Unforgettable Restaurant: helping older people who are living with disability and dementia return to society

On 25 January 2021,a special restaurant named the‘Unforgettable Restaurant’was opened in a prime locality of Shanghai,China;it emerged from a popular publicly broadcast welfare TV programme of the same name.1 This restaurant’s waiters are older patients with cognitive impairment,and the cumu-lative number of views for the programme has now exceeded 1.4 billion online.23 After the show was broadcast for two consecutive years,the filming party decided to open the restaurant officially,and the waiting duties were assumed by older people living with disability and dementia.

A Planning Method for Operational Test of UAV Swarm Based on Mission Reliability

The unmanned aerial vehicle(UAV)swarm plays an increasingly important role in the modern battlefield,and the UAV swarm operational test is a vital means to validate the combat effectiveness of the UAV swarm.Due to the high cost and long duration of operational tests,it is essential to plan the test in advance.To solve the problem of planning UAV swarm operational test,this study considers the multi-stage feature of a UAV swarm mission,composed of launch,flight and combat stages,and proposes a method to find test plans that can maximize mission reliability.Therefore,a multi-stage mission reliability model for a UAV swarm is proposed to ensure successful implementation of the mission.A multi-objective integer optimization method that considers both mission reliability and cost is then formulated to obtain the optimal test plans.This study first constructs a mission reliability model for the UAV swarm in the combat stage.Then,the launch stage and flight stage are integrated to develop a complete PMS(Phased Mission Systems)reliability model.Finally,the Binary Decision Diagrams(BDD)and Multi Objective Quantum Particle Swarm Optimization(MOQPSO)methods are proposed to solve the model.The optimal plans considering both reliability and cost are obtained.The proposed model supports the planning of UAV swarm operational tests and represents a meaningful exploration of UAV swarm test planning.

视知觉训练治疗对弱视儿童视觉表征和双眼视功能的影响

目的:评价视知觉训练治疗对弱视儿童视觉表征和双眼视功能的影响。方法:选取2014-01/2015-12我院眼科门诊收治的94例94眼弱视儿童为研究对象,并按弱视程度进行分组,采用视知觉训练治疗3mo。比较各组临床疗效及治疗前后的知觉水平眼位和差眼视力,并采用Pearson相关系数分析弱视儿童治疗前后差眼视力差值与知觉眼位差值的关系。结果:轻度弱视儿童临床总有效率高于中、重度弱视儿童(P<0.05),中度弱视儿童与重度弱视儿童临床总有效率比较无差异(P>0.05)。弱视儿童治疗后知觉水平眼位明显低于治疗前(P<0.05);轻、中、重度弱视患儿治疗后知觉水平眼位均明显降低(P<0.05),轻、中度弱视儿童知觉水平眼位改善幅度较重度弱视患儿明显(P<0.05)。弱视儿童治疗后差眼视力较治疗前明显提升(P<0.05);轻、中、重度弱视患儿治疗后差眼视力均明显提高(P<0.05),轻、中度弱视儿童差眼视力改善幅度较重度弱视患儿明显(P<0.05)。弱视儿童治疗前后差眼视力差值与知觉眼位差值呈正相关(r=0.371,P<0.001)。结论:视知觉训练治疗能有效改善弱视儿童视觉表征、双眼视功能,适用于弱视儿童的临床治疗。

