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The existing indoor fusion positioning methods based on Pedestrian Dead Reckoning (PDR) and geomagnetic technology have the problems of large initial position error, low sensor accuracy, and geomagnetic mismatch. In this study, a novel indoor fusion positioning approach based on the improved particle filter algorithm by geomagnetic iterative matching is proposed, where Wi-Fi, PDR, and geomagnetic signals are integrated to improve indoor positioning performances. One important contribution is that geomagnetic iterative matching is firstly proposed based on the particle filter algorithm. During the positioning process, an iterative window and a constraint window are introduced to limit the particle generation range and the geomagnetic matching range respectively. The position is corrected several times based on geomagnetic iterative matching in the location correction stage when the pedestrian movement is detected, which made up for the shortage of only one time of geomagnetic correction in the existing particle filter algorithm. In addition, this study also proposes a real-time step detection algorithm based on multi-threshold constraints to judge whether pedestrians are moving, which satisfies the real-time requirement of our fusion positioning approach. Through experimental verification, the average positioning accuracy of the proposed approach reaches 1.59 m, which improves 33.2% compared with the existing particle filter fusion positioning algorithms.

High-precision polar motion (PM) prediction is of important significance in astronomy, geodesy, aviation, hydrographic mapping, interstellar navigation, and so on. SSA can effectively extract the trend and period terms of PM,in the process of achieving high-precision medium- and long-term polar motion prediction, it is necessary to solve the end effect problem and overfitting problem of SSA forecasting method; therefore, ARMA was applied to decreasethe end effect, and a suitable combination of reconstructed components was determined to avoid the high variance reaction of SSA overfitting. Based on the decomposition and reconstruction of the PM by SSA, the reconstructed components are determined to participate in the SSA iterative fitting model according to the variance contribution rate. The combination of the reconstructed components representing the polar motion period term and the trend term is determined according to the correlation analysis of the selected reconstructed components. After the above work, the principal component prediction sequence is obtained by fitting the period term and the trend term to convergence, respectively, and then, the SSA end effect is modified, and the residual term is predicted based on ARMA. The test results show that he prediction accuracy of SSA + ARMA at the front of the X and Y directions are improved by 96.90% and 97.53% compared with those of SSA, respectively, and the forecast accuracy of 365 days are improved by 37.93% and 19.53% in the X and Y directions compared with those of Bulletin A, respectively.

This study focuses on analyzing the time series of DORIS beacon stations and plate motion of the Eurasian plate by applying Singular Spectrum Analysis (SSA) and Fast Fourier Transform (FFT). First, the rend terms and periodic signals are accurately separated by SSA, then, the periodic seasonal signals are detected using SSA, and finally, the main components of the time series are reconstructed successfully. The test results show that the nonlinear trends and seasonal signals of DORIS stations are detected successfully. The periods of the seasonal signals detected are year, half-year, and 59 days, etc. The contribution rates and slopes in E, N, and U directions of the trend items of each beacon station after reconstruction are obtained by least-square fitting. The velocities of these stations are compared with those provided by the GEODVEL2010 model, and it is found that they are in good agreement except the DIOB, MANB, and PDMB stations. Based on the DORIS coordinate time series, the velocity field on the Eurasian plate is constructed, and the test shows that the Eurasian plate moves eastward as a whole with an average velocity of 24.19 ± 0.11 mm/y in the horizontal direction, and the average velocity of it is 1.74 ± 0.07 mm/y in the vertical direction.

This study aimed to explore the impact of ozonated water (OW) disinfestation on soil fungal community composition in continuous ginger field. All soil samples were collected in continuous ginger field. There were two groups and 5 time points (0, 1, 3, 5, 9 day) in our study, including OW disinfestation treatment group (O3 group) and control group (CK group). Via internal transcribed spacer (ITS) sequencing and further analysis, the changes of fungal community composition were determined. As a result, at 0 and 9 days after aeration, the operational taxonomic units (OTUs) in O3 group were significantly higher than that in CK group. Compared with the CK group, in O3 group: the ACE and Chao1 index significantly increased on day 1, and the Shannon index significantly decreased while Simpson index significantly increased on day 0 after aeration. In O3 group, there were dynamic changes of top 10 abundance fungi from the genus-level and the growth of Trichoderma and Rhodotorula had been promoted while Hannaella was inhibited. In conclusion, OW disinfestation had complicated impacts on fungal communities in continuous ginger fields. The growth of Trichoderma and Rhodotorula has been promoted during disinfestation, which provided more reference information for soil OW disinfestation research.

