Validation and evaluation on B1IB3I-based and B1CB2a-based BDS-3 precise orbits from iGMAS

To evaluate the clinical performance of direct composite restorations using the modified stamp technique (MST) in vivo. A total of 30 posterior teeth with undermining caries were randomly divided into two groups and then restored using the MST and conventional technique (CT), respectively. 3D images of the occlusal surface were obtained using an intraoral scanner (CEREC Omnicam, Dentsply Sirona, Charlotte, NC, USA) before and after treatment and the differences between these two 3D images were analysed with reverse engineering software. Statistical analysis was performed using a one-way analysis of variance (ANOVA) combined with a least significant difference (LSD) post hoc test using SPSS 20.0 software (IBM, Armonk, NY, USA). The statistical analysis revealed that the average root mean square (RMS) values of best fit alignment errors were significantly different between groups (P < 0.01). The average RMS values in the MST and CT groups were 0.0738 ± 0.0279 and 0.1638 ± 0.0682, respectively. The LSD post hoc test revealed that the value was significant smaller in the MST group than in the CT group. The MST was effective in direct composite restoration. The morphological consistency of the occlusal surface using the MST was better than with the CT.

Though widely used to generate the global navigation satellite system (GNSS) ultra-rapid orbit products for real-time applications, the batch least-squares (LSQ) adjustment and precise orbit determination (POD) prediction is limited for satellites undergoing maneuvers. To generate the truly real-time orbit products, we introduce the square root information filter (SRIF) real-time POD strategy, in which a real-time satellite maneuver handling algorithm that adapts the stochastic model for irregular satellite behaviors is implemented. The performance of the SRIF POD strategy is first evaluated with 1-month of data from multi-GNSS experiment (MGEX) network and BDS experimental tracking stations (BETS). Compared with the MGEX final products provided by GFZ (GBM), the SRIF solutions show higher precision than the ultra-rapid solutions. The averaged 3D RMS of the orbit differences between the SRIF solutions and the GBM final product is about 29.1 cm and 22.5 cm for the BDS IGSO and MEO satellites. The BDS orbits generated by SRIF are continuous over all the time, while the ultra-rapid orbits exhibit obvious jumps and discontinuity at the orbit update time. Validation by satellite laser ranging (SLR) shows that for GEO satellites, the SRIF solutions have better stability and continuity, whereas the GBM final products exhibit obvious accuracy degradation around the day boundary. To evaluate the performance of maneuver handling, the proposed method is further tested on 10 maneuver cases of BDS GEO and IGSO satellites. The start and end time of all maneuver events in different cases are precisely detected, which are consistent with the officially announced ones. Using the proposed strategy, the filter avoids divergence and outputs continuous orbit solutions during the maneuver periods and restores the normal POD within about 7.5 h after the maneuver is finished.

In recent years, real-time global ionospheric map (RT-GIM) products have been actively developed by the international global navigation satellite system (GNSS) service (IGS) and its ionosphere associate analysis centers (IAACs) along with the increase of RT-GNSS multi-frequency and multi-constellation observations. In this study, the accuracy and consistency of three RT-GIM products from the Chinese Academy of Sciences (CAS), Wuhan University (WHU), and IGS are evaluated and analyzed utilizing three validation methods, namely, comparison with JASON-3 vertical total electron content (VTEC), the difference of slant total electron content (dSTEC), and IGS combined final GIM (IGSG) data. The test period was from 1 January 2019 to 31 December 2022, including the different solar activities. First, the comparison with JASON-3 data illustrates that the quality of the three RT-GIM products over oceans is in great consistency with that of the IGSG during different levels of solar activity and the daily mean bias (MEAN) values in low and high solar activities are approximately 5 and 10 TECU, respectively. The root mean square (RMS) values under low and high solar activities can be up to 7 and 12 TECU. Furthermore, the dSTEC validation results present that the MEAN values of RT-GIM products from different IAACs at high- and mid-latitude stations are about 0.5 TECU, which is smaller than those at low-latitude stations at about 1 TECU over continental regions. The standard deviation (STD) and RMS values for various RT-GIM products are within 3 and 4 TECU at low latitudes, respectively. In terms of the comparison with IGSG, the result shows that IGS combined RT-GIM (IRTG) presents better consistency than CAS RT-GIM (CRTG) and WHU RT-GIM (WRTG) in 2021 and 2022, with average annual STD and RMS values of 2.56 and 2.78 TECU, respectively. The daily biases of the RT-GIM products relative to IGSG can reach 4 TECU in high solar activities and the daily STD and RMS values are mainly within the 5 to 6 TECU range, respectively.

