472 research outputs found
Research Data for Next-day discharge following small uniportal thoracoscopic bullectomy assisted with an anchoring suture
No full textResearch Data, for Next-day discharge following small uniportal thoracoscopic bullectomy assisted with an anchoring suture by Chu Zhang, Miao Zhang, Haiyong Wang, Zhifeng Ma, Yuanlin Wu, Linhai Fu, Ting Zhu and Guangmao Yu in Journal of International Medical Research</p
VGG-MFO-orange for sweetness prediction of Linhai mandarin oranges
No full textAbstract Mandarin orange is a popular fruit in China and known worldwide for its unique flavor and nutritional benefits. As consumer demand for fruit quality increases, the fine assessment and grading of fruit sweetness—especially through non-destructive testing techniques—are becoming increasingly important in agriculture and commerce. In this paper, a new Attention for Orange (AO) attention mechanism and Multiscale Feature Optimization (MFO) feature extraction module are designed and combined with VGG13 convolutional neural network (CNN), innovatively proposed VGG-MFO-Orange CNN model for accurately classifying mandarin oranges with different sweetness. First, a sample of Linhai mandarin oranges was collected, and a sweetness triple classification dataset with 5022 images was formed, utilizing image acquisition and sugar detection. The proposed model was then trained against six influential classical CNN models: DenseNet121, MobileNet_v2, ResNet50, ShuffleNet, VGG13, and VGG13_bn. The experimental results showed that our model achieved an accuracy of 86.8% on the validation set, which was significantly better than the other six models. It also demonstrated excellent generalization ability and effectiveness in predicting the sweetness of Linhai mandarin oranges. Therefore, our model can provide an efficient means of fruit grading for agricultural production, contribute to agricultural modernization, and enhance the competitiveness of agricultural products in the market
Exploring the Relationship Between Rural Development and Marginalization: An Empirical Study from Linhai City, Zhejiang Province, China
No full textThe study focuses on the multidimensional attributes of rural marginalization and their differentiated impact on rural development levels. Based on a systematic review and summary of research findings, this study elucidates the conceptual implications of rural development levels and rural marginalization and deconstructs rural marginalization into five dimensions. Considering Linhai City in Zhejiang Province, China, as the research object, a measurement model for rural development levels was constructed comprising basic and enhancement factors. An influencing factor set was established based on the perspective of marginalization. Spatial autocorrelation and multiscale geographically weighted regression models were comprehensively employed to measure and analyze rural development levels and their influencing factors. The main findings are as follows: (1) the concept of rural marginalization is defined from five dimensions: spatial, technological, policy, social, and infrastructural, and a quantitative evaluation system is established; (2) through quantitative analysis using Linhai City as an example, it is found that the influence of marginalization across different dimensions on rural development exhibits significant spatial variability, meaning that the impact of marginalization on rural development levels is influenced by multiple factors. These findings suggest that, while formulating rural development policies, we should fully consider the actual and external circumstances of different villages, adopt tailored strategies based on local conditions, and avoid implementing one-size-fits-all policies
Influence of Prone Position on the Survival of COVID-19 Patients Undergoing Invasive Mechanical Ventilation: A Propensity Score Matching Study
No full textYuwei Zheng,1,&ast; Chaochao Chen,1,&ast; Xiaojie Bi,1,&ast; Xiaowei Li,2 Jing Wang,1,3 Yufen Zheng,1,3 Yuan Yuan,1 Yongpo Jiang,4 Bo Shen,1,3 Yinghe Xu4 1Department of Clinical Laboratory, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai, Zhejiang, People’s Republic of China; 2Department of Pathology, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai, Zhejiang, People’s Republic of China; 3Key Laboratory of System Medicine and Precision Diagnosis and Treatment of Taizhou, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai, Zhejiang, People’s Republic of China; 4Department of Critical Care Medicine, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai, Zhejiang, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Yinghe Xu, Department of Critical Care Medicine, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, No. 150, Ximen Road, Linhai, Taizhou, Zhejiang, 317000, People’s Republic of China, Email [email protected] Bo Shen, Department of Clinical Laboratory, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai, Zhejiang, People’s Republic of China, Email [email protected]: The role of prone position (PP) in critically ill patients diagnosed with coronavirus