The Tonga volcano erupted on 15 January 2022, at 04:15:45 UTC, which significantly influenced the atmosphere and space environment, at the same time, an unprecedented opportunity to monitor ionospheric anomalies is provided by its powerful eruption. In current studies of traveling ionospheric disturbance (TID) triggered by the 2022 Tonga volcanic eruption, the particular phenomenon of ionospheric disturbances in various parts of the world has not been reasonably explained, and the vertical ionospheric disturbances are still not effectively detected. In this paper, we calculate the high-precision slant total electron content (STEC) from more than 3000 ground-based GPS stations distributed around the world, then we obtain the radio occultation (RO) data from near-field COSMIC-2 profiles and investigate the horizontal TID and the vertical ionospheric disturbances by the singular spectrum analysis (SSA). Horizontal TID propagation captured by GPS STEC results indicates that acoustic-gravity waves dominate the energy input at the beginning of the ionospheric disturbance with an approximate speed of 1050 m/s initially. With the dissipation of the shock energy, lamb waves become a dominant mode of ionospheric disturbances, moving at a more stable speed of about 326 m/s to a range of 16,000 km beyond the far-field. Local characteristics are evident during the disturbance, such as the ionospheric conjugation in Australia and the rapid decay of TID in Europe. The shock-Lamb-tsunami waves’ multi-fluctuation coupling is recorded successively from the COSMIC-2 RO observation data. The shock and Lamb waves can perturb the whole ionospheric altitude. In contrast, the disturbance caused by tsunami waves is much smaller than that of acoustic-gravity waves and Lamb waves. In addition, influenced by the magnetic field, the propagation speed of TID induced by Lamb waves is higher towards the northern hemisphere than towards the southern hemisphere.

COSMIC-2 is a remote sensing satellite mission that mainly provides scientific data for weather forecasting, ionosphere, and climate research. High precise orbit is the basis for the application of remote sensing satellite data. In order to realize the precise orbit determination (POD) of COSMIC-2, we have assessed the quality of space-borne GPS observation in detail, including the utilization of GPS observations, cycle slip ratio (o/slps), multipath error, single-noise ratio (SNR) and ionospheric delay rate (IOD) of the data, realized the POD of COSMIC-2 with the reduced dynamic (RD) method, and evaluated the accuracy of the solved orbit by means of the carrier-phase residual, overlapping orbit comparison and the reference orbit comparison. The data quality assessments show that the data is less affected by the multipath effect, the utilization of the data is low, cycle slips occur frequently, and the carrier-phase data is often interrupted. The POD results indicate that the root mean square (RMS) values of the carrier-phase residuals of six COSMIC-2 satellites are between 6.0 mm and 7.5 mm, The mean RMS values of the overlapping orbit are better than 0.92 cm, 1.33 cm and 1.03 cm in the radial (R), tangential (T) and normal (N) directions respectively, and the mean RMS values of the six satellites in the 3D direction are between 1.38 cm and 1.75 cm. The mean RMS values in R, T and N directions orbit determination accuracy of the reference orbit comparison are better than 5.61 cm, 6.59 cm and 2.29 cm respectively, and the mean RMS values of the six satellites in the 3D direction are between 7.35 cm and 8.79 cm.

ObjectiveTo develop a guideline for selecting biomarkers in the diagnosis and assessment in patients with axial spondyloarthritis (axSpA).MethodA joint effort was carried out by the core team, the literature review team and the multidisciplinary voting panel to formulate recommendations regarding biomarkers in axSpA, using an evidence-based and consensus-based strategy. Certainty of evidence and strength of recommendation were determined, and levels of agreement within the voting panel were calculated.ResultsA total of 20 recommendations were formulated in this guideline, with levels of agreement ranging from 6.48 to 9.71. The two strong recommendations, HLA-B27 testing in patients suspected of axSpA and regular-interval monitoring of CRP/ESR represent the status quo of axSpA evaluation, while the 13 conditional recommendations represent the promising biomarkers with clinical utility in diagnosis, disease activity assessment, prediction of radiographic progression and therapeutic responses. This guideline does not dictate clinical choices of tests on axSpA, and decisions should be made based on comprehensive consideration of costs, accessibility, patients’ values and willingness as well as the objective of testing in the local context.ConclusionThis guideline addresses the interpretation of the clinical significance of biomarkers in axSpA, and the biomarkers endorsed in this guideline composed a clinical toolkit for healthcare professionals to choose from.

