Residual Root Mean Square Research Articles

Kalman filter based acoustic positioning of deep seafloor datum point with two-step systematic error estimation

The systematic errors caused by temporal spatial variation of sound speed and sonar signal delays significantly reduce the positioning accuracy of deep seafloor datum points. To overcome this problem, a Kalman filter (KF) based on two-step systematic error estimation is proposed for the acoustic positioning of deep seafloor datum points. The proposed algorithm first calculates the equivalent sound speed by sound ray tracing. A KF based on first-step systematic error estimation is then constructed to calculate the parameters of position and first-step systematic error, and to obtain the slant range residuals. Based on the slant range residuals, the systematic error related to long-period errors of sound speed is parameterized by empirical mode decomposition (EMD) and function fitting. Finally, a KF based on second-step systematic error estimation is used to calculate the parameters of position and second-step systematic error. The proposed algorithm is verified by a real experiment for the acoustic positioning of deep seafloor datum points. The results demonstrate that the proposed algorithm significantly improves the three-dimensional positioning accuracy of deep seafloor datum points compared with the least squares (LS) traditional underwater positioning model, which does not consider the influence of systematic errors, and a KF based on the single systematic error estimation. Using the proposed method, the root mean square (RMS) of the slant range residuals for deep seafloor datum points can be better than 13 cm.

Proton stopping power prediction based on dual-energy CT-generated virtual monoenergetic images.

The purpose of this work was to assess a proof of concept for a novel method for predicting proton stopping power ratios (SPRs) based on a pair of dual-energy CT generated virtual monoenergetic (VM) images. A rapid kV-switching dual-energy CT scanner was used to acquire Gemstone Spectral Imaging (GSI) and 120kV conventional single-energy CT (SECT) image data of the CIRS 062M phantom. The proposed method was applied to every possible pairing of VM images between 40 and 140keV to find the optimal energy pairs for SPR prediction in lung tissue, soft tissue, and bone. The predicted SPRs were compared against SPRs predicted from the SECT data using the conventional SECT-based method. The impact of different scan and reconstruction parameters was also investigated. The SPR residual root mean square errors (RMSE) yielded by the optimal pairs were 7.2% for lung tissue, 0.4% for soft tissue, and 0.8% for bone. While no direct comparison could be made to other DECT-based methods for SPR prediction, as these methods could not be directly implemented on a fast kV-switching system, the SPR RMSEs for soft tissue and bone in Table 4 are comparable to RMSEs reported in the literature. For the conventional SECT-based method, the SPR RMSEs were 5.9% for lung tissue, 0.9% for soft tissue, and 5.1% for bone. The proposed method is a valid alternative to, and has the potential to improve upon, the conventional SECT-based method for predicting SPRs. The formalism used in the method is applied directly, with no approximations made on our part, and requires neither prior knowledge of the spectra nor calibration with a phantom. This work presents a way of optimizing the proposed method for a specific scanner by determining the optimal energy pairs to use as input and demonstrates the method's robustness to different levels of ASiR-V, reconstruction kernels, and dose levels.

Multipath Error Fusion Modeling Methods for Multi-GNSS

The multipath error is considered to be the most limiting factor for high precision positioning applications. The sidereal filtering (SF) method can be used to mitigate the multipath error in the observation domain, and it has been successfully applied in the multipath mitigation in global positioning systems (GPS) and regional BeiDou navigation satellite systems (BDS2). However, there are few reports on the SF method in other systems. The performance of the SF method relies on the explicit orbit repeat periods of satellites in diverse systems or even different types of constellations. It is therefore inconvenient to utilize the SF method for multi-GNSS multipath error mitigation. Alternatively, a space domain multipath error reduction method, which establishes the multi-point hemispherical grid model (MHGM) using the residuals of the double-differenced carrier phase observations in the ambiguity-fixed period, has been modified. It is an integrated model for multi-GNSS, without considering the diversity of different systems and constellations. To compare the performance of MHGM and SF from a multi-GNSS point of view, the determination method of orbit repeat periods via the broadcast ephemerides is summarized, and the SF method is extended to the global BeiDou navigation satellite system (BDS3) and Galileo navigation satellite system. Further test results show that the performance of MHGM and SF are comparable from the perspective of root mean squares (RMS) and the power spectrum analysis of double-differenced residuals, as well as the static positioning results. This implies that the space domain MHGM can obtain similar correction effects as the SF method in the observation domain, but the former is more flexible for modeling with various systems’ data. In addition, the established MHGM using the data of multi orbit periods demonstrates a better performance compared with that of only one orbit period, and an average improvement of 13.1% in the RMS of the double-differenced residuals can be achieved.

