Accuracy improvement of multi-view 3D laser scanning measurements based on point cloud error correction and global calibration optimization.

Multi-camera laser scanning measurement is emerging as a pivotal element in three-dimensional (3D) optical measurements. It reduces occlusion and enables the gathering of more 3D data. However, it also increases the difficulty of system algorithms in obtaining high measurement accuracy. To improve the measurement accuracy, there is an urgent need to address global calibration and error correction issues caused by the employment of multi-view systems. An accuracy improvement method for multi-view 3D laser scanning measurements based on point cloud error correction and global calibration optimization is then proposed. First, a planar asymmetric circular grid target is designed to calibrate the cameras, laser planes, and initial global transformation matrices of the multi-view 3D laser scanning probe simultaneously. The influence of the position of the laser plane on the measurement error is analyzed and what we believe to be novel mathematical error influencing factors are then modelled for point accuracy. Furthermore, a believed to be novel error model based on the backpropagation (BP) neural network is established for the regression analysis of the mathematical error influencing factors and measurement deviations for each point based on the standard sphere plate measurement. The final measurement is optimized by the correction of point cloud for each camera of the multi-view system and the global calibration optimization based on the error model. The proposed method is reliable and easy to implement, since it only requires a standard sphere plate and a planar target. Several experiments show that the method can effectively improve the measurement accuracy of multi-view 3D laser scanning probe through point cloud error correction and calibration optimization.

Efficient 3D scanning measurement system based on asymmetric trinocular vision and a multi-line laser.

The laser scanning measurement system has a pivotal role in precision measurement thanks to the non-contacting and low-cost advantages, but traditional methods and systems are inadequate in terms of accuracy, efficiency, and adaptability. In this study, an efficient 3D scanning measurement system based on asymmetric trinocular vision and a multi-line laser is developed to improve the measurement performance. The system design, working principle, and 3D reconstruction method are explored, as well as the innovation of the developed system. Furthermore, an efficient multi-line laser fringes indexing method is presented based on K-means ++ clustering and hierarchical processing to improve processing speed with guaranteed accuracy, which is the key point of the 3D reconstruction method. Various experiments are conducted to verify the capability of the developed system, and the results show that the developed system fulfills measurement needs in adaptability, accuracy, effectiveness, and robustness. The developed system achieves better results than commercial probes for complex measurement conditions, and measurement precision can be achieved to within 18 µm.

Absolute distance measurement to coaxial multi-targets based on optical balanced cross-correlation using a single femtosecond laser.

We describe a high-precision ranging method based on an optical balanced cross-correlation system with a scanning repetition rate using a single femtosecond laser. By scanning the repetition rate of a laser, measuring pulses can be overlapped with reference pulses. It is an effective method to make reference pulses overlap with coaxial multiple target pulses without additional mechanical devices. The overlapped pulses are launched to the optical balanced cross-correlation system, which improves the time resolution measurement to the attosecond level. Two nominal distances are measured, and an additional commercial laser interferometer is used as a comparison to evaluate the accuracy of our measurement system. Moreover, the thickness of three stacked glasses is measured by our measurement system to verify that this system can measure coaxial multiple targets more quickly than conventional optical balanced cross-correlation systems using a single optical frequency comb.

Research Progress on Hypoglycemic Mechanisms of Resistant Starch: A Review.

In recent years, the prevalence of diabetes is on the rise, globally. Resistant starch (RS) has been known as a kind of promising dietary fiber for the prevention or treatment of diabetes. Therefore, it has become a hot topic to explore the hypoglycemic mechanisms of RS. In this review, the mechanisms have been summarized, according to the relevant studies in the recent 15 years. In general, the blood glucose could be regulated by RS by regulating the intestinal microbiota disorder, resisting digestion, reducing inflammation, regulating the hypoglycemic related enzymes and some other mechanisms. Although the exact mechanisms of the beneficial effects of RS have not been fully verified, it is indicated that RS can be used as a daily dietary intervention to reduce the risk of diabetes in different ways. In addition, further research on hypoglycemic mechanisms of RS impacted by the RS categories, the different experimental animals and various dietary habits of human subjects, have also been discussed in this review.