连续性血液净化对ICU脓毒症患者血清LA、PCT、CRP水平以及预后的影响

目的探讨脓毒症患者应用连续血液净化治疗的预后效果及对血清LA、PCT、CRP的影响。方法便利择取2015年1月—2019年12月该院ICU收治的62例重症脓毒症患者,分为实验组(ICU常规治疗+连续血液净化,31例)和对照组(ICU常规治疗,31例)。治疗前后,测定两组血清LA、PCT、CRP水平,以APACHE-II量表和SOFA量表评估两组生理健康状况与器官衰竭情况,统计两组ICU收治时间与28 d病死率,评价预后。结果实验组治疗后LA(2.4±1.3)mmol/L、PCT(9.6±4.1)ng/mL、CRP(51.6±13.2)mg/L,APACHE-II(5.9±2.6)分,SOFA(3.0±0.9)分,ICU收治时间(9.4±2.7)d,28 d病死率6.45%,各项指标均优于对照组,差异有统计学意义(t=7.351、14.811、21.937、7.632、5.710、7.892;χ^2=4.292,P<0.05)。结论连续血液净化治疗脓毒症的效果确切,可有效降低患者血清LA、PCT、CRP水平与病死率,对改善预后具有积极作用。

微课在肝胆胰外科住院医师规范化培训中的应用效果研究

目的探究微课在肝胆胰外科住院医师规范化培训中的应用效果。方法选取在武汉大学中南医院肝胆胰外科进行规范化培训的66名学生为研究对象,以2022年3—5月进行规培的29名学生为对照组、2022年9—11月进行规培的37名学生为试验组,对照组采用常规肝胆胰外科规范化培训教学,试验组采用以微课为主的肝胆胰外科规范化培训教学。培训结束后,评估两组学生的理论考试、实践能力考核成绩,以及对肝胆胰外科规范化培训教学的满意度。结果试验组理论考试成绩(86.65±1.98 vs.82.55±2.78,P<0.001)和实践能力考核成绩(94.03±1.55 vs.91.03±2.73,P<0.001)均高于对照组;试验组学生在规范化培训结束后教学满意度显著高于对照组(100%vs.89.65%,P=0.045)。结论将微课应用于肝胆胰外科住院医师规范化培训,有助于提高肝胆胰外科住院医师规范化培训效果、提升临床教学质量和学生的教学满意度。

1例晚期胃癌患者的循证治疗

目的:采用循证医学方法为1例晚期胃癌患者制定诊治方案。方法:根据临床问题检索MEDLINE、ACP Journal Club、中国知网,并利用搜索引擎——谷歌学术搜索在互联网所获取的文献进行归纳分析。结果:共获得有关晚期胃癌姑息手术和新辅助化疗时机的系统评价6篇,临床对照研究病例756例。以上证据表明:晚期胃癌行新辅助化疗的根治性手术率及生存率优于姑息手术组。结合客观证据及患者意愿,为患者实施了两个疗程的奥沙利铂+希罗达(Cape + OX)化疗方案,结合化疗前后病灶的影像学变化,成功实施了手术,无手术后并发症发生。结论:循征医学方法对疑难病例的治疗有一定的指导作用。

Non-alcoholic fatty liver disease:An early mediator predicting metabolic syndrome in obese children?

AIM:To investigate if non-alcoholic fatty liver disease (NAFLD) is an early mediator for prediction of metabolic syndrome,and if liver B-ultrasound can be used for its diagnosis.METHODS:We classified 861 obese children (6-16 years old) into three subgroups:group 0 (normal liver in ultrasound and normal transaminases);group 1 (fatty liver in ultrasound and normal transaminases);and group 2 (fatty liver in ultrasound and elevated transaminases).We measured the body mass index,waist and hip circumference,blood pressure,fasting blood glucose,insulin,homeostasis model assessment of insulin resistance (HOMA-IR),whole-body insulin sensitivity index (WBISI),lipid profile and transaminases in all the participants.The risk of developing metabolic syndrome (MS) was assessed according to the degree of liver fatty infiltration based on the B-ultrasound examination.RESULTS:Among the 861 obese children,587 (68.18%) were classified as having NAFLD,and 221 (25.67%) as having MS.The prevalence of MS in NAFLD children (groups 1 and 2) was 37.64% (221/587),which was much higher than that in non-NAFLD group (group 0,12.04%) (P < 0.01).There were significantly higher incidences concerning every component of MS in group 2 compared with group 0 (P < 0.05).The incidence of NAFLD in MS patients was 84.61% (187/221),which was significantly higher than that of hypertension (57.46%,127/221) and glucose metabolic anomalies (22.62%,50/221),and almost equal to the prevalence of dyslipidemia (89.14%,197/221).Based on the B-ultrasound scales,the presence of moderate and severe liver fatty infiltration carried a high risk of hypertension [odds ratio (OR):2.18,95% confidence interval (95% CI):1.27-3.75],dyslipidemia (OR:7.99,95% CI:4.34-14.73),impaired fasting glucose (OR:3.65,95% CI:1.04-12.85),and whole MS (OR:3.77;95% CI:1.90-7.47,P < 0.01).The state of insulin resistance (calculated by HOMA-IR and WBISI) deteriorated as the degree of fatty infiltration increased.CONCLUSION:NAFLD is not only a liver disease,but also an early mediator that reflects metabolic disorder,and liver B-ultrasound can be a useful tool for MS screening.

