Meta-analysis of new intervention measures for preventing side effects of artificial joint replacement

BACKGROUND Intertrochanteric fracture of the femur occurs mostly among older people,and seriously affects daily life and quality of life.At present,physical intervention,drug treatment,routine intervention and rehabilitation training are widely used for prevention of side effects,but it is still inconclusive which intervention has the best effect.AIM To compare the effects of new intervention measures for preventing side effects of artificial joint replacement.METHODS We searched the Chinese and English literatures for comparative studies on the prevention of side effects of new interventions for artificial joint replacement from July 2013 to June 2023 in China HowNet,PubMed,Wanfang,Weipu and other databases.Study quality was evaluated by improved Jadad scoring standard,and the effects of different interventions on preventing different complications were analyzed by meta-analysis of evidence-based medicine with Review Manager 5.0 software.RESULTS Ten articles,including 869 cases,were finally included.The preventive effects of different interventions on the side effects of artificial joint replacement were studied,and valid data were extracted.There were two articles on the preventive effects of drug intervention,four on comparison of the preventive effects of combined and single interventions,and three on the preventive effects of physical intervention,rehabilitation training and routine intervention.Meta-analysis showed that the preventive effect of rivaroxaban was significantly better than low molecular weight heparin calcium[mean difference(MD)=-0.16,95%CI:-0.28 to-0.04,P<0.05].The effect of combined intervention was significantly better than that of single intervention(MD=-0.08,95%CI:-0.16 to-0.01,P<0.001).Physical intervention was significantly better than routine intervention and rehabilitation training(MD=0.26,95%CI:0.16–0.36,P<0.001).CONCLUSION Rivaroxaban combined with rehabilitation training is preferred for preventing deep vein thrombosis after artificial joint replacement.In the prevention of pulmonary embolism,rivaroxaban drug intervention is given priority.The effect of combined intervention is better than that of single intervention.

Predictive active control of building structures using LQR and artificial intelligence

This study presents a neural network-based model for predicting linear quadratic regulator(LQR)weighting matrices for achieving a target response reduction.Based on the expected weighting matrices,the LQR algorithm is used to determine the various responses of the structure.The responses are determined by numerically analyzing the governing equation of motion using the state-space approach.For training a neural network,four input parameters are considered:the time history of the ground motion,the percentage reduction in lateral displacement,lateral velocity,and lateral acceleration,Output parameters are LQR weighting matrices.To study the effectiveness of an LQR-based neural network(LQRNN),the actual percentage reduction in the responses obtained from using LQRNN is compared with the target percentage reductions.Furthermore,to investigate the efficacy of an active control system using LQRNN,the controlled responses of a system are compared to the corresponding uncontrolled responses.The trained neural network effectively predicts weighting parameters that can provide a percentage reduction in displacement,velocity,and acceleration close to the target percentage reduction.Based on the simulation study,it can be concluded that significant response reductions are observed in the active-controlled system using LQRNN.Moreover,the LQRNN algorithm can replace conventional LQR control with the use of an active control system.

Empowerment of Artificial Intelligence in Teaching Reform of Ideological and Political Courses in Universities

The rapid development of artificial intelligence(AI)technology has brought new opportunities and challenges to the field of education.As an important link in cultivating students’comprehensive quality and socialist core values,it is necessary to carry out continuous teaching reform and innovation in ideological and political courses in colleges and universities.Based on the concept of AI empowering the teaching reform of ideological and political courses,this study aims to explore how to use artificial intelligence technology to improve the teaching effect and learning experience of ideological and political courses.The research first analyzes the application status of artificial intelligence technology in education,and then discusses the application potential of artificial intelligence in ideological and political courses.Subsequently,the teaching reform strategy of ideological and political courses based on artificial intelligence is proposed,including the use of virtual reality technology,the application of intelligent auxiliary teaching tools to enhance personalized teaching,and the construction of an intelligent learning management system.Lastly,a case analysis is conducted to explore the implementation effect of the teaching reform of ideological and political courses in universities.The results showed that the application of artificial intelligence technology can effectively improve the teaching effect and learning experience of ideological and political courses,and provide new ideas and methods for the teaching reform of ideological and political courses in universities.