Simulation analysis of regional surface mass anomalies inversion based on different types of constraints

Surface mass anomalies estimated by mass concentration (mascon) approach using Gravity Recovery and Climate Experiment (GRACE) observations with regularization constraints generally present higher spatial resolution than the spheric harmonic (SH) solutions. To analyze the influence of different types of constraints on the estimation of mascon solutions, we carried out a closed-loop simulation experiment to estimate surface mass anomalies over South America based on simulated GRACE intersatellite geopotential differences. Tikhonov regularization with spatial constraint (SC), uniform weighting constraint (UWC), and a prior information constraint (APC) were employed to stabilize the mascon solutions, and the corresponding optimal regularization parameters were determined based on the minimum residual root-mean-square (RMS) criterion. The results show that mascon solutions estimated under different types of constraints are consistent and equivalent when the optimal regularization parameters are selected. The spatial distributions and main characteristics of regional surface mass anomalies estimated by the three types of constraints agree well, and the values of residual RMS with different constraints are very close. But due to the smoothing effect of regularization, the signal strength of mascon solutions is a bit weaker than that of original true signal, especially in the regions with strong signals. In addition, due to the ill-conditioned problem is more serious for higher grid resolution, the relative contribution of the three types of constraints to the final mascon solutions would be stronger. The results show that the averages of relative contribution percentages of these constraints for 2°×2° mascon grids are 80% -90%, while the corresponding values for 4°×4° mascon grids are 30% -60%. However, based on the minimum residual RMS criterion, the accuracy of estimation results is not affected by the type of constraints and their relative contribution to the final mascon solutions.

Factor analysis of the cross-cultural adaptation of the Multidimensional Attitudes Scale towards deaf persons in chilean dental students

There are various instruments to measure attitudes toward persons with disabilities (PwD). The Multidimensional Attitudes Scale (MAS) toward PwD is a three-dimension scale with good psychometric properties; the Spanish version has been validated with a four-factor structure. Aim: To examine the factor structure of a cross-cultural adapted version of the Spanish MAS towards deaf persons in a sample of Chilean dental students. Methods: This cross-sectional study involved five Chilean public health experts that reviewed the scale for obtaining a preliminary version of a 30-item modified MAS towards deaf persons; a pilot with 15 dental students was performed, and a final sample composed of 311 students was included. For the exploratory factor analysis (EFA), maximum likelihood estimation (ML) for determining the number of factors and parallel analysis (PA) was used, with Oblimin for the rotation method. Cronbach’s alpha was used to assess reliability. The root mean square error of approximation (RMSEA), comparative fit index (CFI), incremental fit index (IFI), goodness of fit index (GFI), Tucker-Lewis fit index (TLI-NNF) and root mean square of residuals (RMSR) were used to assess model fit. Results: All items had a normal distribution with the exception of items 7 and 10. The four-factor structure without item 10 in this EFA presented an adequate Cronbach’s alpha (>0.83), suggesting acceptable reliability. RMSEA, TLI-NNFI, RMSR, GFI and CFI indices suggested a good fit of the model and were consistent with the literature. Conclusion: The Spanish modified version of the MAS towards deaf persons has a four-factor structure, which in consistent with a previous version of the MAS.

