Improved spatio-temporal alignment measurement method for hull deformation

In this paper,an improved spatio-temporal alignment measurement method is presented to address the inertial matching measurement of hull deformation under the coexistence of time delay and large misalignment angle.Large misalignment angle and time delay often occur simultaneously and bring great challenges to the accurate measurement of hull deformation in space and time.The proposed method utilizes coarse alignment with large misalignment angle and time delay estimation of inertial measurement unit modeling to establish a brand-new spatiotemporal aligned hull deformation measurement model.In addition,two-step loop control is designed to ensure the accurate description of dynamic deformation angle and static deformation angle by the time-space alignment method of hull deformation.The experiments illustrate that the proposed method can effectively measure the hull deformation angle when time delay and large misalignment angle coexist.

Ultrasound Scanning Competencies in Midwifery Education in Zambia: Findings from a Desk Review and Needs Assessment

Introduction: Ultrasound is an essential component of antenatal care. Midwives provide most of the antenatal care but they do not perform ultrasound as it has been beyond their scope of practice. This leaves many women in Low and Middle-Income Countries without access to ultrasound scanning. The aim of this study was to identify competencies in ultrasound scanning in midwifery education. Methods: A desk review and needs assessment were conducted between July and October 2023. Articles and curricula on the internet, Google scholar and PubMed were searched for content on ultrasound scanning competencies. A Google form consisting of 20 questions was administered via email and WhatsApp to 135 participants. Descriptive statistics were used to analyse data. Results: The desk review showed that it is feasible to train midwives in ultrasound scanning. The training programs for midwives in obstetric ultrasound were conducted for 1 week to 3 months with most of them running for 4 weeks. Content included introduction to general principles of ultrasound, physics, basic knowledge in embryology, obstetrics, anatomy, measuring foetal biometry, estimating amniotic fluid and gestational age. Experts like sonographers trained midwives. Theory and hands on were the teaching methods used. Written and practical assessments were conducted. Needs assessment revealed that majority of participants 71 (53%) knew about basic ultrasound training for midwives. All participants (100%) said it is necessary to train midwives in basic ultrasound scan in Zambia. Some content should include, anatomy, measuring foetal biometry, assessing amniotic fluid level, and gestational age determination. Most participants 91 (67%) suggested that the appropriate duration of training is 4 - 6 weeks. Conclusion: Empowering every midwife with ultrasound scanning skills will enable early detection of any abnormality among pregnant women and prompt intervention to save lives.

Acousto-optic scanning multi-photon lithography with high printing rate

As a manufacturing method that is focused on end-users,3D printing has gained a lot of attention in recent years due to its unique advantages in fabricating complex three-dimensional structures.Various new micro-nano 3D printing methods have been developed to meet the demand for high-precision and high-yield manufacturing1-9.Among them,multi-photon-photon lithography(MPL) is a promising 3D nanofabrication technology due to its capability of true 3D digital processing and nanoscale processing resolution beyond the diffraction limit.It has been widely used to fabricate microoptics10,11,photonic crystals12,microfluidics13,meta-surfaces14,and mechanical metamaterials15.

Epidemic Characteristics and Spatio-Temporal Patterns of HFRS in Qingdao City,China,2010-2022

Objective This study investigated the epidemic characteristics and spatio-temporal dynamics of hemorrhagic fever with renal syndrome(HFRS)in Qingdao City,China.Methods Information was collected on HFRS cases in Qingdao City from 2010 to 2022.Descriptive epidemiologic,seasonal decomposition,spatial autocorrelation,and spatio-temporal cluster analyses were performed.Results A total of 2,220 patients with HFRS were reported over the study period,with an average annual incidence of 1.89/100,000 and a case fatality rate of 2.52%.The male:female ratio was 2.8:1.75.3%of patients were aged between 16 and 60 years old,75.3%of patients were farmers,and 11.6%had both“three red”and“three pain”symptoms.The HFRS epidemic showed two-peak seasonality:the primary fall-winter peak and the minor spring peak.The HFRS epidemic presented highly spatially heterogeneous,street/township-level hot spots that were mostly distributed in Huangdao,Pingdu,and Jiaozhou.The spatio-temporal cluster analysis revealed three cluster areas in Qingdao City that were located in the south of Huangdao District during the fall-winter peak.Conclusion The distribution of HFRS in Qingdao exhibited periodic,seasonal,and regional characteristics,with high spatial clustering heterogeneity.The typical symptoms of“three red”and“three pain”in patients with HFRS were not obvious.