An Air Defense Weapon Target Assignment Method Based on Multi-Objective Artificial Bee Colony Algorithm

With the advancement of combat equipment technology and combat concepts,new requirements have been put forward for air defense operations during a group target attack.To achieve high-efficiency and lowloss defensive operations,a reasonable air defense weapon assignment strategy is a key step.In this paper,a multi-objective and multi-constraints weapon target assignment(WTA)model is established that aims to minimize the defensive resource loss,minimize total weapon consumption,and minimize the target residual effectiveness.An optimization framework of air defense weapon mission scheduling based on the multiobjective artificial bee colony(MOABC)algorithm is proposed.The solution for point-to-point saturated attack targets at different operational scales is achieved by encoding the nectar with real numbers.Simulations are performed for an imagined air defense scenario,where air defense weapons are saturated.The non-dominated solution sets are obtained by the MOABC algorithm to meet the operational demand.In the case where there are more weapons than targets,more diverse assignment schemes can be selected.According to the inverse generation distance(IGD)index,the convergence and diversity for the solutions of the non-dominated sorting genetic algorithm III(NSGA-III)algorithm and the MOABC algorithm are compared and analyzed.The results prove that the MOABC algorithm has better convergence and the solutions are more evenly distributed among the solution space.

Quantum Anti-Zeno Effect in Artificial Quantum Systems

In this paper, we study a quantum anti-Zeno effect （QAZE） purely induced by repetitive measurements for an artificial atom interacting with a structured bath. This bath can be artificially realized with coupled resonators in one dimension and possesses photonic band structure like Bloeh electron in a periodic potential. In the presence of repetitive measurements, the pure QAZE is discovered as the observable decay is not negligible even for the atomic energy level spacing outside of the energy band of the artificial bath. If there were no measurements, the decay would not happen outside of the band. In this sense, the enhanced decay is completely induced by measurements through the relaxation channels provided by the bath. Besides, we also discuss the controversial golden rule decay rates originated from the van Hove＇s singularities and the effects of the counter-rotating terms.

Artificial intelligence technology and ultrasound-guided nerve block for analgesia in total knee arthroplasty

BACKGROUND Knee diseases are more common in middle-aged and elderly people,so artificial knee replacement is also more used in middle-aged and elderly people.Although the patient’s pain can be reduced through surgery,often accompanied by moderate pain after surgery and neutralization,which not only increases the psychological burden of the patient,but also greatly reduces the postoperative recovery effect,and may also lead to the occurrence of postoperative adverse events in severe cases.AIM To investigate the analgesic effect of artificial intelligence(AI)and ultrasoundguided nerve block in total knee arthroplasty(TKA).METHODS A total of 92 patients with TKA admitted to our hospital from January 2021 to January 2022 were opted and divided into two groups according to the treatment regimen.The control group received combined spinal-epidural anesthesia.The research group received AI technique combined with ultrasound-guided nerve block anesthesia.The sensory block time,motor block time,visual analogue scale(VAS)at different time points and complications were contrasted between the two groups.RESULTS The time of sensory block onset and sensory block perfection in the research group was shorter than those in the control group,but the results had no significant difference(P>0.05).Duration of sensory block in the research group was significantly longer than those in the control group(P<0.05).The time of motor block onset and motor block perfection in the research group was shorter than those in the control group,but the results had no significant difference(P>0.05).Duration of motor block in the research group was significantly longer than those in the control group.The VAS scales of the research group were significantly lower than that of the control group at different time points(P<0.05).The postoperative hip flexion and abduction range of motion in the research group were significantly better than those in the control group at different time points(P<0.05).The incidence of complications was significantly lower in the research group than in the control group(P=0.049).CONCLUSION In TKA,the combination of AI technology and ultrasound-guided nerve block has a significantly effect,with fewer postoperative complications and significantly analgesic effect,which is worthy of application.