The Structural Equation Model of Ecological Footprint and Inspiration of Public Mind Affecting Student’s Pro-Environmental Behaviour

The research objectives were to verify the structural equation model of Ecological Footprint (EF) and Public Mind Inspiration (PMI) affecting the Pro-environmental Behaviour (PB) of undergraduate students. The samples were 400 undergraduates of Rajabhat Mahasarakham University, collected by The MultiStage sampling technique. The research tool was a five-rating scaled questionnaire. The data was analysed by employing descriptive statistics and the factor analysis with LISREL Mplus. The results revealed that EF and PMI were able to explain the variation of PB with 72.00 percent. EF had the most direct effect on PB with an effect of 0.45, subsequently was PMI with an effect of 0.42. Moreover, EF had an effect on PMI with an effect of 0.31 and was able to predict the variation of PMI with 75.00 percent. The structural equation model of EF affecting PB through PMI verified the proposed model. It fitted with all observed variables in line with the criteria of a ChiSquare/df value less or equal to 1.929 and it was less than or equal to 5.00 ( χ /df 5.00 2  ). RMSEA (Root Mean Square Error Approximation) equalled 0.045 (RMSEA < 0.05) and RMR (Root Mean Square Residual) equalled 0.024 (RMR < 0.05) and included the index level of model congruent value of Goodness of Fit Index (GFI) equal to 0.95, and Adjust Goodness of Fit Index (AGFI) equal to 0.93, which are between 0.90-1.00.

Wavefront correction algorithm based on a complete second-order DM-SHWS model for free-space optical communications.

Free-space optical communication brings large-capacity communication with excellent confidentiality, though fatal obstacles are set by atmospheric turbulence that causes phase shifting in laser links. Therefore, we derived a novel, to the best of our knowledge, iterative wavefront correction algorithm based on a complete second-order deformable mirror (DM) Shack-Hartmann wavefront sensor model as a solution to it. For correcting static wavefront aberration, the proposed algorithm possesses a converging speed faster than the traditional one. In terms of correcting dynamic atmospheric turbulence, it can achieve convergence within two iterations with a residual wavefront root mean square value of less than 1/8 wavelength. The input wavefront under 1.5 wavelength can be corrected on our testbed due to the deformability of the micromachined membrane DM. The research result offers a solution for atmospheric turbulence in the adaptive optics field and may contribute to the development of free-space optical communication.

Estimation of fractional cycle bias for GPS/BDS-2/Galileo based on international GNSS monitoring and assessment system observations using the uncombined PPP model

The Fractional Cycle Bias (FCB) product is crucial for the Ambiguity Resolution (AR) in Precise Point Positioning (PPP). Different from the traditional method using the ionospheric-free ambiguity which is formed by the Wide Lane (WL) and Narrow Lane (NL) combinations, the uncombined PPP model is flexible and effective to generate the FCB products. This study presents the FCB estimation method based on the multi-Global Navigation Satellite System (GNSS) precise satellite orbit and clock corrections from the international GNSS Monitoring and Assessment System (iGMAS) observations using the uncombined PPP model. The dual-frequency raw ambiguities are combined by the integer coefficients (4,− 3) and (1,− 1) to directly estimate the FCBs. The details of FCB estimation are described with the Global Positioning System (GPS), BeiDou-2 Navigation Satellite System (BDS-2) and Galileo Navigation Satellite System (Galileo). For the estimated FCBs, the Root Mean Squares (RMSs) of the posterior residuals are smaller than 0.1 cycles, which indicates a high consistency for the float ambiguities. The stability of the WL FCBs series is better than 0.02 cycles for the three GNSS systems, while the STandard Deviation (STD) of the NL FCBs for BDS-2 is larger than 0.139 cycles. The combined FCBs have better stability than the raw series. With the multi-GNSS FCB products, the PPP AR for GPS/BDS-2/Galileo is demonstrated using the raw observations. For hourly static positioning results, the performance of the PPP AR with the three-system observations is improved by 42.6%, but only 13.1% for kinematic positioning results. The results indicate that precise and reliable positioning can be achieved with the PPP AR of GPS/BDS-2/Galileo, supported by multi-GNSS satellite orbit, clock, and FCB products based on iGMAS.

The Empathic Capacity and the Ability to Regulate It: Construction and Validation of the Empathy Management Scale (EMS).