disease 2019 (COVID-19) undergoing invasive mechanical ventilation remains unclear. This study aimed to evaluate the potential prognostic benefits of PP.Patients and methods: This retrospective study included data from 289 critically ill patients with COVID-19 who underwent invasive mechanical ventilation in a multicenter setting. Propensity score matching was used to match 156 patients (78 PP-treated, 78 non-PP-treated) after adjusting for age, sex, underlying disease, and Sequential Organ Failure Assessment score. Between-group comparisons of clinical data, laboratory results, and prognosis were performed. Kaplan–Meier (K–M) survival curve and univariate and multivariate Cox regression analyses were used to explore the relationship between PP and prognosis.Results: Prone positioning improved oxygenation (oxygenation index in the PP group increased consistently, with the greatest improvement observed on days 12– 13 compared with the non-PP group [48 vs 32 mmHg; P < 0.001]) and increased hospital survival (80.8% vs 65.4%; P = 0.047). K–M survival curve analysis revealed that patients treated with PP had a more favorable prognosis (P = 0.025). Multivariate Cox regression revealed that PP was linked to lower risk of death (HR 0.389 [95% CI 0.173– 0.878]), while age (HR 1.053 [95% CI 1.012– 1.096]), Acute Physiology and Chronic Health Evaluation II score (HR 1.055 [95% CI 1.006– 1.107]), and troponin T levels (HR 2.028 [95% CI 1.222– 3.367]) were linked to higher risk of death in the overall survival of patients with COVID-19.Conclusion: PP improved oxygenation and increased the survival rate of critically ill patients with COVID-19 undergoing invasive mechanical ventilation. Adopting PP as much as possible during nursing care may enhance patient survival.Keywords: COVID-19, prone position, mechanical ventilation, survival, prognosi
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Towards Improving the Adversarial Robustness of Deep Neural Networks
No full textDeep neural networks (DNNs) have achieved state-of-the-art performance in various tasks. However, studies show that DNNs are vulnerable to adversarial noises that are unperceivable perturbations to the input of a DNN and can lead to significant variation in the output. Lots of efforts have been made to develop defense methods to improve the robustness of DNNs against adversarial noises. I focus on developing novel methods to improve DNN robustness against adversarial noises with applications for ECG signal analysis and medical image analysis. First, I propose a regularization method, named NSR, to improve DNN's adversarial robustness by minimizing the estimated upper bound of the noise-to-signal ratio (NSR) in the output. Two ECG signal classification tasks are used to show the effectiveness of my proposed regularization method and its superiority over baseline methods. Second, I propose an adversarial training method, named IMA. For each individual training sample, IMA makes a sample-wise estimation of the upper bound of the adversarial perturbation. I evaluate this method on six publicly available image datasets. The experiments show that IMA achieves the highest adversarial robustness for image classification and segmentation with a minimal reduction in accuracy on clean data. Third, I propose an adversarial training method named AME, which is parameter-free for the user. I evaluate AME on three commonly used image benchmark datasets. The results show that AME has the best overall performance. Fourth, I propose a general defense method, named AMAT, that can be applied to various deep learning-based tasks. I apply this method on state-of-the-art DNNs, including the Unet-based model (nnUnet) for Heart, Hippocampus, and Prostate MRI images segmentation, multi-task Unet-based model for cephalometric landmark detection and YOLO V5 for blood cell bounding box detection. The experimental results demonstrate the effectiveness of my proposed method. </p
Douglas Fir Productivity Estimation Using Very High Spatial Resolution Imagery: A Case Study on Ground Treatment Impact in West Kootenay, British Columbia, Canada
No full textGeospatial Technologies & Natural Resource ManagementGeospatial Technologie
The datasets generated to plot the Figure 2 to Figure 9.
No full text(1) The Terrestrial Hybrid Repeated Gravity Observation data is applied from Data Sharing Infrastructure of National Earthquake Data Center(http://data.earthquake.cn).Only Chinese language link(https://data.earthquake.cn/datashare/report.shtml?PAGEID=datasourcelist&dt=40280d0453e5add30153e5ee3dc1001f; https://data.earthquake.cn/datashare/report.shtml?PAGEID=datasourcelist&dt=40280d0453e5add30153e5f03dd10022). Data can be requested through the email application form or the offline application form.
(2) Earthquake catalog data comes from the end of China Seismic Experimental Site webpage (http://www.cses.ac.cn/sjcp/ggmx/2021/132.shtml). Click on "cata2019".
(3) 3He/4He release data is downloaded from the supplementary data of published article. (https://github.com/mzhangrocks/Plateau-Growth) We have cited this article in this paper.
