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.

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%.

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.

Continuity of Care in Primary Health Care Affecting Control of Diabetes

Background: Continuity of care is a distinguishing feature of primary care. Better continuity of care program showed a significant effect in controlling diabetes and it is complications. This study explores the effect of continuity of care on control of diabetes mellites in primary health care centres. Objectives: 1) To assess the effect of Continuity of care on controlling haemoglobin (Hb A1C) and fasting blood Sugar (FBS);2) To compare the control of Diabetes by using (Hb A1C and FBS) indices on same patient before and after application of chronic illness clinic;3) To identify the relation between age and gender affecting continuity of care in diabetic patient. Methods: It is a Prospective cohort study design. Included both gender and diabetic patient age above 24 years old. The data extracted from health care specialty center (HCSC) clinics in National guard hospital at Riyadh, through HCSC data base on three phases: 1) Phase 1: the data extracted of diabetic patients from October to November 2022 including MRN, diabetic patient, age, Hb A1C, Fasting blood glucose. 2) Phase 2: the same MRN extracted from phase 1 was extracted again retrospectively for six months from April to September 2022, to compare the indices before implanting the chronic illness clinic including Hb A1C, Fasting blood glucose. 3) Phase 3: prospectively from December 2022 to September 2023. Results: Among diabetic patients aged 60 years old and above showed better control of HbA1C and FBS comparing to these patients below age of 60 years old, with significant improvement of HbA1C after implanting chronic illness clinic. Conclusion: The significant improvement in the control of diabetic patients followed in primary health care centers reinforce the evidence of the importance of continuity of care.

Continuity of truncated Hardy-Littlewood maximal function

This paper focuses on the continuity of the truncated Hardy-Littlewood maximal function.We first show that the truncated Hardy-Littlewood maximal function is lower semi-continuous.Then by investigating the behavior of the truncated Hardy-Littlewood maximal function when the truncated parameterγchanges,we obtain an equivalent condition of the continuity of the truncated Hardy-Littlewood maximal function.

GLOBAL CONVERGENCE OF A CAUTIOUS PROJECTION BFGS ALGORITHM FOR NONCONVEX PROBLEMS WITHOUT GRADIENT LIPSCHITZ CONTINUITY

A cautious projection BFGS method is proposed for solving nonconvex unconstrained optimization problems.The global convergence of this method as well as a stronger general convergence result can be proven without a gradient Lipschitz continuity assumption,which is more in line with the actual problems than the existing modified BFGS methods and the traditional BFGS method.Under some additional conditions,the method presented has a superlinear convergence rate,which can be regarded as an extension and supplement of BFGS-type methods with the projection technique.Finally,the effectiveness and application prospects of the proposed method are verified by numerical experiments.

Analysis of the Nursing Effect of Continuity of Care on Elderly Patients with Coronary Heart Disease Unstable Angina and its Impact on Quality of Life

Objective:To analyze the effect of using continuity of care for elderly patients with coronary heart disease(CHD)with unstable angina pectoris(UAP)and its impact on their quality of life.Methods:100 cases of elderly patients with CHD with UAP admitted to our hospital from March 2022 to March 2023 were selected and grouped into an observation group and a control group of 50 cases each according to the randomized number table method.The nursing effect and quality of life of the observation group(continuity nursing)and the control group(routine nursing)were compared.Results:The total effective rate of nursing care was 96.00%observation group and 80.00%for the control group,and the differences were significant(χ2=6.061,P<0.05).Patients in the observation group had fewer episodes(1.42±0.21)times/week and a shorter duration(5.46±0.39)min,which were better than the control group(t=3.465,2.973;P<0.05).The depression self-rating depression scale(SDS)score(42.16±6.64)and anxiety self-rating scale(SAS)score(32.26±7.35)in the observation group were lower and the quality of life was higher as compared to that of the control group(P<0.05).Conclusion:Continuous nursing care improved the nursing effect of elderly CHD with UAP patients,promoted the alleviation of UAP symptoms,improved patient mentality,and improved their quality of life.Hence,continuous nursing care possesses significant clinical application value.

Multi-Scale Location Attention Model for Spatio-Temporal Prediction of Disease Incidence

Due to the increasingly severe challenges brought by various epidemic diseases,people urgently need intelligent outbreak trend prediction.Predicting disease onset is very important to assist decision-making.Most of the exist-ing work fails to make full use of the temporal and spatial characteristics of epidemics,and also relies on multi-variate data for prediction.In this paper,we propose a Multi-Scale Location Attention Graph Neural Networks(MSLAGNN)based on a large number of Centers for Disease Control and Prevention(CDC)patient electronic medical records research sequence source data sets.In order to understand the geography and timeliness of infec-tious diseases,specific neural networks are used to extract the geography and timeliness of infectious diseases.In the model framework,the features of different periods are extracted by a multi-scale convolution module.At the same time,the propagation effects between regions are simulated by graph convolution and attention mechan-isms.We compare the proposed method with the most advanced statistical methods and deep learning models.Meanwhile,we conduct comparative experiments on data sets with different time lengths to observe the predic-tion performance of the model in the face of different degrees of data collection.We conduct extensive experi-ments on real-world epidemic-related data sets.The method has strong prediction performance and can be readily used for epidemic prediction.

