Seismic isolation design and resilience improvement of railway station considering the influence of near-fault pulse-like ground motions

To improve the resilience of railway stations,a typical station was selected as the research object,and an isolation design was introduced.Twenty-four groups of near-fault pulse-like ground motions were selected.The seismic resilience of the no-isolation railway stations(NIRS)and the isolation railway stations(IRS)were compared to provide a numerical result of the improvement in resilience.The results show that in the station isolation design,the station's functional requirements and structural characteristics should be considered and the appropriate placement of isolation bearings is under the waiting room.Under the action of a rare earthquake,the repair cost,repair time,rate of harm and death of the IRS were decreased by 8.04 million,18.30 days,6.93×10^(-3)and 1.21×10^(-3),respectively,when compared to the NIRS.The IRS received a seismic resilience grade of three-stars and the NIRS only one-star,indicating that rational isolation design improves the seismic resilience of stations.Thus,for the design of stations close to earthquake faults,it is suggested to utilize appropriate isolation techniques to improve their seismic resilience.

将Range of motion内容操作规程化的探索与研究

目的提高本科护生Range ofmotion练习的手法技能.方法通过编制被动性Range ofmotion的操作规程,选择从头颈部屈曲、伸展、左、右侧屈、顺时针、逆时针旋转;肩关节屈曲、伸展、外展、外旋、内旋;肘关节伸直、屈曲、内旋、外旋;腕关节屈曲、伸展;手指关节屈曲、伸直;髋、膝关节屈曲、伸直、内收、外展;踝关节背屈、跖屈、内旋、外旋;脚趾关节屈曲、伸展的活动,结合患者病情,在合适的体位配合下,按一定的节拍、顺序、时间完成Range of motion的操作练习.结论使Range ofmotion的练习具有一定的操作性、规范性和指导性,让护生对被动性Range ofmotion的练习内容、操作程序、动作要领、手法、时间、注意事项都能全面掌握并正确予以实施,提高了护生对被动性Range of motion练习的技能.

Charge Couple Device-Based Systemfor3-di mensional Real Ti me Positioning on the Assessment of Segmental Range of Motion of Lumbar Spine

Objective： To observe the tested results of the segmental range of motion （ROM） of lumbar spine by charge couple device （CCD）-based system for 3-dimensional real-time positioning （CCD system）, and to analyze its clinical significance. Methods： Seven patients with lumbar joint dysfunction and 8 healthy subjects were tested twice by the CCD-based system with an interval of 10 min. Results： The ROM of the patients was obviously lesser than that of the healthy subjects. The measuring data of segmental ROM of lumbar spine by CCD system is correlated significantly to the same data checked later on the same subjects in every direction of the movements. The differences between two checks are usually less than 1 degree. Conclusion： Specially designed CCD based system for 3-dimensional real-time positioning could objectively reflect the segmental ROM of lumbar spine. The system would be of great clinical significance in the assessment of the biomechanical dysfunction of lumbar spine and the effect of the treatment applied.

Immediate Knee Joint Range of Motion after Stable Fixation of Tibial Plateau Fractures

The purpose of this study was to evaluate factors that affect initiation of early postoperative range of motion (ROM) rehabilitation and to investigate whether the postoperative ROM and clinical outcomes were affected by initiation of early ROM, immobilization and other factors. We conducted a retrospective analysis of tibial plateau fractures treated using stable internal fixation between December 2003 and June 2007. The resulting degree of flexion and Rasmussen Clinical and Radiographic Scores were evaluated. Thirty-nine patients were included, and 23 patients underwent a lateral submeniscal arthrotomy for evaluation of joint surface reduction, with 6 lateral meniscus lesions identified via arthrotomy. Three lateral collateral ligament lesions, 3 medial collateral ligament lesions and 1 anterior cruciate ligament lesion were found. Meniscus and ligament lesions significantly and negatively affected the initiation of knee joint ROM. Early ROM was achieved in 26 cases and 13 patients underwent immobilization for 4 weeks. At the final evaluation, the early ROM group had 130.42° ± 5.50° of flexion, compared with 122.92° ± 5.28° in the immobilization group. Moreover, the final Rasmussen score was 25.69 ± 2.92 in the early motion group, compared with 22.61 ± 3.5 in the immobilization group. There was no difference between radiographic scores of the groups. Although the initiation of early ROM improved the clinical results, soft tissue lesions influenced initiation of early knee joint motion. Therefore, meniscus and ligament injuries should be considered as prognostic factors in similar cases.

