High-quality 3D reconstruction results are very important in many application fields. However, current texture generation methods based on point sampling and fusion often produce blur. To solve this problem, we propose a new volumetric fusion strategy which can be embedded in the current online and offline reconstruction framework as a basic module to achieve excellent geometry and texture effects. The improvement comes from two aspects. Firstly, we establish an adaptive weight field to evaluate and adjust the reliability of data from RGB-D images by using a probabilistic and heuristic method. By using this adaptive weight field to guide the voxel fusion process, we can effectively preserve the local texture structure of the mesh, avoid wrong texture problems and suppress the influence of outlier noise on the geometric surface. Secondly, we use a new texture fusion strategy that combines replacement, integration, and fixedness operations to fuse and update voxel texture to reduce blur. Experimental results demonstrate that compared with the classical KinectFusion, our approach can significantly improve the accuracy in geometry and texture clarity, and can achieve equivalent texture reconstruction effects in real-time as the offline reconstruction methods such as intrinsic3d, even better in relief scenes. With the increasing importance of three-dimensional reconstruction technology in the fields of automatic driving, virtual reality, robot positioning, and navigation, the reconstruction of high-quality 3D scenes using low-cost consumer-grade RGB-D sensors has become a hot issue and has been widely studied.The general framework for reconstructing static scenes consists of five parts: input RGB-D data stream, image preprocessing, camera pose estimation, volumetric fusion and update, and surface mesh extraction, as shown in the left image in Generally speaking, classical voxel fusion methods have two shortcomings: (1) the weighted averaging methods are not suitable for texture fusion since they tend to destroy the texture structure and cause color blur. (2) Current data quality evaluation models are mostly concerned with depth information while ignoring the RGB information that however is crucial to the visual appearance.Current research methods on improving the texture quality of the reconstruction results can be divided into two types.The first type is attempts to adopt high-quality data for fusion. View-dependent ,2 or varThe second type is to use a joint optimization method to refine and correct the texture of low-quality reconstruction results that are obtained by using classic reconstruction frameworks such as KinectFusion. For example, a joint optimization method combines texture and geometry with the camera poses and lighting illuminations are designed to generate high clarity texture results . Such a To effectively reduce texture blur and generate a high-quality texture, we design a new volumetric fusion strategy from two aspects: (1) evaluate and select high-quality data for fusion and (2) design a texture fusion method that can preserve texture structure. As shown in the right side of Extensive qualitative and quantitative experiments and comparative analysis show that our method can remarkably improve the accuracy of geometric and texture reconstruction compared with classical weighted average fusion methods, and can achieve no less or even better results than the state-of-art off-line reconstruction methods. As demonstrated in A new texture fusion strategy combining replacement, integration, and fixedness operations is proposed. It can effectively preserve texture structure information to generate accurate texture results with high clarity.An adaptive weight field is established effectively by using the combination of probability and heuristics, which can evaluate and adjust the reliability of RGB-D data. This adaptive weight together with a refined camera pose estimation method are used to guide the voxel fusion process to avoid texture blur, wrong texture, and rough surface.Our method can be easily embedded in the current online and offline reconstruction framework as a basic module, and can effectively improve the accuracy of reconstruction results.Overall, our technical contributes are as follows:The rest of the paper is organized as follows. After reviewing the related works in Weighted averaging volumetric fusion has become a basic component of many online ,7,8,9 anData evaluation model of RGB-D Images has been widely studied to effectively reduce the noise on the RGB-D images acquired from commercial times-of-flight (ToF) sensors such as the Microsoft Kinect v2, Intel RealSense, or Google Tango. The noise of this kind of sensor comes from many factors, such as distances, viewpoint angles, scene materials, ambient lighting, normal vectors of scene surfaces, etc. Different models have been developed to describe the noise distribution ,24,25. FTexture reconstruction based point sampling and fusion are mainly used in real-time RGB-D reconstruction, and its accuracy improvement methods are mainly divided into two categories. The first selects high-reliability data for volumetric fusion , the sec(1)The adaptive weight fields describe the reliability of depth data and RGB data, respectively, to clearly distinguish the high-reliability data from input data by considering the consistency of texture structure features, the risk of wrong texture, and the outlier noise of depth map.(2)In the fusion update part, a new texture fusion strategy combining replacement, integration, and fixedness is proposed to effectively reduce texture blur by considering the characteristics of texture structure.In our pipeline, geometry reconstruction and texture reconstruction are separated, and different update strategies are used to effectively save the texture structure of the reconstructed mesh to reduce the problem of texture blur. Consequently, high clarity texture can be generated, as illustrated in When inputting the real-time frame, camera pose, and the result of previous fusion, our method firstly calculates the adaptive weight field of depth data and RGB data, respectively. Then, we fuse and update the geometry and texture of voxels with the calculated adaptive weight field.The main purpose of building the adaptive weight field is to solve the problem of texture blur, wrong texture, and the influence of depth outlier noise on the geometric surface by evaluating and adjusting the reliability of RGB-D data. By establishing the photometric consistency weight field, we can successfully evaluate the local consistency of texture features between frames in the image domain, to provide highly reliable texture data for texture fusion and maintain the accurate texture structure of the global mesh. The edge error weight field is established to evaluate the high-risk areas where error textures are prone to occur. By adjusting the reliability of these areas, the problem of wrong textures can be effectively avoided. The edge noise weight field describes the characteristics of outlier noise in the edge region of the depth map. By adjusting its reliability in this weight field, the influence of these noises on the geometric surface can be effectively suppressed. By establishing these weight fields, we can provide high-reliability data for the voxel updating process and achieve accurate geometry and texture results.In the voxel update process, we fusing the depth data and RGB data with different strategies. For the depth data fusion, since the weighted averaging method is suitable for geometry fusion, we use a similar method as the classical fusion approach. But we add a truncation term of low-confidence weights (CW) to discard the low-quality data from fusion, thus more precise surface reconstruction results can be obtained. For texture fusion, we propose a new volumetric fusion strategy that combines data operations of replacement, integration, and fixedness to fuse and update voxel textures. Its main idea is to introduce replacement and fixedness operations to retain texture structure information. The principal purpose of preserving integration operation is to make the structural texture edge change as smooth as possible and avoid the seam problem. By judging the variation of the confidence of the adaptive weight field estimation along with frames, we update the texture of voxel accordingly with the above three operations to preserve texture structure and reduce texture blur.As camera pose is crucial to generate high clarity texture, we accurately estimate it with a two-steps optimization. We firstly use frame to a frame iterative closest points (ICP) method to estimate the initial camera pose, and based on this initial pose to establish the adaptive weight field which flags the reliability of RGB-D data; Secondly, we refine the camera pose by adopting the high-reliability texture data for ICP. The refined camera pose is reversely used to improve the quality of reconstructed texture.current frame. ith frames and the current frame. ith frames and the current frame. We follow the classical fusion method to update the geometry with the alteration that the truncation function To effectively preserve the texture structure of the scene and reduce texture blur, we propose a new texture fusion strategy combining replacement, integration, and fixedness operations to obtain a clearer texture.Our core ideas are as follows: when the reliability of the current frame sampling information is much higher than that of the previous fusion