Multivariate Time Series Anomaly Detection Based on Spatial-Temporal Network and Transformer in Industrial Internet of Things

In the Industrial Internet of Things(IIoT),sensors generate time series data to reflect the working state.When the systems are attacked,timely identification of outliers in time series is critical to ensure security.Although many anomaly detection methods have been proposed,the temporal correlation of the time series over the same sensor and the state(spatial)correlation between different sensors are rarely considered simultaneously in these methods.Owing to the superior capability of Transformer in learning time series features.This paper proposes a time series anomaly detection method based on a spatial-temporal network and an improved Transformer.Additionally,the methods based on graph neural networks typically include a graph structure learning module and an anomaly detection module,which are interdependent.However,in the initial phase of training,since neither of the modules has reached an optimal state,their performance may influence each other.This scenario makes the end-to-end training approach hard to effectively direct the learning trajectory of each module.This interdependence between the modules,coupled with the initial instability,may cause the model to find it hard to find the optimal solution during the training process,resulting in unsatisfactory results.We introduce an adaptive graph structure learning method to obtain the optimal model parameters and graph structure.Experiments on two publicly available datasets demonstrate that the proposed method attains higher anomaly detection results than other methods.

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.

AFSTGCN:Prediction for multivariate time series using an adaptive fused spatial-temporal graph convolutional network

The prediction for Multivariate Time Series(MTS)explores the interrelationships among variables at historical moments,extracts their relevant characteristics,and is widely used in finance,weather,complex industries and other fields.Furthermore,it is important to construct a digital twin system.However,existing methods do not take full advantage of the potential properties of variables,which results in poor predicted accuracy.In this paper,we propose the Adaptive Fused Spatial-Temporal Graph Convolutional Network(AFSTGCN).First,to address the problem of the unknown spatial-temporal structure,we construct the Adaptive Fused Spatial-Temporal Graph(AFSTG)layer.Specifically,we fuse the spatial-temporal graph based on the interrelationship of spatial graphs.Simultaneously,we construct the adaptive adjacency matrix of the spatial-temporal graph using node embedding methods.Subsequently,to overcome the insufficient extraction of disordered correlation features,we construct the Adaptive Fused Spatial-Temporal Graph Convolutional(AFSTGC)module.The module forces the reordering of disordered temporal,spatial and spatial-temporal dependencies into rule-like data.AFSTGCN dynamically and synchronously acquires potential temporal,spatial and spatial-temporal correlations,thereby fully extracting rich hierarchical feature information to enhance the predicted accuracy.Experiments on different types of MTS datasets demonstrate that the model achieves state-of-the-art single-step and multi-step performance compared with eight other deep learning models.

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.

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.

Comprehensive evaluation and spatial-temporal evolution characteristics of urban resilience in Chengdu-Chongqing Economic Circle

To clarify the connotations and extensions of urban resilience,this study focuses on the Chengdu-Chongqing Economic Circle with 16 cities as research subjects.A comprehensive evaluation index system was constructed to measure the resilience of each city from 2003 to 2020.The spatial-temporal evolution characteristics were analyzed using Kernel density estimation,standard deviation ellipse,and spatial Markov chain analysis,and the spatial Tobit model was introduced to discover the influencing factors.The results indicate the following:①Urban resilience in the Chengdu-Chongqing Economic Circle displays an upward trend,with the center of gravity moving to the southwest,and the polarization phenomenon intensifying.②The urban resilience level in a region has certain spatial and geographical dependence,while the probability of urban resilience transfer differs in adjacent cities with different resilience levels.③Urban centrality,economic scale,openness level,and financial development promote urban resilience,whereas government scale significantly inhibits it.Finally,this paper proposes countermeasures and suggestions to improve the urban resilience of the Chengdu-Chongqing Economic Circle.

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.

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.

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.

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.

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.

Spatial-temporal distribution and geochemistry of highly evolved Mesozoic granites in Great Xing’an Range,NE China:Discriminant criteria and geological significance

Highly evolved granite is an important sign of the mature continent crust and closely associated with deposits of rare metals.In this work,the authors undertake systematically zircon U-Pb ages and whole rock elemental data for highly evolved granitic intrusions from the Great Xing’an Range(GXR),NE China,to elucidate their discriminant criteria,spatial-temporal distribution,differentiation and geodynamic mecha-nism.Geochemical data of these highly evolved granites suggest that high w(SiO_(2))(>70%)and differentiation index(DI>88)could be quantified indicators,while strong Eu depletion,high TE_(1,3),lowΣREE and low Zr/Hf,Nb/Ta,K/Rb could only be qualitative indicators.Zircon U-Pb ages suggest that the highly evolved gran-ites in the GXR were mainly formed in Late Mesozoic,which can be divided into two major stages:Late Ju-rassic-early Early Cretaceous(162-136 Ma,peak at 138 Ma),and late Early Cretaceous(136-106 Ma,peak at 126 Ma).The highly evolved granites are mainly distributed in the central-southern GXR,and display a weakly trend of getting younger from northwest to southeast,meanwhile indicating the metallogenic potential of rare metals within the central GXR.The spatial-temporal distribution,combined with regional geological data,indicates the highly evolved Mesozoic granites in the GXR were emplaced in an extensional environ-ment,of which the Late Jurassic-early Early Cretaceous extension was related to the closure of the Mongol-Okhotsk Ocean and roll-back of the Paleo-Pacific Plate,while the late Early Cretaceous extension was mainly related to the roll-back of the Paleo-Pacific Plate.

