Outcomes of astigmatic correction with and without two different cyclotorsion compensation methods in small incision lenticule extraction surgery.

Purpose: To compare the astigmatic correction outcomes of small incision lenticule extraction (SMILE) surgery with or without two different cyclotorsion compensation methods.

Methods: This is a prospective randomized clinical trial. Patients with myopic astigmatism that underwent SMILE surgery were randomly divided into static cyclotorsion compensated group (SCC group), slit-lamp group and control group.

Effect of acupuncture at Shuitong and Shuijin points on sufentanil-induced cough in general anesthesia induction: a randomized controlled trial.

Objectives: To observe the therapeutic effect of acupuncture at Shuitong and Shuijin points on preventing sufentanil-induced cough and its influence on hemodynamics in general anesthesia induction.

Methods: A total of 80 patients scheduled for elective surgery undergoing general anesthesia were randomly divided into an observation group (40 cases) and a control group (39 cases,1 case eliminated). In the control group, the routine anesthesia was performed,with intravenous injection of 1% sufentanil citrate 0.

Spatio-temporal data prediction of multiple air pollutants in multi-cities based on 4D digraph convolutional neural network.

In response to the problem that current multi-city multi-pollutant prediction methods based on one-dimensional undirected graph neural network models cannot accurately reflect the two-dimensional spatial correlations and directedness, this study proposes a four-dimensional directed graph model that can capture the two-dimensional spatial directed information and node correlation information related to multiple factors, as well as extract temporal correlation information at different times. Firstly, A four-dimensional directed GCN model with directed information graph in two-dimensional space was established based on the geographical location of the city. Secondly, Spectral decomposition and tensor operations were then applied to the two-dimensional directed information graph to obtain the graph Fourier coefficients and graph Fourier basis.

Lake eutrophication prediction based on improved MIMO-DD-3Q Learning.

As for the problem that the traditional single depth prediction model has poor strain capacity to the prediction results of time series data when predicting lake eutrophication, this study takes the multi-factor water quality data affecting lake eutrophication as the main research object. A deep reinforcement learning model is proposed, which can realize the mutual conversion of water quality data prediction models at different times, select the optimal prediction strategy of lake eutrophication at the current time according to its own continuous learning, and improve the reinforcement learning algorithm. Firstly, the greedy factor, the fixed parameter of Agent learning training in reinforcement learning, is introduced into an arctangent function and the mean value reward factor is defined.

A Cooperative Hunting Method for Multi-USV Based on the A* Algorithm in an Environment with Obstacles.

A single unmanned surface combatant (USV) has poor mission execution capability, so the cooperation of multiple unmanned surface ships is widely used. Cooperative hunting is an important aspect of multi USV collaborative research. Therefore, this paper proposed a cooperative hunting method for multi-USV based on the A* algorithm in an environment with obstacles.

Remote sensing image analysis and prediction based on improved Pix2Pix model for water environment protection of smart cities.

Background: As an important part of smart cities, smart water environmental protection has become an important way to solve water environmental pollution problems. It is proposed in this article to develop a water quality remote sensing image analysis and prediction method based on the improved Pix2Pix (3D-GAN) model to overcome the problems associated with water environment prediction of smart cities based on remote sensing image data having low accuracy in predicting image information, as well as being difficult to train.

Methods: Firstly, due to inversion differences and weather conditions, water quality remote sensing images are not perfect, which leads to the creation of time series data that cannot be used directly in prediction modeling.

Research on the Construction of Grain Food Multi-Chain Blockchain Based on Zero-Knowledge Proof.

As the main food source of the world's population, grain quality safety is of great significance to the healthy development of human beings. The grain food supply chain is characterized by its long life cycle, numerous and complex business data, difficulty defining private information, and difficult managing and sharing. In order to strengthen the ability of information application processing and coordination of the grain food supply chain under many risk factors, an information management model suitable for the grain food supply chain is studied based on the blockchain multi-chain technology.

Ginkgolide C attenuates cerebral ischemia/reperfusion-induced inflammatory impairments by suppressing CD40/NF-κB pathway.