results, the previous result will be replaced by the data of the current frame. On the contrary, the fixedness operation is used to retain the high-quality fusion results of the previous frame. When the current frame is similar to the previous result in reliability, the data in the current frame will be integrated into the previous result.As shown in Specifically, in this figure, “A” represents voxels that undergo a complete updating period and their confidence weights of frames change from low to high and then to low again with time, which means it will exist in the whole operation of replacement, integration, and fixedness. “B” represents voxels that undergo the updating process with the only low weight of frames, which means that it only uses the integration operation to keep the texture continuity because of a lack of reliable data. “C” represents voxels that undergo the updating process from high to low weight change after the voxels are initialized, which means it will experience integration and fixedness operations.Since the fusion process of “A” includes “B” and “C”, we take “A” as an example to illustrate our method in detail. For a full updating period of a single voxel, firstly, the texture weight of the voxel is initialized to 0. When the real-time frame’s weight is low, the voxel texture is integrated to keep the continuous, as shown in The pseudocode of our new texture fusion strategy is detailed in Algorithm 1. Where We add the replacement operation mainly considering that the high-weight information in the image domain is very close to the real texture structure, but the texture of the mesh usually contains errors. Instead of using weighted averaging to correct texture errors gradually, it is better to use replacement operation to discard worse date and use more reliable information to obtain higher clarity texture results. At the same time, it can also retain its texture structure. We further introduce fixedness operation to maintain the results of high-weight information fusion, which make it no longer affected by low-weight information containing wrong textures.Algorithm 1 Texture Fusion StrategyInput:Output:ifthen1:  ifthen2:  3:   4:   else5:  6:   7:   end if8:  end if9:  10:ifthen11: ifthen12:  13:   14:   else15:  16:   17:   end if18:  end if19: We still retain the integration operation mainly considering that for the counterparts between the real-time frame and previous frame fusion result with high-reliability, the probability of mismatching is very low, so we fuse high-quality data to approximate the true value. For the counterparts with low-reliability, the information errors between them are very large, if we replace or fix them into the fusion result, it tends to cause local discontinuity, so we keep the integration operation to smooth the results.By controlling the range of high weight in the adaptive weight field, we can minimize the number of voxels whose reconstruction period is complete in the low update weight stage, such as the voxels undergoing the “B” process. So almost all voxels can experience replacement operations to obtain high-quality information, and finally, the blurring problem can be greatly reduced or even ignored.Our adaptive weight field of RGB-D images follows two basic principles. The first is to effectively model some factors affecting geometric and texture results, such as texture structure, wrong texture, and edge outlier noise. The second is to distinguish high-reliability data by increasing the weight difference based on data reliability assessment. Combined with the above two principles, the adaptive weight field is established.To satisfy the first principles, we propose a method combining probability and heuristics to model various factors and evaluate the reliability of the data.To achieve the second principle, we introduce some kernels into the quantization of weight. These kernels will not affect the validity of the reliability estimation results but will increase the distinction between low-reliability data and high-reliability data, thereby reducing the impact of low-reliability data on the subsequent fusion process.We build an adaptive weight field of color image mainly to solve the problem of texture blur and wrong texture. For the former, we evaluate the quality of texture features consistency in the image domain to ensure that the mesh maintains a consistent texture structure. For the latter, we mainly suppress the reliability of error-prone areas to avoid the generation of the wrong texture. Besides, we need to effectively adjust the update range of data, so our color weight field can be represented asThe current real-time reconstruction method usually does not consider how to keep the texture structure characteristics of the mesh, but it’s quite important to avoid texture blur. So we build the photometric consistency weight field to preserve the mesh texture structure in the fusion process. The main method is to ensure that the texture provided to the global model for updating should have high structure consistency and data reliability. The consistency and reliability in the image domain can be obtained by evaluating the texture feature difference between the real-time frame and the previous frame. It should be emphasized that texture features are different from texture colors. The former describes the texture structure of local neighborhood pixels, while the latter only describes the color of a single pixel.If the difference of texture feature between frames in some regions is very small, such texture is assigned with high reliability and consistency weight in texture fusion. On the contrary, if the difference between frames in some regions is large, the related texture data should be excluded in the texture fusion. The poor consistency of texture features may occur on surfaces with large geometric gradients. Based on the above idea, we design a photometric consistency weight field to evaluate the consistency of the local texture feature of the real-time frame.Although many features can be used to describe the local texture structure, such as SIFT, SURF, and ORB, etc, these features are generally sparse and can’t effectively evaluate the dense local texture features through the whole image. Therefore, we propose a new texture feature to describe the local texture structure.i, With the inspiration of the Laplacian coordinate that can well describe the local geometric feature, we introduce the Laplacian texture coordinates to describe the local texture features in the image domain. Our Laplacian texture coordinates are defined by photometric values, which can ensure the invariance of texture rotation and translation, and facilitate the calculation of the weight field. To obtain more accurate texture features, different from directly using Euclidean distance to evaluate the difference between adjacent points in geometry, we consider that the change of color in RGB space is usually anisotropic, so we use Mahalanobis distance to calculate the difference between textures. Our Laplacian texture coordinates can be written asTo evaluate the consistency of texture features, we first calculate the dense texture feature map for the real-time frame and the previous frame respectively. Then we calculate the texture feature difference between them based on the estimated camera pose and projection model and establish the photometric consistency weight field. This weight field can be calculated byTexture errors mainly occur in the edge area of the scene, especially when there is an occlusion structure. As shown in The core idea is to select the edge of the scene, evaluate its influence range, and then set its weight to 0. Through these operations, the edge area can no longer affect the high-quality texture that has been fused previously, thus avoiding the occurrence of the wrong texture. Because the scene information collected by RGB-D is highly redundant, the texture of these regions can be obtained by fusing the high-reliability data from other viewpoints without being affected by the edge.We first extract all edges of the scene according to the angle between the viewpoint and the normal vector of the mesh surface. To determine its influence range, we perform a morphological expansion operation on these edges to obtain boundary areas, which is the high-risk region be shown in According to the definition of Viewpoint-dependent uncertainty is a widely accepted and effective description of noise distribution in the depth map. However, in the color image, we use viewpoint dependence mainly to evaluate the texture quality of the surface and control the range of texture update. These two points can be realized by adjusting the model parameters by establishing the view-dependent weight field.We first calculate the viewpoint dependent uncertainty Then we calculate the color view-dependent weight field byWe use low coefficients to reduce the weight instead of setting it to zero directly, mainly to keep the low-weight data continuous when texture fusion.Here we use this kernel function mainly considering that the texture fusion process is more sensitive to the difference between high-quality data and low-quality data of RGB image, and the greater difference is conducive to better texture reconstruction effect.When the texture data is on a relatively smooth surface and the angle between the normal vector of the surface and the opposite direction of the viewpoint is small, we can think that the texture is better and its reliability is higher. So, based on the