The Effect of Low Frequency Repetitive Transcranial Magnetic Stimulation Combined with Range of Motion Exercise on Paretic Hand Function in Female Patients after Stroke

Repetitive transcranial magnetic stimulation (rTMS) has recently been demonstrated to improve motor function after stroke. However, no study has yet tested the synergetic effects of physical exercise on rTMS in clinical settings. We investigated the effect of a 6-session course of low frequency rTMS on contralesional primary motor cortex combined with range-of motion (ROM) exercise on paretic hand function in female stroke patients. This was a single-blind study of the effects of rTMS with or without ROM exercise in female hemiplegic patients after stroke. All patients underwent rTMS on the contralesional primary motor cortex for 15 minutes and ROM exercise on the paretic hand. The cortical excitability determined by the amplitude and latency of the motor evoked potential (MEP) was measured in both first dorsal interosseous (FDI) muscles. We also evaluated arm function using Box and Block, arm reach, 9-hole pegboard, power grip, and pinch grip force tests. The rTMS-induced MEP amplitude of the paretic side significantly increased whereas the non-paretic side showed a decrease through every session. However, the MEP latency significantly increased on the non-paretic hand at post-rTMS with exercise, but a tendency of decrement on paretic hand at same application. Motor function showed improvement in the 9-hole pegboard and arm reach tests at post-rTMS with exercise on the paretic side compared with the non-paretic side. A significant correlation was especially noted between motor function and MEP on the paretic side of stroke patients. Low frequency rTMS with ROM exercise improved hand function after stroke. This may, in part, result in additional rehabilitation in stroke patients.

Species’ geographical range, environmental range and traits lead to specimen collection preference of dominant plant species of grasslands in Northern China

Many different factors,such as species traits,socio-economic factors,geographical and environmental factors,can lead to specimen collection preference.This study aims to determine whether grassland specimen collection in China is preferred by species traits(i.e.,plant height,flowering and fruiting period),environmental range(i.e.,the temperature and precipitation range)and geographical range(i.e.,distribution range and altitudinal range).Ordinary least squares models and phylogenetic generalized linear mixed models were used to analyze the relationships between specimen number and the explanatory variables.Random Forest models were then used to find the most parsimonious multivariate model.The results showed that interannual variation in specimen number between 1900 and 2020 was considerable.Specimen number of these species in southeast China was notably lower than that in northwest China.Environmental range and geographical range of species had significant positive correlations with specimen number.In addition,there were relatively weak but significant associations between specimen number and species trait(i.e.,plant height and flowering and fruiting period).Random Forest models indicated that distribution range was the most important variable,followed by flowering and fruiting period,and altitudinal range.These findings suggest that future floristic surveys should pay more attention to species with small geographical range,narrow environmental range,short plant height,and short flowering and fruiting period.The correction of specimen collection preference will also make the results of species distribution model,species evolution and other works based on specimen data more accurate.

