Quantifying multi-regional indirect economic losses: An assessment based on the 2021 rainstorm events in China

Quantitative assessment of economic losses from disasters can benefit government decision-making as well as mitigation and adaptation strategies. Here, we identified significant rainstorm events in China in 2021 using an objective identification method and investigated the direct economic losses (DELs) from each event. Then, a loss assessment model was developed to estimate the indirect economic losses (IDELs) from rainstorm events. We found that, in 2021, China experienced 36 major rainstorm events, causing approximately 179.8 billion yuan in DELs. The north of China was severely affected by rainstorms and floods, with Henan, Hebei and Shaanxi being the main loss centers. The assessment of IDELs based on rainstorm events showed a non-linear relationship between direct and indirect losses. The socio-economic impact of the 2021 Henan flood (Event No. 15) was the most serious, with direct and indirect losses of 125.8 billion yuan and 269.1 billion yuan, respectively. The primary industry in Henan was seriously affected, and the impact also spread to Inner Mongolia and Guangdong, causing indirect losses of 23.9 billion and 13.1 billion yuan, respectively. We recommend that the indirect losses resulting from such interregional trade linkages should be considered in catastrophe risk management. Finally, the sensitivity analysis showed that moderate overproduction can reduce the indirect impacts caused by disasters. A more detailed study is required to explore how to determine the appropriate levels of disaster relief, as well as a rational funding allocation mechanism

Identification and Validation of lncRNA-SNHG17 in Lung Adenocarcinoma: A Novel Prognostic and Diagnostic Indicator

BackgroundLung cancer has the highest death rate among cancers globally. Accumulating evidence has indicated that cancer-related inflammation plays an important role in the initiation and progression of lung cancer. However, the prognosis, immunological role, and associated regulation axis of inflammatory response-related gene (IRRGs) in non-small-cell lung cancer (NSCLC) remains unclear.MethodsIn this study, we perform comprehensive bioinformatics analysis and constructed a prognostic inflammatory response-related gene (IRRGs) and related competing endogenous RNA (ceRNA) network. We also utilized the Pearson’s correlation analysis to determine the correlation between IRRGs expression and tumor mutational burden (TMB), microsatellite instability (MSI), tumor-immune infiltration, and the drug sensitivity in NSCLC. Growth curve and Transwell assay used to verify the function of SNHG17 on NSCLC progression.ResultsFirst, we found that IRRGs were significantly upregulated in lung cancer, and its high expression was correlated with poor prognosis; high expression of IRRGs was significantly correlated with the tumor stage and poor prognosis in lung cancer patients. Moreover, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment indicated that these IRRGs are mainly involved in the inflammatory and immune response-related signaling pathway in the progression of NSCLC. We utilized 10 prognostic-related genes to construct a prognostic IRRGs model that could predict the overall survival of lung adenocarcinoma (LUAD) patients possessing high specificity and accuracy. Our evidence demonstrated that IRRGs expression was significantly correlated with the TMB, MSI, immune-cell infiltration, and diverse cancer-related drug sensitivity. Finally, we identified the upstream regulatory axis of IRRGs in NSCLC, namely, lncRNA MIR503HG/SNHG17/miR-330-3p/regulatory axis. Finally, knockdown of SNHG17 expression inhibited lung adenocarcinoma (LUAD) cell proliferation and migration. Our findings confirmed that SNHG17 is a novel oncogenic lncRNA and may be a biomarker for the prognosis and diagnosis of LUAD.ConclusionDNA hypomethylation/lncRNA MIR503HG/SNHG17/microRNA-330-3p/regulatory axis may be a valuable biomarker for prognosis and is significantly correlated with immune cell infiltration in lung cancer