Optical scanning endoscope via a single multimode optical fiber

Optical endoscopy has become an essential diagnostic and therapeutic approach in modern biomedicine for directly observing organs and tissues deep inside the human body,enabling non-invasive,rapid diagnosis and treatment.Optical fiber endoscopy is highly competitive among various endoscopic imaging techniques due to its high flexibility,compact structure,excellent resolution,and resistance to electromagnetic interference.Over the past decade,endoscopes based on a single multimode optical fiber(MMF)have attracted widespread research interest due to their potential to significantly reduce the footprint of optical fiber endoscopes and enhance imaging capabilities.In comparison with other imaging principles of MMF endoscopes,the scanning imaging method based on the wavefront shaping technique is highly developed and provides benefits including excellent imaging contrast,broad applicability to complex imaging scenarios,and good compatibility with various well-established scanning imaging modalities.In this review,various technical routes to achieve light focusing through MMF and procedures to conduct the scanning imaging of MMF endoscopes are introduced.The advancements in imaging performance enhancements,integrations of various imaging modalities with MMF scanning endoscopes,and applications are summarized.Challenges specific to this endoscopic imaging technology are analyzed,and potential remedies and avenues for future developments are discussed.

Three-dimensional finite element simulation and reconstruction of jointed rock models using CT scanning and photogrammetry

The geometry of joints has a significant influence on the mechanical properties of rocks.To simplify the curved joint shapes in rocks,the joint shape is usually treated as straight lines or planes in most laboratory experiments and numerical simulations.In this study,the computerized tomography (CT) scanning and photogrammetry were employed to obtain the internal and surface joint structures of a limestone sample,respectively.To describe the joint geometry,the edge detection algorithms and a three-dimensional (3D) matrix mapping method were applied to reconstruct CT-based and photogrammetry-based jointed rock models.For comparison tests,the numerical uniaxial compression tests were conducted on an intact rock sample and a sample with a joint simplified to a plane using the parallel computing method.The results indicate that the mechanical characteristics and failure process of jointed rocks are significantly affected by the geometry of joints.The presence of joints reduces the uniaxial compressive strength (UCS),elastic modulus,and released acoustic emission (AE) energy of rocks by 37%–67%,21%–24%,and 52%–90%,respectively.Compared to the simplified joint sample,the proposed photogrammetry-based numerical model makes the most of the limited geometry information of joints.The UCS,accumulative released AE energy,and elastic modulus of the photogrammetry-based sample were found to be very close to those of the CT-based sample.The UCS value of the simplified joint sample (i.e.38.5 MPa) is much lower than that of the CT-based sample (i.e.72.3 MPa).Additionally,the accumulative released AE energy observed in the simplified joint sample is 3.899 times lower than that observed in the CT-based sample.CT scanning provides a reliable means to visualize the joints in rocks,which can be used to verify the reliability of photogrammetry techniques.The application of the photogrammetry-based sample enables detailed analysis for estimating the mechanical properties of jointed rocks.

Adaptive spatial-temporal graph attention network for traffic speed prediction

Considering the nonlinear structure and spatial-temporal correlation of traffic network,and the influence of potential correlation between nodes of traffic network on the spatial features,this paper proposes a traffic speed prediction model based on the combination of graph attention network with self-adaptive adjacency matrix(SAdpGAT)and bidirectional gated recurrent unit(BiGRU).First-ly,the model introduces graph attention network(GAT)to extract the spatial features of real road network and potential road network respectively in spatial dimension.Secondly,the spatial features are input into BiGRU to extract the time series features.Finally,the prediction results of the real road network and the potential road network are connected to generate the final prediction results of the model.The experimental results show that the prediction accuracy of the proposed model is im-proved obviously on METR-LA and PEMS-BAY datasets,which proves the advantages of the pro-posed spatial-temporal model in traffic speed prediction.

Spatial-temporal Variation Characteristics of Water Quality in the Lower Reaches of the Nenjiang River

As an important river in the western part of Jilin Province,the lower reach of the Nenjiang River is an important wetland water source conservation area in Jilin Province.Within the watershed,it governs the Momoge Wetland,the Xianghai Wetland,and the Danjiang Wetland in Jilin Province.The main problem in the lower reaches of the Nenjiang River is the uneven distribution of water resources in time and space,and the intensification of land salinization.Zhenlai County and Da an City in the Nenjiang River Basin have sufficient surface water resources,with surface water as the drinking water source.Baicheng City and Tongyu County have scarce surface water resources,and both use groundwater as their domestic water source.The main polluted section in the basin is the Xianghai Reservoir,and the annual water quality evaluation is Class V.However,the water quality of the Tao er River,the main stream of the Nenjiang River,is significantly better than that of the Xianghai Reservoir.In order to better study the water environmental pollution situation in the Nenjiang River basin,monitoring data from five sections of non seasonal rivers in the basin from 2012 to 2021 were selected for studying water quality.This in-depth exploration of the water pollution status and river water quality change trends in the Nenjiang River basin is of great significance for future rural development,agricultural pattern transformation,and the promotion of water ecological civilization construction.