Robust and accurate sub-pixel extraction method of laser stripes in complex circumstances.

Line laser scanning measurement is a major area of interest within the field of 3D laser scanning measurement. Traditionally, sub-pixel extraction of laser stripes is a dominant point for line laser scanning measurement. In particular, the noise separation of laser stripe images and the accuracy of feature extraction of the laser stripe are the main challenges for sub-pixel extraction of laser stripes in complex circumstances. To this end, this study utilizes a robust and accurate method with two steps to extract sub-pixel features of laser stripes for 3D laser scanning measurement. Laser stripe segmentation based on a deep semantic segmentation network is initially implemented for noise elimination of images. Then, the sub-pixel extraction of the gray peak points of laser stripes is accomplished by Shepard sub-pixel interpolation and gray surface fitting, which can adequately utilize the gray distribution of laser stripes and obtain high-precision and anti-interference results. The robustness, effectiveness, and accuracy are verified by comparative experiments with classical methods. The results indicate that the proposed method can obtain much more complete, denser, and smoother results than traditional methods, especially in challenging measurement conditions, such as a large curved surface, a highly reflective surface, or intense ambient light. The accuracy of the proposed method can meet the requirements of high-precision measurement.

Absolute Positioning Accuracy Improvement in an Industrial Robot.

The absolute positioning accuracy of a robot is an important specification that determines its performance, but it is affected by several error sources. Typical calibration methods only consider kinematic errors and neglect complex non-kinematic errors, thus limiting the absolute positioning accuracy. To further improve the absolute positioning accuracy, we propose an artificial neural network optimized by the differential evolution algorithm. Specifically, the structure and parameters of the network are iteratively updated by differential evolution to improve both accuracy and efficiency. Then, the absolute positioning deviation caused by kinematic and non-kinematic errors is compensated using the trained network. To verify the performance of the proposed network, the simulations and experiments are conducted using a six-degree-of-freedom robot and a laser tracker. The robot average positioning accuracy improved from 0.8497 mm before calibration to 0.0490 mm. The results demonstrate the substantial improvement in the absolute positioning accuracy achieved by the proposed network on an industrial robot.

Compensation of Rotary Encoders Using Fourier Expansion-Back Propagation Neural Network Optimized by Genetic Algorithm.

The measurement accuracy of the precision instruments that contain rotation joints is influenced significantly by the rotary encoders that are installed in the rotation joints. Apart from the imperfect manufacturing and installation of the rotary encoder, the variations of ambient temperature could cause the angle measurement error of the rotary encoder. According to the characteristics of the 2π periodicity of the angle measurement at the stationary temperature and the complexity of the effects of ambient temperature changes, the method based on the Fourier expansion-back propagation (BP) neural network optimized by genetic algorithm (FE-GABPNN) is proposed to improve the angle measurement accuracy of the rotary encoder. The proposed method, which innovatively integrates the characteristics of Fourier expansion, the BP neural network and genetic algorithm, has good fitting performance. The rotary encoder that is installed in the rotation joint of the articulated coordinate measuring machine (ACMM) is calibrated by using an autocollimator and a regular optical polygon at ambient temperature ranging from 10 to 40 °C. The contrastive analysis is carried out. The experimental results show that the angle measurement errors decrease remarkably, from 110.2″ to 2.7″ after compensation. The mean root mean square error (RMSE) of the residual errors is 0.85″.

Risk factors of mental disorders among empty and non-empty nesters in Shanxi, China: a cross-sectional study.