Protease-activated receptor(PAR)1, PAR2 and PAR4 expressions in esophageal squamous cell carcinoma

Here,we used reverse transcription-PCR(RT-PCR) and western blot to detect protease-activated receptor(PAR) 1,PAR 2 and PAR 4 expression in cancer tissues and cell lines of esophageal squamous cell carcinoma,and investigated the co-relationship between PAR expression and clinic-pathological data for esophageal cancer.The methylation of PAR4 gene promoter involved in esophageal carcinoma was also analyzed.By comparing the mRNA expressions of normal esophageal tissue and human esophageal epithelial cells(HEEpiC),we found that among the 28 cases of esophageal squamous cell carcinoma,PAR1(60%) and PAR2(71%) were elevated in 17 and 20 cases,respectively,and PAR4(68%) expression was lowered in 19 cases.Whereas,in human esophageal squamous cells(TE-1 and TE-10),PAR1 and PAR2 expression was increased but PAR4 was decreased.Combined with clinical data,the expression of PAR1 in poorly differentiated(P=0.016) and middle and lower parts of the esophagus(P=0.016) was higher; expression of PAR4 in poorly differentiated carcinoma was lower(P=0.049).Regarding TE-1 and TE-10 protein expression,we found that in randomized esophageal carcinoma,PAR1(P=0.027) and PAR2(P=0.039) expressions were increased,but lowered for PAR4(P=0.0001).In HEEpiC,TE-1,TE-10,esophageal and normal esophagus tissue samples(case No.7),the frequency of methylation at the 19 CpG loci of PAR4 was 35.4%,95.2%,83.8%,62.6% and 48.2%,respectively.Our results indicate that the expression of PAR1 and PAR2 in esophageal squamous cell carcinoma is increased but PAR4 is decreased.Hypermethylation of the promoter of the PAR4 gene may contribute to reduced expression of PAR4 in esophageal squamous cell carcinoma.

Whole Body Positron Emission Tomography/Computed Tomography （PET/CT） in the Evaluation of Ophthalmic Tumors

The clinical value of whole body positron emission tomography/computed tomography （PET/CT） as an imaging tool in diagnosis of ophthalmic tumors was investigated. The retrospective observational case series were performed on the patients with suspected ophthalmic tumors who underwent whole body PET/CT. The golden standard of diagnosis was the final pathological diagnosis or the results of long-term follow-up for patients without surgery/ biopsy. PET/CT findings were compared with the golden standard. The sensitivity, specificity, accuracy an^t positive likelihood ratio of PET/CT in the detection of ophthalmic tumors were calculated. The clinical application of PET/CT in different types of ophthalmic tumors was evaluated. The results showed that 30 patients （18 males and 12 females） with a mean age of 43.0 years （range 4-63 years） were collected. The mean sizes of orbital tumors and intraocular tumors were 26.8 mmxl7.8 mm and 11.2 minx6.1 mm, respectively. The overall sensitivity, specificity, accuracy and positive likelihood ratio of whole body PET/CT in ophthalmic tumors were 76.5%, 71.4%, 75.0% and 2.67, and were 62.5%, 100% and 70.0% in intraocular tumors, and those were 100%, 60.0% and 84.6% in orbital tumors, respectively. PET/CT findings were applied to help make appropriate treatment options in 27 out of 30 patients （90.0%）, and 12 （40.0%） patients changed the treatment strategy. False negative results in 4 cases and false positive results in 2 cases were observed in this series. It was suggested that PET/CT was an effective imaging modality in detecting, diagnosing and developing therapeutic schedule for patients with ophthalmic tumors. It was more sensitive and accurate for detecting orbital tumors than for detecting intraocular tumors.