The aim of this study was to develop a measure to evaluate the management of empathic capacity. To this end, two studies were conducted. Study 1 (N = 277, 172 females) describes the scale creation procedure, factorial validity, and internal consistency. The exploratory factor analysis yielded a five-factor model with 18 items (62.4% of the variance explained). The dimensions were as follows: D1: identification, D2: incorporation, D3: reverberation, D4: separation, and D5: projection. The internal consistency was good (alpha values ranging from 0.70 to 0.80). Study 2 (N = 480, 323 females) examined the validity (including convergent validity) of the model and the relationships with sociodemographic variables. The five-factor model showed a robust goodness of fit, χ2 = 240.5, p < 0.001, root mean square residual (RMSR) = 0.05. The fit indices were satisfactory, Non-normed fit index (NNFI) = 0.89, comparative fit index (CFI) = 0.90, mean square error of approximation (RMSEA) = 0.04. The convergent validity analysis showed that, as empathy management increased, so too did the empathy level and emotional intelligence. Some differences by age and sex were found. In conclusion, the Empathy Management Scale is a valid and reliable instrument for analyzing the empathic process that allows vulnerabilities and strengths to be estimated, which could improve professional practice in the healthcare context.

Construct validity of the Quebec Back Pain Disability Scale: a factor analytic and Rasch study.

Studies on structural validity of the Quebec Back Pain Disability Scale (QBPDS) showed uncertain unidimensionality. The aim of this study was to investigate dimensionality and internal construct validity of the QBPDS, using advanced psychometric methods. The design of this study is a secondary analysis of data from a cross-sectional observational study. The setting was an outpatient rehabilitation hospital. Analyzed subjects consisted of 201 patients with chronic low back pain (40% men; mean age 48±12 years). Confirmatory (CFA) and then Exploratory Factor Analysis (EFA), and Rasch analysis were used. CFA could not provide a satisfactory one-factor solution. Thus, according to a preliminary parallel analysis, two factor structures were examined: 1) a single-factor solution, that showed good model fit according to Goodness of Fit Index and Comparative Fit Index, acceptable fit according to Root Mean Square Error of Approximation, and poor fit according to Standardized Root Mean Square of Residuals; and 2) a bi-factor solution, both showing a good fit in all 4 indices. The Explained Common Variance Index was 0.87. Thus, it was considered appropriate to apply Rasch analysis to our QBPDS data. Four items underfit the Rasch model and showed (two by two) local dependency. Removing these 4 misfitting items resulted in an acceptable fit to the Rasch model of the 16 remaining items. All results pointed towards an essential unidimensionality of the QBPDS. Thus, we suggest to provisionally use the full QBPDS and its global score, pending further research on scale's construct validity. If the suboptimal performance of 4 items would be confirmed, the deletion of some of them could improve the metric quality of the scale. This study fills an evidence gap on important measurement properties of the QBPDS (namely, dimensionality and internal construct validity), thus representing a useful step towards the definition of the more suitable outcome measures for research and clinical practice in nonspecific chronic LBP.

An Improved Stress-Scale Specifically Designed to Measure Stress of Women with Newly Diagnosed Breast Cancer.

Most breast cancer patients are middle-aged women actively involved in establishing a family, developing a career, or raising children. With the exception of the Newly Diagnosed Breast Cancer Stress Scale (NDBCSS), few stress scales have been designed for women with breast cancer. This study checked the dimensionality of the NDBCSS by confirmatory factor analysis (CFA) and the results showed a poor fit, indicating an urgent need for improvement. Exploratory factor analysis (EFA) using the varimax rotation method was performed to improve the model, the revised NDBCSS (NDBCSS-R), which showed a good Kaiser-Meyer-Olkin value, Bartlett’s test of sphericity, and internal consistency reliability. The NDBCSS-R showed improved indices compared with NDBCSS, including: chi-square fit statistics/degree of freedom (CMIN/DF), goodness-of-fit index (GFI), adjusted goodness of fit index (AGFI), normed fix index (NFI), relative fit index (RFI), incremental fix index (IFI), Tucker–Lewis index (TLI), comparative fix index (CFI), root mean square error of approximation (RMSEA), root mean square residual (RMR), parsimonious goodness-fit-index (PGFI), and parsimonious normed fit index (PNFI). In conclusion, the improved NDBCSS-R can provide health professionals with an early understanding of the stress levels of women with breast cancer so that they can provide immediate medical intervention to prevent vicious cycles in a timely manner.