Dynamic adaptive spatio-temporal graph network for COVID-19 forecasting

Appropriately characterising the mixed space-time relations of the contagion process caused by hybrid space and time factors remains the primary challenge in COVID-19 forecasting.However,in previous deep learning models for epidemic forecasting,spatial and temporal variations are captured separately.A unified model is developed to cover all spatio-temporal relations.However,this measure is insufficient for modelling the complex spatio-temporal relations of infectious disease transmission.A dynamic adaptive spatio-temporal graph network(DASTGN)is proposed based on attention mechanisms to improve prediction accuracy.In DASTGN,complex spatio-temporal relations are depicted by adaptively fusing the mixed space-time effects and dynamic space-time dependency structure.This dual-scale model considers the time-specific,space-specific,and direct effects of the propagation process at the fine-grained level.Furthermore,the model characterises impacts from various space-time neighbour blocks under time-varying interventions at the coarse-grained level.The performance comparisons on the three COVID-19 datasets reveal that DASTGN achieves state-of-the-art results with a maximum improvement of 17.092%in the root mean-square error and 11.563%in the mean absolute error.Experimental results indicate that the mechanisms of designing DASTGN can effectively detect some spreading characteristics of COVID-19.The spatio-temporal weight matrices learned in each proposed module reveal diffusion patterns in various scenarios.In conclusion,DASTGN has successfully captured the dynamic spatio-temporal variations of COVID-19,and considering multiple dynamic space-time relationships is essential in epidemic forecasting.

An Intelligent Framework for Resilience Recovery of FANETs with Spatio-Temporal Aggregation and Multi-Head Attention Mechanism

Due to the time-varying topology and possible disturbances in a conflict environment,it is still challenging to maintain the mission performance of flying Ad hoc networks(FANET),which limits the application of Unmanned Aerial Vehicle(UAV)swarms in harsh environments.This paper proposes an intelligent framework to quickly recover the cooperative coveragemission by aggregating the historical spatio-temporal network with the attention mechanism.The mission resilience metric is introduced in conjunction with connectivity and coverage status information to simplify the optimization model.A spatio-temporal node pooling method is proposed to ensure all node location features can be updated after destruction by capturing the temporal network structure.Combined with the corresponding Laplacian matrix as the hyperparameter,a recovery algorithm based on the multi-head attention graph network is designed to achieve rapid recovery.Simulation results showed that the proposed framework can facilitate rapid recovery of the connectivity and coverage more effectively compared to the existing studies.The results demonstrate that the average connectivity and coverage results is improved by 17.92%and 16.96%,respectively compared with the state-of-the-art model.Furthermore,by the ablation study,the contributions of each different improvement are compared.The proposed model can be used to support resilient network design for real-time mission execution.

Warhead fragments motion trajectories tracking and spatio-temporal distribution reconstruction method based on high-speed stereo photography

High speed photography technique is potentially the most effective way to measure the motion parameter of warhead fragment benefiting from its advantages of high accuracy,high resolution and high efficiency.However,it faces challenge in dense objects tracking and 3D trajectories reconstruction due to the characteristics of small size and dense distribution of fragment swarm.To address these challenges,this work presents a warhead fragments motion trajectories tracking and spatio-temporal distribution reconstruction method based on high-speed stereo photography.Firstly,background difference algorithm is utilized to extract the center and area of each fragment in the image sequence.Subsequently,a multi-object tracking(MOT)algorithm using Kalman filtering and Hungarian optimal assignment is developed to realize real-time and robust trajectories tracking of fragment swarm.To reconstruct 3D motion trajectories,a global stereo trajectories matching strategy is presented,which takes advantages of epipolar constraint and continuity constraint to correctly retrieve stereo correspondence followed by 3D trajectories refinement using polynomial fitting.Finally,the simulation and experimental results demonstrate that the proposed method can accurately track the motion trajectories and reconstruct the spatio-temporal distribution of 1.0×10^(3)fragments in a field of view(FOV)of 3.2 m×2.5 m,and the accuracy of the velocity estimation can achieve 98.6%.