Rapid and accurate ambiguity resolution is the core of high-precision precise point positioning (PPP) data processing. However, the ambiguity parameters in PPP observation models are easily affected by atmospheric residual and gross errors, which lead to the probability of successfully fixing decreases and computational burden increases in full ambiguity resolution. Therefore, an increasing number of partial ambiguity resolution (PAR) strategies have been proposed. The selection of the optimal subset of PAR is crucial in this method. The traditional optimal subset selection method of PAR commonly leads to a single judgment criterion and weakened geometric configuration strength because the satellites with low elevation angles are often easily eliminated during the optimal subset selection. In this paper, a multi-factor constrained optimal subset selection method for PAR was proposed, which incorporates the ambiguity variance, the ambiguity dilution of precision (ADOP), satellite position dilution of precision (PDOP) and ratio test values. In order to verify the feasibility of the proposed optimal subset selection method, PAR tests under two schemes were performed for GPS/Galileo based on the static observation data of 15 Multi-GNSS Experiment (MGEX) tracking stations. The results show that, compared with the ambiguity variance sorting method, the proposed subset selection method can further improve the accuracy of the coordinate solution and the strength of geometric figure positioning. The average root mean square of the coordinate residuals is found to decrease by about 12.90%, 6.83% and 9.39% in the eastern, northern and vertical directions, respectively. The increase in the fixed epoch rate ranged from 0.87% to 33.33%, with an average of about 8.71%.

ABSTRACTUpdating of reservoir models by history matching of 4D seismic data along with production data gives us a better understanding of changes to the reservoir, reduces risk in forecasting and leads to better management decisions. This process of seismic history matching requires an accurate representation of predicted and observed data so that they can be compared quantitatively when using automated inversion. Observed seismic data is often obtained as a relative measure of the reservoir state or its change, however. The data, usually attribute maps, need to be calibrated to be compared to predictions. In this paper we describe an alternative approach where we normalize the data by scaling to the model data in regions where predictions are good. To remove measurements of high uncertainty and make normalization more effective, we use a measure of repeatability of the monitor surveys to filter the observed time‐lapse data.We apply this approach to the Nelson field. We normalize the 4D signature based on deriving a least squares regression equation between the observed and synthetic data which consist of attributes representing measured acoustic impedances and predictions from the model. Two regression equations are derived as part of the analysis. For one, the whole 4D signature map of the reservoir is used while in the second, 4D seismic data is used from the vicinity of wells with a good production match. The repeatability of time‐lapse seismic data is assessed using the normalized root mean square of measurements outside of the reservoir. Where normalized root mean square is high, observations and predictions are ignored. Net: gross and permeability are modified to improve the match.The best results are obtained by using the normalized root mean square filtered maps of the 4D signature which better constrain normalization. The misfit of the first six years of history data is reduced by 55 per cent while the forecast of the following three years is reduced by 29 per cent. The well based normalization uses fewer data when repeatability is used as a filter and the result is poorer. The value of seismic data is demonstrated from production matching only where the history and forecast misfit reductions are 45% and 20% respectively while the seismic misfit increases by 5%. In the best case using seismic data, it dropped by 6%. We conclude that normalization with repeatability based filtering is a useful approach in the absence of full calibration and improves the reliability of seismic data.

