基于GRU-DRSN的双通道人体活动识别

人体活动识别(human activity recognizition, HAR)在医疗、军工、智能家居等领域有很大的应用空间。传统机器学习方法特征提取难度较大且精度不高。针对上述问题并结合传感器时序特性,提出了一种融合CBAM(convolutional block attention module)注意力机制的GRU-DRSN双通道并行模型,有效避免了传统串行模型因网络深度加深引起梯度爆炸和消失问题。同时并行结构使得两条支路具有相同的优先级,使用深度残差收缩网络(deep residual shrinkage network, DRSN)提取数据的深层空间特征,同时使用门控循环结构(gated recurrent unit, GRU)学习活动样本在时间序列上的特征,同时进行提取样本不同维度的特征,并通过CBAM模块进行特征的权重分配,最后通过Softmax层进行识别,实现了端对端的人体活动识别。使用公开数据集(wireless sensor data mining, WISDM)进行验证,模型平均精度达到了97.6%,与传统机器学习模型和前人所提神经网络模型相比,有更好的识别效果。

基于CAM-YOLOX的大场景SAR图像近岸场景舰船目标检测

针对大场景SAR图像近岸场景舰船目标检测中遇到的陆地目标虚警和岸边目标漏检等问题,基于YOLOX设计了一种轻量化的改进模型CAM-YOLOX。首先,在骨干部分嵌入CAM,增强舰船特征提取以保持较高的检测性能;其次,在特征金字塔网络结构中增加一个浅层分支,以增强对小目标特征的提取能力;最后,在特征融合网络中用Shuffle unit替换CSPLayer中的CBS和堆叠的Bottleneck结构,实现了模型压缩。在LS-SSDD-v1.0遥感数据集上进行实验,实验结果表明,本文改进算法相较于原始算法在近岸场景舰船检测的精确率P提高了5.51%,召回率R提高了3.68%,模型参数量减小了16.33%。本文算法能在不增加模型参数量的情况下,有效抑制近岸场景中陆地上的虚警和减少岸边舰船漏检率。

Sustained release of vascular endothelial growth factor A and basic fibroblast growth factor from nanofiber membranes reduces oxygen/glucose deprivation-induced injury to neurovascular units

Upregulation of vascular endothelial growth factor A/basic fibroblast growth factor(VEGFA/b FGF)expression in the penumbra of cerebral ischemia can increase vascular volume,reduce lesion volume,and enhance neural cell proliferation and differentiation,thereby exerting neuroprotective effects.However,the beneficial effects of endogenous VEGFA/b FGF are limited as their expression is only transiently increased.In this study,we generated multilayered nanofiber membranes loaded with VEGFA/b FGF using layer-by-layer self-assembly and electrospinning techniques.We found that a membrane containing 10 layers had an ideal ultrastructure and could efficiently and stably release growth factors for more than 1 month.This 10-layered nanofiber membrane promoted brain microvascular endothelial cell tube formation and proliferation,inhibited neuronal apoptosis,upregulated the expression of tight junction proteins,and improved the viability of various cellular components of neurovascular units under conditions of oxygen/glucose deprivation.Furthermore,this nanofiber membrane decreased the expression of Janus kinase-2/signal transducer and activator of transcription-3(JAK2/STAT3),Bax/Bcl-2,and cleaved caspase-3.Therefore,this nanofiber membrane exhibits a neuroprotective effect on oxygen/glucose-deprived neurovascular units by inhibiting the JAK2/STAT3 pathway.

Volumetric lattice Boltzmann method for pore-scale mass diffusionadvection process in geopolymer porous structures