Spatio-Temporal Change of Dispersal Areas of Greater Kudu (Tragelaphus strepsiceros) in Lake Bogoria Landscape, Kenya

Decline in wildlife populations is manifest globally, regionally and locally. A wildlife decline of 68% has been reported in Kenya’s rangelands with Baringo County experiencing more than 85% wildlife loss in the last four decades. Greater Kudu (Tragelaphus strepsiceros) is endemic to Lake Bogoria landscape in Baringo County and constitutes a major tourist attraction for the region necessitating use of its photo on the County’s logo and thus a flagship species. Tourism plays a central role in Baringo County’s economy and is a major source of potential growth and employment creation. The study was carried out to assess spatio-temporal change of dispersal areas of Greater Kudu (GK) in Lake Bogoria landscape in the last four years for enhanced adaptive management and improved livelihoods. GK population distribution primary data collected in December 2022 and secondary data acquired from Lake Bogoria National Game Reserve (LBNGR) for 2019 and 2020 were digitized using in a Geographic Information System (GIS). Measures of dispersion and point pattern analysis (PPA) were used to analyze dispersal of GK population using GIS. Spatio-temporal change of GK dispersal in LBNR was evident thus the null hypothesis was rejected. It is recommended that anthropogenic activities contributing to GK’s habitat degradation be curbed by providing alternative livelihood sources and promoting community adoption of sustainable technologies for improved livelihoods.

Research on the Spatio-Temporal Evolution and Driving Forces of Green Spaces in the Central Urban Area of Zunyi City

Green space,as a medium for carrying out urban functions and guiding urban development,is becoming a scarce resource along with the urbanization process and the intensification of environmental problems.In the face of the spatial mismatch between high demand and low supply,it is of great significance to clarify the evolution mechanism of green space to undertake national spatial planning,protect the natural strategic resources in the urban fringe area,and promote the sustainable development of the“three living spaces.”The study focuses on the Zunyi City Center,selecting the 20 years of rapid development following its establishment as a city as the study period.It explores the dynamic evolution of green space and the main driving forces during different periods using remote-sensing image data.The study shows that from 2003 to 2023,the total scale of green space has an obvious decreasing trend along with the expansion of the urban built-up area.A large amount of arable land is being converted to construction land,resulting in a sudden decrease in arable land area.In the past 10 years,the comprehensive land use dynamics have accelerated.Still,the spatial difference has gradually narrowed,indicating that the overall development intensity of Zunyi City’s central urban area has increased.There is a gradual spread of the trend to the hilly areas.The limiting effect of the mountainous natural environment on the city’s development has gradually diminished under the superposition of external factors,such as economic development,industrial technological upgrading,and policy orientation so the importance of the effective protection and rational utilization of urban green space has become more prominent.

Traveling Wave Solutions of a SIR Epidemic Model with Spatio-Temporal Delay

In this paper, we studied the traveling wave solutions of a SIR epidemic model with spatial-temporal delay. We proved that this result is determined by the basic reproduction number R0and the minimum wave speed c*of the corresponding ordinary differential equations. The methods used in this paper are primarily the Schauder fixed point theorem and comparison principle. We have proved that when R0>1and c>c*, the model has a non-negative and non-trivial traveling wave solution. However, for R01and c≥0or R0>1and 0cc*, the model does not have a traveling wave solution.

Application Effect of WeChat Platform Continuity of Care Model Based on KAP Theory on Self-Management of Stroke Patients with Hypertension

Objective: To explore the impact of the WeChat platform continuity of care model based on the KAP (knowledge, attitudes, and practices) theory on the self-management of stroke patients with hypertension after discharge from the hospital. Methods: 62 stroke patients with hypertension discharged from the rehabilitation department of a tertiary A hospital in Nanning City, Guangxi Zhuang Autonomous Region, from October 2022 to April 2023 were sampled by convenience sampling method. Patients discharged from Rehabilitation I were included in the control group, and conventional nursing care was used;while patients discharged from Rehabilitation II were included in the observation group, and WeChat platform continuity of nursing care model based on the KAP theory was implemented. The intervention effect of the two groups was compared. Results: After 4 and 12 weeks of intervention, the diastolic and systolic blood pressure of the patients in the observation group were lower than those in the control group (P < 0.05);after 12 weeks of intervention, the rate of medication adherence and the score of adherence to hypertension treatment in the observation group were significantly higher than those in the control group (P < 0.05). Conclusion: The application of the WeChat platform continuity of care model based on KAP theory to stroke patients with hypertension can improve blood pressure, medication adherence rate, hypertension treatment adherence, and overall enhance the self-management level of these patients.