Ethnopharmacological Relevance: Ginkgo biloba L. (Ginkgoaceae), a traditional Chinese medicine, has been applied for thousands of years for the treatment of cardio-cerebral vascular diseases in China. It is written in Compendium of Materia Medica that Ginkgo has the property of "dispersing poison", which is now referred to as anti-inflammatory and antioxidant.

Stress load and volunteer motivation of patient volunteers in Fangcang shelter hospitals in Shanghai, China during the COVID-19 pandemic: a cross-sectional survey.

Objectives: This study aims to assess the volunteer motivation and stress load of patient volunteers in the Fangcang shelter hospitals (FSHs), examine their associations, and explore the potential influence factors of volunteer motivation.

Design: Cross-sectional online survey conducted from 21 April to 20 May 2022.

Setting: Questionnaires were collected from patient volunteers selected by random cluster sampling in the FSHs in Shanghai, China.

Research on Grain Food Blockchain Traceability Information Management Model Based on Master-Slave Multichain.

Aiming at the problems such as slow traceability efficiency, poor sharing, and the difficulty of matching the throughput of a blockchain single chain structure due to the complexity of the grain food supply chain links, the large number of participants, and the large amount of data information, this paper proposes a grain food blockchain traceability information management model based on the master-slave multichain structure by analyzing the processes and data characteristics of each link in the grain food supply chain; on this basis, the PLEW consensus algorithm based on Raft + improved PoW algorithm is designed for the master chain, and the CI-PBFT consensus algorithm based on trusted information degree is designed for the slave chain. The master chain and slave chain are anchored to each other through hash locking, and the data is uploaded and queried through smart contracts. In order to verify the effectiveness of the model, the blockchain traceability system is designed and implemented based on Hyperledger Fabric2.

Construction of rice supply chain supervision model driven by blockchain smart contract.

The outbreak of the COVID-19 and the Russia Ukraine war has had a great impact on the rice supply chain. Compared with other grain supply chains, rice supply chain has more complex structure and data. Using digital means to realize the dynamic supervision of rice supply chain is helpful to ensure the quality and safety of rice.

A Refined Supervision Model of Rice Supply Chain Based on Multi-Blockchain.

With the development of Agriculture 4.0, the requirements for sustainable agriculture and precision agriculture continue to grow. As one of the three major staple foods globally, the quality and safety of rice affect human health as well as social development.

Information Traceability Model for the Grain and Oil Food Supply Chain Based on Trusted Identification and Trusted Blockchain.

The grain and oil food supply chain has a complex structure, long turnover cycles, and many stakeholders, so it is challenging to maintain the security of this supply chain. A reliable traceability system for the whole grain and oil food supply chain will help to improve the quality and safety of these products, thus enhancing people's living standards. Driven by the trusted blockchain and trusted identity concepts, this paper constructs an information traceability model for the whole grain and oil food supply chain, and it describes how contract implementation and example verification are performed.

Effect Observation of Electro-Acupuncture Anesthesia Combined with General Anesthesia in Elderly Patients Undergoing Gastrointestinal Tumor Resection.

Objective: To investigate the anesthetic effect of electro-acupuncture (EA) anesthesia combined with general anesthesia in elderly patients undergoing gastrointestinal tumor resection, and to analyze the effects of EA anesthesia on inflammatory factors, stress state and T lymphocyte subsets in elderly patients.

Methods: Total of 118 elderly patients who underwent gastrointestinal tumor resection in our hospital from June 2018 to March 2021 were selected and divided into the control group (59 cases) and the observation group (59 cases) according to the random number method. General anesthesia was adopted in the control group and EA anesthesia combined with general anesthesia was adopted in the observation group.

Research on the Cross-Chain Model of Rice Supply Chain Supervision Based on Parallel Blockchain and Smart Contracts.

Rice is one of the three major staple foods in the world, and the quality and safety of rice are related to the development of human beings. The new crown epidemic, pesticide residues, insect pests, and heavy metal pollution have a certain security impact on the food supply chain. The rice supply chain is characterized by a long life cycle; complex roles in the main links; many types of hazards; and multidimensional, multisource, and heterogeneous information.