above model, we can find that by adjusting parameter For the geometric fusion error, we mainly consider the influence of noise in the foreground edge area of the depth map. Because of these areas usually contain a large number of outliers and large-scale noise caused by environmental illumination, measurement methods, and other factors, they cannot be accurately described by the existing models. More importantly, this noise will destroy the reconstructed surface, reduce the surface quality, and slow down the convergence speed. Therefore, it is necessary to model to suppress the noise influence in the edge area.The current methods usually use bilateral filtering to deal with the noise in the foreground edge region, but this method cannot effectively remove large-scale outliers, which often lead to obvious geometric fusion errors. Therefore, we establish a heuristic and probability edge noise model, which can effectively remove outliers and evaluate the noise distribution in these areas.The core idea is to remove these outliers by heuristic method firstly, and then use the probability method to evaluate the reliability of the information at the edge.We use depth truncation and region growth to obtain the foreground of the target scene in the depth image. Then heuristically, we divide the foreground pixels into three categories: outer point, edge region point, and interior point. Outer points refer to the pixels in an image that are not related to the target scene. Edge region points mainly refer to points extending along the edge of the scene to the interior, and they form a strip area. Their noise distribution can be approximated by a Gaussian probability model. The interior points refer to the points in the interesting region.We calculate the Manhattan distance Considering that our reconstruction results have high-quality texture, we propose a two-step refined camera pose estimation strategy combining our adaptive weight field, fused geometry, and texture information. Firstly, we use a frame to frame ICP to obtain the initial relative pose between the real-time frame and the previous frame. Secondly, we refine the projection matrix Different from the general frame to model ICP methods using 1.0 as the weight of error term and does not consider the texture information, we use the dynamically changing weight The energy function in the form of least square can be effectively solved by a GPU style Gauss–Newton iteration. The refined pose results are stored and used for the updating of the mesh.We use a two-step pose estimation mainly to improve the robustness of frame to model registration because with the increase of time, the relative pose between the real-time frame and global model will increase, and the estimated pose error will be larger, which will lead to easy tracking failure, especially for incomplete surfaces. So we use the frame to frame estimation results to provide a better initial pose and further improve the robustness of frame to model pose estimation process.We have designed three experiments to verify the effectiveness of the new fusion strategy, adaptive weight field, and two-step refined pose estimation, respectively. Firstly, we compared our method with the current mainstream online and offline methods in qualitative and quantitative ways to illustrate the effectiveness of our method. Secondly, we have illustrated the effectiveness of the adaptive weight field in improving texture quality by establishing a real reference experimental platform . FinallyIn the first experiment, we embedded the new volumetric fusion method into the framework of KinectFusion, and compared the public RGB-D dataset  and geneWe set e method  to selecThe public RGB-D dataset we use is shown in This weight calculation method effectively considers the uncertainty of viewpoint angle, distance, and TSDF and is the representative fusion weight calculation of the classical voxel method. However, this weight calculation method mainly aims at depth map, and does not deal with the possible texture blur and wrong texture problems of the color image, and also does not consider the outlier noise at the edge of the depth map. This means that they may only get poor texture results.Experimental comparisons are given in By comparing By comparing the results of geometric reconstruction in To show that our method can effectively suppress the influence of noise, we use the Sokrates model  to generWe use the Square Sum Error (SSE) and Mean Square Error (MSE) of the geometric position and texture color between the reconstruction model and the standard model to evaluate the accuracy of the reconstruction results. The results are shown in As shown in As far as the accuracy of the geometric reconstruction is concerned, as shown in From the texture accuracy comparison, as shown in In the second experiment, we use a robotic mannequin  and custThe custom-made clothing contains many different colored and disc-shaped textures, as shown in We design two kinds of reconstruction frameworks, one of which only uses the new fusion strategy (FS), the other uses the combination of adaptive weight field (AWF) and new fusion strategy (FS). During the experiment, we used the same parameters as the first experiment but set the resolution of the voxel grid to 4 mm. We study the influence of color adaptive weight field on texture reconstruction and depth adaptive weight field on geometry reconstruction. The results are shown in To illustrate the effectiveness of our two-step pose estimation method, we compared the accumulated pose error from the frame to frame ICP method (FF-ICP), the frame to model ICP method (FM-ICP), our two-step pose estimation method without adaptive weight (TSN-ICP) and two-step pose estimation method with adaptive weight (TSW-ICP) using the real scene RGB-D dataset collected based on our experimental platform. The difference between TSN-ICP and TSW-ICP is that the former uses the same weight for each data item, while the latter uses different weights for each data item, and these weights are based on the adaptive weight field.Based on our experimental platform, using the same scene and data acquisition method as the second experiment, we collected an RGB-D dataset containing 479 frames and uniformly sampled and selected 50 frames as keyframes to test the pose accumulative error of different pose estimation methods. We use the off-line global optimization method to get the pose of our dataset to approximate the true value to calculate the pose error, such as the method proposed by Zhou . TherefoBy comparing the changing trend of accumulated pose error in Although the calculated cost of two-step optimization is slightly higher than that of one-step FF-ICP and FM-ICP, the calculated cost proportion of camera pose estimation is relatively small in the whole reconstruction process. Therefore, to significantly improve the accuracy of reconstructed results, this cost is acceptable compared with the offline pose optimization method.Although our new texture fusion method and adaptive weight field can effectively preserve texture structure, avoid the wrong texture, and suppress outlier noise, there are still some problems that limit the application of our method. The lighting illumination factor is not considered in the adaptive weighting field. Therefore, currently, our method cannot robustly deal with scenes with obvious illumination changes. Considering the lighting illumination usually requires physical-based rendering, it requires a large computational cost and makes it hard to run in real-time. In the future, the simplified spherical harmonic illumination model may be used to obtain some degree of illumination evaluation and effect improvement. For a similar reason, our method is mainly applied to reconstruct the scene with Lambert material, which may cause a large error in reconstructing a scene with specular reflective materials. In our method, texture discontinuity may occur when there is a large error in the camera pose evaluation. However, our TSW-ICP method can obtain good enough camera poses without obvious discontinuity.We have proposed an adaptive weight field in image space to effectively evaluate the reliability of RGB-D data to preserve texture structure, avoid wrong texture, and suppress outlier noise. Based on our adaptive weight field, a new texture fusion strategy using the combination of replacement, integration, and fixedness has been designed. Because this method can effectively preserve the local texture structure information of the global mesh, it can achieve an excellent texture clarity compared with the online KinectFusion and offline method based on joint optimization, such as Intrinsic3d. In addition, a two-step pose estimation method considering geometry and texture information is also proposed to refine the estimated pose, which can further improve the quality of reconstruction results and avoid the discontinuity of texture.More importantly, our method can be easily embedded into various online and offline reconstruction frameworks as a basic module, and can significantly improve the reconstruction quality, especially for texture.Further work is required to explore an efficient environmental illumination assessment model, which can robustly solve the impact of illumination on our algorithm and reconstruct a wider range of scenes and may be achieved by introducing a simplified spherical harmonic illumination model. On the other hand, we plan to extend the current method to the reconstruction of non-rigid scenes.