Clinical Study on the Effect of Continuity of Care in CICU on Improving Cognitive Function and Psychological State in Patients with Heart Failure

Objective:To analyze the effect of continuity of care in the cardiac intensive care unit(CICU)on improving cognitive function and psychological state in patients with heart failure(HF).Methods:A total of 112 chronic HF patients admitted to the CICU of Xuzhou Traditional Chinese Medicine Hospital from July 2022 to August 2024 were selected and randomly divided into two groups using the red and blue ball method:a control group(n=56)and a study group(n=56).The control group received routine CICU nursing management,while the study group received routine CICU nursing combined with continuity of care management.Cognitive function(using the Montreal Cognitive Assessment,MoCA),psychological state(using the Self-Rating Depression Scale,SDS,and Self-Rating Anxiety Scale,SAS),and quality of life(using the Minnesota Living with Heart Failure Questionnaire,MLHFQ)were compared between the two groups.Results:After the intervention,the cognitive function scores of the study group were significantly higher than those of the control group(P<0.05).The SDS and SAS scores of the study group were significantly lower than those of the control group after the intervention(P<0.05).The quality of life in the study group was also significantly better than in the control group(P<0.05).Conclusion:CICU continuity of care can effectively improve cognitive function and psychological state in patients with HF,while also enhancing their quality of life.

Spatio-temporal distribution of net primary productivity along the northeast China transect and its response to climatic change

An improved Carnegie Ames Stanford Approach model （CASA model） was used to estimate the net primary productivity （NPP） of the Northeast China Transect （NECT） every month from 1982 to 2000. The spatial-temporal distribution of NPP along NECT and its response to climatic change were also analyzed. Results showed that the change tendency of NPP spatial distribution in NECT is quite similar to that of precipitation and their spatial correlation coefficient is up to 0.84 （P 〈 0.01）. The inter-annual variation of NPP in NECT is mainly affected by the change of the aestival NPP every year, which accounts for 67.6% of the inter-annual increase in NPP and their spatial correlation coefficient is 0.95 （P 〈 0.01）. The NPP in NECT is mainly cumulated between May and September, which accounts for 89.8% of the annual NPP. The NPP in summer （June to August） accounts for 65.9% of the annual NPP and is the lowest in winter. Recent climate changes have enhanced plant growth in NECT. The mean NPP increased 14.3% from 1980s to 1990s. The inter-annual linear trend of NPP is 4.6 gC·m^-2·a^-1, and the relative trend is 1.17%, which owns mainly to the increasing temperature.

Analysis on Spatio-temporal Distribution of Lightning in Dalian Area of China between 2007 and 2008

The cloud-to-ground lightning data between 2007 and 2008 were collected by lightning detection and location system,which was composed of four lightning detectors in four different sites of Dalian area.The spatio-temporal distribution of cloud-to-ground lightning in surrounding areas of Dalian was analyzed from several aspects of polarity distribution,diurnal variation,lightning intensity and lightning density.The results showed that the number of negative lightning accounted for 93.9% of the total number of lightning,and its average lightning intensity was 27.99 kA.The number of positive lightning accounted for 6.1% of the total number of lightning,and its average lightning intensity was 35.56 kA.The diurnal variation of lightning frequency showed an obvious structure of two peaks (17:00-18:00 and 04:00-05:00) and two valleys (09:00-10:00 and 00:00-01:00).The number of lightning between May and September was 91.5% of the annual number,and the lightning occurred the most frequently between June and August.Most of positive and negative lightning was at the intensity of 15-35 kA,80.0% lower than 40 kA,and 99.3% lower than 100 kA.The lightning density had obvious regional differences in distribution,high in the Liaodong Bay and the Dalian Bay and low in inland areas.Therefore,coastal areas should attract more attention in lightning disaster defense in the surrounding areas of Dalian.

Spatio-temporal GIS和GPS优化集成在城市交通管制中的应用研究

本文基于城市交通日益恶化现状和3S集成的迅速发展,表述了Spatio-temporal GIS的定义、时空路径、人类活动的四种时空关系及其坐标系统模型的建立;并根据GPS空间定位、空间导航的原理和模型,将Spatio-temporal GIS和GPS的功能优化集成,阐述了其对城市交通信息的收集、分析、显示等功能;最后论述了Spatio-temporal GIS和GPS的集成对城市交通预警、报警、协调等管制作用。

THE IMPLICIT CONTINUITY OF DISCONTINUOUS SYSTEMS

An example is presented to introduce the concept of implicit continuity proposed as contrasted with the explicit continuity.A sufficient and necessary condition of the implicit continuity is given and proved in forms of implicit system.This condition also offers the solution of initial values at the points where the dynamic system is discontinuous.Some discussions are contributed to the physical significance of implicit continuity.