Nursing Care of a Case of Mediastinal Tumor Resection Combined with Postoperative Thoracic Hemorrhage after Video-assisted Thoracoscopic Surgery (VATS)

Objective: To summarize the nursing experience of a patient withpostoperative intrathoracic hemorrhage after thoracoscopic-assistedresection of the right upper mediastinal tumor through the original incision.Methods: Summarize the main points of nursing care of postoperativeintrathoracic hemorrhage after thoracoscopic mediastinal surgery, includingobservation and nursing when internal hemorrhage occurs after operation,respiratory management, activity management and pain managementmeasures. Result: After careful care, the patient recovered and dischargedsmoothly. Conclusion: It is particularly important to observe the overallobservation and take timely corresponding nursing measures for patientswith intrathoracic hemorrhage after thoracoscopic mediastinal surgery

Lead to Elevate the Temperature and Speed of Emergency Rescue and Nursing Care of Common Carotid Artery Rupture and Massive Hemorrhage after Operation of Typical Esophageal Cancer

Objective: Objective To explore the first aid and nursing of patientswith anastomotic fistula after radical resection of esophagus carcinomacomplicated with major carotid hemorrhage. Methods: The clinical dataof anastomotic fistula complicated with carotid artery rupture and massivehemorrhage after radical resection of typical esophageal carcinoma wereanalyzed and summarized. Results: Through the close cooperation ofmedical care, the rescue was successful. Conclusion: Earlier preventionobservation, raising first aid consciousness and actively cooperating withdoctors can improve the success rate of rescue

Spatial and Temporal Variability of Sea Surface Temperature in the Yellow Sea and East China Sea over the Past 141 Years

The Yellow Sea and East China Sea (YES) are marginal seas in the northwest Pacific. There is in fact a smaller sea, the Bohai Sea, to the north of the Yellow Sea. For most discussions in the chapter, we shall treat the Bohai Sea as part of the Yellow Sea. The YES is one of the mostly intensively utilized sea in the world, for example, heavy fishery and marine aquaculture. The use of the YES is closely related to its climate variability, though it is not well-know because until now there has been a lack of adequate observational data. To know the climatology of sea surface temperature (SST, all the acronyms used in the chapter are listed in Table 1) in the YES and their relationship with regional and global climate have both scientific and social importance.https://digitalcommons.usu.edu/modern_climatology/1007/thumbnail.jp

Joint Power and Multiple Access Control for Wireless Mesh Network with Rose Projection Method

This paper investigates the utility maximization problem for the downlink of the multi-interface multichannel wireless mesh network with orthogonal frequency division multiple access. A cross-layer joint power and multiple access control algorithm are proposed. Rosen projection matrix is combined with Solodov projection techniques to build a three-memory gradient Rosen projection method, which is applied to solve this optimization problem. The convergence analysis is given and simulations show that the proposed solution achieves significant throughput compared with existing approaches

SNN2ANN: A Fast and Memory-Efficient Training Framework for Spiking Neural Networks

Spiking neural networks are efficient computation models for low-power environments. Spike-based BP algorithms and ANN-to-SNN (ANN2SNN) conversions are successful techniques for SNN training. Nevertheless, the spike-base BP training is slow and requires large memory costs. Though ANN2NN provides a low-cost way to train SNNs, it requires many inference steps to mimic the well-trained ANN for good performance. In this paper, we propose a SNN-to-ANN (SNN2ANN) framework to train the SNN in a fast and memory-efficient way. The SNN2ANN consists of 2 components: a) a weight sharing architecture between ANN and SNN and b) spiking mapping units. Firstly, the architecture trains the weight-sharing parameters on the ANN branch, resulting in fast training and low memory costs for SNN. Secondly, the spiking mapping units ensure that the activation values of the ANN are the spiking features. As a result, the classification error of the SNN can be optimized by training the ANN branch. Besides, we design an adaptive threshold adjustment (ATA) algorithm to address the noisy spike problem. Experiment results show that our SNN2ANN-based models perform well on the benchmark datasets (CIFAR10, CIFAR100, and Tiny-ImageNet). Moreover, the SNN2ANN can achieve comparable accuracy under 0.625x time steps, 0.377x training time, 0.27x GPU memory costs, and 0.33x spike activities of the Spike-based BP model