Intelligent Fusion of Infrared and Visible Image Data Based on Convolutional Sparse Representation and Improved Pulse-Coupled Neural Network

Multi-source information can be obtained through the fusion of infrared images and visible light images,which have the characteristics of complementary information.However,the existing acquisition methods of fusion images have disadvantages such as blurred edges,low contrast,and loss of details.Based on convolution sparse representation and improved pulse-coupled neural network this paper proposes an image fusion algorithm that decompose the source images into high-frequency and low-frequency subbands by non-subsampled Shearlet Transform(NSST).Furthermore,the low-frequency subbands were fused by convolutional sparse representation(CSR),and the high-frequency subbands were fused by an improved pulse coupled neural network(IPCNN)algorithm,which can effectively solve the problem of difficulty in setting parameters of the traditional PCNN algorithm,improving the performance of sparse representation with details injection.The result reveals that the proposed method in this paper has more advantages than the existing mainstream fusion algorithms in terms of visual effects and objective indicators.

The Dual Functionals for the Generalized Ball Basis of Wang-Said Type and Basis Transformation Formulas

The generalized Ball curves of Wang-Said type with a position parameter L not only unify the Wang-Ball curves and the Said-Ball curves, but also include several useful intermediate curves. This paper presents the dual functionals for the generalized Ball basis of Wang-Said type. The relevant basis transformation formulae are also worked out.

Designing single-atom catalysts toward improved alkaline hydrogen evolution reaction

Electrochemical water splitting powered by renewables-generated electricity represents a promising approach for green hydrogen production.However,the sluggish kinetics for the hydrogen evolution reaction(HER)under an alkaline medium causes a massive amount of energy losses,hindering large-scale production.Exploring efficient and low-cost catalyst candidates for large-scale H_(2) generation becomes a crucial demand.Single-atom catalysts(SACs)demonstrate great promise for enabling efficient alkaline HER catalysis at maximum atom utilization efficiency.In this review,we provide a comprehensive overview of the recent progress in SACs for the HER application in alkaline environments.The fundamentals of alkaline HER are first introduced,followed by a justification of the need to develop SACs.The rational design of the SACs including the inherent element property,coordination environment,SAC morphology,and SAC mass loading are highlighted.To facilitate the development of SACs for alkaline HER,we further propose the remaining challenges and perspectives in this research field.

Evaluation of the clenbuterol imprinted monolithic column prepared by reversible addition-fragmentation chain transfer polymerization

To make more homogenous organic monolithic structure, reversible addition-fragmentation chain transfer （RAFT） process was employed in the synthesis of the clenbuterol imprinted polymer. In the synthesis, the influence of synthetic conditions on the polymer structure and separation efficiency was studied. The result demonstrated that the imprinted columns prepared with RAFT process have higher column efficiency and selectivity than the columns prepared with conventional polymerization in the present study, which may result from the higher surface area, smaller pore size and the narrower globule size distribution in their structures. The result indicated that RAFT polymerization provided better conditions for the clenbuterol imprinted monolithic polymer preparation. 2009 Xiang Chao Dong. Published by Elsevier B.V. on behalf of Chinese Chemical Society. All rights reserved.