Nicotiana tabacum L.) have long-range correlations at critical temperatures. Further experimental evidence has been found to support the claim that the autonomous growth organization of extreme plant cell expansion is accomplished by self-organizing criticality (SOC), which is an orchestrated instability that occurs in an optimally evolving cell. The temperature-induced synchronous action of the ionic fluxes that are manifested, inter alia, by minimal dynamic entropy enabled the molecularly encoded information about germination and optimal growth temperatures of tobacco pollen tubes to be determined.Detecting the presence of an irregularity/regularity or chaos in the ion flows of an evolving plant cell is an important task that can be unraveled by performing the analyses by different metrics. Here I show that the results of the advanced fluctuation estimation methods that are obtained from the time series that is generated by the extracellular ion fluxes of tobacco pollen tubes ( They are highly polarized tip-growing cells that depend on the cytosolic +-ATPase has been theoretically proposed to supply the energy for pollen tube growth and underlie, throughout the chemical potential of H+ ions, the synchronous growth oscillations [In seed plants, the pollen tube is a cellular extension that serves as a conduit through which the male gametes pass until the egg is fertilized. It consists of a single elongated cell that has a distinctive feature that changes its growth rate periodically e.g., . Pollen d growth . Plasma llations . These pllations  with pH Nicotiana tabacum L.) was examined. It was shown that the scale-free processes that result from the critical phenomena can be an essential property of a living cell. In particular, the canonical value of the spectral exponent  the advanced statistical measures, namely the Hurst exponent, the largest  Lyapunov exponent (LLE) and the Kolmogorov-Sinai dynamic entropy of an experimental time series for the detected external ion fluxes from elongating pollen tubes. I also reconstructed the corresponding phase space according to Takens’ theorem.The Hurst exponent  is used not a function of the state of a system, but a function of its dynamics. It was found that the dynamic entropy of extracellular ionic fluxes of tobacco pollen tubes (net current) as a function of temperature can be calculated by analyzing the time series of the electromotive force  that is generated by the unperturbed ion fluxes. In the case of strong correlations, due to critical fluctuations, the dynamic entropy of the tobacco pollen tubes has a minimum at the characteristic temperatures for germination and optimal growth.Entropy is a crucial state variable in thermodynamics, statistical mechanics, quantum mechanics and information processing  that carnot experimental points) result from the approximate entropy calculation [The results of the calculations are shown in culation . Each onWhile the Hurst exponent  represendynamic phase transition in the system with a change in the control parameter, i.e., temperature. The latter, however, presumably reflects the formation of the onset (like in the two-fluid model: condensate/non-condensate fraction) of the dynamic collective modes [This apparent inconsistency can be resolved by noting that the deterministic component in the signal  comes frve modes ,15.It seems that the obtained results can be framed in the research line that showed that macroscopic coherent states are formed in the processes of quantum condensation at the microscopic level  in noneqβc) in . Howeverro in Tc , there aliving cells) at a critical point in non-equilibrium phase transition. Synchronization  and already mentioned global oscillations may also emerge from the system dynamics. Needless to say, the synchronized ion avalanches (SOC) that are considered in this report may also be related to the microscopic explanation of the oscillating growth characteristics of the pollen tubes of tobacco [e.g., Fig. 6.1 and Fig. 6.3 in A recurrent idea in the investigation of complex systems is that optimal (information) processing is to be found near phase transitions . HoweverThe analysis according to five different indexes confirmed the previously observed criticality of the plant cell ensemble living under optimal temperature conditions and an excellent agreement with our previous findings for the spectral exponent was achieved in the calculated minimum for entropy. The observed long-range correlations, or even coherence, that occur at the optimal growth temperature, which are expressed by the lowest dynamic entropy value, indicate a synchronous (wave) operation without scattering (dispersion) of the ion/electron collective excitations, which presumably paves the way for innovative research in this emerging multidisciplinary field.Methods The measurement system consisted of an external polystyrene thermostat and an internal Al-coated polystyrene measurement chamber containing a semiconductor-solute interface [ELoPvC detector, Nicotiana tabacum L. pollen tubes was placed in a liquid (conductive) germination medium [see


The occlusion of buildings in urban environments leads to the intermittent reception of satellite signals, which limits the utilization of observations. This subsequently results in a decline of the positioning and attitude accuracy of Global Navigation Satellite System (GNSS)/Inertial Navigation System (INS) integrated system (GNSS/INS). This study implements a smooth post-processing strategy based on a tightly coupled differential GNSS/INS. Specifically, this strategy used the INS-estimated position to reinitialize integer ambiguity. The GNSS raw observations were input into the Kalman filter to update the measurement. The Rauch–Tung–Striebel smoothing (RTSS) algorithm was used to process the observations of the entire period. This study analyzed the performance of loosely coupled and tightly coupled systems in an urban environment and the improvement of the RTSS algorithm on the navigation solution from the perspective of fully mining the observations. The experimental results of the simulation data and real data show that, compared with the traditional tightly coupled processing strategy which does not use INS-aided integer ambiguity resolution and RTSS algorithm, the strategy in this study sufficiently utilized INS observations and GNSS observations to effectively improve the accuracy of positioning and attitude and ensure the continuity of navigation results in an obstructed environment. With the development of the geospatial information service industry, the demand for rapid and accurate geospatial information access has increased. As an important means of obtaining spatial position information, Global Navigation Satellite System (GNSS)/Inertial Navigation System (INS) technology has wide application prospects in mobile measurement , autonomIn recent years, domestic and foreign researchers have investigated partial and complete GNSS signal lock of loss. The improved methods mostly increased the accuracy of the integrated system by adding observations; these can be divided according to whether additional sensors are added or not. One method involves maintaining heading and speed updates using observations from external sensors or equipment, such as odometers and laser scanners. In , GNSS, IScholars have also studied how to improve the positioning and attitude accuracies of integrated systems in an urban environment using GNSS/INS integration methods and filtering models without any additional observations. Currently, GNSS/INS integration is primarily divided into three methods: loosely coupled, tightly coupled, and deeply coupled. The deeply coupled method combines GNSS and INS observations and GNSS signal tracking into one filter and uses GNSS to track satellite signals