Background and purpose: Rheumatoid arthritis (RA) is called “immortal cancer”, and it affects the quality of life, disability rate and even the survival of patients. This study aimed to observe the clinical efficacy, and adverse reactions of intradermal acupuncture (IA) in the treatment of RA patients with liver and kidney deficiency syndrome. Materials and methods: 132 RA patients were split into an IA group and a sham IA group at a 1:1 ratio. Both groups were assessed before and after the intervention with the assessments: a traditional Chinese medicine (TCM) syndrome evaluation, the Health Assessment Questionnaire (HAQ), the Disease Activity Score 28 (DAS28) and serum C-reactive protein (CRP). Results: There was a statistically significant difference in TCM syndrome evaluation, HAQ, DAS28, and CRP between both groups before and after treatment (P 0.05). Both groups had comparable results in the implementation of RA in the upper and lower extremity acupoints and did not differ due to different sites (IA group: P = 0.852; sham IA group: P = 0.861). The comparison of effective rate of the upper limb as well as that of the lower limb was statistically significant (P = 0.001). Besides, patients reported no adverse effects. Conclusion: The IA intervention was associated with a promising effect on the decrease in RA disease activity and delayed overall disease progression.

In order to optimize the current prediction method of coalbed methane production and solve the problem of losing key information due to the influence of historical state of coalbed methane production data and too long sequence, a coalbed methane production prediction model based on attention mechanism of convolutional neural network was proposed. Firstly, the five drainage parameters with high correlation with daily gas production are selected, and the CBM productivity prediction model is constructed and trained based on the field drainage data of the well in Hancheng Block. Finally, the production capacity of the well area in the next 160 days is predicted by the model. The research results show that combined model CNN-GRUA with attention mechanism overcomes the problems that traditional prediction methods cannot deal with, including nonlinearity between data, time sequence and information loss, by extracting high-level features of data and learning the correlation of time series. Compared with BP neural network, convolutional neural network (CNN), gated recurrent unit(GRU) and CNN-GRU without attention mechanism model, the CNN-GRUA combined model has higher prediction accuracy, and the mean absolute percentage error is 1.72%.

Spatial and temporal variation of water quality in two main tributaries of Yellow River was characterized with statistical methods including Discriminant Analysis (DA), Principal Component Analysis (PCA) and Factor Analysis (FA). The DA analysis determined the most significant parameters for spatial discrimination in the rivers: biological oxygen demand (BOD5) and total phosphorous (TP) for Luohe River and BOD5, total nitrogen (TN) and TP for Yihe River. The temporal discrimination of the water quality in the rivers mainly depended on the variables influenced by natural environmental process including, water temperature (WT), dissolved oxygen (DO) and pH. The variance factors obtained from the PCA/FA analysis suggested that the parameters associated with organic pollution and nutrient pollution accounted for water quality variations mostly. The FCA results showed that the water quality of the two rivers was higher than the water quality requirement in the water functional zones and got better in recent years. The temporal trend of the water quality in the two rivers showed that all the environmental actions implemented by the local government in the last years are contributive to the water quality upgrade in the region and should be kept or implemented more stringently in the future. [ABSTRACT FROM AUTHOR]

When a fire occurs on storage racks in a warehouse, it is not advisable to find the location of the fire point accurately, because there are a large number of goods on the storage rack, and many interference factors such as light will disturb the precise location of the fire. In response to the above problems, and thanks to the high-speed growth of deep learning technology, we propose an edge detection method and apply it in fire locations successfully. We adopt VGG-16 as our backbone and introduce an attention module to suppress background information and eliminate interference. We test the proposed method on our collected dataset, and the results show that our proposed model can extract the shelf edges more completely and locate the fire point accurately. In terms of detection speed, our method can achieve 0.188 s per image, which meets the requirements of real-time detection. Our approach lays a good foundation for the precise extinguishing of fire that occurs on storage racks.