Effects of metabolic syndrome on onset age and long-term outcomes in patients with acute coronary syndrome

BACKGROUND: We aim to investigate effects of metabolic syndrome on onset age and long-termoutcomes in patients with acute coronary syndrome (ACS).METHODS: Patients with ACS (n=6,431) who underwent percutaneous coronary interventionfrom January to December 2013 were enrolled. After excluding patients with previous coronary arterydisease, 1,558 patients were diagnosed with early-onset ACS (men aged ≤50 years;women aged≤60 years) and 3,044 patients with late-onset ACS. Baseline characteristics and five-year clinicaloutcomes were measured.RESULTS: Body mass index, triglyceride, low-density lipoprotein cholesterol, and uric acidconcentrations were significantly higher, while the high-density lipoprotein cholesterol (HDL-C)concentration was lower in the early-onset ACS group (P<0.001). Multivariate logistic regression revealedobesity (odds ratio [OR] 1.590, 95% confi dence interval [CI] 1.345–1.881), hypertriglyceridemia (OR 1.403,95% CI 1.185–1.660), and low HDL-C (OR 1.464, 95% CI 1.231–1.742) as independent risk factorsfor early-onset ACS (all P<0.001). The fi ve-year follow-up showed that the incidences of all cause death(1.5% vs. 3.8%, P<0.001), cardiac death (1.1% vs. 2.0%, P=0.023), and recurrent stroke (2.2% vs. 4.2%,P<0.001) were lower, while bleeding events were more frequent in the early-onset ACS group. A subgroupanalysis showed higher incidences of recurrent myocardial infarction (MI) and revascularization in patientswith early-onset ACS and metabolic syndrome.CONCLUSIONS: Obesity, hypertriglyceridemia, and lower HDL-C level are independent riskfactors for early-onset ACS, recurrent MI, and revascularization. The control of metabolic syndromemay reduce the incidence of early-onset ACS and improve the long-term prognosis.

Sorption equilibrium moisture and isosteric heat of Chinese wheat bran products added to rice to increase its dietary fibre content

More and more people concern about supplementing dietary food with wheat bran to increase fibre content,but there has been little study of the sorption isotherms and isosteric heats of wheat bran fibre products,which are important to the quality and storage durability of such commodities.This study collected equilibrium moisture content(EMC)and equilibrium relative humidity(ERH)data on six Chinese wheat bran products via the static gravimetric method and analysed their sorption isosteric heats.Results showed that all six wheat bran products had sigmoidal isotherms.The data were best fitted by polynomial,modified GAB,modified Oswin,and modified Halsey models.The relative safe moisture contents of the six wheat bran products were 12.20%–13.86%wet basis(w.b.).The heat of vaporization of wheat bran products approached the latent heat of pure water at around a moisture content(MC)of 22.5%and approximately 2450 kJ/kg.A process of extrusion and ultrafine grinding reduced the solid surface area and sorption isosteric heats of the monolayer,multilayer and condensed water regions in the wheat bran products.In the temperature range of 10–37℃,the EMC of sorption in monolayer,multilayer and condensed water regions decreased with increasing temperature.The milled rice to which 1%–3%200-mesh wheat bran product was added maintained its texture when made into cooked rice and its thermomechanical properties when made into rice dough.After processing by extrusion and ultrafine grinding,wheat bran products have a lower solid surface area and lower monolayer water content(Mm)and sorption isosteric heat values.Some 3%200-mesh wheat bran product can be added to cooked rice for increasing its fibre content and making it more nutritious.

Identification of Crop Diseases Based on Improved Genetic Algorithm and Extreme Learning Machine

As an indispensable task in crop protection,the detection of crop diseases directly impacts the income of farmers.To address the problems of low crop-disease identification precision and detection abilities,a new method of detection is proposed based on improved genetic algorithm and extreme learning machine.Taking five different typical diseases with common crops as the objects,this method first preprocesses the images of crops and selects the optimal features for fusion.Then,it builds a model of crop disease identification for extreme learning machine,introduces the hill-climbing algorithm to improve the traditional genetic algorithm,optimizes the initial weights and thresholds of the machine,and acquires the approximately optimal solution.And finally,a data set of crop diseases is used for verification,demonstrating that,compared with several other common machine learning methods,this method can effectively improve the crop-disease identification precision and detection abilities and provide a basis for the identification of other crop diseases.