BACKGROUND: China has the world's largest size of elderly population. Mental disorders of the elders deserve keen attention. This study aims to comparatively explore mental disorders and risk factors among empty and non-empty nesters. METHODS: Using the stratified random cluster sampling method, we recruited 8526 elders aged 60 years and above from 11 cities in Shanxi Province in central China, comprising 4901 empty and 3625 non-empty nesters. The mental disorders were assessed with the 12-item Chinese Health Questionnaire (CHQ-12). The binary logistic regression was performed to analyze the risk factors in the two groups. RESULTS: The prevalence of mental disorders in empty nesters was significantly higher than that in non-empty ones (26.9% vs 23.5%). Binary logistic regression showed that the empty nesters who lived alone or lived in an institution were more likely to suffer from mental disorders compared with the non-empty ones, empty nesters living with spouse showed no significant deviation. And single status, hardly or part self-care ability, having chronic diseases, having lower income, and paying less attention to daily healthy diet had positive associations with mental disorders for empty nesters, and no or partial self-care ability and having chronic diseases for non-empty nesters. CONCLUSIONS: The study indicated that empty nesters had a higher prevalence of mental disorders than non-empty ones. Empty nesters living alone, with no or partial self-care ability, chronic disease, lower income and less attention to daily healthy diet were more vulnerable to mental disorders. And the lack of self-care ability and having chronic diseases were risk factors of mental disorders for non-empty nesters.

Are overweight people more susceptible to anxiety?

OBJECTIVES: This study aimed to investigate anxiety status and its relationship with body mass index (BMI) among empty nesters in China, so as to improve their quality of life and provide direction for further research. METHODS: A cross-sectional survey was conducted among 4901 empty nesters in Shanxi, China. Anxiety, weight, height, depression, socio-demographic variables, attention to daily nutritional health, social activities, and self-care ability were evaluated in the study. T-tests and chi-square tests were used to compare differences in categorical and continuous variables. Binary logistic regression was performed to explore the association between anxiety and BMI among male and female empty nesters. RESULTS: The results showed that 44.5% of empty nesters reported anxiety, of which, 43.2% were male participants and 45.9% were female participants. After adjusting for other variables, overweight empty nesters odds ratio (OR; 95% confidence interval [CI]) = 0.813 (0.692-0.954) were less likely to be anxious, compared with their normal-weight counterparts. Gender was a significant factor in the relationship, with the negative association between overweight and anxiety only found in female empty nesters OR (95%CI) = 0.718 (0.572-0.901). Income, education, complete self-care ability, and depression showed significant associations with anxiety. CONCLUSION: The prevalence of anxiety was high in the study population. Gender is a significant factor in the relationship between anxiety and BMI among empty nesters. The results intend to inform the government and media that overweight is a protective factor for anxiety among female empty nesters, necessitating a move toward eliminating weight bias.

Improvement of social support in empty-nest elderly: results from an intervention study based on the Self-Mutual-Group model.

BACKGROUND: China has the world's largest elderly population and an increasing number of empty-nest elderly. The purpose of this study is to evaluate the effectiveness of the Self-Mutual-Group model on social support of the empty-nest elderly, thus providing reference for improving their quality of life. METHODS: A intervention study was conducted between October 2016 and May 2017 at six communities in Taiyuan, Shanxi Province, China. A total of 350 empty-nest elderly aged 60-88 years were randomly assigned in the intervention group (n = 167) with a 7-month SMG-based intervention or to a control group (n = 183) with no intervention. The social support of the participating elderly (n = 350) was assessed by the Social Support Rating Scale (SSRS) at the baseline and 7 months later, respectively. RESULTS: A 7-month follow-up showed an increasing mean scores of SSRS, objective support, subjective support and support utilization of the intervention group, and reached statistical significance (P < 0.05). CONCLUSIONS: The Self-Mutual-Group model was considered to be a positive intervention and was effective in increasing social support among the empty-nest elderly. Furthermore, future research should extend the intervention period and introduce multi-point measurement to better evaluate the intervention process and outcomes. TRIAL REGISTRATION: Study on the 'SMG' Health Management Model Based on Community Organization Theory among empty-nest elderly (ChiCTR1800015884).

A Compact Impact Rotary Motor Based on a Piezoelectric Tube Actuator with Helical Interdigitated Electrodes.