Investigation of reflection anisotropy induced by micropipe defects on the surface of a 4H-SiC single crystal using scanning anisotropy microscopy

Optical reflection anisotropy microscopy mappings of micropipe defects on the surface of a 4H-SiC single crystal are studied by the scanning anisotropy microscopy(SAM)system.The reflection anisotropy(RA)image with a'butterfly pattern'is obtained around the micropipes by SAM.The RA image of the edge dislocations is theoretically simulated based on dislocation theory and the photoelastic principle.By comparing with the Raman spectrum,it is verified that the micropipes consist of edge dislocations.The different patterns of the RA images are due to the different orientations of the Burgers vectors.Besides,the strain distribution of the micropipes is also deduced.One can identify the dislocation type,the direction of the Burgers vector and the optical anisotropy from the RA image by using SAM.Therefore,SAM is an ideal tool to measure the optical anisotropy induced by the strain field around a defect.

Prophylactic Pattern Scanning Laser Retinal Photocoagulation for Diabetic Retinopathy in Spontaneously Diabetic Torii Fatty Rats: Preliminary Experimental Results

Research Background and Purpose: The number of diabetic patients is rapidly increasing, making it crucial to find methods to prevent diabetic retinopathy (DR), a leading cause of blindness. We investigated the effects of prophylactic pattern scanning laser retinal photocoagulation on DR development in Spontaneously Diabetic Torii (SDT) fatty rats as a new prevention approach. Methods: Photocoagulation was applied to the right eyes of 8-week-old Spontaneously Diabetic Torii (SDT) fatty rats, with the left eyes serving as untreated controls. Electroretinography at 9 and 39 weeks of age and pathological examinations, including immunohistochemistry for vascular endothelial growth factor and glial fibrillary acidic protein at 24 and 40 weeks of age, were performed on both eyes. Results: There were no significant differences in amplitude and prolongation of the OP waves between the right and left eyes in SDT fatty rats at 39 weeks of age. Similarly, no significant differences in pathology and immunohistochemistry were observed between the right and left eyes in SDT fatty rats at 24 and 40 weeks of age. Conclusion: Prophylactic pattern scanning retinal laser photocoagulation did not affect the development of diabetic retinopathy in SDT fatty rats.

A cloud model target damage effectiveness assessment algorithm based on spatio-temporal sequence finite multilayer fragments dispersion

To solve the problem of target damage assessment when fragments attack target under uncertain projectile and target intersection in an air defense intercept,this paper proposes a method for calculating target damage probability leveraging spatio-temporal finite multilayer fragments distribution and the target damage assessment algorithm based on cloud model theory.Drawing on the spatial dispersion characteristics of fragments of projectile proximity explosion,we divide into a finite number of fragments distribution planes based on the time series in space,set up a fragment layer dispersion model grounded in the time series and intersection criterion for determining the effective penetration of each layer of fragments into the target.Building on the precondition that the multilayer fragments of the time series effectively assail the target,we also establish the damage criterion of the perforation and penetration damage and deduce the damage probability calculation model.Taking the damage probability of the fragment layer in the spatio-temporal sequence to the target as the input state variable,we introduce cloud model theory to research the target damage assessment method.Combining the equivalent simulation experiment,the scientific and rational nature of the proposed method were validated through quantitative calculations and comparative analysis.

Self-Attention Spatio-Temporal Deep Collaborative Network for Robust FDIA Detection in Smart Grids

False data injection attack(FDIA)can affect the state estimation of the power grid by tampering with the measured value of the power grid data,and then destroying the stable operation of the smart grid.Existing work usually trains a detection model by fusing the data-driven features from diverse power data streams.Data-driven features,however,cannot effectively capture the differences between noisy data and attack samples.As a result,slight noise disturbances in the power grid may cause a large number of false detections for FDIA attacks.To address this problem,this paper designs a deep collaborative self-attention network to achieve robust FDIA detection,in which the spatio-temporal features of cascaded FDIA attacks are fully integrated.Firstly,a high-order Chebyshev polynomials-based graph convolution module is designed to effectively aggregate the spatio information between grid nodes,and the spatial self-attention mechanism is involved to dynamically assign attention weights to each node,which guides the network to pay more attention to the node information that is conducive to FDIA detection.Furthermore,the bi-directional Long Short-Term Memory(LSTM)network is introduced to conduct time series modeling and long-term dependence analysis for power grid data and utilizes the temporal selfattention mechanism to describe the time correlation of data and assign different weights to different time steps.Our designed deep collaborative network can effectively mine subtle perturbations from spatiotemporal feature information,efficiently distinguish power grid noise from FDIA attacks,and adapt to diverse attack intensities.Extensive experiments demonstrate that our method can obtain an efficient detection performance over actual load data from New York Independent System Operator(NYISO)in IEEE 14,IEEE 39,and IEEE 118 bus systems,and outperforms state-of-the-art FDIA detection schemes in terms of detection accuracy and robustness.