Satellite laser ranging (SLR) to the satellites of the global navigation satellite systems (GNSS) provides substantial and valuable information about the accuracy and quality of GNSS orbits and allows for the SLR-GNSS colocation in space. In the framework of the NAVSTAR-SLR experiment two GPS satellites of Block-IIA were equipped with laser retroreflector arrays (LRAs), whereas all satellites of the GLONASS system are equipped with LRAs in an operational mode. We summarize the outcome of the NAVSTAR-SLR experiment by processing 20 years of SLR observations to GPS and 12 years of SLR observations to GLONASS satellites using the reprocessedmicrowave orbits provided by the center for orbit determination in Europe (CODE). The dependency of the SLR residuals on the size, shape, and number of corner cubes in LRAs is studied. We show that the mean SLR residuals and the RMS of residuals&#13;\ndepend on the coating of the LRAs and the block or type of GNSS satellites. The SLR mean residuals are also a function of the equipment used at SLR stations including the single-photon and multi-photon detection modes.We also showthat the SLR observations to GNSS satellites are important to validate GNSS orbits and to assess deficiencies in the solar radiation pressure models. We found that the satellite signature effect, which is defined as a spread of optical pulse signals due to reflection from multiple reflectors, causes the variations of mean SLR residuals of up to 15mmbetween the observations at nadir angles of 0◦ and 14◦. in case of multiphoton SLR stations. For single-photon SLR stations this effect does not exceed 1 mm. When using the new empirical&#13;\nCODE orbit model (ECOM), the SLR mean residual falls into the range 0.1–1.8 mm for high-performing singlephoton SLR stations observing GLONASS-M satellites with uncoated corner cubes. For best-performing multi-photon stations the mean SLR residuals are between −12.2 and&#13;\n−25.6 mm due to the satellite signature effect.

Determining precise multi-satellite orbits and geodetic parameters using satellite laser ranging (SLR) observations of spherical laser geodetic satellites is essential for high-accuracy geodetic scientific applications. Weekly multi-satellite combined solutions for satellite orbits, station coordinates and earth rotation parameters (ERPs) using SLR observations from LAGEOS, Etalon and newly launched LARES-2 satellites are achieved using a self-developed software function based on a new processing strategy. We present an in-depth accuracy analysis of the satellite orbits and geodetic parameters determined from the combined solution of LAGEOS-Etalon and LAGEOS-Etalon-LARES-2, in which the impact of two years of LARES-2 SLR observations is mainly studied. The root mean square (RMS) value of post-fit residuals is 0.81 cm for LARES-2, which is comparable to or slightly smaller than that of the LAGEOS and Etalon satellites. The statistics of the differences in overlapping orbit and external orbit comparison are performed for orbit accuracy assessment. For LAGEOS and Etalon, the results of overlapping orbit and external orbit comparison present similar conclusions. The mean of the RMS values of orbit difference for LAGEOS is about 3 cm in the three-dimensional (3D) direction, and less than 1 cm in the radial (R) direction. The mean RMS value of orbit difference for Etalon is about 15 cm in the 3D direction, and less than 3 cm in the R direction. The inclusion of LARES-2 SLR observations can slightly improve the orbit accuracy of Etalon. For LARES-2, the mean RMS values of overlapping orbit difference are 1.79 cm and 0.29 cm in the 3D and R directions, respectively, which are smaller than those for LAGEOS. Moreover, the stability and accuracy of the estimated station coordinates and ERPs are improved after adding LARES-2 SLR observations to multi-satellite combined solutions.

The aim of this study was to compare mechanomyogram (MMG) recorded by a condenser microphone (MIC) and an accelerometer (ACC) during submaximal isometric, concentric and eccentric contractions in 14 males. The maximal voluntary force (MVC) of the biceps brachii was measured. The subjects were asked to do short duration isometric, concentric and eccentric contraction at 10%, 30%, 50%, 70% MVC twice. For the concentric and eccentric contraction, the subject bent his arm for 3 s (concentric) then held it for 3 s and extended (eccentric) during 3 s. The normalized root mean square (RMS) and mean power frequency (MPF) increased linearly with increased force for both transducers. There was a correlation between MIC MPF and ACC MPF at 10%, 30%, 50% MVC, and between MIC RMS and ACC RMS at 30% MVC during isometric contractions. There was significantly higher MPF for the ACC than for the MIC in concentric and eccentric modes, while the RMS did not differ among transducers in the three contraction modes. The RMS and MPF values coefficient of variations were significantly larger during anisometric contractions compared with isometric contractions and were lower for the accelerometer than for the microphone. The present results obtained during isometric, concentric and eccentric contractions of increased intensity showed that the information contained in microphone- and accelerometer-based MMG signals is different despite similar trends. It can be concluded that at low-moderate movement velocity, concentric contractions can be investigated by means of accelerometer and microphone.