A HEVC Video Steganalysis Method Using the Optimality of Motion Vector Prediction

Among steganalysis techniques,detection against MV(motion vector)domain-based video steganography in the HEVC(High Efficiency Video Coding)standard remains a challenging issue.For the purpose of improving the detection performance,this paper proposes a steganalysis method that can perfectly detectMV-based steganography in HEVC.Firstly,we define the local optimality of MVP(Motion Vector Prediction)based on the technology of AMVP(Advanced Motion Vector Prediction).Secondly,we analyze that in HEVC video,message embedding either usingMVP index orMVD(Motion Vector Difference)may destroy the above optimality of MVP.And then,we define the optimal rate of MVP as a steganalysis feature.Finally,we conduct steganalysis detection experiments on two general datasets for three popular steganographymethods and compare the performance with four state-ofthe-art steganalysis methods.The experimental results demonstrate the effectiveness of the proposed feature set.Furthermore,our method stands out for its practical applicability,requiring no model training and exhibiting low computational complexity,making it a viable solution for real-world scenarios.

Multiparameter Numerical Investigation of Two Types of Moving Interactions Between the Deep-Sea Mining Vehicle Track Plate and Seabed Soil:Digging and Rotating Motions

To ensure the safe performance of deep-sea mining vehicles(DSMVs),it is necessary to study the mechanical characteristics of the interaction between the seabed soil and the track plate.The rotation and digging motions of the track plate are important links in the contact between the driving mechanism of the DSMV and seabed soil.In this study,a numerical simulation is conducted using the coupled Eulerian–Lagrangian(CEL)large deformation numerical method to investigate the interaction between the track plate of the DSMV and the seabed soil under two working conditions:rotating condition and digging condition.First,a soil numerical model is established based on the elastoplastic mechanical characterization using the basic physical and mechanical properties of the seabed soil obtained by in situ sampling.Subsequently,the soil disturbance mechanism and the dynamic mechanical response of the track plate under rotating and digging conditions are obtained through the analysis of the sensitivity of the motion parameters,the grouser structure,the layered soil features and the soil heterogeneity.The results indicate that the above parameters remarkably influence the interaction between the DSMV and the seabed soil.Therefore,it is important to consider the rotating and digging motion of the DSMV in practical engineering to develop a detailed optimization design of the track plate.

Neural Dynamics for Cooperative Motion Control of Omnidirectional Mobile Manipulators in the Presence of Noises: A Distributed Approach

This paper presents a distributed scheme with limited communications, aiming to achieve cooperative motion control for multiple omnidirectional mobile manipulators(MOMMs).The proposed scheme extends the existing single-agent motion control to cater to scenarios involving the cooperative operation of MOMMs. Specifically, squeeze-free cooperative load transportation is achieved for the end-effectors of MOMMs by incorporating cooperative repetitive motion planning(CRMP), while guiding each individual to desired poses. Then, the distributed scheme is formulated as a time-varying quadratic programming(QP) and solved online utilizing a noise-tolerant zeroing neural network(NTZNN). Theoretical analysis shows that the NTZNN model converges globally to the optimal solution of QP in the presence of noise. Finally, the effectiveness of the control design is demonstrated by numerical simulations and physical platform experiments.

Extraction of Acoustic Normal Mode Depth Functions Using Range-Difference Method with Vertical Linear Array Data

Data-derived normal mode extraction is an effective method for extracting normal mode depth functions in the absence of marine environmental data.However,when the corresponding singular vectors become nonunique when two or more singular values obtained from the cross-spectral density matrix diagonalization are nearly equal,this results in unsatisfactory extraction outcomes for the normal mode depth functions.To address this issue,we introduced in this paper a range-difference singular value decomposition method for the extraction of normal mode depth functions.We performed the mode extraction by conducting singular value decomposition on the individual frequency components of the signal's cross-spectral density matrix.This was achieved by using pressure and its range-difference matrices constructed from vertical line array data.The proposed method was validated using simulated data.In addition,modes were successfully extracted from ambient noise.

Quantitative analysis of the morphing wing mechanism of raptors:IMMU-based motion capture system and its application on gestures of a Falco peregrinus

This paper presented a novel tinny motion capture system for measuring bird posture based on inertial and magnetic measurement units that are made up of micromachined gyroscopes, accelerometers, and magnetometers. Multiple quaternion-based extended Kalman filters were implemented to estimate the absolute orientations to achieve high accuracy.Under the guidance of ornithology experts, the extending/contracting motions and flapping cycles were recorded using the developed motion capture system, and the orientation of each bone was also analyzed. The captured flapping gesture of the Falco peregrinus is crucial to the motion database of raptors as well as the bionic design.