Accuracy of tree mapping based on hand-held laser scanning comparing leaf-on and leaf-off conditions in mixed forests

The use of mobile laser scanning to survey forest ecosystems is a promising,scalable technology to describe forest 3D structures at high resolution.To confirm the con-sistency in the retrieval of forest structural parameters using hand-held laser scanning(HLS),before operationalizing the method,confirming the data is crucial.We analyzed the per-formance of tree-level mapping based on HLS under differ-ent phenology conditions on a mixed forest in western Spain comprising Pinus pinaster and two deciduous species,Alnus glutinosa and Quercus pyrenaica.The area was surveyed twice during the growing season(July 2022)and once in the deciduous season(February 2022)using several scan-ning paths.Ground reference data(418 trees,15 snags)was used to calibrate the HLS data and to assess the influence of phenology when converting 3D data into tree-level attrib-utes(DBH,height and volume).The HLS-based workflow was robust at isolating tree positions and recognizing stems despite changes in phenology.Ninety-six percent of all pairs matched below 65 cm.For DBH,phenology barely altered estimates.We observed a strong agreement when comparing HLS-based tree height distributions.The values exceeded 2 m when comparing height measurements,confirming height data should be carefully used as reference in remote sensing-based inventories,especially for deciduous species.Tree volume was more precise for pines(r=0.95,and rela-tive RMSE=21.3–23.8%)compared to deciduous species(r=0.91–0.96,and relative RMSE=27.3–30.5%).HLS data and the forest structural complexity tool performed remark-ably,especially in tree positioning considering mixed forests and mixed phenology conditions.

A review of understanding electrocatalytic reactions in energy conversion and energy storage systems via scanning electrochemical microscopy

To address climate change and promote environmental sustainability,electrochemical energy conversion and storage systems emerge as promising alternative to fossil fuels,catering to the escalating demand for energy.Achieving optimal energy efficiency and cost competitiveness in these systems requires the strategic design of electrocatalysts,coupled with a thorough comprehension of the underlying mechanisms and degradation behavior occurring during the electrocatalysis processes.Scanning electrochemical microscopy(SECM),an analytical technique for studying surface electrochemically,stands out as a powerful tool offering electrochemical insights.It possesses remarkable spatiotemporal resolution,enabling the visualization of the localized electrochemical activity and surface topography.This review compiles crucial research findings and recent breakthroughs in electrocatalytic processes utilizing the SECM methodology,specifically focusing on applications in electrolysis,fuel cells,and metal–oxygen batteries within the realm of energy conversion and storage systems.Commencing with an overview of each energy system,the review introduces the fundamental principles of SECM,and aiming to provide new perspectives and broadening the scope of applied research by describing the major research categories within SECM.

Fatigue properties and damage constitutive model of salt rock based on CT scanning

To investigate the macroscopic fatigue properties and the mesoscopic pore evolution characteristics of salt rock under cyclic loading,fatigue tests under different upper-limit stresses were carried out on salt rock,and the mesoscopic pore structures of salt rock before and after fatigue tests and under different cycle numbers were measured using CT scanning instrument.Based on the test results,the effects of the cycle number and the upper-limit stress on the evolution of cracks,pore morphology,pore number,pore volume,pore size,plane porosity,and volume porosity of salt rock were analyzed.The failure path of salt rock specimens under cyclic loading was analyzed using the distribution law of plane porosity.The damage variable of salt rock under cyclic loading was defined on basis of the variation of volume porosity with cycle number.In order to describe the fatigue deformation behavior of salt rock under cyclic loading,the nonlinear Burgers damage constitutive model was further established.The results show that the model established can better reflect the whole development process of fatigue deformation of salt rock under cyclic loading.