Precise orbit determination and rapid orbit recovery supported by time synchronization

Geostationary Earth Orbit (GEO) satellites play a significant role in the space segment of the Chinese Area Navigation System. The C-Band transfer ranging method developed by the National Time Service Center (NTSC) has been widely used in the Chinese Area Positioning System (CAPS), with its advantages of separating satellite ranging from time synchronization and being unaffected by weather. The explicit ranging correction models for the C-Band transfer ranging method are introduced in detail in this article for the first time. Precise Orbit Determination (POD) using C-Band pseudo-range observation of GEO satellite 2010-001A in July 2012 has been conducted. The residual Root Mean Square (RMS) of each site and POD are analysed with orbit difference over overlaps of adjacent orbit arcs. Moreover, the orbit of the GEO satellite has been evaluated by Satellite Laser Ranging (SLR) data from both domestic and foreign SLR sites for the first time. The residual RMS of POD using C-Band observation is better than 0·1 m, and the orbit difference over overlaps of adjacent orbit arcs is better than 3 m. In addition, the residual RMS in line-of-sight for a SLR site in China are better than 1 m, while the RMS for the Yarragadee site in Australia is about 3·4 m. It has been shown that the GEO satellite orbit accords very well with the C-Band observation. Also, the distribution of CAPS stations affects the orbit precision. All sites in CAPS are now located in China with low and medium latitudes. The residual RMS of the SLR site in the southern hemisphere is larger than that of the site in China.

Regarding the problem of systematic multipath bias on BeiDou navigation system code observations, ten days BeiDou triple-frequency observations of multi-stations were collected, the relationships between the characteristic of multipath bias and the type of the satellite, the signal frequency and the satellite elevation angle were analyse d. In order to solve this problem, a modified sidereal filtering based on zero-phase filter was proposed to mitigate the multipath bias on GEO and IGSO satellites code observations, and elevation-angle correction method was introduced to decrease the multipath bias of IGSO and MEO satellite code observations. The experimental results show that the modified sidereal filtering can decrease the multipath bias of B1, B2 and B3 frequencies code observations for GEO and IGSO satellites over 17.0, 18.6 and 10.5%, respectively, and the elevation-angle correction method can reduce the multipath bias of IGSO and MEO satellite B1, B2 and B3 frequencies code measurements by 5.0, 6.8, and 4.1%, respectively. After mitigating the multipath bias of BeiDou code observations, the precision of single point position for east, north and up directions can be improved about 34, 45 and 51%, respectively.

The inter-satellite link (ISL) equipment of the third-generation BeiDou Navigation Satellite System (BDS-3) can enhance the accuracy of precise orbit determination (POD) for BDS-3 satellites. However, the hardware delays within ISL observations can impact the measurement accuracy of ISL observations. This study evaluates the characteristics of hardware delays in ISL observations for BDS-3 medium Earth orbit (MEO) satellites and investigates their effects on POD. Analysis shows that most links exhibit slow variations in hardware delays, with standard deviations (STD) of 6.4 cm and 3.6 cm over 45 days for the C19-C25 and C20-C21 links, respectively. Conversely, some links like C30-C23 and C30-C33 show more pronounced variations, with STD values reaching 17.7 cm and 14.1 cm within three days. Links involving satellites C23 and C30 display higher variability and significant jumps in hardware delays compared with other links. The larger variations in hardware delays of these links can be absorbed by other parameters, thereby affecting the accuracy of parameter estimation. To mitigate their impact on POD, a segmented estimation strategy for hardware delays is proposed. This strategy divides a single link into multiple segments based on a set interval length and estimates the hardware delay parameters for each segment separately, thereby absorbing the variations in hardware delays or unmodeled errors. The effectiveness of this strategy is demonstrated through ISL POD residual analysis, comparison with L-band orbit determination results, and validation using Satellite Laser Ranging (SLR) residuals. The root mean square (RMS) of ISL observation residuals decreased by approximately 44.3%, from 6.1 cm to 3.4 cm. Comparisons with L-band orbits confirmed an approximate 28.2% reduction in the 3D RMS of orbit discrepancies, from 26.5 cm to 19.0 cm. Additionally, the RMS of the overall SLR residuals showed a slight decrease. Overall, the improved segmented estimation strategy effectively reduces the influence of hardware delay variations on BDS-3 orbit determination, notably enhancing the orbit determination accuracy of BDS-3 satellites, especially for C23 and C30, which experience larger hardware delay fluctuations.