Aeolian Activities and Protective Effects of Artificial Plants in Re-vegetated Sandy Land of Qinghai Lake,China

Land desertification and aeolian activity are currently the greatest threats to alpine ecological environments and are also the primary challenges of desertification control and ecological restoration projects.Afforestation of sandy lands around the Qinghai Lake in China has effectively controlled the desertification of this watershed.However,certain issues remain which challenge its overall success,including lack of diverse biological species and poor theoretical understanding of aeolian processes,such as controlling wind-sand flow in relation to complex alpine ecological factors.Therefore,to help improving afforestation techniques,this research focused on Hippophae rhamnoides,Salix cheilophila,Pinus sylvestris,Populus simonii and Artemisia desertorum vegetation implanted in the mobile dunes on the eastern shore of Qinghai Lake.Aeolian transport characteristics and annual changes to community ecological factors from 2010–2016 were monitored in comparison with uncontrolled sand dunes.Based on simultaneous observations using gradient anemometers and sand samplers,it was found that the aeolian activities exhibited the following features:1)In re-vegetated lands,the logarithmic growth of wind speed was disrupted by the wind speed amplification in the middle and high layers and wind speed reduction in the low layers,while vegetation had significant wind-breaking(>37%)and sand-fixing(>85%)effects in 2016.2)Wind speeds in re-vegetated lands and mobile dunes showed a linear correlation,especially in lower layers of H.rhamnoides and S.cheilophila,while sand transport in re-vegetated land increased linearly or exponentially with increasing wind speed.3)The four artificial shrubs and forests had greater sand deposition with intensities of 280–860 t/(ha·yr),largely concentrated during winter and spring which accounted for 60%–85%of the annual cycle,while A.desertorum experienced significant root undercutting;and 4)Intensity of aeolian activity in re-vegetated lands,except for A.desertorum,was significantly negative with respect to plant growth structure,community cover,topsoil moisture,and regional precipitation.Overall,these five sand-binding species produced optimistic wind-sand protection effects for the alpine sandy lands,which relied on the plants’physical disturbance of wind-sand flow during the early stages of community development.In comparison,H.rhamnoides and S.cheilophila individually maintained stable wind-sand protection effects,while P.sylvestris and P.simonii were better in mixing with other shrubs and herbs to achieve a comprehensive ecological system for future control of aeolian activity.

Effect of Mirena placement on reproductive hormone levels at different time intervals after artificial abortion

BACKGROUND Improper methods of contraception greatly increase the risk of abortion,cervical or endometrial lesions,and the number of recurrent artificial abortions.These complications result in the deterioration of a patient’s outcome.Further,the proportion of artificial abortions is highest among unmarried females.Placement of an intrauterine device,such as the Mirena,after an artificial abortion may decrease the likelihood of an endometrial injury caused by recurrent abortions while significantly improving its contraceptive effects.AIM To discuss the effect of Mirena placement on reproductive hormone levels at different time points after an artificial abortion.METHODS Women(n=119)undergoing an artificial abortion operation were divided into the study(n=56)and control(n=63)groups.In the study group,the Mirena was inserted immediately after the artificial abortion,whereas in the control group,it was inserted 4–7 d after the onset of the first menstrual cycle after abortion.All participants were followed-up for 6 mo to observe the continuation and expulsion rates and adverse reactions and to measure the levels of serum estradiol(E2),follicle stimulating hormone(FSH),and luteinizing hormone(LH).RESULTS The continuation rates were 94.64%and 93.65%in the study group and the control group,respectively.The expulsion rates were 1.79%and 3.17%in the study group and the control group,respectively.There was no statistically significant difference between the two groups(P>0.05).There were also no statistically significant differences in the proportion of patients with bacterial vaginitis,trichomonas vaginitis,or cervicitis between the groups(P>0.05).Six months after Mirena placement,E2 Levels were 45.50±7.13 pg/mL and 42.91±8.10 pg/mL,FSH 13.60±3.24 mIU/mL and 14.54±3.11 mIU/mL,and LH 15.11±2.08 mIU/mL and 14.60±3.55 mIU/mL in the study and control groups,respectively.There were no significant differences in hormone levels between the two groups(P>0.05).There were also no statistically significant differences in the proportions of abnormal menstruation,prolonged menstruation,or pain during intercourse between the study and control groups after Mirena placement(P>0.05).There were no statistically significant differences in uterine volume,sexual desire,sexual activity,or the sexual satisfaction score between the study and control groups before and after Mirena placement(P>0.05).CONCLUSION Placement of a Mirena intrauterine device immediately after an artificial abortion does not increase the risk of adverse reactions and can help prevent endometrial injury caused by recurrent abortions.