Porous materials present significant advantages for absorbing radioactive isotopes in nuclear waste streams.To improve absorption efficiency in nuclear waste treatment,a thorough understanding of the diffusion-advection process within porous structures is essential for material design.In this study,we present advancements in the volumetric lattice Boltzmann method(VLBM)for modeling and simulating pore-scale diffusion-advection of radioactive isotopes within geopolymer porous structures.These structures are created using the phase field method(PFM)to precisely control pore architectures.In our VLBM approach,we introduce a concentration field of an isotope seamlessly coupled with the velocity field and solve it by the time evolution of its particle population function.To address the computational intensity inherent in the coupled lattice Boltzmann equations for velocity and concentration fields,we implement graphics processing unit(GPU)parallelization.Validation of the developed model involves examining the flow and diffusion fields in porous structures.Remarkably,good agreement is observed for both the velocity field from VLBM and multiphysics object-oriented simulation environment(MOOSE),and the concentration field from VLBM and the finite difference method(FDM).Furthermore,we investigate the effects of background flow,species diffusivity,and porosity on the diffusion-advection behavior by varying the background flow velocity,diffusion coefficient,and pore volume fraction,respectively.Notably,all three parameters exert an influence on the diffusion-advection process.Increased background flow and diffusivity markedly accelerate the process due to increased advection intensity and enhanced diffusion capability,respectively.Conversely,increasing the porosity has a less significant effect,causing a slight slowdown of the diffusion-advection process due to the expanded pore volume.This comprehensive parametric study provides valuable insights into the kinetics of isotope uptake in porous structures,facilitating the development of porous materials for nuclear waste treatment applications.

Uncertainties of landslide susceptibility prediction:influences of different study area scales and mapping unit scales

This study aims to investigate the effects of different mapping unit scales and study area scales on the uncertainty rules of landslide susceptibility prediction(LSP).To illustrate various study area scales,Ganzhou City in China,its eastern region(Ganzhou East),and Ruijin County in Ganzhou East were chosen.Different mapping unit scales are represented by grid units with spatial resolution of 30 and 60 m,as well as slope units that were extracted by multi-scale segmentation method.The 3855 landslide locations and 21 typical environmental factors in Ganzhou City are first determined to create spatial datasets with input-outputs.Then,landslide susceptibility maps(LSMs)of Ganzhou City,Ganzhou East and Ruijin County are pro-duced using a support vector machine(SVM)and random forest(RF),respectively.The LSMs of the above three regions are then extracted by mask from the LSM of Ganzhou City,along with the LSMs of Ruijin County from Ganzhou East.Additionally,LSMs of Ruijin at various mapping unit scales are generated in accordance.Accuracy and landslide suscepti-bility indexes(LSIs)distribution are used to express LSP uncertainties.The LSP uncertainties under grid units significantly decrease as study area scales decrease from Ganzhou City,Ganzhou East to Ruijin County,whereas those under slope units are less affected by study area scales.Of course,attentions should also be paid to the broader representativeness of large study areas.The LSP accuracy of slope units increases by about 6%–10%compared with those under grid units with 30 m and 60 m resolution in the same study area's scale.The significance of environmental factors exhibits an averaging trend as study area scale increases from small to large.The importance of environmental factors varies greatly with the 60 m grid unit,but it tends to be consistent to some extent in the 30 m grid unit and the slope unit.

Assessment of Wet Season Precipitation in the Central United States by the Regional Climate Simulation of the WRFG Member in NARCCAP and Its Relationship with Large-Scale Circulation Biases

Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss possible causes of biases in a WRF-based RCM with a grid spacing of 50 km,named WRFG,from the North American Regional Climate Change Assessment Program(NARCCAP)in simulating wet season precipitation over the Central United States for a period when observational data are available.The RCM reproduces key features of the precipitation distribution characteristics during late spring to early summer,although it tends to underestimate the magnitude of precipitation.This dry bias is partially due to the model’s lack of skill in simulating nocturnal precipitation related to the lack of eastward propagating convective systems in the simulation.Inaccuracy in reproducing large-scale circulation and environmental conditions is another contributing factor.The too weak simulated pressure gradient between the Rocky Mountains and the Gulf of Mexico results in weaker southerly winds in between,leading to a reduction of warm moist air transport from the Gulf to the Central Great Plains.The simulated low-level horizontal convergence fields are less favorable for upward motion than in the NARR and hence,for the development of moist convection as well.Therefore,a careful examination of an RCM’s deficiencies and the identification of the source of errors are important when using the RCM to project precipitation changes in future climate scenarios.