Influence of network structure on spreading dynamics via tie range

There are various phenomena of malicious information spreading in the real society, which cause many negative impacts on the society. In order to better control the spreading, it is crucial to reveal the influence of network structure on network spreading. Motifs, as fundamental structures within a network, play a significant role in spreading. Therefore, it is of interest to investigate the influence of the structural characteristics of basic network motifs on spreading dynamics.Considering the edges of the basic network motifs in an undirected network correspond to different tie ranges, two edge removal strategies are proposed, short ties priority removal strategy and long ties priority removal strategy. The tie range represents the second shortest path length between two connected nodes. The study focuses on analyzing how the proposed strategies impact network spreading and network structure, as well as examining the influence of network structure on network spreading. Our findings indicate that the long ties priority removal strategy is most effective in controlling network spreading, especially in terms of spread range and spread velocity. In terms of network structure, the clustering coefficient and the diameter of network also have an effect on the network spreading, and the triangular structure as an important motif structure effectively inhibits the spreading.

On the Adaptability Range, Self-Selection, and Economic Nature of Biological Evolution

This article employs a combined approach of biology and economics to reveal that biological evolution has an economic nature, evolving towards improved energy efficiency. The orthodox Darwinian theory of evolution describes evolution as the random variation of organisms and their survival through natural selection. In fact, the natural environment itself is a constantly changing context, and the strategy to adapt to this change is to enhance behavioral capabilities, thereby expanding the range and dimensions of behavior. Therefore, the improvement of behavioral capabilities is an important aspect of evolution. The enhancement of behavioral capabilities expands the range of adaptation to the natural environment and increases the space for behavioral choices. Within this space of behavioral choices, some options are more effective and superior to others;thus, the ability to select is necessary to make the improved behavioral capabilities more beneficial to the organism itself. The birth and development of the brain serve the purpose of selection. By using the brain to make selections, at least the “better” behavior will be chosen between two alternatives. Once the better behavior yields better results, and the organism can associate these results with the corresponding behavior, it will persist in this behavior. The persistent repetition of a behavior over generations will form a habit. Habits passed down through generations constitute a new environment, causing the organism’s genes to activate or deactivate certain functions, ultimately leading to genetic changes that are beneficial to that habit. Since the brain’s selection represents the organism’s self-selection, it differs from random variation;it is also a rational selection, choosing behaviors that either obtain more energy or reduce energy consumption. Thus, this evolution possesses an economic nature.

A Framework of LSTM Neural Network Model in Multi-Time Scale Real-Time Prediction of Ship Motions in Head Waves

Ship motions induced by waves have a significant impact on the efficiency and safety of offshore operations.Real-time prediction of ship motions in the next few seconds plays a crucial role in performing sensitive activities.However,the obvious memory effect of ship motion time series brings certain difficulty to rapid and accurate prediction.Therefore,a real-time framework based on the Long-Short Term Memory(LSTM)neural network model is proposed to predict ship motions in regular and irregular head waves.A 15000 TEU container ship model is employed to illustrate the proposed framework.The numerical implementation and the real-time ship motion prediction in irregular head waves corresponding to the different time scales are carried out based on the container ship model.The related experimental data were employed to verify the numerical simulation results.The results show that the proposed method is more robust than the classical extreme short-term prediction method based on potential flow theory in the prediction of nonlinear ship motions.