An Evaluation of Artificial Fish Nest for Assessment Enhancement Effects of Fishery Resources of in Xiangjiang River

Artificial fish nests are set in Lukou section and Hengyang section of Xiangjiang River from March 20 to May 10, 2019. The structure of artificial fish nest is bamboo frame, with the size of 2.5 m × 5.0 m × 4 and a unit frame area of 60 m2. A total of 58,201 eggs were collected by 24 monitoring times, of which 30,441 were from Lukou and 27,760 from Hengyang. 3831 fish eggs identify 8 fish species using morphological or molecular biological methods. The results showed that the number of eggs peaked from the 8th day to the 24th day after the nest entered the water, and then decreased rapidly. There was significant negative correlation between egg number in per m2 fish nest and days of fish nest (P < 0.01). The economic benefits of artificial fish nests were RMB 11.81 million. The artificial fish nest can not only increase the population of fish, but also has significant economic benefits.

OML:an online multi-particle locating method for high-resolution single-event effects studies

Identifying sensitive areas in integrated circuits susceptible to single-event effects(SEE)is crucial for improving radiation hardness.This study presents an online multi-track location(OML)framework to enhance the high-resolution online trajectory detection for the Hi’Beam-SEE system,which aims to localize SEE-sensitive positions on the IC at the micrometer scale and in real time.We employed a reparameterization method to accelerate the inference speed,merging the branches of the backbone of the location in the deployment scenario.Additionally,we designed an irregular convolution kernel,an attention mechanism,and a fused loss function to improve the positioning accuracy.OML demonstrates exceptional realtime processing capabilities,achieving a positioning accuracy of 1.83μm in processing data generated by the Hi’Beam-SEE system at 163 frames per second per GPU.

Transport through artificial single-molecule magnets:Spin-pair state sequential tunneling and Kondo effects

The transport properties of an artificial single-molecule magnet based on a CdTe quantum dot doped with a single Mn＋2 ion（S=5/2） are investigated by the non-equilibrium Green function method.We consider a minimal model where the Mn-hole exchange coupling is strongly anisotropic so that spin-flip is suppressed and the impurity spin S and a hole spin s entering the quantum dot are coupled into spin pair states with（2S＋1） sublevels.In the sequential tunneling regime,the differential conductance exhibits（2S＋1） possible peaks,corresponding to resonance tunneling via（2S＋1） sublevels.At low temperature,Kondo physics dominates transport and（2S＋1） Kondo peaks occur in the local density of states and conductance.These peaks originate from the spin-singlet state formed by the holes in the leads and on the dot via higher-order processes and are related to the parallel and antiparallel spin pair states.

A gelatin-based artificial SEI for lithium deposition regulation and polysulfide shuttle suppression in lithium-sulfur batteries

Lithium-sulfur(Li-S) battery is one of the best candidates for the next-generation energy storage system due to its high theoretical capacity(1675 mA h-1),low cost and environment friendliness.However,lithium(Li) dendrites formation and polysulfide shuttle effect are two major challenges that limit the commercialization of Li-S batteries.Here we design a facile bifunctional interlayer of gelatin-based fibers(GFs),aiming to protect the Li anode surface from the dendrites growth and also hinder the polysulfide shuttle effect.We reveal that the 3D structural network of GFs layer with abundant polar sites helps to homogenize Li-ion flux,leading to uniform Li-ion deposition.Meanwhile,the polar moieties also immobilize the lithium polysulfides and protect the Li metal from the side-reaction.As a result,the anodeprotected batteries have shown significantly enhanced performance.A high coulombic efficiency of 96% after 160 cycles has been achieved in the Li-Cu half cells.The Li-Li symmetric cells exhibit a prolonged lifespan for 800 h with voltage hysteresis(10 mV).With the as-prepared GFs layer,the Li-S battery shows approximately 14% higher capacity retention than the pristine battery at 0.5 C after 100 cycles.Our work presents that this gelatin-based bi-functional interlayer provides a viable strategy for the manufacturing of advanced Li-S batteries.

