convolutional layers to simplify the computation process.For nonlinear activation functions,we use composite polynomials for approximate calculation.Regarding the noise accumulation caused by homomorphic multiplication operations,we realize the refreshment of ciphertext noise through minimal“decryption-encryption”interactions,instead of adopting bootstrapping operations.Additionally,in practical implementation,we convert three-dimensional convolution into two-dimensional convolution to reduce the amount of computation in the encryption domain.Finally,we conduct extensive experiments on four IoT datasets,different CNN architectures,and two platforms with different resource configurations to evaluate the performance of EPPA in detail.
基金the Special Project of the Shanghai Municipal Commission of Economy and Information Technology for Promoting High-Quality Industrial Development(No.2024-GZL-RGZN-02011)the Shanghai City Digital Transformation Project(No.202301002)the Project of Shanghai Shenkang Hospital Development Center(No.SHDC22023214)。
文摘Surgical site infections(SSIs)are the most common healthcare-related infections in patients with lung cancer.Constructing a lung cancer SSI risk prediction model requires the extraction of relevant risk factors from lung cancer case texts,which involves two types of text structuring tasks:attribute discrimination and attribute extraction.This article proposes a joint model,Multi-BGLC,around these two types of tasks,using bidirectional encoder representations from transformers(BERT)as the encoder and fine-tuning the decoder composed of graph convolutional neural network(GCNN)+long short-term memory(LSTM)+conditional random field(CRF)based on cancer case data.The GCNN is used for attribute discrimination,whereas the LSTM and CRF are used for attribute extraction.The experiment verified the effectiveness and accuracy of the model compared with other baseline models.
基金supported by the National Key Research and Development Program of China(Grant Nos.2024YFB2906504 and 2024YFB2906500)the National Natural Science Foundation of China(Grant Nos.62401067 and 62272051)the 111 Project(Grant No.B21049).
文摘Previous bidirectional quantum private comparison(BQPC)protocols cannot meet the requirements in some special application scenarios,where only one party needs to obtain the comparison results without a third party(TP),such as scenarios for authority surveys or healthcare data sharing.In addition to this,the BQPC protocol has the potential of information leakage in multiple comparisons.Therefore,we design a new unidirectional quantum private comparison(UQPC)protocol based on quantum private query(QPQ)protocols with ideal database security and zero failure probability(IDS-ZF),for the reason that they have excellent unidirectionality and security.Concretely,we design a UQPC protocol based on Wei et al.’s work[IEEE Transactions on Computers 672(2017)]and it includes an authentication process to increase the resistance to outside attacks.Moreover,we generalize the protocol and propose a general model that can transform a QPQ protocol with or without the IDS-ZF property into a secure UQPC protocol.Finally,our study shows that protocols using our model are secure,practical,and have the IDS-ZF property.
基金Sponsored by the National Natural Science Foundation of China(Grant No.51077032).
文摘The precise mathematical method was adopted to simulate the breakdown process of 5 mm rod and plate electrode gap,which was filled with supercritical nitrogen at the condition of 127 K,4 MPa and seed electron density 1×10^(6) m^(-3) under 29 kV DC voltage.The result shows that the discharge process was completed within 11.8 ns from seed electron triggering,avalanche bulking to streamer extending until gap eventually breakdown.The entire gap breakdown process was divided into three discharge stages,namely,the initial discharge triggered(0-4 ns),avalanche(4-7 ns)and streamer phase(7-11.8 ns).At the same time,the facts were also revealed that the discharge evolution,electric field distribution,and electron density had different values,and also showed different temporal and spatial distribution characteristics along the axis of the discharge gap.Specifically,the discharge characteristics of SCN2 under 1,2,3,4,4.5,and 5 MPa at 127 K were theoretically analyzed respectively,and the microscopic mechanisms of the breakdown process were also detailed.The results indicate that the gas discharge law remained applicable within the 1-3 MPa range.However,the discharge characteristics of supercritical nitrogen at 3.4-5 MPa differed significantly from those at lower pressures,likely attributable to the unique state of matter exhibited by supercritical nitrogen.This study contributes to understanding the discharge mechanism of supercritical nitrogen and offers theoretical guidance for its practical application in the power industry.
基金Project supported by the National Natural Science Foundation of China(Nos.62266030 and 61863025)。
文摘The diversity and complexity of the user population on the campus network increase the risk of computer virus infection during terminal information interactions.Therefore,it is crucial to explore how computer viruses propagate between terminals in such a network.In this study,we establish a novel computer virus spreading model based on the characteristics of the basic network structure and a classical epidemic-spreading dynamics model,adapted to real-world university scenarios.The proposed model contains six groups:susceptible,unisolated latent,isolated latent,infection,recovery,and crash.We analyze the proposed model's basic reproduction number and disease-free equilibrium point.Using real-world university terminal computer virus propagation data,a basic computer virus infection rate,a basic computer virus removal rate,and a security protection strategy deployment rate are proposed to define the conversion probability of each group and perceive each group's variation tendency.Furthermore,we analyze the spreading trend of computer viruses in the campus network in terms of the proposed computer virus spreading model.We propose specific measures to suppress the spread of computer viruses in terminals,ensuring the safe and stable operation of the campus network terminals to the greatest extent.