Extending the solid solution range of sodium ferric pyrophosphate:Off‐stoichiometric Na_(3)Fe(2.5)(P_(2)O_(7))_(2)as a novel cathode for sodium‐ion batteries

Iron‐based pyrophosphates are attractive cathodes for sodium‐ion batteries due to their large framework,cost‐effectiveness,and high energy density.However,the understanding of the crystal structure is scarce and only a limited candidates have been reported so far.In this work,we found for the first time that a continuous solid solution,Na_(4−α)Fe_(2+α)_(2)(P_(2)O_(7))_(2)(0≤α≤1,could be obtained by mutual substitution of cations at center‐symmetric Na3 and Na4 sites while keeping the crystal building blocks of anionic P_(2)O_(7) unchanged.In particular,a novel off‐stoichiometric Na_(3)Fe(2.5)(P_(2)O_(7))_(2)is thus proposed,and its structure,energy storage mechanism,and electrochemical performance are extensively investigated to unveil the structure–function relationship.The as‐prepared off‐stoichiometric electrode delivers appealing performance with a reversible discharge capacity of 83 mAh g^(−1),a working voltage of 2.9 V(vs.Na^(+)/Na),the retention of 89.2%of the initial capacity after 500 cycles,and enhanced rate capability of 51 mAh g^(−1)at a current density of 1600 mA g^(−1).This research shows that sodium ferric pyrophosphate could form extended solid solution composition and promising phase is concealed in the range of Na_(4−α)Fe_(2+α)_(2)(P_(2)O_(7))_(2),offering more chances for exploration of new cathode materials for the construction of high‐performance SIBs.

The interaction between temperature and precipitation on the potential distribution range of Betula ermanii in the alpine treeline ecotone on the Changbai Mountain

Alpine treeline ecotones are highly sensitive to climate warming.The low temperature-determined alpine treeline is expected to shift upwards in response to global warming.However,little is known about how temperature interacts with other important factors to influence the distribution range of tree species within and beyond the alpine treeline ecotone.Hence,we used a GF-2 satellite image,along with bioclimatic and topographic variables,to develop an ensemble suitable habitat model based on the species distribution modeling algorithms in Biomod2.We investigated the distribution of suitable habitats for B.ermanii under three climate change scenarios(i.e.,low(SSP126),moderate(SSP370)and extreme(SSP585)future emission trajectories)between two consecutive time periods(i.e.,current-2055,and 2055-2085).By 2055,the potential distribution range of B.ermanii will expand under all three climate scenarios.The medium and high suitable areas will decline under SSP370 and SSP585scenarios from 2055 to 2085.Moreover,under the three climate scenarios,the uppermost altitudes of low suitable habitat will rise to 2,329 m a.s.l.,while the altitudes of medium and high suitable habitats will fall to 2,201 and2,051 m a.s.l.by 2085,respectively.Warming promotes the expansion of B.ermanii distribution range in Changbai Mountain,and this expansion will be modified by precipitation as climate warming continues.This interaction between temperature and precipitation plays a significant role in shaping the potential distribution range of B.ermanii in the alpine treeline ecotone.This study reveals the link between environmental factors,habitat distribution,and species distribution in the alpine treeline ecotone,providing valuable insights into the impacts of climate change on high-elevation vegetation,and contributing to mountain biodiversity conservation and sustainable development.

Study of the response of 10B-doped MCP to wide-energy range neutrons from eV to MeV

Neutron-sensitive microchannel plates(nMCPs)have applications in neutron detection,including energy spectrum measurements,neutron-induced cross sections,and neutron imaging.10B-doped MCPs(B-MCPs)have attracted significant attention owing to their potential for exhibiting a high neutron detection efficiency over a large neutron energy range.Good spatial and temporal resolutions are useful for neutron energy-resolved imaging.However,their practical applications still face many technical challenges.In this study,a B-MCP with 10 mol%10B was tested for its response to wide-energy neutrons from eV to MeV at the Back-n white neutron source at the China Spallation Neutron Source.The neutron detection efficiency was calibrated at 1 eV,which is approximately 300 times that of an ordinary MCP and indicates the success of 10 B doping.The factors that caused the reduction in the detection efficiency were simulated and discussed.The neutron energy spectrum obtained using B-MCP was compared with that obtained by other measurement methods,and showed very good consistency for neutron energies below tens of keV.The response is more complicated at higher neutron energy,at which point the elastic and nonelastic reactions of all nuclides of B-MCP gradually become dominant.This is beneficial for the detection of neutrons,as it compensates for the detection efficiency of B-MCP for high-energy neutrons.