Contribution of CT Scanning in the Investigation of Cranioencephalic Lesions in Bangui

Introduction: Cranioencephalic exploration has always played a major role in CT scans. In the Central Africa Republic (CAR), the lack of cross-sectional imaging before the year 2020 meant that no study had focused on cranioencephalic lesions. The aim of this study was to contribute to improving the management of cranioencephalic pathologies in CAR. Patients and Method: The study took place at the Bangui National Medical Imaging Centre (CNIMB). It was a retrospective study over a two-year period (March 1, 2021 to February 30, 2023). All patients referred for cranioencephalic CT scans were included, regardless of age or sex. Results: 1745 CT scans were performed, 575 of which were cranioencephalic CT scans. The majority of patients were male (53%). Most lived in the capital Bangui (90.9%). Patients aged 61 and over were the most representative. The distribution of patients by requesting department showed that the reception and emergency department was one of the least requesting departments. The main abnormalities observed were strokes, 82.1% of which were ischaemic strokes and 17.9% haemorrhagic strokes. Strokes were followed by degenerative lesions. Post-traumatic injuries included haemorrhagic contusions (38.3%), subdural haematomas in 20.5% of cases, and extradural haematomas (9.3%). Craniofacial lesions (fractures) were observed in 45.8% of cases. Conclusion: Cranioencephalic scans accounted for 1/3 of CT examinations performed during the study period. It revealed pathologies that could not be detected by conventional means. All in all, CT scans contributed to the diagnosis of cerebral pathologies.

Study on Joint Method of 3D Acoustic Emission Source Localization Simplex and Grid Search Scanning

Acoustic emission(AE)source localization is a fundamental element of rock fracture damage imaging.To improve the efficiency and accuracy of AE source localization,this paper proposes a joint method comprising a three-dimensional(3D)AE source localization simplex method and grid search scanning.Using the concept of the geometry of simplexes,tetrahedral iterations were first conducted to narrow down the suspected source region.This is followed by a process of meshing the region and node searching to scan for optimal solutions,until the source location is determined.The resulting algorithm was tested using the artificial excitation source localization and uniaxial compression tests,after which the localization results were compared with the simplex and exhaustive methods.The results revealed that the localization obtained using the proposed method is more stable and can be effectively avoided compared with the simplex localization method.Furthermore,compared with the global scanning method,the proposed method is more efficient,with an average time of 10%–20%of the global scanning localization algorithm.Thus,the proposed algorithm is of great significance for laboratory research focused on locating rupture damages sustained by large-sized rock masses or test blocks.

Algorithm of automatic identification of diabetic retinopathy foci based on ultra-widefield scanning laser ophthalmoscopy

AIM:To propose an algorithm for automatic detection of diabetic retinopathy(DR)lesions based on ultra-widefield scanning laser ophthalmoscopy(SLO).METHODS:The algorithm utilized the FasterRCNN(Faster Regions with CNN features)+ResNet50(Residua Network 50)+FPN(Feature Pyramid Networks)method for detecting hemorrhagic spots,cotton wool spots,exudates,and microaneurysms in DR ultra-widefield SLO.Subimage segmentation combined with a deeper residual network FasterRCNN+ResNet50 was employed for feature extraction to enhance intelligent learning rate.Feature fusion was carried out by the feature pyramid network FPN,which significantly improved lesion detection rates in SLO fundus images.RESULTS:By analyzing 1076 ultra-widefield SLO images provided by our hospital,with a resolution of 2600×2048 dpi,the accuracy rates for hemorrhagic spots,cotton wool spots,exudates,and microaneurysms were found to be 87.23%,83.57%,86.75%,and 54.94%,respectively.CONCLUSION:The proposed algorithm demonstrates intelligent detection of DR lesions in ultra-widefield SLO,providing significant advantages over traditional fundus color imaging intelligent diagnosis algorithms.