Reducing Operation Emissions and Improving Work Efficiency Using a Pure Electric Wheel Drive Tractor

In response to the problems of excessive greenhouse-gas and particulate emissions and the low traction efficiency of conventional diesel tractors in the field,a purely electric wheel-side drive tractor was studied,including an electric motor drive system,a battery ballast system,and an electro–hydraulic suspension system.This paper develops a dynamics model of an electric tractor-ploughing unit under complex soil conditions,leading to the proposal of an active control method for drive wheel torque and a joint control method for the traction force of the suspension system and the front-and rear-axle loads of a tractor.Finally,the tractor is prototyped and assembled,and ploughing tests are carried out.The ploughing results show that the active torque-distribution control method proposed in this study reduces the tractor slip by 14.83%and increases the traction efficiency by 10.28%compared with the average torquedistribution mode.Compared with the conventional traction control mode,the joint control method for traction and ballast proposed in this paper results in a 3.7%increase in traction efficiency,a 15.05%decrease in slip,and a 4.9%reduction in total drive motor energy consumption.This study will help to improve the operation quality and traction efficiency of electric tractors in complex soil conditions.

Impact of apolipoprotein E isoforms on sporadic Alzheimer's disease:beyond the role of amyloid beta

The impact of apolipoprotein E(ApoE)isoforms on sporadic Alzheimer's disease has long been studied;however,the influences of apolipoprotein E gene(APOE)on healthy and pathological human brains are not fully understood.ApoE exists as three common isoforms(ApoE2,ApoE3,and ApoE4),which differ in two amino acid residues.Traditionally,ApoE binds cholesterol and phospholipids and ApoE isoforms display diffe rent affinities for their receptors,lipids transport and distribution in the brain and periphery.The role of ApoE in the human depends on ApoE isoforms,brain regions,aging,and neural injury.APOE E4 is the strongest genetic risk factor for sporadic Alzheimer's disease,considering its role in influencing amyloid-beta metabolism.The exact mechanisms by which APOE gene variants may increase or decrease Alzheimer's disease risk are not fully understood,but APOE was also known to affect directly and indirectly tau-mediated neurodegeneration,lipids metabolism,neurovascular unit,and microglial function.Consistent with the biological function of ApoE,ApoE4 isoform significantly alte red signaling pathways associated with cholesterol homeostasis,transport,and myelination.Also,the rare protective APOE variants confirm that ApoE plays an important role in Alzheimer's disease pathogenesis.The objectives of the present mini-review were to describe classical and new roles of various ApoE isoforms in Alzheimer's disease pathophysiology beyond the deposition of amyloid-beta and to establish a functional link between APOE,brain function,and memory,from a molecular to a clinical level.APOE genotype also exerted a heterogeneous effect on clinical Alzheimer's disease phenotype and its outcomes.Not only in learning and memory but also in neuro psychiatric symptoms that occur in a premorbid condition.Cla rifying the relationships between Alzheimer's disease-related pathology with neuropsychiatric symptoms,particularly suicidal ideation in Alzheimer's disease patients,may be useful for elucidating also the underlying pathophysiological process and its prognosis.Also,the effects of anti-amyloid-beta drugs,recently approved for the treatment of Alzheimer's disease,could be influenced by the APOE genotype.

One memristor–one electrolyte-gated transistor-based high energy-efficient dropout neuronal units

Artificial neural networks(ANN) have been extensively researched due to their significant energy-saving benefits.Hardware implementations of ANN with dropout function would be able to avoid the overfitting problem. This letter reports a dropout neuronal unit(1R1T-DNU) based on one memristor–one electrolyte-gated transistor with an ultralow energy consumption of 25 p J/spike. A dropout neural network is constructed based on such a device and has been verified by MNIST dataset, demonstrating high recognition accuracies(> 90%) within a large range of dropout probabilities up to40%. The running time can be reduced by increasing dropout probability without a significant loss in accuracy. Our results indicate the great potential of introducing such 1R1T-DNUs in full-hardware neural networks to enhance energy efficiency and to solve the overfitting problem.