The Psychometric Properties of General Adherence Scale in Chinese (GAS-C) in Patients with Type 2 Diabetes Using Insulin.

PurposeTranslate General Adherence Scale (GAS) into Chinese and test its psychometric properties in middle-aged and elderly type 2 diabetes (T2D) patients using insulin in the Han people of urban China.Subjects and MethodsWe translated the GAS into Chinese and established General Adherence Scale in Chinese (GAS-C). 136 T2D subjects were selected for testing GAS-C’s reliability and validity, of which 100 study subjects were retested with GAS-C two weeks later. The other 200 T2D subjects were selected for performing Confirmatory Factor Analysis(CFA). The ceiling effect and floor effect of GAS-C data were checked.ResultsNo data was lost in our research. In exploratory factor analysis(EFA), the Kaiser-Meyer-Olkin measure of sampling adequacy (KMO) =0.899, Bartlett’s Test’s χ2=611.821 (df=10 p<0.001). The communalities of the items were between 0.740 and 0.862; The values of Measure of Sampling Adequacy (MSA) were between 0.883 and 0.945. All five items entered the factor analysis process. A common factor was extracted, and it could explain 81.403% of the total variance. CFA validated the.one-factor model was good fits with the data of GAS-C (Ratio of Chi-square to Degrees of Freedom (CMIN/DF)=2.032, Goodness of Fit Index (GFI) =0.981, Comparative Fit Index (CFI) =0.996, Tucker–Lewis Index (TLI) =0.992, Root Mean Square Residual (RMR) =0.011, Root Mean Square Error of Approximation (RMSEA) =0.072). Correlation analysis was performed between GAS-C and MMAS-8 to calculate the criterion-related validity (r=0.542 p<0.001). The internal consistency reliability α=0.942, Intraclass Correlation Coefficient (ICC)= 0.941 (95% CI 0.924–0.955). The correlation coefficient r of the test-retest reliability was 0.772 (p<0.001). Spearman-Brown coefficient of split-half was 0.939. There was no floor effect and ceiling effect on the data.ConclusionGAS-C has good reliability and validity. It can be used for general adherence studies of middle-aged and elderly type 2 diabetic patients using insulin in the Han people of Chinese cities.

Correlation of Supervision Process and the Performance of the Graduate Program in Faculty of Education Mahachulalongkornrajavidyalaya University

The objectives of this research were 1) to study the supervision process and the performance of the graduate program, 2) to study the correlation of the supervisory components and the performance of the graduate program, 3) to assess the supervision process related to the performance of the graduate program in Faculty of Education Mahachulalongkornrajavidyalaya University with empirical data. Mixed methods research was designed. Research sample consisted of 500 samples, and research tools were interview form and questionnaires. Data were analyzed by using descriptive statistics, Pearson correlation analysis, and analyzed factors of the supervision and the performance by computer software packages. Research results indicated that 1) appropriate supervision process and the performance of graduate programs were classified into five main processes, 64 sub-processes. 2) All supervisory and performance components were significantly correlated at the .001 level, with a correlation coefficient range from .054 to .620, which able to be analyzed for the process. 3) The validation of the supervision process related to the performance of the graduate program in Faculty of Education Mahachulalongkornrajavidyalaya University found that it was fit with empirical data, and analysis results were x2 = 103.82, df = 84, p = 0.07, Goodness of Fit Index (GFI) was .98, Adjusted Goodness of Fit Index (AGFI) was 0.94, Root Mean Square Residual (RMR) was .14 and Root Mean Square Error of Approximation (RMSEA) was .02, indicating that the model was consistent with the empirical data. Therefore, the supervision process correlated to the performance of the graduate program

Improved fixed bed models for correlating asymmetric adsorption breakthrough curves