through INS. It is an integration on the hardware level, which is difficult to implement and has not been widely used ,12. The Differential GNSS (DGNSS) based on the carrier phase is a commonly used high-precision positioning method. Under the premise that the integer ambiguity is fixed correctly, the DGNSS/INS can achieve centimeter-level positioning accuracy. In the DGNSS/INS tightly coupled model, the integer ambiguity solution is primarily divided into two methods: a centralized Kalman filter  and a deCurrently, research on the tightly coupled GNSS/INS in an urban environment is focused on improving the filtering model and adding redundant observations. There are few studies regarding making full use of available observations in an environment with frequent losses of satellite signals. Therefore, this study aims to implement a smooth post-processing strategy based on a tightly coupled carrier phase DGNSS/INS. This strategy utilizes a decentralized filter to fix integer ambiguity, thereby avoiding the existing problem of the RTSS algorithm in the tightly coupled GNSS/INS. After the GNSS signal is interrupted, the ambiguity is quickly fixed by the INS in the ambiguity initialization stage. Then, the result is further smoothed by the RTSS. This study first analyzes the positioning and attitude determination performance of the loosely coupled and tightly coupled DGNSS/INS when the number of observable satellites is insufficient through a simulated satellite lock-loss experiment, and verifies the effectiveness of the RTSS in improving the pose accuracy in an occlusion environment. Then, field experiments are used to verify method effectiveness. The results show that the proposed strategy can effectively improve the pose accuracy even during the intermittent reception of satellite signals. It can provide a more reliable and high-precision solution for navigation and positioning tasks in challenging environments.In the tightly coupled DGNSS/INS extended Kalman filter model, Correct IAR is the premise driving high-precision carrier phase positioning. Using decentralized filters, the tightly coupled model is divided into two parts: a tightly coupled filter module and an IAR module, which lowers the dimensionality of the filter matrix and improves fault tolerance. The primary function of the IAR module is to estimate the integer ambiguity parameters. When a new satellite is observed, the position information output by the filter assists with IAR. After the satellite signal interruption ends and the integer ambiguity must be fixed again, the position information calculated by the INS is used to assist the reinitialization of the integer ambiguity. The tightly coupled filter module exhibits the simplest system model because the ambiguity is not extended to the state vector. The state vector, covariance matrix, INS pose, and other sequentially stored information are inputted into the RTSS module to optimally smooth the entire filtering process. The system model is based on the INS error an Earth-centered Earth-fixed (ECEF) frame, the error equation in the ECEF is selected to construct the system model more conveniently. The INS psi-angle error model in the ECEF is given as (1) and (3), the bias error is expanded to the state parameters for estimation. The system equation can be expressed as follows:found in .Equation (4) is a continuous dynamics equation, and it must be discretized as follows:The specific form of each matrix in Equation (6) can be found in . In thisGNSS uses satellites in orbit to transmit radio signals to provide users with position information through passive ranging. The basic observation equation is as follows :(7)λiφi,There are a variety of error terms in Equation (7), which inhibit integer characteristic maintenance by non-difference ambiguity; thus, the accuracy of the solution directly using the non-difference observation equation is limited. The use of double-difference observations for positioning calculations can eliminate error items such as the receiver clock error, satellite clock error, and receiver and satellite hardware phase delay, and it can greatly reduce the impact of ionospheric and tropospheric delays on the observations to ensure the integer characteristics of double-difference ambiguity . The obsSimplified as:The position and speed corrected by the lever arm value are considered in Equation (9) and linearized to obtain the double-difference observation equation:The details of above matrix are given as follows:In Equation (11), Further, the observations from Equation (10) can be expressed asFor the covariance matrix of the observation noise INS-assisted IAR uses high-precision prior position information provided by the INS to assist the GNSS in obtaining a more precise ambiguity float solution, reducing the search range and improving its accuracy and search efficiency. In particular, when the GNSS signal is partially interrupted, the tightly coupled filter still predicts the parameter error and continuously corrects the navigation result. When the satellite signal is received again, the position and variance matrices obtained by the INS are used to initialize the GNSS navigation module and serve as additional observations. After the integer ambiguity parameters are solved, the GNSS observations and the integer ambiguities are inputted into the tightly coupled filter to update the measurement. In this study, we use the position information predicted by INS as virtual observations. The observation equation for the INS-assisted acquisition of GNSS ambiguity float solution is as follows:To improve the ambiguity initialization efficiency and solution accuracy, after obtaining the ambiguity float point solution, we implement different IAR strategies for different navigation stages. In the initialization phase, the float solution of the double-difference wide-lane ambiguity is directly rounded, and the two nearest integer values of each ambiguity are combined with other ambiguity values. Each combination is considered in the error equation for the least-squares solution, and the combination with the smallest error σ is used to calculate the ratio of the second smallest ly fixed . In the ly fixed  is used In the GNSS/INS integration system, the forward Kalman filter can only use historical information to estimate the current state, and it is susceptible to the influence of satellite signal interruption, which leads to great error accumulation. The RTSS algorithm can effectively limit the accumulation of pose errors by fully utilizing forward observations from the initial time to the current time and the backward dynamic constraint information from the end time to the current time . Figure Reversing the RTSS algorithm based using forward Kalman filtering is conducted as follows. The forward Kalman filter solution is first used to obtain the state vector To study the performance of the DGNSS/INS tightly coupled RTSS post-processing strategy in this study under the GNSS signal lock loss environment, we analyze and experimentally verified the following three aspects from the perspective of fully mining observations: (1) the ability of loosely coupled and tightly coupled to use observations in an environment with insufficient satellites, (2) the effectiveness of the RTSS algorithm during a period of GNSS signal interruption, and (3) the influence of INS-assisted IAR on the position and attitude accuracy in an environment with frequent lock loss. Experiments were conducted near Shandong University of Science and Technology . The split closed-loop fiber optic integrated navigation system SPAN-LCI manufactured by NovAtel  was usedThe GNSS receiver used was NovAtel ProPark6, which can realize the data collection of GPS, BDS, and GLONASS data. The sampling frequency was 20 Hz, and the GNSS antenna