CLIP-Driven Universal Model for Organ Segmentation and Tumor Detection

An increasing number of public datasets have shown a marked impact on automated organ segmentation and tumor detection. However, due to the small size and partially labeled problem of each dataset, as well as a limited investigation of diverse types of tumors, the resulting models are often limited to segmenting specific organs/tumors and ignore the semantics of anatomical structures, nor can they be extended to novel domains. To address these issues, we propose the CLIP-Driven Universal Model, which incorporates text embedding learned from Contrastive Language-Image Pre-training (CLIP) to segmentation models. This CLIP-based label encoding captures anatomical relationships, enabling the model to learn a structured feature embedding and segment 25 organs and 6 types of tumors. The proposed model is developed from an assembly of 14 datasets, using a total of 3,410 CT scans for training and then evaluated on 6,162 external CT scans from 3 additional datasets. We rank first on the Medical Segmentation Decathlon (MSD) public leaderboard and achieve state-of-the-art results on Beyond The Cranial Vault (BTCV). Additionally, the Universal Model is computationally more efficient (6x faster) compared with dataset-specific models, generalized better to CT scans from varying sites, and shows stronger transfer learning performance on novel tasks.Comment: Rank first in Medical Segmentation Decathlon (MSD) Competitio

Capturing Cognitive Fingerprints from Keystroke Dynamics

Conventional authentication systems identify a user only at the entry point. Keystroke dynamics can continuously authenticate users by their typing rhythms without extra devices. This article presents a new feature called cognitive typing rhythm (CTR) to continuously verify the identities of computer users. Two machine techniques, SVM and KRR, have been developed for the system. The best results from experiments conducted with 1,977 users show a false-rejection rate of 0.7 percent and a false-acceptance rate of 5.5 percent. CTR therefore constitutes a cognitive fingerprint for continuous. Its effectiveness has been verified through a large-scale dataset. This article is part of a special issue on security

Risk factors for diabetic foot ulcers mortality and novel negative pressure combined with platelet-rich plasma therapy in the treatment of diabetic foot ulcers

The purpose of this study was to assess the risk factors for morbidity and mortality of diabetic foot ulcers (DFUs). For the treatment of diabetic foot ulcers, negative pressure wound therapy (NPWT) combined with platelet-rich plasma-fibrin glue (PRP) was also investigated. There were 653 patients in the diabetic foot ulcer group and 510 patients in the diabetic patients without foot ulceration (NFU) group, for a total of 1163 patients in the study samples after individuals without follow-up were excluded. The patients were randomized into two groups: the negative pressure wound therapy group and the negative pressure wound therapy combined with the PRP group. The findings of the univariate analysis revealed the blood indicators for predicting diabetic foot ulcer morbidity risk factors, such as C-reactive protein, albumin, creatinine, alkaline phosphatase, procalcitonin, platelets, 25-hydroxyvitamin D, β-2-microglobulin, monocyte ratio, low-density protein cholesterol (LDL), triglyceride, alanine aminotransferase (ALT), aminotransferase (AST), creatine kinase (CK) and total cholesterol. Using logistic regression analysis revealed only albumin and age to be independent predictors of diabetic foot ulcer mortality. Our study also revealed that, compared to negative pressure wound therapy alone, negative pressure wound therapy combined with PRP accelerated wound healing and reduced the mortality rate. According to the findings of this pilot study, new risk factors for diabetic foot ulcer morbidity and mortality have been found, and negative pressure wound therapy combined with PRP therapy may provide the first information that it is an effective adjunct treatment for diabetic foot ulcers

DeePMD-kit v2: A software package for Deep Potential models

DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials (MLP) known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, Deep Potential - Range Correction (DPRc), Deep Potential Long Range (DPLR), GPU support for customized operators, model compression, non-von Neumann molecular dynamics (NVNMD), and improved usability, including documentation, compiled binary packages, graphical user interfaces (GUI), and application programming interfaces (API). This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, the article benchmarks the accuracy and efficiency of different models and discusses ongoing developments.Comment: 51 pages, 2 figure

China\u27s Spring Festival

Xi Ru once stated that amid the western culture merging into the Chinese society, globalization, and China\u27s market economy, the Chinese community in the People\u27s Republic of China strives to prevent the erosion of culture. In their poster presentation, Yi Xiao and Jiji will present their findings on how the traditional Spring Festival takes agricultural culture as a basis and how this festival is set according to the lunar calendar instead of the solar calendar. Most importantly, the significance of the century old annual Spring Festival will also be discussed.https://dc.swosu.edu/rf_2016/1001/thumbnail.jp