Foam rolling and stretching do not provide superior acute flexibility and stiffness improvements compared to any other warm-up intervention: A systematic review with meta-analysis

Background:Acute improvement in range of motion(ROM)is a widely reported effect of stretching and foam rolling,which is commonly explained by changes in pain threshold and/or musculotendinous stiffness.Interestingly,these effects were also reported in response to various other active and passive interventions that induce responses such as enhanced muscle temperature.Therefore,we hypothesized that acute ROM enhancements could be induced by a wide variety of interventions other than stretching or foam rolling that promote an increase in muscle temperature.Methods:After a systematic search in PubMed,Web of Science,and SPORTDiscus databases,38 studies comparing the effects of stretching and foam rolling with several other interventions on ROM and passive properties were included.These studies had 1134 participants in total,and the data analysis resulted in 140 effect sizes(ESs).ES calculations were performed using robust variance estimation model with R-package.Results:Study quality of the included studies was classified as fair(PEDro score=4.58)with low to moderate certainty of evidence.Results showed no significant differences in ROM(ES=0.01,p=0.88),stiffness(ES=0.09,p=0.67),or passive peak torque(ES=-0.30,p=0.14)between stretching or foam rolling and the other identified activities.Funnel plots revealed no publication bias.Conclusion:Based on current literature,our results challenge the established view on stretching and foam rolling as a recommended component of warm-up programs.The lack of significant difference between interventions suggests there is no need to emphasize stretching or foam rolling to induce acute ROM,passive peak torque increases,or stiffness reductions.

Gastrointestinal manifestations of critical ill heatstroke patients and their associations with outcomes:A multicentre,retrospective,observational study

BACKGROUND Extreme heat exposure is a growing health problem,and the effects of heat on the gastrointestinal(GI)tract is unknown.This study aimed to assess the incidence of GI symptoms associated with heatstroke and its impact on outcomes.AIM To assess the incidence of GI symptoms associated with heatstroke and its impact on outcomes.METHODS Patients admitted to the intensive care unit(ICU)due to heatstroke were included from 83 centres.Patient history,laboratory results,and clinically relevant outcomes were recorded at ICU admission and daily until up to day 15,ICU discharge,or death.GI symptoms,including nausea/vomiting,diarrhoea,flatulence,and bloody stools,were recorded.The characteristics of patients with heatstroke concomitant with GI symptoms were described.Multivariable regression analyses were performed to determine significant predictors of GI symptoms.RESULTS A total of 713 patients were included in the final analysis,of whom 132(18.5%)patients had at least one GI symptom during their ICU stay,while 26(3.6%)suffered from more than one symptom.Patients with GI symptoms had a significantly higher ICU stay compared with those without.The mortality of patients who had two or more GI symptoms simultaneously was significantly higher than that in those with one GI symptom.Multivariable logistic regression analysis revealed that older patients with a lower GCS score on admission were more likely to experience GI symptoms.CONCLUSION The GI manifestations of heatstroke are common and appear to impact clinically relevant hospitalization outcomes.

Hydrodynamic Assessment of A New Nature-Based Armour Unit on Rubble Mound Breakwater for Coastal Protection

This research proposes a novel nature-based design of a new concrete armour unit for the cover layer of a rubblemoundbreakwater. Armour units are versatile with respect to shape, orientation, surface condition details, and porosity.Therefore, a detailed analysis is required to investigate the exact state of their hydraulic interactions and structuralresponses. In this regard, the performance results of several traditional armour units, including the Antifer cube,Tetrapod, X-block and natural stone, are considered for the first step of this study. Then, the related observed resultsare compared with those obtained for a newly designed (artificial coral) armour unit. The research methodology utilizesthe common wave flume test procedure. Furthermore, several verified numerical models in OpenFOAM code areused to gain the extra required data. The proposed armour is configured to provide an effective shore protection as anenvironmental-friendly coastal structure. Thus it is designed with a main trunk including deep grooves to imitate thetypical geometry of a coral type configuration, so as to attain desirable performance. The observed results and ananalytic hierarchy process (AHP) concept are used to compare the hydraulic performance of the studied traditionaland newly proposed (artificial coral) armour units. The results indicate that the artificial coral armour unit demonstratesacceptable performance. The widely used traditional armour units might be replaced by newer designs for betterwave energy dissipation, and more importantly, for fewer adverse effects on the marine environment.