Breakthrough curves of water contaminants are usually analyzed using simple fixed bed models such as the Bohart-Adams, Thomas, and Yoon-Nelson equations, which are by design symmetric. Because breakthrough data often follow an asymmetric pattern, the use of models that do not account for asymmetry could lead to poor fits, consequently resulting in erroneous estimates of breakthrough and exhaustion times. To address this issue, the Bohart-Adams, Thomas, and Yoon-Nelson models were modified by a logarithmic transformation to enhance their data fitting ability. The three modified models were found capable of providing robust fits to seven separate sets of previously reported asymmetric breakthrough data of water contaminants (fluoride, methylene blue, salicylic acid, lead, mercury, nickel, and arsenic), with reported residual root mean square error (RRMSE) values ranging from 0.019 to 0.046. In consequence, the new models were found capable of providing reliable estimates of breakthrough and exhaustion times corresponding to any predetermined concentration level. By contrast, the three original models were found to perform poorly, reporting inferior RRMSE values ranging from 0.038 to 0.086 for data fits and providing grossly inaccurate estimates of breakthrough and exhaustion times. The new models contain only parameters that appear in the original models, and are highly flexible, being able to assume virtually all monotonically increasing sigmoid shapes. They represent a far more accurate alternative to the original models.

Improving Detectability of Seafloor Deformation From Bottom Pressure Observations Using Numerical Ocean Models

We investigated ocean bottom pressure (OBP) observation data at six plate subduction zones around the Pacific Ocean. The six regions included the Hikurangi Trough, the Nankai Trough, the Japan Trench, the Aleutian Trench, the Cascadia Subduction Zone, and the Chile Trench. For the sake of improving the detectability of seafloor deformation using OBP observations, we used numerical ocean models to represent realistic oceanic variations, and subtracted them from the observed OBP data. The numerical ocean models included four ocean general circulation models (OGCMs) of HYCOM, GLORYS, ECCO2, and JCOPE2M, and a single-layer ocean model (SOM). The OGCMs are mainly driven by the wind forcing. The SOM is driven by wind and/or atmospheric pressure loading. The modeled OBP was subtracted from the observed OBP data, and root-mean-square (RMS) amplitudes of the residual OBP variations at a period of 3–90 days were evaluated by the respective regions and by the respective numerical ocean models. The OGCMs and SOM driven by wind alone (SOMw) contributed to 5–27% RMS reduction in the residual OBP. When SOM driven by atmospheric pressure alone (SOMp) was added to the modeled OBP, residual RMS amplitudes were additionally reduced by 2–15%. This indicates that the atmospheric pressure is necessary to explain substantial amounts of observed OBP variations at the period. The residual RMS amplitudes were 1.0–1.7 hPa when SOMp was added. The RMS reduction was relatively effective as 16–42% at the Hikurangi Trough, the Nankai Trough, and the Japan Trench. The residual RMS amplitudes were relatively small as 1.0–1.1 hPa at the Nankai Trough and the Chile Trench. These results were discussed with previous studies that had identified slow slips using OBP observations. We discussed on further accurate OBP modeling, and on improving detectability of seafloor deformation using OBP observation arrays.

A measure development study of sugar-sweetened beverage-related knowledge, self-efficacy, and intention among urban, low-income adults