Coupled thermo-hydro-mechanical modeling of frost heave and water migration during artificial freezing of soils for mineshaft sinking

Artificial freezing of water-bearing soil layers composing a sedimentary deposit can induce frost heave and water migration that affect the natural stress-strain state of the soil layers and freezing process.In the present paper,a thermo-hydro-mechanical(THM)model for freezing of water-saturated soil is proposed to study the effects of frost heave and water migration in frozen soils on the formation of a frozen wall and subsequent excavation activity for sinking a vertical shaft.The governing equations of the model are formulated relative to porosity,temperature,and displacement which are considered as primary variables.The relationship between temperature,pore water,and ice pressure in frozen soil is established by the Clausius-Clapeyron equation,whereas the interaction between the stress-strain behavior and changes in porosity and pore pressure is described with the poromechanics theory.Moreover,constitutive relations for additional mechanical deformation are incorporated to describe volumetric expansion of soil during freezing as well as creep strain of soil in the frozen state.The ability of the proposed model to capture the frost heave of frozen soil is demonstrated by a comparison between numerical results and experimental data given by a one-sided freezing test.Also to validate the model in other freezing conditions,a radial freezing experiment is performed.After the validation procedure,the model is applied to numerical simulation of artificial freezing of silt and sand layers for shaft sinking at Petrikov potash mine in Belarus.Comparison of calculated temperature with thermal monitoring data during active freezing stage is presented.Numerical analysis of deformation of unsupported sidewall of a shaft inside the frozen wall is conducted to account for the change in natural stress-strain state of soil layers induced by artificial freezing.

Stand basal area modelling for Chinese fir plantations using an artificial neural network model

Artificial neural network models are a popular estimation tool for fitting nonlinear relationships because they require no assumptions about the form of the fitting function,non-Gaussian distributions,multicollinearity,outliers and noise in the data.The problems of backpropagation models using artificial neural networks include determination of the structure of the network and overlearning courses.According to data from 1981 to 2008 from 15 permanent sample plots on Dagangshan Mountain in Jiangxi Province,a back-propagation artificial neural network model(BPANN)and a support vector machine model(SVM)for basal area of Chinese fir(Cunninghamia lanceolata)plantations were constructed using four kinds of prediction factors,including stand age,site index,surviving stem numbers and quadratic mean diameters.Artificial intelligence methods,especially SVM,could be effective in describing stand basal area growth of Chinese fir under different growth conditions with higher simulation precision than traditional regression models.SVM and the Chapman–Richards nonlinear mixed-effects model had less systematic bias than the BPANN.

Evaluation on Fishery Resources in Daxingshan Artificial Reef Area of Huidong County

In order to evaluate placement of artificial reefs in Huidong County and observe biological aggregating effect of fishery resources,background investigation and follow-up investigation were carried out for trawl fishing and gill-net fishing in Daxingshan artificial reef area.The biological resource density index(D),Margalef species richness index(R),Shannon-Winener diversity index(H'),and Pileou evenness index(J')were used to study diversity of water biological population and resource density.Trawl fishing investigation indicated that after placement of reefs,there was significant increase in quantity of species of nekton,total resource density,species richness index,and diversity index in reef area,which were 1.321,2.07,1.012 and 1.084 times the value before placement of reefs respectively.Gill-net fishing investigation indicated that after placement of reefs,the quantity of species of nekton,total resource density,species richness index,and diversity index in reef area were 2.571,7.976,2.399 and 2.667 times the value before placement of reefs respectively.After reef placement,fishes and crabs become dominant population.It showed that after reef placement,attraction effect of fishes is significant,community structure is obviously optimized,and water environment in reef area is significantly improved.Thus,it proved that the multiplication system through artificial reefs has been basically established in Daxingshan reef area of Huidong County.

A NEW METHOD FOR STABILITY ANALYSIS OF UNDERGROUND OPENING USING ARTIFICIAL NEURAL NETWORK

The stability of underground opening is strongly constrained by a variety of factors. These include initial stress, structure of rock mass, and underground water, etc. A new approach proposed in this paper aims at revealing the degree of significance of them in order to catch the key factors. This new approach utilizes the mapping potentiality of artificial neural network and works out the sophisticated interactions among those factors from sample set. As a demonstration, an example is given for the application of this method to an underground opening. All results of this paper prove the efficiency of artificial neural network in stability analysis of underground opening.