Dynamic Response of Foundations during Startup of High-Frequency Tunnel Equipment

The specialized equipment utilized in long-line tunnel engineering is evolving towards large-scale,multifunctional,and complex orientations.The vibration caused by the high-frequency units during regular operation is supported by the foundation of the units,and the magnitude of vibration and the operating frequency fluctuate in different engineering contexts,leading to variations in the dynamic response of the foundation.The high-frequency units yield significantly diverse outcomes under different startup conditions and times,resulting in failure to meet operational requirements,influencing the normal function of the tunnel,and causing harm to the foundation structure,personnel,and property in severe cases.This article formulates a finite element numerical computation model for solid elements using three-dimensional elastic body theory and integrates field measurements to substantiate and ascertain the crucial parameter configurations of the finite element model.By proposing a comprehensive startup timing function for high-frequency dynamic machines under different startup conditions,simulating the frequency andmagnitude variations during the startup process,and suggesting functions for changes in frequency and magnitude,a simulated startup schedule function for high-frequency machines is created through coupling.Taking into account the selection of the transient dynamic analysis step length,the dynamic response results for the lower dynamic foundation during its fundamental frequency crossing process are obtained.The validation checks if the structural magnitude surpasses the safety threshold during the critical phase of unit startup traversing the structural resonance region.The design recommendations for high-frequency units’dynamic foundations are provided,taking into account the startup process of the machine and ensuring the safe operation of the tunnel.

Analysis of the Erosion-Corrosion Mechanism of the Air Cooler in a Hydrocracking Unit:A Numerical and Experimental Study

Corrosion leakages often occur in the air cooler of a hydrocracking unit,with the failure sites mainly located in the entrance area of the tubes.An analysis of the macroscopic morphology and corrosion products confirmed that the damage was caused by erosion-corrosion(E-C).Numerical and experimental methods were applied to investigate the E-C mechanism in the air cooler.Computational fluid dynamics(CFD)was used to calculate the hydrodynamic parameters of the air cooler.The results showed that there was a biased flow in the air cooler,which led to a significant increase in velocity,turbulent kinetic energy and wall shear within 0.2 m of the tube entrance.A visualization experiment was then performed to determine the principles of migration and transformation of multiphase flow in the air cooler tubes.Various flow patterns(pure droplet flow,mist flow,and annular flow)and their evolutionary processes were clearly depicted experimentally.The initiation mechanism and processes leading to the development of E-C in the air cooler were also determined.This study provided a comprehensive explanation for the E-C failures that occur in air coolers during operation.

A new evolutional model for institutional field knowledge flow network

Purpose:This paper aims to address the limitations in existing research on the evolution of knowledge flow networks by proposing a meso-level institutional field knowledge flow network evolution model(IKM).The purpose is to simulate the construction process of a knowledge flow network using knowledge organizations as units and to investigate its effectiveness in replicating institutional field knowledge flow networks.Design/Methodology/Approach:The IKM model enhances the preferential attachment and growth observed in scale-free BA networks,while incorporating three adjustment parameters to simulate the selection of connection targets and the types of nodes involved in the network evolution process Using the PageRank algorithm to calculate the significance of nodes within the knowledge flow network.To compare its performance,the BA and DMS models are also employed for simulating the network.Pearson coefficient analysis is conducted on the simulated networks generated by the IKM,BA and DMS models,as well as on the actual network.Findings:The research findings demonstrate that the IKM model outperforms the BA and DMS models in replicating the institutional field knowledge flow network.It provides comprehensive insights into the evolution mechanism of knowledge flow networks in the scientific research realm.The model also exhibits potential applicability to other knowledge networks that involve knowledge organizations as node units.Research Limitations:This study has some limitations.Firstly,it primarily focuses on the evolution of knowledge flow networks within the field of physics,neglecting other fields.Additionally,the analysis is based on a specific set of data,which may limit the generalizability of the findings.Future research could address these limitations by exploring knowledge flow networks in diverse fields and utilizing broader datasets.Practical Implications:The proposed IKM model offers practical implications for the construction and analysis of knowledge flow networks within institutions.It provides a valuable tool for understanding and managing knowledge exchange between knowledge organizations.The model can aid in optimizing knowledge flow and enhancing collaboration within organizations.Originality/value:This research highlights the significance of meso-level studies in understanding knowledge organization and its impact on knowledge flow networks.The IKM model demonstrates its effectiveness in replicating institutional field knowledge flow networks and offers practical implications for knowledge management in institutions.Moreover,the model has the potential to be applied to other knowledge networks,which are formed by knowledge organizations as node units.