Patient outcomes in the field of nursing: A concept analysis

Purpose:This paper reports an analysis of the concept of patient outcomes.Methods:The Walker and Avant concept analysis approach was applied.Results:The attributes of patient outcomes include(1)patient functional status(maintained or improved),(2)patient safety(protected or unharmed),and(3)patient satisfaction(patient reporting of comfort and contentment).These attributes are influenced by the antecedents of individual patient characteristics and health problems,the structure of healthcare organizations and received health interventions.Additionally,patient outcomes do significantly impact the quality of nursing care,the cost of effective care and healthcare policy making formulation.Conclusion:Providing good nursing care to all patients is a central goal of nursing.Patient outcomes in nursing are primarily about the results for the patient receiving nursing care.This analysis provides nurses with a new perspective by helping them to understand all the components within the concept of patient outcomes.

Extraction of Robot Primitive Control Rules from Natural Language Instructions

A support vector rule based method is investigated for the construction of motion controllers via natural language training. It is a two-phase process including motion control information collection from natural language instructions, and motion information condensation with the aid of support vector machine （SVM） theory. Self-organizing fuzzy neural networks are utilized for the collection of control rules, from which support vector rules are extracted to form a final controller to achieve any given control accuracy. In this way, the number of control rules is reduced, and the structure of the controller tidied, making a controller constructed using natural language training more appropriate in practice, and providing a fundamental rule base for high-level robot behavior control. Simulations and experiments on a wheeled robot are carried out to illustrate the effectiveness of the method.

Self-healing elastomer modified proppants for proppant flowback control in hydraulic fracturing

To address proppant flowback issues during post-fracturing treatments and production,self-healing elastomer modified proppants(SMPs)are proposed.Owing to their inherent self-aggregation behavior,the SMPs can aggregate together spontaneously to prevent proppant flowback and increase the pack porosity.It is noteworthy that the SMPs have a firm and dry self-healing elastomer(SE)coating,making their storage,transport and use as conventional proppants possible.The SE synthesized through polymerization is rich in amidogens and carbonyl groups as characterized by Fourier transform infrared spectroscopy and the proton nuclear magnetic resonance.Thermal and thermomechanical properties of the SE coating are revealed by the thermogravimetric analysis,the differential scanning calorimetry and the rheological tests.The self-aggregation behavior of the SMPs is demonstrated by the adhesion force tests.The reversible hydrogen bonding interactions in SE coating contribute to the self-aggregation behavior of the SMPs,which is revealed by the thixotropy test and the FTIR analysis at different temperatures.With the self-aggregation behavior,the crushed proppants can aggregate in situ to form a stable structure again and therefore reduce the threat of narrowing down the fracture and proppant flowback,which has an important practical significance during oil and gas production.

Faint Space Debris Detection Algorithm Based on Small Aperture Telescope Detection System

Ground-based optical observation has unique advantages in space target observation.However,due to the weak light-gathering ability of small-aperture optoelectronic observation telescopes,the space debris in the image is weak and easily drowned in noise.In order to solve the above problems,we use digital image processing technology to extract faint space debris.We propose a high detection rate space debris automatic extraction algorithm,aiming to automatically detect space debris.We first establish a new space target description model.Our algorithm is mainly divided into two stages.The purpose of the first stage is to reduce the influence of a large number of stars.We perform wavelet transform and guided filtering for three consecutive frames,and the reconstructed wavelet that takes the median value can achieve the effect of eliminating stars.In the second stage,we adopt the method of robust principal component analysis and attribute the problem of target detection to the problem of separating the target and background of a single frame of image.After a large number of experimental results analysis,it is proved that the algorithm can effectively detect faint debris in the monitoring system of small aperture telescope,and has high precision and low computational complexity.