type was NOV703GGG. The reference station was set up at a known point in the marine survey comprehensive experimental field of Shandong University of Science and Technology, with an open surrounding environment. The data collection time of the mobile station was approximately 2.5 h, the baseline length typically exceeded 10 km, and the satellite suffered lock loss in several places. The experimental trajectory on Google Earth is displayed in To analyze and verify the performance of the tightly coupled and loosely coupled systems in an environment where the number of available satellites is insufficient, experimental data within 6500 to 6560 epochs from the experimental data are intercepted. In a realistic urban environment, satellites with lower altitudes are more likely to be blocked, and satellites with higher altitudes are more suitable for simulating GNSS satellite loss-of-lock experiments. Therefore, G27, G26, and G16 were selected when simulating an observation environment with only three visible satellites, and G27 and G26 were selected when simulating an observation environment with only two visible satellites. What needs to be emphasized here is that the integer ambiguity of these selected satellites has been correctly fixed in the previous observation epoch.In In tightly coupled system, within a short period, the number of observable satellites substantially influences the position error, but the influence on the attitude error is not apparent. The RMSEs of the roll and pitch are 0.0058° and 0.0114°, respectively. The observability of the heading is poor, and when the number of observable satellites is sufficient, the RMSE is 0.0238°. The heading angle also conforms to the law that there are more available observations and sufficient accuracy. In general, when more observations are used, more accurate pose results can be obtained. Under the premise that the IAR is correct, the tightly coupled system can be measured and updated normally when there are fewer than four satellites, this can guarantee navigation solution accuracy. Therefore, the tightly coupled system is more suitable for observation environments where the satellite is partially locked.To analyze the improvement effect of the RTSS algorithm on the navigation solution, this experiment performed loosely coupled forward filtering processing and loosely coupled reverse RTSS processing on simulated data in Test 1.The position and attitude error curves in In the partial satellite lock-out simulation experiments of Tests 1 and 2, satellites whose integer ambiguities have been correctly fixed in the previous epoch are selected. In an actual urban canyon environment, the satellite signal is received intermittently after the satellite signal is completely blocked for a short time, and the integer ambiguity must be fixed again. To analyze the performance of the INS-assisted IAR strategy in this study, we intercepted data within 374,470–374,560 epochs and designed four sets of experimental schemes.Plan 1: The satellite signal is completely interrupted for 10 s and then continues to observe three satellites for 30 s.Plan 2: The satellite signal is completely interrupted for 20 s and then continues to observe three satellites for 30 s.Plan 3: The satellite signal is completely interrupted for 30 s and then continues to observe three satellites for 30 s.Plan 4: First, the satellite signal is completely out of lock, and only three satellites are observed; finally, over four satellites are observed. The above three observation environments last for 10 s each. The specific experimental situation of plan4 is shown in Based on the pose errors in In addition, after the satellite signal is interrupted for 10 s to 20 s, the position accuracy obtained after the INS-aided integer ambiguity is quickly fixed and remains at the centimeter level. After the satellite signal was interrupted for 30 s, the position error estimated by the INS reached the decimeter level. Even if the integer ambiguity was quickly fixed, and the measurement was updated, the position error still accumulated, and the final position error was at the decimeter level. The effectiveness of the INS-aided IAR therefore depends on the position accuracy of the INS estimation.Based on To verify the performance of the tightly coupled post-processing solution strategy in this study in an urban environment, data from the final hour of the Qingdao medium and a short baseline experiment were intercepted. Then, the tightly coupled solution without INS-aided IAR (Method 1), the tightly coupled solution with INS-aided IAR (Method 2), and the tightly coupled solution strategy in this study (Method 3) were used to process the data. In In an actual urban environment, due to the influence of tall buildings, trees, and other occlusion factors, the satellite signal frequently suffers lock loss, causing a reduction in the accuracy of the GNSS/INS integrated system, rendering it unable to meet application requirements. This study implemented an INS-aided IAR DGNSS-INS tightly coupled smoothing post-processing strategy. This strategy uses INS-aided IAR in the ambiguity initialization stage after the GNSS signal is interrupted to achieve fast IAR, followed by RTSS to determine the navigation solution during lock-out period processing. Moreover, this solution strategy does not require additional observations but improves the accuracy of the integrated system by fully utilizing existing observations. The primary results obtained through experimental analysis in this study are as follows.(1) The performances of the loosely and tightly coupled systems and the improvement effect of the RTSS algorithm on the navigation solution were analyzed through simulation experiments where available satellites is insufficient. The experimental results demonstrate that when the number of observable satellites was sufficient, there is no significant difference in the positioning and attitude determination performance of the loosely and tightly coupled satellites. When the number of observation satellites was less than four, compared to the loosely coupled system, the tightly coupled system fully utilized the observations of satellites to update the measurements and constrain the drift error of the inertial device. In addition, during the lock-out period, the accuracy of the loosely coupled system after RTSS was significantly improved. The position accuracy was improved by approximately 95%. The degree of improvement in the roll and pitch was approximately 10%, and that in the heading was approximately 50%.(2) The performances of the tightly coupled system without INS-aided IAR, the tightly coupled system with INS-aided IAR, and the solution strategy were compared and analyzed through simulation and field experiments. The results demonstrate that the strategy proposed in this study can use the position provided by the INS to quickly fix integer ambiguity of the three satellites after the satellite signal is completely interrupted, allowing the observations of the three satellites to become available observations. The strategy in this study effectively limited the growth of the pose error, and the position and attitude accuracy of the navigation solution was further improved after smoothing.In this study, the performance of the tightly coupled DGNSS/INS under the condition of short-term satellite signal multi-occlusion was analyzed, and solutions were provided. However, it was difficult to obtain centimeter-level positioning accuracy with GNSS signals that are completely out of lock for a long period. Future work should focus on special environments where GNSS is completely out of lock for a long period, such as garages and tunnels, to further enrich quality control methods and to obtain more reliable and accurate navigation information.