Optimal decision-making method for equipment maintenance to enhance the resilience of power digital twin system under extreme disaster

Digital twins and the physical assets of electric power systems face the potential risk of data loss and monitoring failures owing to catastrophic events,causing surveillance and energy loss.This study aims to refine maintenance strategies for the monitoring of an electric power digital twin system post disasters.Initially,the research delineates the physical electric power system along with its digital counterpart and post-disaster restoration processes.Subsequently,it delves into communication and data processing mechanisms,specifically focusing on central data processing(CDP),communication routers(CRs),and phasor measurement units(PMUs),to re-establish an equipment recovery model based on these data transmission methodologies.Furthermore,it introduces a mathematical optimization model designed to enhance the digital twin system’s post-disaster monitoring efficacy by employing the branch-and-bound method for its resolution.The efficacy of the proposed model was corroborated by analyzing an IEEE-14 system.The findings suggest that the proposed branch-and-bound algorithm significantly augments the observational capabilities of a power system with limited resources,thereby bolstering its stability and emergency response mechanisms.

On implications of somatostatin in diabetic retinopathy

Somatostatin,a naturally produced neuroprotective peptide,depresses excitatory neurotransmission and exerts anti-proliferative and anti-inflammatory effects on the retina.In this review,we summarize the progress of somatostatin treatment of diabetic retinopathy through analysis of relevant studies published from February 2019 to February 2023 extracted from the PubMed and Google Scholar databases.Insufficient neuroprotection,which occurs as a consequence of declined expression or dysregulation of retinal somatostatin in the very early stages of diabetic retinopathy,triggers retinal neurovascular unit impairment and microvascular damage.Somatostatin replacement is a promising treatment for retinal neurodegeneration in diabetic retinopathy.Numerous pre-clinical and clinical trials of somatostatin analog treatment for early diabetic retinopathy have been initiated.In one such trial(EUROCONDOR),topical administration of somatostatin was found to exert neuroprotective effects in patients with pre-existing retinal neurodysfunction,but had no impact on the onset of diabetic retinopathy.Overall,we concluded that somatostatin restoration may be especially beneficial for the growing population of patients with early-stage retinopathy.In order to achieve early prevention of diabetic retinopathy initiation,and thereby salvage visual function before the appearance of moderate non-proliferative diabetic retinopathy,several issues need to be addressed.These include the needs to:a)update and standardize the retinal screening scheme to incorporate the detection of early neurodegeneration,b)identify patient subgroups who would benefit from somatostatin analog supplementation,c)elucidate the interactions of somatostatin,particularly exogenously-delivered somatostatin analogs,with other retinal peptides in the context of hyperglycemia,and d)design safe,feasible,low cost,and effective administration routes.

Petrogenesis and Tectonic Implications of the Early Triassic Nianzi Adakitic Granite Unit in the Yanshan Fold and Thrust Belt:New Constraints from U-Pb Geochronology and Sr-Nd-Hf Isotopes