Phase behavior of gas condensate in porous media using real-time computed tomography scanning

The phase behavior of gas condensate in reservoir formations differs from that in pressure-volume-temperature(PVT)cells because it is influenced by porous media in the reservoir formations.Sandstone was used as a sample to investigate the influence of porous media on the phase behavior of the gas condensate.The pore structure was first analyzed using computed tomography(CT)scanning,digital core technology,and a pore network model.The sandstone core sample was then saturated with gas condensate for the pressure depletion experiment.After each pressure-depletion state was stable,realtime CT scanning was performed on the sample.The scanning results of the sample were reconstructed into three-dimensional grayscale images,and the gas condensate and condensate liquid were segmented based on gray value discrepancy to dynamically characterize the phase behavior of the gas condensate in porous media.Pore network models of the condensate liquid ganglia under different pressures were built to calculate the characteristic parameters,including the average radius,coordination number,and tortuosity,and to analyze the changing mechanism caused by the phase behavior change of the gas condensate.Four types of condensate liquid(clustered,branched,membranous,and droplet ganglia)were then classified by shape factor and Euler number to investigate their morphological changes dynamically and elaborately.The results show that the dew point pressure of the gas condensate in porous media is 12.7 MPa,which is 0.7 MPa higher than 12.0 MPa in PVT cells.The average radius,volume,and coordination number of the condensate liquid ganglia increased when the system pressure was between the dew point pressure(12.7 MPa)and the pressure for the maximum liquid dropout,Pmax(10.0 MPa),and decreased when it was below Pmax.The volume proportion of clustered ganglia was the highest,followed by branched,membranous,and droplet ganglia.This study provides crucial experimental evidence for the phase behavior changing process of gas condensate in porous media during the depletion production of gas condensate reservoirs.

Tree species identity and interaction determine vertical forest structure in young planted forests measured by terrestrial laser scanning

Vertical forest structure is closely linked to multiple ecosystem characteristics,such as biodiversity,habitat,and productivity.Mixing tree species in planted forests has the potential to create diverse vertical forest structures due to the different physiological and morphological traits of the composing tree species.However,the relative importance of species richness,species identity and species interactions for the variation in vertical forest structure remains unclear,mainly because traditional forest inventories do not observe vertical stand structure in detail.Terrestrial laser scanning(TLS),however,allows to study vertical forest structure in an unprecedented way.Therefore,we used TLS single scan data from 126 plots across three experimental planted forests of a largescale tree diversity experiment in Belgium to study the drivers of vertical forest structure.These plots were 9–11years old young pure and mixed forests,characterized by four levels of tree species richness ranging from monocultures to four-species mixtures,across twenty composition levels.We generated vertical plant profiles from the TLS data and derived six stand structural variables.Linear mixed models were used to test the effect of species richness on structural variables.Employing a hierarchical diversity interaction modelling framework,we further assessed species identity effect and various species interaction effects on the six stand structural variables.Our results showed that species richness did not significantly influence most of the stand structure variables,except for canopy height and foliage height diversity.Species identity on the other hand exhibited a significant impact on vertical forest structure across all sites.Species interaction effects were observed to be site-dependent due to varying site conditions and species pools,and rapidly growing tree species tend to dominate these interactions.Overall,our results highlighted the importance of considering both species identity and interaction effects in choosing suitable species combinations for forest management practices aimed at enhancing vertical forest structure.

Surface evolution of thermoelectric material KCu_(4)Se_(3) explored by scanning tunneling microscopy

Novel two-dimensional thermoelectric materials have attracted significant attention in the field of thermoelectric due to their low lattice thermal conductivity.A comprehensive understanding of their microscopic structures is crucial for driving further the optimization of materials properties and developing novel functional materials.Here,by using in situ scanning tunneling microscopy,we report the atomic layer evolution and surface reconstruction on the cleaved thermoelectric material KCu_(4)Se_(3) for the first time.We clearly revealed each atomic layer,including the naturally cleaved K atomic layer,the intermediate Se^(2-)atomic layer,and the Se^(-)atomic layer that emerges in the thermodynamic-stable state.Departing from the maj ority of studies that predominantly concentrate on macroscopic measurements of the charge transport,our results reveal the coexistence of potassium disorder and complex reconstructed patterns of selenium,which potentially influences charge carrier and lattice dynamics.These results provide direct insight into the surface microstructures and evolution of KCu_(4)Se_(3),and shed useful light on designing functional materials with superior performance.