Negative effects of artiffcial nest boxes on birds:A review

Artificial nest boxes are placed to attract birds to nest and breed in a specific location,and they are widely used in avian ecology research and in the attraction of insectivorous birds.There is evidence that artificial nest boxes can adversely affect breeding fitness but no great focus has been placed on this issue by researchers.Therefore,we retrieved 321 research papers regarding artificial nest boxes published from 2003 to 2022 and used the'Biblioshiny'program to extract and integrate keywords;we then summarized the adverse effects of artificial nest boxes on avian breeding success.The studies highlighted many drawbacks and misuses in the designing and placement of nest boxes;furthermore,bird attraction was decreased by their inappropriate selection,thus reducing breeding success.Regarding nest box production,there were shortcomings in the construction material,color,smell,and structural design of the boxes used.Nest boxes were also placed at inappropriate densities,locations,orientations,heights,and managed incorrectly.Finally,we propose suggestions for more efficient and safer artificial nest boxes for future use in avian ecology research and bird conservation.

The Analysis of Peculiar Control Parameters of Artificial Bee Colony Algorithm on the Numerical Optimization Problems

Artificial bee colony (ABC) algorithm is one of the popular swarm intelligence algorithms. ABC has been developed by being inspired foraging and waggle dance behaviors of real bee colonies in 2005. Since its invention in 2005, many ABC models have been proposed in order to solve different optimization problems. In all the models proposed, there are only one scout bee and a constant limit value used as control parameters for the bee population. In this study, the performance of ABC algorithm on the numeric optimization problems was analyzed by using different number of scout bees and limit values. Experimental results show that the results obtained by using more than one scout bee and different limit values, are better than the results of basic ABC. Therefore, the control parameters of the basic ABC should be tuned according to given class of optimization problems. In this paper, we propose reasonable value ranges of control parameters for the basic ABC in order to obtain better results on the numeric optimization problems.

机器学习在人工增雨效果统计检验中的应用

利用福建省古田人工增雨试验基地2014年1月—2023年1月小时自然降水数据,结合线性拟合、多项式回归和样条回归等多种数学统计方法,开展决策树、支持向量机(SVM)和卷积神经网络(CNN)3种机器学习方法在估测目标区自然降水中的应用研究。目标区和对比区自然雨量关系模型对比结果表明:以区域平均面雨量为统计变量时,CNN和四项式回归效果相对较好,其中CNN的确定系数为0.516,均方根误差为1.097 mm;对平均面雨量进行六次方根变换后,各模型的精准度大幅提升,CNN表现最优,确定系数为0.658,其次为SVM;为克服目标区和对比区雨量时间序列效应及空间分布不均等问题,以面雨量空间格点数据作为研究对象,采用CNN 3种优化器(自适应矩估计、均方根传递和梯度随机下降)算法进行对比,发现基于自适应矩估计优化器建立目标区和对比区雨量关系模型最优,其降水估测值与实测值更接近,均方根误差最小,为0.61 mm。因此,利用CNN方法能够进一步优化目标区和对比区雨量关系模型,可为定量评估人工增雨效果提供参考。

许氏平鲉幼鱼对人工鱼礁模型不同阴影情况的行为响应

阴影效应是影响人工鱼礁诱集效果的主要因素之一,为研究许氏平鲉(Sebastes schlegelii)对人工鱼礁不同阴影情况的行为响应,采用室内模拟实验方法,在实验水槽顶部固定光源,共设计3组实验:A组实验探究不同阴影面积的鱼礁模型对实验鱼的诱集效果;B组实验探究不放置鱼礁模型、悬挂不同开孔率顶板对实验鱼的诱集效果;C组实验探究阴影面积相同但开孔数量不同的鱼礁模型对实验鱼的诱集效果;对照组实验水槽中不放置鱼礁模型、不悬挂顶板。观察并记录许氏平鲉幼鱼(体长(5.06±0.09)cm,体质量(3.22±0.16)g)在水槽中的行为与分布特征。研究表明:3个实验组中许氏平鲉在鱼礁放置区域的出现率均显著高于对照组和其他区域;A组实验中,许氏平鲉在鱼礁放置区的平均出现率随着鱼礁阴影面积的增大而上升;B组实验中,许氏平鲉在顶板放置区的平均出现率显著高于对照组,但不同水平组之间差异不显著;C组实验中,开孔数为1时许氏平鲉在鱼礁放置区的平均出现率与开孔数为9时相近且高于开孔数为4和6时。研究结果表明,阴影面积越大的人工鱼礁对许氏平鲉的诱集效果越好,阴影面积相同时开孔数较多的人工鱼礁能够在提供良好庇护所的同时保证诱集效果。