Deformation is a ubiquitous phenomenon in nature. This process usually refers to the change in shape, size, and position of an object in the time and spatial domain under various loads. Under normal circumstances, during engineering construction, technicians are generally required to monitor the safe operation of structural facilities in the transportation field and the health of bridge, because monitoring in the engineering process plays an important role in construction safety. Considering the reliability risk of sensors after a long-time work period, such as signal drift, accurate measurement of strain gauges is inseparable from the value traceability system of high-precision strain gauges. In this study, two vibrating wire strain gauges with the same working principle were measured using the parallel method at similar positions. First, based on the principle of time series, the experiment used high-frequency dynamic acquisition to measure the thermometer strain of two vibrating wire strain gauges. Second, this experiment analyzed the correlation between strain and temperature measured separately. Under the condition of different prestress, this experiment studied the influencing relationship of temperature corresponding variable. In this experiment, the measurement repetitiveness was analyzed using the meteorology knowledge of single sensor data, focused on researching the influence of temperature and prestress effect on sensors by analyzing differences of their measurement results in a specified situation. Then, the reliability and stability of dynamic vibrating wire strain gauge were verified in the experiment. The final conclusion of the experiment is the actual engineering in the later stage. Onsite online meteorology in the application provides support. The designed cutout of the diaphragm was applied to the RTD weld at the welded connection between the U rib and diaphragm. This cutout was validated as a means to help achieve better fatigue resistance for the RTD weld [Bridge health monitoring and diagnostic discriminant models have always been a key challenge for the transportation sector worldwide. In a previous study, on a regular and irregular basis, construction workers used different monitoring instruments to test some components of structure, analyzed the data, and finally evaluated the performance of structure. In 2018, Mao by monitoring dynamic characteristics of Sutong cable-stayed bridge (SCB), including acceleration and strain responses, as well as modal frequencies, are investigated through one-year continuous monitoring data under operating conditions by the structural health monitoring system. One-year continuous modal frequencies of SCB are identified using the Hilbert–Huang transform method. Variability analysis of the structural modal frequencies due to environmental temperature and operational traffic is then conducted. Results show that temperature is the most important environmental factor for vertical and torsional modal frequencies. The traffic load is the second critical factor especially for the fundamental vertical frequency of SCB [RTD weld . For briIn recent years, studies on the heat of vibrating wire sensors at home and abroad have continued unabated, and domestic and foreign experts and scholars have conducted a lot of research to improve the sensor performance. The research on sensors is gradually extended towards high precision, large scale, small volume, and multiple applications. During the improvement in the performance of the sensor, higher requirements are also imposed on the measurement accuracy. To improve accuracy, in 2010, He proposed a low-voltage excitation with the feedback method. By pre-excitations, the vibration frequency of the sensor can be used as the output of the driver. The feedback signal frequency is very close to the real frequency of the sensor, so the wire can reach resonance state quickly. The optimal excitation strategy was verified by the new designed detection circuit. The data perform as short-time excitations with large resonance amplitude, therefore the anti-interference ability got enhanced at lower cost of signal processing circuit, finally increasing the measurement time and improving the accuracy of measured frequency . In 2010In the research process, we carried out a number of relevant tests. For example, the calibration of fixed excitation by a simply supported beam model is shown in During this study, two vibrating wire strain gauges with the same working principle were measured using the parallel method at similar positions. The feasibility of a parallel measurement scheme was verified . Under tA vibrating wire sensor is tested by steel string vibration. An experiment is conducted to characterize the force according to the variation in vibration frequency. In an actual output frequency signal, there is no strain gauge; it must be field calibration, signal drift, long distance transmission, and long time. The problem of poor durability was used, and the robustness was good . This exA vibrating wire sensor has good measurement characteristics; it can achieve nonlinear characteristics of less than 0.1%, sensitivity of 0.05%, and less than 0.1%/10 °C temperature error.After the strain gauge is manufactured, its steel string has a certain initial tensile force Assuming that the strain increment of strain gauge can be set to the strain increment of vibrating wire, Equation (3) can be derived as follows:When A mathematical model of the vibrating wire sensor can be expressed using Equations (5) and (6) as follows:When the length is such that the fine string of mass m is subjected to tension F , the natSensitivity can be derived using Equation (10) as follows:After differentiation, Equations (11) and (12) can be deduced as follows:The material coefficient can be calculated using Equation (13):The above formula shows that sensitivity After many experiments, the initial frequency is At that time Its quadratic nonlinearity error can be expressed as Equation (17):The above formula shows that the larger −1) of the structural material to be tested;−1) of a steel string of a vibrating wire strain gauge;When the ambient temperature changes, the vibrating wire strain gauge material and the measured structural material have different linear expansion coefficients, and the sensor is subjected to additional stretching or compression. The additional strain can be expressed as Equation (19):−6);−6/(kHz2);2;2;−6 °C;In actual application, the vibrating wire strain sensing system generally adopts software compensation. After the thermistor is set to collect the working environment temperature in the electromagnetic coil, the optimized temperature compensation algorithm is combined with the software to compensate in the demodulation instrument. The temperature strain compensation of the vibrating wire strain gauge mostly utilizes the two-dimensional regression method, polynomial fitting method, and neural network method. After the test results of the vibrating wire strain gauge are linearly fitted, the strain calculation method can be expressed as Equation (20):When using polynomial fitting, the coefficients a and b were calculated using the least squares fitting method, and the strain calculation method for integrating temperature changes is shown in Equation (21):The abovementioned various theoretical calculation methods and vibrating wire strain gauge measurement characteristics can better measure the strain, eliminate the strain generated by environmental influence, more accurately understand the mechanical strain of structure, and analyze the stress state of structural facility.Two sensors were installed in parallel on the 45th steel tooling for free acquisition at the same frequency. The device  shows thThe measurement module used the patented 8,671,758 products, and the dynamic measurement rate is 20 to 333 Hz. At the same time of dynamic measurement, the module also performs auxiliary measurement, performs static measurement at 1 Hz, provides finer measurement resolution, and better anti-interference to external noise source performance. The thermistor input signal of each vibrating string acquisition channel was measured at a high resolution of 24 bits at 1 Hz. The performance of thermistor parameters is shown in In the measurement, both steel plate and strain gauge will produce different deformations due to temperature changes. To minimize the acquisition error, a correlation curve between temperature and strain was analyzed. During the test, welding was used. To solder the two sensor holders on the tooling and for better verification, the effect of temperature response, and correlation, when collecting the zero point, one sensor was set to the free state, one sensor passed the fixture. The force was applied such that the sensor zero point acquisition and the first sensor’s zero point acquisition strain difference is about 140 The relationship between temperature and strain measurement shows that the strain changes correspondingly when the temperature changes. The strain reversely sways as the temperature changes. We got a good corresponding relationship. The temperature and strain data collected using the two sensors A and B were compared, and the correlation between the two data was analyzed. During the analysis, there are usually two ways of correlation: Autocorrelation and cross-correlation. The autocorrelation function is known as the autocorrelation equation and used to describe the correlation between the correlation functions of related data at different times as shown in Equation (22):At the same time, cross-correlation or cross-covariance were also used to represent a measure of similarity between two signals. Cross-correlation mainly analyzes the degree of correlation between two time series. Cross-correlation is essentially similar to the convolution of two functions. For discrete functions If the continuous signal is set to two sets of During this test analysis, the data collected using the two sensors A and B were compared, and the correlation between the two sets of data was analyzed. Their similarities were derived to verify the accuracy and reliability of dynamic acquisition of data obtained using sensors A and B. The correlation coefficient between the temperature data of sensors A and B was calculated to be 0.9983, and the correlation degree is highly correlated. The correlation coefficient between the strain data of sensors A and B is 0.9895, and the correlation degree is highly correlated. Cross-calculation can be obtained. The correlation between temperature and strain of sensor A is −0.6683, and the correlation between temperature and strain of sensor B is −0.5573. The experimental results show that the values are significantly correlated .i-th measurement, με;During