This paper presents a novel impact rotary motor based on a piezoelectric tube actuator with helical interdigitated electrodes which has a compact structure and high resolution. The assembled prototype motor has a maximum diameter of 15 mm and a length of 65 mm and works under a saw-shaped driving voltage. The LuGre friction model is adopted to analyze the rotary motion process of the motor in the dynamic simulations. From the experimental tests, the first torsional resonant frequency of the piezoelectric tube is 59.289 kHz with a free boundary condition. A series of experiments about the stepping characteristics of different driving voltages, duty cycles, and working frequencies are carried out by a laser Doppler vibrometer based on a fabricated prototype motor. The experimental results show that the prototype rotary motor can produce a maximum torsional angle of about 0.03° using a driving voltage of 480 Vp-p (peak-to-peak driving voltage) with a duty ratio of 0% under a small friction force of about 0.1 N. The motor can produce a maximum average angle of about 2.55 rad/s and a stall torque of 0.4 mN∙m at 8 kHz using a driving voltage of 640 Vp-p with a duty ratio of 0% under a large friction force of about 3.6 N. The prototype can be driven in forward and backward motion and is working in stick-slip mode at low frequencies and slip-slip mode at high frequencies.

[Research on the stage characteristics of Shanxi college students' dietary behavior improvement based on the Health Action Process Approach model].

OBJECTIVE: To analyze the stage characteristics in the dietary behavior improvement of college students and explore the role of social cognitive variables in the dietary behavior change based on the Health Action Process Approach. METHODS: Selfmade college students' eating behavior scales, college students' dietary rating scales and social cognitive scales were used to investigate their eating behavior, dietary stages, and eating intentions. A cluster random sampling was employed to select 2100 college students in 8 colleges and universities in Shanxi Province from April to November 2015, a total of 1933 valid questionnaires were retrieved. The respondents were grade one to four undergraduates, of whom 613 were boys and 1320 were girls. RESULTS: Cross-sectional survey result showed that the dietary behavior of college students in Shanxi Province was 118. 17 ± 15. 27. In the social cognitive variables, positive expectancy( t =-3. 98, P <0. 001) and behavioral intentions( t =-4. 03, P < 0. 001) had significant difference in gender, where girls were higher than boys. Self-efficacy, risk perception, outcome expectancy, action planning and dietary behavior all showed significant difference among preintenders, intenders and actors( P < 0. 01). CONCLUSION: The action stage of dietary behavior improvement had the most students and there were different social cognitive variables at different dietary behavior stages. Researchers should implement targed health management for students at different dietary behavior stages to make their dietary behavior more reasonablely and scientifically.

Sub-pixel projector calibration method for fringe projection profilometry.

Digital projectors are used as standard parts at present in fringe projection profilometry systems to project structured-light patterns onto the object surface to be measured, and the distortion of the projector lens must be calibrated and compensated accurately to satisfy the accuracy requirement of industrial applications. A novel method is proposed to determine the projector pixel coordinates of the marker points of a calibration target accurately in terms of projective transform. With the method, the projector can be calibrated with accuracy of sub-pixel level. The method is applicable for the calibration target with a chessboard pattern or a circle pattern, and the calibration result is independent on the results of camera calibration. Experimental results are shown to demonstrate the effectiveness and validity of the proposed method.

[An intervention study of college student' dietary behavior based on the health action process approach].