The Nianzi granite unit,which includes the Nianzi,Xiaolianghou and Xiawopu granitic intrusions,is a significant component of the northern part of the North China Craton(NCC)and is situated in the Yanshan fold and thrust belt(YFTB).However,there is still debate regarding the tectonic evolutionary history of the YFTB during the late Permian to Triassic period,specifically regarding the timing of subduction and collision between the NCC and the Paleo-Asian Ocean.The Nianzi granite unit exhibits unique petrological,geochronological and geochemical signatures that shed light on the tectonic evolutionary history of the YFTB.This study presents detailed petrology,whole-rock geochemistry,together with Sr-Nd isotopic,zircon U-Pb dating and Lu-Hf isotopic data of the granites within the Nianzi granite unit.Our findings demonstrate that the granites primarily consist of subhedral K-feldspar,plagioclase,quartz,minor biotite and hornblende,with accessory titanite,apatite,magnetite and zircon.Zircon U-Pb dating indicates that the Xiaolianghou granite was emplaced at 247.5±0.62 Ma.Additionally,the adakitic characteristics of the Nianzi,Xiawopu and Xiaolianghou granitic intrusions,such as high Sr and Ba contents and high ratios of Sr/Y and(La/Yb)N,combined with negative Sr-Nd and Lu-Hf isotopes(87Sr/86Sr)i=0.705681–0.7057433,εNd(t)=−21.98 to−20.97,zirconεHf(t)=−20.26 to−9.92,as well as the I-type granite features of high SiO_(2),Na_(2)O and K_(2)O/Na_(2)O ratios,enriched Rb,K,Sr and Ba,along with depleted Th,U,Nb,Ta,P and Ti,suggest that the Nianzi granitic unit was mainly derived from the partial melting of a thickened lower crust containing hydrous,calc-alkaline to high-K calc-alkaline,mafic to intermediate metamorphic rocks.In light of these parameters,we further integrate our data with previous studies and conclude that the Nianzi granitic unit was generated in a post-collisional extensional environment during the Early Triassic.

Bionic lightweight design of limb leg units for hydraulic quadruped robots by additive manufacturing and topology optimization

Galloping cheetahs,climbing mountain goats,and load hauling horses all show desirable locomotion capability,which motivates the development of quadruped robots.Among various quadruped robots,hydraulically driven quadruped robots show great potential in unstructured environments due to their discrete landing positions and large payloads.As the most critical movement unit of a quadruped robot,the limb leg unit(LLU)directly affects movement speed and reliability,and requires a compact and lightweight design.Inspired by the dexterous skeleton–muscle systems of cheetahs and humans,this paper proposes a highly integrated bionic actuator system for a better dynamic performance of an LLU.We propose that a cylinder barrel with multiple element interfaces and internal smooth channels is realized using metal additive manufacturing,and hybrid lattice structures are introduced into the lightweight design of the piston rod.In addition,additive manufacturing and topology optimization are incorporated to reduce the redundant material of the structural parts of the LLU.The mechanical properties of the actuator system are verified by numerical simulation and experiments,and the power density of the actuators is far greater than that of cheetah muscle.The mass of the optimized LLU is reduced by 24.5%,and the optimized LLU shows better response time performance when given a step signal,and presents a good trajectory tracking ability with the increase in motion frequency.

EEG光子处理器——基于衍射光子计算单元的癫痫发作检测

Electroencephalography(EEG)analysis extracts critical information from brain signals,enabling brain disease diagnosis and providing fundamental support for brain–computer interfaces.However,performing an artificial intelligence analysis of EEG signals with high energy efficiency poses significant challenges for electronic processors on edge computing devices,especially with large neural network models.Herein,we propose an EEG opto-processor based on diffractive photonic computing units(DPUs)to process extracranial and intracranial EEG signals effectively and to detect epileptic seizures.The signals of the EEG channels within a second-time window are optically encoded as inputs to the constructed diffractive neural networks for classification,which monitors the brain state to identify symptoms of an epileptic seizure.We developed both free-space and integrated DPUs as edge computing systems and demonstrated their applications for real-time epileptic seizure detection using benchmark datasets,that is,the Children’s Hospital Boston(CHB)–Massachusetts Institute of Technology(MIT)extracranial and Epilepsy-iEEG-Multicenter intracranial EEG datasets,with excellent computing performance results.Along with the channel selection mechanism,both numerical evaluations and experimental results validated the sufficiently high classification accuracies of the proposed opto-processors for supervising clinical diagnosis.Our study opens a new research direction for utilizing photonic computing techniques to process large-scale EEG signals and promote broader applications.