(4) The 3-D P- and S-wave community velocity model of the crust and uppermost mantle in southwest China is downloaded from the supplementary data of published article. (https://github.com/liuyingustc/SWChinaCVM),(SWChinaCVM-1.0, DOI:10.12093/02md.02.2019.01.v1). We have cited this article in this paper
Canopy Vertical Parameters Estimation Using Unmanned Aerial Vehicle (UAV) Imagery
No full textGeospatial Technologies & Natural Resource ManagementGeospatial Technologie
Prognostic Value of the Preoperative Lymphocyte‐to‐Monocyte Ratio for Postoperative Adverse Events in Patients with Acute Type a Aortic Dissection
No full textLimin Jia,1 Yanfeng Wang,2 Junqiang Wang,1 Yulian Lin,1 Chunguo Wang,1 Caihua Chen1 1Department of Cardiothoracic Surgery, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou, Zhejiang, People’s Republic of China; 2Department of Geriatrics, Taizhou Central Hospital (Taizhou University Hospital) of Zhejiang, Taizhou, Zhejiang, People’s Republic of ChinaCorrespondence: Caihua Chen, Department of Cardiothoracic Surgery, Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, No. 150, Ximen Street, Linhai City, Taizhou, Zhejiang, 317000, People’s Republic of China, Tel +86-13867656416, Email [email protected]: To investigate the prognostic value of the preoperative lymphocyte‐to‐monocyte ratio (LMR) for postoperative adverse events in patients with acute type A aortic dissection (ATAAD).Methods: A retrospective study of the clinical data collected in our hospital between March 2015 and January 2024 was performed on 290 patients diagnosed with ATAAD who underwent surgical treatment and met the inclusion criteria for patient selection. The included patients were divided into a low LMR group (< 1.70, 50 cases) and a high LMR group (≥ 1.70, 51 cases). Clinical data, including white blood cell counts (WBCs), D-dimer (D-D) levels, lymphocyte count (LYM) and platelet count (PLT), were compared between the two groups. Logistic regression analysis assessed the association between the preoperative LMR and postoperative adverse events.Results: The high LMR group had lower WBCs and NEU than the low LMR group (P < 0.05). The high LMR group also had higher LYM than the low LMR group (P < 0.05). Within 30 days postoperative, the all‐cause mortality rate was higher in the low LMR group than in the high LMR group (P = 0.047). Within 1 year postoperative, the incidence of aortic adverse events (AAEs) (P = 0.010), Re-intervention events (P = 0.011) and Cardiovascular and cerebrovascular adverse events (P < 0.001) has no difference between the high LMR group and the low LMR group. Logistic regression analysis indicated that the preoperative LMR was a significant prognostic marker for AAEs within 30 days and 1 year postoperative.Conclusion: The preoperative LMR is a prognostic indicator of all‐cause mortality within 30 days and 1 year postoperative in patients with ATAAD.Keywords: lymphocyte‐monocyte ratio, acute type A aortic dissection, adverse aortic even
Physicochemical stability of ternary admixtures of butorphanol, ketamine, and droperidol in polyolefin bags for patient-controlled analgesia use
No full textBaoxia Fang,1 Linhai Wang,2 Junfeng Gu,3 Fuchao Chen,1 Xiao-ya Shi1 1Department of Pharmacy, Dongfeng Hospital, 2Department of Pharmacy, 3Department of Anesthesiology, Renmin Hospital, Hubei University of Medicine, Hubei, People’s Republic of China Background: Delivery of drug admixtures by intravenous patient-controlled analgesia is a common practice for the management of postoperative pain; however, analytical confirmation of the compatibility and stability of butorphanol tartrate, ketamine hydrochloride, and droperidol combined in ternary admixtures is not available.Methods: Butorphanol tartrate, ketamine hydrochloride, and droperidol have been examined for compatibility and stability when combined with 0.9% sodium chloride injection stored at 4°C and 25°C with light protection for a total of 14 days. Concentrations were 0.067 mg/mL, 1.33 mg/mL, and 0.033 mg/mL for butorphanol tartrate, ketamine hydrochloride, and droperidol, respectively. Drug concentrations were determined using high-performance liquid chromatographic analysis.Results: All three drugs were very stable (>97%) at 4°C and 25°C for 14 days. The ternary admixtures were initially clear and colorless throughout the observation period, and the pH value did not change significantly.Conclusion: The results confirm that the ternary admixture of butorphanol tartrate 0.067 mg/mL, ketamine hydrochloride 1.33 mg/mL, and droperidol 0.033 mg/mL in 0.9% sodium chloride injection were stable for 14 days when stored in polyolefin bags at 4°C and 25°C and protected from light. Keywords: analgesia, patient-controlled analgesia, drug stability, butorphanol, ketamine, droperidol, HPL
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