NiO hollow microspheres interconnected by carbon nanotubes as an anode for lithium ion batteries

In this work, NiO hollow microspheres interconnected by multi-walled carbon nanotubes (MWCNTs) were prepared, characterized, and evaluated in terms of lithium ion storage properties. Characterization results showed that the NiO hollow microspheres were formed by self assembly of NiO nanoparticles promoted by MWCNTs, which connected the NiO microspheres to form a long-range network. Electrochemical measurement results showed a charge capacity as high as 597.2 mAh g when cycling at the rate 2 C and maintained 85.3% capacity of 0.1 C. After cycling for 100 times at 1 C, it maintained a capacity of 692.3 mAh g with retention 89.3% of the initial capacity. The observed excellent electrochemical performance is attributed to the presence of MWCNTs interconnecting the NiO microspheres of the composite material, of which electronic conductivity was improved, and the mesoporous hollow structure effectively alleviated the volume changes to maintain the structural stability during cycling

ATGL promotes the proliferation of hepatocellular carcinoma cells via the p‐AKT signaling pathway

Abnormal metabolism, including abnormal lipid metabolism, is a hallmark of cancer cells. Some studies have demonstrated that the lipogenic pathway might promote the development of hepatocellular carcinoma (HCC). However, the role of adipose triglyceride lipase (ATGL) in hepatocellular carcinoma cells has not been elucidated. We evaluated the function of ATGL in hepatocellular carcinoma using methyl azazolyl blue and migration assay through overexpression of ATGL in HepG2 cells. Quantitative reverse‐transcription polymerase chain reaction and Western blot analyses were used to assess the mechanisms of ATGL in hepatocellular carcinoma. In the current study, we first constructed and transiently transfected ATGL into hepatocellular carcinoma cells. Secondly, we found that ATGL promoted the proliferation of hepatoma cell lines via upregulating the phosphorylation of AKT, but did not affect the metastatic ability of HCC cells. Moreover, the p‐AKT inhibitor significantly eliminated the effect of ATGL on the proliferation of hepatoma carcinoma cells. Taken together, our results indicated that ATGL promotes hepatocellular carcinoma cells proliferation through upregulation of the AKT signaling pathway

Generation of 100 m, Hourly Land Surface Temperature Based on Spatio-Temporal Fusion

Landsat surface temperature (LST) is an important physical quantity for global climate change monitoring. Over the past decades, several LST products have been produced by satellite thermal infrared (TIR) bands or land surface models (LSMs). Recent research has increased the spatio-temporal resolution of LST products to 2 km, hourly based on Geostationary Operational Environmental Satellites (GOES)-R Advanced Baseline Imager (ABI) LST data. The spatial resolution of 2 km, however, is insufficient for monitoring at the regional scale. This paper investigates the feasibility of applying spatio-temporal fusion to generate reliable 100 m, hourly LST data based on fusion of the newly released 2 km, hourly GOES-16 ABI LST and 100 m Landsat LST data. The most accurate fusion method was identified through a comparison between several popular methods. Furthermore, a comprehensive comparison was performed between fusion (with Landsat LST) involving satellite-derived LST (i.e., GOES) and model-derived LSMs (i.e., European Centre for Medium-range Weather Forecasts (ECMWF) Reanalysis v .5 (ERA5)-Land). The spatial and temporal adaptive reflectance fusion model (STARFM) method was demonstrated to be an appropriate method to generate 100 m, hourly data, which produced an average root mean square error (RMSE) of 2.640 K, mean absolute error (MAE) of 2.159 K and average coefficient of determination ( R 2 ) of 0.982 referring to the in situ time-series. Furthermore, inheriting the advantages of direct observation, and the fusion of Landsat and GOES for the generation of 100 m, hourly LST produced greater accuracy compared to the fusion of Landsat and ERA5-Land LST in the experiments. The generated 100 m, hourly LST can provide important diurnal data with fine spatial resolution for various monitoring applications