OBJECTIVE: To carry out a stage-matched intervention study on dietary behavior based on the Health Action Process Approach( HAPA), in order to verify the effectiveness of the intervention on improving the dietary behavior of college students. METHODS: The study recruited 184 medical university 's students who were admitted between 2013 and 2015 from Shanxi, including 37 males and 147 females to participate the intervention of dietary behavioral based on HAPA from October 2015 to May 2016 by method of random sampling. They were divided into control group( 98) and intervention group( 86). No intervention was conducted on participants in the control group, differentintervention measures were applied to non-intenders, intenders and actors according to their characteristics in intervention group. Epi Data 3. 1 and SPSS 20. 0 were employed to analyze data. RESULTS: After the stage-matched intervention, the proportion of actors in the intervention group increased from 52. 33% to 66. 28%. In the intervention group the scores of participants after intervention were significantly higher than those before intervention, and were also significantly higher after intervention than those from control group in dietary behaviors( P < 0. 001), dietary concepts( P < 0. 001), taste tendency( P < 0. 001, P = 0. 002), eating regular( P < 0. 001) and dietary habits( P = 0. 006, P < 0. 001). In the intervention group, the total scores in dietary behavior at nonintenders( t =-5. 22, P < 0. 001), intenders( t =-13. 69, P < 0. 001) and actors( t =-8. 82, P < 0. 001) after intervention were significantly higher than those before intervention. CONCLUSION: Stage-matched intervention based on the HAPA has a positive effect on improving the dietary behavior of college students.

2D absolute position measurement based on the hybrid encoding method.

This paper introduces a new method of absolute position measurement based on the hybrid encoding principle that can precisely measure the absolute position of a two-dimensional (2D) micro displacement table. The method uses pseudo-random sequences and binary codes to generate the long-distance position encoding sequences. It combines the encoding sequences with checkerboards to form a hybrid encoding to complete the design of the 2D encoding of plane positions. Then a 2D encoding disk is designed as a tool to measure 2D absolute position. Among them, the X and Y positions are designed by the modular approach, respectively, to efficiently detect the accuracy of 2D position values during the measurement. Moreover, the designed 2D encoding disk can quickly realize image correction. In order to verify the feasibility of the designed 2D encoding disk for measuring the 2D absolute position, the corresponding measurement system is built using a 2D encoding disk, a CCD camera, and a telecentric lens. The experimental results demonstrate that the average position deviation of the 2D absolute position measurement system is less than ±1 µm.

Pyrochlore-type cobalt and manganese antimonate electrocatalysts with excellent activity and stability for OER in acidic solution.

Developing robust electrocatalysts for the oxygen evolution reaction (OER) in acidic solutions that exhibit both good activity and stability remains a significant challenge. This study focuses on the pyrochlore-type Co2Sb2O7 (CSO) material, which exhibits high electrocatalytic activity in harsh acidic solutions by exposing more Co2+ atoms on the surface. In 0.5 M H2SO4, CSO requires a low overpotential of 288 mV to achieve a current density of 10 mA cm-2, and its high activity can remain for 40 h at a current density of 1 mA cm-2 in acidic solutions. BET measurement and TOF calculation verify that the high activity results from the large number of exposed active sites on the surface, as well as the high activity of each active site. The high stability in acidic solutions is due to the in situ formation of the acid-stable oxide CoSb2O6 on the surface during the OER test. Based on first-principles calculations, the high OER activity arises from the special CoO8 dodecahedra and the intrinsic formation of oxygen and cobalt vacancy complexes, which decrease the charge-transfer energy and improve interfacial electron transfer from the electrolyte to the CSO surface. Our findings provide a promising direction for developing efficient and stable OER electrocatalysts in acidic solutions.

An optical method based auto-collimation for measuring five degrees of freedom error motions of rotary axis.

The paper presents an optical method based on auto-collimation to simultaneously measure five degrees of freedom error motions of the rotary axis. The proposed method consists of the collimated lasers, beam splitters, focusing lens, quadrant photodiode detectors, a high-precision steel ball, and a special mirror fixed to the rotary axis. The mathematical model is established byoptical ray tracing, and the corresponding optical path is also simulated by OpticStudio. Meanwhile, an adjusting mechanism for X-Y micro-displacement, based on the elastic deformation of the material, is designed to adjust the installation eccentricity error of the high-precision steel ball. The calibration results of the proposed system demonstrate that the displacement errors are ±0.25 µm within the measuring range of ±10 µm, and the tilt angle errors are ±0.6 arcsec within the measuring range of ±25 arcsec. Taking a direct drive (DD) motor as the test object, the radial error motions of the rotary axis range from -3.2 to 4.1 µm, the axial error motions range from -4.9 to 4.7 µm, and the tilt error motions around the X and Y axes range from -2.8 to 1.8 arcsec and -2.6 to 2.0 arcsec, respectively.