基金Project supported by the National Key Research and Development Program of China(Grant Nos.2022YFE0136000 and 2024YFC3013100)the Joint Meteorological Fund(Grant No.U2342211)+1 种基金the Joint Research Project for Meteorological Capacity Improvement(Grant No.22NLTSZ004)the National Meteorological Information Center(Grant No.NMICJY202301)。
文摘Using complex network methods,we construct undirected and directed heatwave networks to systematically analyze heatwave events over China from 1961 to 2023,exploring their spatiotemporal evolution patterns in different regions.The findings reveal a significant increase in heatwaves since the 2000s,with the average occurrence rising from approximately 3 to 5 times,and their duration increasing from 15 to around 30 days,nearly doubling.An increasing trend of“early onset and late withdrawal”of heatwaves has become more pronounced each year.In particular,eastern regions experience heatwaves that typically start earlier and tend to persist into September,exhibiting greater interannual variability compared to western areas.The middle and lower reaches of the Yangtze River and Xinjiang are identified as high-frequency heatwave areas.Complex network analysis reveals the dynamics of heatwave propagation,with degree centrality and synchronization distance indicating that the middle and lower reaches of the Yangtze River,Northeast China,and Xinjiang are key nodes in heatwave spread.Additionally,network divergence analysis shows that Xinjiang acts as a“source”area for heatwaves,exporting heat to surrounding regions,while the central region functions as a major“sink,”receiving more heatwave events.Further analysis from 1994 to 2023 indicates that heatwave events exhibit stronger network centrality and more complex synchronization patterns.These results suggest that complex networks provide a refined framework for depicting the spatiotemporal dynamics of heatwave propagation,offering new avenues for studying their occurrence and development patterns.
基金Natural Science Foundation of Fujian Province(2023J011338)Guided Foundation of Xiamen Science and Technology Bureau(3502Z20214ZD4009,3502Z20214ZD4010)+1 种基金Key Projects of East China Phased Array Weather Radar Application Joint Laboratory(EPJL_RP2025010)National Natural Science Foundation of China(41905049)。
文摘In September 2020,a pioneering observational network of three X-band phased-array radars(XPARs)was established in Xiamen,a subtropical coastal and densely populated city in southeastern China.Statistically,this study demonstrated that the XPAR network outperforms single S-band radar in revealing the warm-season convective storms in Xiamen in a fine-scale manner.The findings revealed that convective activity in Xiamen is most frequent in the central and northern mountainous regions,with lower frequency observed in the southern coastal areas.The diurnal pattern of convection occurrence exhibited a unimodal distribution,with a peak in the afternoon.The frequent occurrence of convective storms correlates well in both time and space with the active terrain uplift that occurs when the prevailing winds encounter mountainous areas.Notably,September stands apart with a bimodal diurnal pattern,featuring a prominent afternoon peak and a significant secondary peak before midnight.Further examination of dense rain gauge data in Xiamen indicates that high-frequency areas of short-duration heavy rainfall largely coincide with regions of active convective storms,except for a unique rainfall hotspot in southern Xiamen,where moderate convection frequency is accompanied by substantial rainfall.This anomalous rainfall,predominantly nocturnal,appears less influenced by terrain uplift and exhibits higher precipitation efficiency than daytime rainfall.These preliminary findings offer insights into the characteristics of convection occurrence in Xiamen's subtropical coastal environment and hold promise for enhancing the accuracy of convection and precipitation forecasts in similar environments.
基金financial support from the National Natural Science Foundation of China(Grant Nos.42274112 and 41804016)supported by Danmarks Frie Forskningsfond[https://doi.org/10.46540/2035-00247B]through the DANSk-LSM project and HPC Platform of Huazhong University of Science and Technology。
文摘Atmospheric de-aliasing is one of the most important background models for recovering Earth's temporal gravity field from gravity satellite missions.To meet the needs of China's gravimetric satellite platform,an independent atmospheric dealiasing model that relies on Chinese meteorological data needs to be developed.The release of CRA-40,as the firstgeneration Chinese atmospheric reanalysis,provides the opportunity.This study proposes a revised modeling method to calibrate CRA-40 and develops a new atmospheric de-aliasing model(HUST-CRA,2002-20).Intensive assessments are made between HUST-CRA and the latest official de-aliasing product of the international gravity satellite mission.The tidal components of the two products demonstrate high consistency,e.g.,the spatial correlation for the major tide S_1 is 0.96.The non-tidal components of the two products are also equivalent:(1)the temporal correlation of low-degree terms is higher than 0.97,except for the term of S22(0.93);(2)the spectral correlation of degree geoid height up to degree/order 100 is as high as 0.99;(3)the confidence interval of the spatial correlation(2002-20)is[0.971,0.995]at a confidence level of 95%;and(4)the difference in KBRR(K-band range rate)residuals is less than 0.08μm s^(-1),the difference in the derived temporal gravity field is less than 0.32 mm in terms of geoid height,and both are apparently beyond the ability of the current gravity satellite mission.This confirms that CRA-40 is of high quality and that the derived de-aliasing product,HUST-CRA,is accurate enough to be used in both Chinese and international gravity satellite missions.