A Hybrid Multi-Target Path Planning Algorithm for Unmanned Cruise Ship in an Unknown Obstacle Environment.

To solve the problem of traversal multi-target path planning for an unmanned cruise ship in an unknown obstacle environment of lakes, this study proposed a hybrid multi-target path planning algorithm. The proposed algorithm can be divided into two parts. First, the multi-target path planning problem was transformed into a traveling salesman problem, and an improved Grey Wolf Optimization (GWO) algorithm was used to calculate the multi-target cruise sequence.

Blockchain-Based Information Supervision Model for Rice Supply Chains.

Rice is a major food crop around the world, and its various quality and safety problems are closely related to human health. As an important area of food safety research, the rice supply chain has attracted increasing attention. Based on blockchain technology, this study investigated problems of data privacy and circulation efficiency caused by complex rice supply networks, long circulation cycles, and various risk factors in each link.

Screening Candidates for Refractive Surgery With Corneal Tomographic-Based Deep Learning.

Importance: Evaluating corneal morphologic characteristics with corneal tomographic scans before refractive surgery is necessary to exclude patients with at-risk corneas and keratoconus. In previous studies, researchers performed screening with machine learning methods based on specific corneal parameters. To date, a deep learning algorithm has not been used in combination with corneal tomographic scans.

Comparison of outcome between small incision lenticule extraction and FS-LASIK in eyes having refractive error greater than negative 10 diopters.

Purpose: To compare small incision lenticule extraction (SMILE) and femtosecond laser-assisted laser in situ keratomileusis (FS-LASIK) in terms of safety, refractive outcomes, visual quality, and biomechanical responses in correcting myopia with maximum myopic meridian exceeding 10 diopters (D).

Setting: Zhongshan Ophthalmic Center, Sun Yat-sen University.

Design: Prospective, randomized, comparative study.

Development of low laser energy levels in small-incision lenticule extraction: clinical results, black area, and ultrastructural evaluation.

Purpose: To evaluate the outcomes of 4 low laser energy levels after small-incision lenticule extraction (SMILE) surgery.

Setting: Zhongshan Ophthalmic Center, Guangzhou, China.

Design: Prospective randomized clinical trial.

Dynamic Correlation Analysis Method of Air Pollutants in Spatio-Temporal Analysis.

Pollutant analysis and pollution source tracing are critical issues in air quality management, in which correlation analysis is important for pollutant relation modeling. A dynamic correlation analysis method was proposed to meet the real-time requirement in atmospheric management. Firstly, the spatio-temporal analysis framework was designed, in which the process of data monitoring, correlation calculation, and result presentation were defined.

Hard Decision-Based Cooperative Localization for Wireless Sensor Networks.

Reliable and accurate localization of objects is essential for many applications in wireless networks. Especially for large-scale wireless sensor networks (WSNs), both low cost and high accuracy are targets of the localization technology. However, some range-free methods cannot be combined with a cooperative method, because these range-free methods are characterized by low accuracy of distance estimation.

Effect of Cyclotorsion Compensation With a Novel Technique in Small Incision Lenticule Extraction Surgery for the Correction of Myopic Astigmatism.

Purpose: To comparatively investigate the clinical outcomes of small incision lenticule extraction (SMILE) surgery with or without cyclotorsion compensation for the correction of myopic astigmatism.

Methods: This prospective, double-blinded, randomized controlled trial included patients who underwent SMILE surgery with bilateral myopic astigmatism. Two eyes of a single patient were randomly divided into the static cyclotorsion compensation (SCC) group and the control group.

Present status and expectation of aristaless-related homeobox (ARX) in endocrine pancreas.

The aristaless-related homeobox (ARX) gene has become one of most frequently mutated genes which is closely linked with development of the vertebrate central nervous system; however, the molecular and clinical bases of its function in the proliferation and differentiation of the endocrine pancreas have not, to date, been systematically characterized. ARX is considered as a regulator which determines endocrine cell fate and a bio-marker of the pancreatic α-cell. Disruption and mutation of ARX are found to lead to the deletion and reduction of α-cells both in mice models and in humans.