BackgroundSugar-sweetened beverage (SSB) consumption is an important behavior that can influence individuals’ risk for diabetes, obesity, and other chronic diseases. Nonetheless, there is a lack of valid measures to assess SSB-related constructs. Reliable and valid measures can help evaluate the efficacy of interventions designed to curb SSB consumption. Our aim was to develop a valid and reliable instrument to measure constructs related to SSB consumption in English and Spanish.MethodsA cross-sectional survey was conducted among a convenience sample of 150 adult residents of public housing developments in Boston, Massachusetts between July of 2016 and January of 2017. All households from two public housing developments were approached by study staff to solicit participation via door-to-door knocking and posted flyers. We developed questions to measure three SSB-related constructs informed by the Social Cognitive Theory: SSB knowledge, and self-efficacy and intention to act on SSB consumption. The questions were pilot tested in the population, and then administered in-person by bilingual study staff in either English or Spanish. Interviews were conducted most often in the participant’s home and less frequently within a community space. Item normality was assessed with descriptive statistics. Difficulty of knowledge items was assessed with percent correct. Construct validity of self-efficacy items was assessed using confirmatory factor analysis (CFA). A model was considered a good fit if confirmatory factor index (CFI) > 0.95, root mean square error of approximation (RMSEA) < 0.05, and standardized root mean square residual (RMSR) < 0.05. Pearson correlations with consumption scores assessed criterion validity, and intraclass correlation coefficients (ICC) assessed test-retest reliability.ResultsOf the eight knowledge items tested, only four items resulted in correct answers less than half of the time. CFA resulted in a 5-item scale with excellent fit indices (CFI = .99; RMSEA = .025: SRMR = .02) and Cronbach’s (0.79), test-retest (ICC = 0.68), and significant correlation with intention and SSB consumption. Of the four intention items, one was significantly correlated with SSB consumption.ConclusionsThis study provides evidence for the validity of key constructs related to SSB consumption for use in adults, which could provide important theory-based markers for program evaluations of SSB-related interventions.

A Method for Rapid Measurement of the Deformation and Spatial Attitude of Large Radar Antennas Inside Radomes

It is challenging to measure, analyze, and control the deformation and space attitude of antennas in narrow radomes through geometric measurement to ensure the accuracy of phased array radar application. In this manuscript, a method for rapid measurement of antennas by adopting the combination of photogrammetry system, laser tracker and total station was proposed. The photogrammetric method was used with a homemade auxiliary tool to measure and calculate the antenna’s deformation under different temperatures and pitch angles. Mapping relations between the instrumental coordinate systems of photogrammetry system, laser tracker and total station were established through common points, including target balls and reflectors. Coordinates of mark points on antenna surface were converted from photogrammetric coordinate system to laser tracker’s and total station’s coordinate system. Thus, antenna’s pitch angles relative to the local horizontal plane and deflection angles relative to the north of the engineering coordinate system were calculated. Planar fitting, coordinate transformation and space attitude calculation were all carried out in the Spatial Analyzer (SA) software. The photogrammetric method detected the antenna’s gravitational deformation sensitively, the maximum Root Mean Square Residual (RMSR) of the reference length was $54~\mu \text{m}$ , and that of the mark points was $59~\mu \text{m}$ , which was stably in line with its nominal accuracy. Deviations caused by coordinate transformation had no significant effect on the calculation of antenna’s spatial attitude, for the maximum deviation between the converted and measured coordinates in laser tracker’s coordinate system was 0.139 mm, and that in total station’s coordinate system was 1.037 mm, both of which were within reasonable limits of the derived theoretical maximum deviations between different instruments. As a result, the maximum deviation between the calculated value and servo system’s nominal value of antenna’s pitch angle was $59.4''$ , and that of antenna’s deflection angle was $91.87''$ . This method’s efficiency was greatly improved by about ten times compared with traditional methods through statistics and estimates.

Development and psychometric assessment of the public health emergency risk perception scale: Under the outbreak of COVID-19

ObjectiveCorrectly understanding and evaluating the level of public risk perception toward public health emergencies not only helps experts and decision-makers understand the public’s preventative health behaviors to these emergencies but also enhances their risk information communication with the public. The aim of this study was to develop a risk perception scale for public health emergencies and test its validity and reliability during the coronavirus disease 2019 (COVID-19) pandemic. MethodsGuided by the theoretical model of risk perception, an initial scale was generated through literature review, group meetings, resident interviews, and expert consultation. A pretest and item screening were then conducted to develop a formal risk perception scale for public health emergencies. Finally, the reliability and validity of the scale were validated through a questionnaire survey of 504 Chinese adults. ResultsThe final scale had 9 items. The content validity index of the scale was 0.968, and the content validity index of individual items ranged from 0.83 to 1.00. Three common factors, dread risk perception, severe risk perception, and unknown risk perception, were extracted for exploratory factor analysis, and together they explained 66.26% of the variance in the score. Confirmatory factor analysis showed that the model had a satisfactory fit, where χ2/df = 1.384, the goodness-of-fit index (GFI) = 0.989, root mean square error of approximation (RMSEA) = 0.028, root mean square residual (RMR) = 0.018, comparative fit index (CFI) = 0.995, normed fit index (NFI) = 0.982, and non-normed fit index (NNFI) = 0.990. The correlations between dimensions ranged from 0.306 to 0.483 (P < 0.01). Cronbach’s α was 0.793 for the total scale and ranged between 0.687 and 0.801 for the individual dimensions. The split-half coefficient was 0.861 for the total scale and ranged from 0.727 to 0.856 for induvial dimensions. The test-retest coefficient was 0.846 for the total scale and ranged from 0.843 to 0.868 for induvial dimensions. ConclusionThe developed scale for the risk perception of public health emergencies showed acceptable levels of reliability and validity, suggesting that it is suitable for evaluating residents’ risk perception of public health emergencies.