Improving the measuring length accuracy of articulated arm coordinate measuring machine using artificial neural network.

A new method for further improving the measuring length accuracy of the articulated arm coordinate measuring machine (AACMM) is proposed. The detailed procedure of the proposed method involves kinematic error calibration with the Levenberg-Marquardt algorithm and then non-kinematic error (such as link deflection, thermal errors, and error motions of the rotation shaft) compensation with a back-propagation neural network optimized by the mind evolutionary algorithm. In order to verify the effectiveness and correctness of the proposed method, the simulation and experiment were carried out on an AACMM. The simulated and experimental results demonstrate that the measuring length accuracy of the AACMM is improved significantly after kinematic error calibration and non-kinematic error compensation, confirming the effectiveness and correctness of the proposed method.

Prevalence and related influencing factors of depressive symptoms among empty-nest elderly in Shanxi, China.

BACKGROUND: In China, aging has become a serious social problem, and the number of empty-nest elderly is on the rise. The aim of this study is to clarify the prevalence of depressive symptoms among empty-nest elderly in Shanxi province and evaluate the effects of sociodemographic factors and health-promoting lifestyles so as to provide a scientific reference for preventing and intervening their depression. METHODS: A cross-sectional study, which used a multi-stage random cluster sampling way, was conducted among 4901 empty-nest elderly in Shanxi. An independent t-test and a chi square test were used to compare the sociodemographic factors, depression scores, and health-promoting lifestyle scores of the empty-nest elderly. Multinomial logistic regression was used to analyze the potential influencing factors for depression. RESULTS: The prevalence of depressive symptoms in the population was 64.2%. Among all participants 1,776 (36.2%) had mild depression, 1,236 (25.2%) had moderate depression, and 135 (2.8%) had severe depression. The health-promoting lifestyle of the empty nesters in this study was at the medium level (2.51 ±â€¯0.47). Gender, education level, old-age provision model, exercise frequency, chronic disease, relationships with children, self-care ability, and health-promoting lifestyles were found to be influencing factors of depression and all variables had different effects on different degrees of depression. LIMITATIONS: This was a cross-sectional study, so the results cannot establish causal relationships among the study variables. CONCLUSIONS: Depression was prevalent among the empty-nest elderly in Shanxi. Maintaining good interpersonal relationships, developing extensive interests, and maintaining healthy lifestyles including good nutrition habits and regular exercises can reduce the incidence of depression among empty nesters.

A Study on the Applicability of the Health Action Process Approach to the Dietary Behavior of University Students in Shanxi, China.

OBJECTIVE: To confirm the applicability of the Health Action Process Approach in predicting and explaining the healthy dietary behavior of college students. DESIGN: Cross-sectional survey. The data were collected though the self-administrated questionnaires. SETTING: Eight universities in Shanxi province, China. PARTICIPANTS: A total of 1,933 undergraduates were randomly selected using random cluster sampling from Shanxi, China (92.0% response; 31.7% males). MAIN OUTCOME MEASURES: Each variable was measured using questionnaires. ANALYSIS: Data were analyzed by 2-sample t test, linear correlation, and path analysis. Significance was set at P < .05. RESULTS: Risk perception, self-efficacy, and positive expectancy began functioning during the intention formation stage (P < .01). Outcome expectancy, self-efficacy, and behavioral intentions had a predictive role in plan formation (P < .001). Action planning, positive expectancy, and self-efficacy were effective predictors of dietary behavior (P < .001). An action plan was a mediator between behavioral intention and dietary behavior; the mediation effect was 0.086. CONCLUSIONS AND IMPLICATIONS: As a first step, application of Health Action Process Approach to the dietary behavior of Chinese college students was confirmed. Future research expanding on this study could consider including additional sociodemographic factors in the model structure using a broader study population.