Computational modeling, such as finite element analysis, is employed in a range of biomechanics specialties, including impact biomechanics and surgical planning. These models rely on accurate material properties for skeletal muscle, which comprises roughly 40% of the human body. Due to surrounding tissues, compressed skeletal muscle in vivo likely experiences a semi-confined state. Nearly all previous studies investigating passively compressed muscle at the tissue level have focused on muscle in unconfined compression. The goals of this study were to (1) examine the stiffness and time-dependent material properties of skeletal muscle subjected to both confined and unconfined compression (2) develop a model that captures passive muscle mechanics under both conditions and (3) determine the extent to which different assumptions of volumetric behavior affect model results. Muscle in confined compression exhibited stiffer behavior, agreeing with previous assumptions of near-incompressibility. Stress relaxation was found to be faster under unconfined compression, suggesting there may be different mechanisms that support load these two conditions. Finite element calibration was achieved through nonlinear optimization (normalized root mean square error <6%) and model validation was strong (normalized root mean square error <17%). Comparisons to commonly employed assumptions of bulk behavior showed that a simple one parameter approach does not accurately simulate confined compression. We thus recommend the use of a properly calibrated, nonlinear bulk constitutive model for modeling of skeletal muscle in vivo. Future work to determine mechanisms of passive muscle stiffness would enhance the efforts presented here.

The first lactation weekly test day milk yield (WTDMY) records (57233) and monthly test day milk yield (MTDMY) records (11970) spread over a period of 23 years (1984– 2006) sired by 82 bulls of Karan Fries cattle were used to develop the best lactation curve model. The lactation curve parameters of Quadratic cum log model (QCLM), Gamma function (GF), Cobby Le Du model (CLDM), Polynomial regression function (PRF) and Multiphasic logistic function (MLF) were estimated. The average weekly test day milk yield was predicted with high degree of accuracy (R2 &gt; 85%) by all the models with the maximum accuracy (R2 = 99.50%) obtained by polynomial regression function (PRF) and the least fit (R2 = 87.90%) was obtained by Gamma function (GF). However Quadratic cum log model (R2 = 99.20%) was almost equal to polynomial regression function and was better than Cobby Le Du model (R2 = 92.80%). The average root mean square error (RMSE) was found to be minimum with PRF (0.0121 Kg) followed by MLF (Triphasic). Thus the best fit model was polynomial regression function, which was better than other functions for prediction of first lactation WTDMY. The average monthly test day milk yield was predicted with high degree of accuracy (R2 &gt; 75%) by all the models with the maximum accuracy (R2 &gt; 99.41%) obtained by polynomial regression function (PRF) and the least fit was obtained with gamma function (R2 = 79.05%). However, quadratic-cum-log model (R2 = 99.28%) was almost equal to polynomial regression function and was better than CLDM (R2 = 89.50%). The average root mean square error (RMSE) was found to be minimum with PRF (0.0061 kg) followed by QCLM (0.0620). Thus the best fit model was polynomial regression function for prediction of both weekly and monthly test day milk yield of first lactation in Karan Fries cows.

Phenological shifts in plant species are one of the most conspicuous signs of climate change impact on the biosphere. Modeling phenological variations of plant species over broad regions is challenging because of the varied climatic requirements of geographic populations due to local adaptation. In this study, we developed an empirical method to calibrate phenological models of temperate trees using latitude as a predictor to account for local adaptation of populations to a N-S temperature gradient. Fourteen widely distributed tree species in the eastern U.S.A. were investigated using data from the USA-National Phenology Network. We implemented the method in a basic thermal time bud break model to introduce the algorithm of the method and test its effectiveness. For each species, dates of breaking leaf buds were first predicted using a traditional non-spatial model and then with a spatial model that has the critical thermal forcing requirements calibrated for different populations at varied latitudes. As anticipated, non-spatial model predictions that assumed a uniform forcing requirement across latitudes showed consistent and systematic biases at both higher (overestimation-predictions being later) and lower (underestimation-predictions being earlier) latitudes. Spatial models that have been calibrated using our method removed the geographic biases and yielded latitudinal gradients that more closely matched those of the observations. The spatial models also reduced the overall prediction errors from an average root mean square error (RMSE) of 32.2 days to 20.4 days for the training dataset and an average root mean square error for prediction (RMSEP) of 32.2 days to 19.9 days for the testing dataset. This paper is focused on introducing the new calibration method as a preparatory step toward developing operational models that may potentially predict large-scale and range-wide phenological responses of various plant species to climatic changes with improved local accuracy.