Introduction Pulmonary vein isolation (PVI) is the cornerstone of radiofrequency (RF) ablation for atrial fibrillation (AF). However, a single ablation strategy does not always achieve the desired therapeutic effect in all patients with persistent AF, and individualised strategies are required for different clinical characteristics.Methods and analysis This study aimed to determine the optimal catheter ablation strategy for persistent AF by comparing the efficacy of PVI and BCXL (BC: big circles encircling pulmonary vein isolation; XL: unfixed number of lines based on the left atrial substrate). The BCXL-AF study (clinical trial no. ChiCTR2200067081) was designed as a prospective, randomised, parallel-controlled, single-blinded clinical trial. Overall, 400 patients with persistent AF were randomised in a 1:1 ratio into PVI-only and BCXL-individualised ablation groups. Patients randomised to the individualised ablation group will be further categorised into risk strata according to their clinical condition using the actual ablation method determined by the strata. Seven postoperative visits were conducted from discharge to 24 months of age. The primary observation endpoint will be the incidence of atrial tachyarrhythmia (including AF, atrial flutter and atrial tachycardia with a duration of ≥30 s) without using antiarrhythmic drugs after a blank period of 3 months following a single ablation procedure. The BCXL-AF study will assess an optimal approach for persistent AF RF ablation and evaluate the effectiveness of individualised RF ablation strategies in reducing the recurrence rate of AF.Ethics and dissemination The study protocol was reviewed, and ethical approval was obtained from the Army Medical University Human Ethics Committee (approval number: 2022-484-01). All the participants provided written informed consent. This study was conducted according to the principles of the Declaration of Helsinki and its amendments. The results of this study will be disseminated through manuscript publication and conference presentations.Trial registration number ChiCTR2200067081.

In recent years, due to the increasing number of patients with limb movement disorder, the development of rehabilitation robots has become a research hot spot. One of the control systems combining biomechanics and rehabilitation robots has many advantages, so it is necessary to study the interactive control and rehabilitation evaluation methods of rehabilitation robots based on surface EMG signals. The purpose of this article is to solve how to combining with multichannel SEMG rehabilitation robots, in turn, improve the robot performance problems, through the study how to obtain the body in real time on the surface of the muscle, multichannel SEMG and extraction, the feature information of the joints, muscle activity, and by using high precision microscope to prove the validity of the information, so as to adjust rehabilitation robot according to get the correct information of medical gas supply pressure effect, and on the basis of this article established the degree of evaluation system for the patient rehabilitation make a scientific evaluation. The research results show that the use of multichannel SEMG rehabilitation robot adaptive control system can be completed independent efficient pressure on the multichannel SEMG acquisition and real-time display, signal analysis and signal, can be adjusted according to the collected signal independent pressure increases medical effect, adopt the rehabilitation robot of patients recovery rate increased by 15%. In addition, the proposed rehabilitation evaluation system can determine the score and evaluation model according to the level of patients' movement disorders, and can independently give the effect and status of patients' rehabilitation training. [ABSTRACT FROM AUTHOR]

Abstract Aim To study the feasibility and effectiveness of a m‐Health app in improving the management of rheumatoid arthritis. Design Randomized controlled trial. Methods Sixty rheumatoid arthritis participants will be recruited for a 6‐month feasibility study. Patients meeting the inclusion criteria will be randomly allocated to receive standard care or standard care plus the m‐Health intervention. The primary outcome is the feasibility of a randomized controlled trial. In addition, we will investigate patient satisfaction in using the “Rheumatism Center” app in the intervention group. The secondary outcomes include the scores for the simplified disease activity index, clinical disease activity index, disease activity score 28, health assessment questionnaire and 6‐item self‐efficacy scale for chronic diseases. The assessments will be performed at baseline and at 4 weeks, 3 months and 6 months after the study is initiated. At the end of the study, we will also collect user views of the app through qualitative interviews. Results This study is ongoing. The findings of this study will determine the feasibility and effectiveness of m‐Health intervention in the management of rheumatoid arthritis, hoping to enhance the awareness of disease management and quality of life for rheumatoid arthritis patients.