Towards trustworthy multi-modal motion prediction:Holistic evaluation and interpretability of outputs

Predicting the motion of other road agents enables autonomous vehicles to perform safe and efficient path planning.This task is very complex,as the behaviour of road agents depends on many factors and the number of possible future trajectories can be consid-erable(multi-modal).Most prior approaches proposed to address multi-modal motion prediction are based on complex machine learning systems that have limited interpret-ability.Moreover,the metrics used in current benchmarks do not evaluate all aspects of the problem,such as the diversity and admissibility of the output.The authors aim to advance towards the design of trustworthy motion prediction systems,based on some of the re-quirements for the design of Trustworthy Artificial Intelligence.The focus is on evaluation criteria,robustness,and interpretability of outputs.First,the evaluation metrics are comprehensively analysed,the main gaps of current benchmarks are identified,and a new holistic evaluation framework is proposed.Then,a method for the assessment of spatial and temporal robustness is introduced by simulating noise in the perception system.To enhance the interpretability of the outputs and generate more balanced results in the proposed evaluation framework,an intent prediction layer that can be attached to multi-modal motion prediction models is proposed.The effectiveness of this approach is assessed through a survey that explores different elements in the visualisation of the multi-modal trajectories and intentions.The proposed approach and findings make a significant contribution to the development of trustworthy motion prediction systems for autono-mous vehicles,advancing the field towards greater safety and reliability.

Behaviour recognition based on the integration of multigranular motion features in the Internet of Things

With the adoption of cutting-edge communication technologies such as 5G/6G systems and the extensive development of devices,crowdsensing systems in the Internet of Things(IoT)are now conducting complicated video analysis tasks such as behaviour recognition.These applications have dramatically increased the diversity of IoT systems.Specifically,behaviour recognition in videos usually requires a combinatorial analysis of the spatial information about objects and information about their dynamic actions in the temporal dimension.Behaviour recognition may even rely more on the modeling of temporal information containing short-range and long-range motions,in contrast to computer vision tasks involving images that focus on understanding spatial information.However,current solutions fail to jointly and comprehensively analyse short-range motions between adjacent frames and long-range temporal aggregations at large scales in videos.In this paper,we propose a novel behaviour recognition method based on the integration of multigranular(IMG)motion features,which can provide support for deploying video analysis in multimedia IoT crowdsensing systems.In particular,we achieve reliable motion information modeling by integrating a channel attention-based short-term motion feature enhancement module(CSEM)and a cascaded long-term motion feature integration module(CLIM).We evaluate our model on several action recognition benchmarks,such as HMDB51,Something-Something and UCF101.The experimental results demonstrate that our approach outperforms the previous state-of-the-art methods,which confirms its effective-ness and efficiency.

3D motion and geometric information system of single-antenna radar based on incomplete 1D range data

A 3D motion and geometric information system of single-antenna radar is proposed,which can be supported by spotlight synthetic aperture radar（SAR） system and inverse SAR（ISAR） system involving relative 3D motion of the rigid target.In this system,applying the geometry invariance of the rigid target,the unknown 3D shape and motion of the radar target can be reconstructed from the 1D range data of some scatterers extracted from the high-resolution range image.Compared with the current 1D-to-3D algorithm,in the proposed algorithm,the requirement of the 1D range data is expanded to incomplete formation involving large angular motion of the target and hence,the quantity of the scatterers and the abundance of 3D motion are enriched.Furthermore,with the three selected affine coordinates fixed,the multi-solution problem of the reconstruction is solved and the technique of nonlinear optimization can be successfully utilized in the system.Two simulations are implemented which verify the higher robustness of the system and the better performance of the 3D reconstruction for the radar target with unknown relative motion.