Clustering Code Biases between BDS-2 and BDS-3 Satellites and Effects on Joint Solution

China’s BeiDou navigation satellite system (BDS) has finished global constellation construction and can achieve joint solution, simultaneously relying on the B1I + B3I signals of the BDS-2 and BDS-3 satellites. For reasons mostly related to chip shape distortions, navigation satellite observations are corrupted by receiver-dependent code biases. Those biases are brought into observation residuals and degrade the pseudorange correction accuracy. Herein, we present a code bias estimation algorithm, using what we found to be an obvious clustering code bias phenomenon between the BDS-2 and BDS-3 satellites, leading to the systematic biases existing in the BDS-2+3 joint solution. Therefore, we propose a BDS-2+3 joint solution with code bias self-calibration, which can accurately strip off clustering code biases between the BDS-2 and BDS-3 satellites, and can greatly improve precise point positioning (PPP) convergence speed and accuracy. The statistics showed that the residual biases and root mean square (RMS) improved by 36% and 15% and the convergence time improved by approximately 35%. In the convergence stage, the positioning accuracy improved by approximately 38% and 21% in the horizontal and vertical directions, respectively. Meanwhile, in the post-convergence stage, the accuracy improved by approximately 10%.

Development and External Validity of a Short-Form Version of the INICIARE Scale to Classify Nursing Care Dependency Level in Acute Hospitals.

Background: The increasing dependence care in patients hospitalized in acute hospitals around the world entails classification systems heeding the wide range of care dependency levels generated by the many different types of dependent patients. This article is a report of a study assessing the validity and reliability of a short-from version of the instrument (Inventario del NIvel de Cuidados mediante Indicadores de Resultados de Enfermería (INICIARE)) used to classify inpatients according to their care dependency level. Methods: The validation, carried out in a multicenter longitudinal study, included three different samples: the first sample of 1800 patients to evaluate the reliability and validity, a second of 762 patients for confirmatory factor analysis, and a third of 762 to test the short-form version. Patients over 16 years of age, admitted to medical or surgical units at 11 public hospitals, were included. Results: The final sample included 3605 patients. Patients had a mean age of 64.5 years, 60% were admitted to medical units, with severe dependency. The validation process yielded two versions of the instrument: a 40-item version, with eight factors with 83.6% of total variance explained and Cronbach’s alpha values between 0.98 and 0.92, and a short-form with 26 items, with five factors and Cronbach’s alpha values between 0.96 and 0.90. The Confirmatory Factor Analysis yielded a good fit model to the 40-item version (Chi Square on Degrees of Freedom CMIN/DF) = 1.335; Normed Fit Index (NFI); Tucker–Lewis Index (TLI); Comparative Fit Index (CFI) > 0.90; Standardized Residual Root Mean Square (RMSEA) = 0.02; and Standardized Residual Root Mean Square (SRMR) = 0.027) and 26-item version (Chi Square on Degrees of Freedom CMIN/DF = 1.385; NFI = 0.998; CFI = 0.999; RMSEA = 0.02; and SRMR 0.02). Both INICIARE versions obtained a high correlation between them (r = 0.96; p < 0.001). Conclusion: INICIARE has proved to be a valid and reliable instrument for the assessment of the level of care dependency of acutely hospitalized patients.