the test, to better use the knowledge of metrology to analyze the dynamic RMS change output, verify the reliability of linear relationship between temperature and strain monitoring, and repeat the calculation of temperature measurement and strain measurement, the experiment measured the comprehensive reflection of various random influencing factors, including the instability of tooling materials used, random error caused by the laying process, instability of sensing instrument, environmental conditions, and other factors, as well as the actual measured randomness. The measured object also affects the dispersion of measured values, especially when the random variation in the measured object during the bridge monitoring process is large. Therefore, the dispersion of experimentally measured values is typically slightly greater than the dispersion introduced by the sensor static calibration standard itself. To be less affected by outliers, all the deformations and the corresponding temperature were measured. During the calculation of repeatability of the experiment, the arithmetic mean value of measured value should be calculated first, and the calculation formula can be expressed as Equation (25):i-th measurement, με;με;The measurement repeatability can be quantitatively expressed using the experimental standard deviation Using the above formula, under the synchronous acquisition test conditions, sensors A and B were repetitively used for the temperature and strain measurements, respectively. The repeatability of sensor A strain indication is 0.16071, and the temperature measurement repeatability is 0.09971. The repeatability of strain measurement of sensor B is 0.11743, and the repeatability of temperature measurement is 0.08209. The repeatability shows that the stability of sensor B is better, and the experiment can be performed under the condition that the initial state of sensor is small. The measured values are more stable and more clearly characterized by the corresponding relationship between temperature and strain.At the same time, the relationship between strain and temperature was analyzed during a temperature variation of 0.2, 0.6, and 1.8 °C.  signals .−9After calculating different temperature changes, the experimental values show the correlation between strain and temperature. By analyzing the strain-temperature correlation function, it can be found that the temperature change is less than that of sensor B when there is no external excitation. At the same time, the change in output corresponding to the strain is small. In different temperature variation ranges, the experimental data were used to analyze the relationship between the temperature and strain of sensor A. It was observed that the acquisition device is in a free state, and the temperature is small. The effect of corresponding change will be produced. According to statistical analysis, the strain-temperature correlation can be expressed as In engineering, the strain test method is usually used to determine the actual stress state of structure and monitor the structural deformation increment, and the structural strain test is an important method to solve the structural strength problem. During strain detection and monitoring, the calibration of strain gauge plays a significant role in the accuracy of data. To ensure the accuracy of traceability of magnitude, we should study the corresponding relationship between the temperature and strain of strain gauge and the online calibration test method, which is important for the online metrological traceability system of strain monitoring sensor. We focused on researching the influence of temperature and prestress effect on sensors by analyzing differences of their measurement results in specified situation. In this study, a dynamic vibrating wire measurement module was used to dynamically collect the temperature and strain of two vibrating wire sensors in the free state, and the correlation between temperature and strain was analyzed. The correlation coefficient between the temperature data of sensors A and B were statistically analyzed. The degree of relevance 0.9983 is highly correlated. The experimental results show that the correlation coefficient between the strain data of sensors A and B is 0.9895, and the correlation degree is highly correlated. After cross-calculation, a significant correlation was observed between temperature and strain indications. An experiment was carried out to analyze the measurement repeatability by using the knowledge of metrology. After analysis, it was found that the repeatability of temperature and strain values is within 0.2, and the consistency between the measured results of the same measurement is good. At the same time, the relationship between strain and temperature in different temperature variation intervals was analyzed. It was found that the temperature change has a small effect on the strain in the prestressed state, but the relationship between temperature and strain is relatively stable. Finally, the experiment verified the feasibility of parallel measurement scheme corresponding to the online calibration of variable monitoring sensor and analyzed the effect of temperature corresponding to the variable measurement under different prestress conditions, providing theoretical and experimental verification support for establishing an online metrological verification standard. This study can also better confirm the accuracy of bridge health monitoring data, effectively reduce the monitoring error caused by temperature drift, effectively eliminate the impact of environmental load, and better feedback the essential deformation of bridge structure. Considering the reliability risk of sensors after a long-time work period, such as signal drift, the approach proposed in this paper can be used as a substitute to such strain monitoring system in order to determine whether these sensors should be replaced. We expect our approach to be expandable to various applications. It can provide important support for the effective monitoring data extraction of the bridge health monitoring system.


Scaffold material is essential in providing mechanical support to tissue, allowing stem cells to improve their function in the healing and repair of trauma sites and tissue regeneration. The scaffold aids cell organization in the damaged tissue. It serves and allows bio mimicking the mechanical and biological properties of the target tissue and facilitates cell proliferation and differentiation at the regeneration site. In this study, the developed and assayed bio-composite made of unique collagen fibers and alginate hydrogel supports the function of cells around the implanted material. We used an in vivo rat model to study the scaffold effects when transplanted subcutaneously and as an augment for tendon repair. Animals’ well-being was measured by their weight and daily activity post scaffold transplantation during their recovery. At the end of the experiment, the bio-composite was histologically examined, and the surrounding tissues around the implant were evaluated for inflammation reaction and scarring tissue. In the histology, the formation of granulation tissue and fibroblasts that were part of the inclusion process of the implanted material were noted. At the transplanted sites, inflammatory cells, such as plasma cells, macrophages, and giant cells, were also observed as expected at this time point post transplantation. This study demonstrated not only the collagen-alginate device biocompatibility, with no cytotoxic effects on the analyzed rats, but also that the 3D structure enables cell migration and new blood vessel formation needed for tissue repair. Overall, the results of the current study proved for the first time that the implantable scaffold for long-term confirms the well-being of these rats and is correspondence to biocompatibility ISO standards and can be further developed for medical devices application. Collagen is a main extracellular matrix protein that supports the structure mainly of skeletal tissues. Collagen has a main function during the healing process and in cases when the tissue will not heal spontaneously, there is a need to foster it. These bring the collagen to serve both as an essential protein and a major component in biomedical scaffolding for various tissue regeneration approaches. The scaffold facilitates and promotes the autologous stem cells growth and differentiation that will progressively enter the scaffold and replace it by the regenerating tissue. The tissue-engineered scaffolds approach mimics the natural tissue structure and physical properties of the targeted tissue. Such an approach also aims to minimize the use of autologous grafts, which are limited by the availability of the patient’s own tissue and may avoid additional surgical procedures. Thus, the challenge is to find a suitable source of collagen, whose extraction and purification procedures will be suitable for medical applications. The overall goal is to find a replacement to synthetic polymer materials used as medical devices, which do not integrate with the body and may trigger an immune response such as chronic inflammation . The useCollagens are a heterogeneous family of extracellular matrix proteins, but are highly conserved through evolution. The collagen structure is highly homologous among invertebrates and mammalians, including mice and humans, which allow the collagen to be metabolically compatible through different phylogenetic groups. The collagen family is divided into fibrillar and non-fibrillar categories based on packing and ultrastructure, and this study focus on a fibrillar collagen that was studied in detail and described by us for its molecular and ultrastructure . Marine Most invertebrate collagens appear as extracellular matrices, and their mechanical properties are limited. In this study, the unique collagen fibers were shown to be extracted by a rather simple procedure by pulling out from the coral tissues ,13. ThesThis study further analyses the biocompatibility of the bio composite in vivo in a rat animal model. The experiment demonstrated the healing of a rotator cuff tear, the most common musculoskeletal injury occurring in the shoulder . The bioThe bio-composite production is demonstrated in The bio composite film aimed to serve as scaffold for tissue repair was recently used in a cell culture system and analyzed for growth, migration, and differentiation in 2D and 3D scaffolds in vitro . In the At the end of the experiment, the scaffolds transplanted as augments or at subcutaneous sites and the surrounded tissues were extracted and examined histologically. This analysis was performed in order to assess cells’ interaction with the bio-composite and a potential cytotoxic effect or foreign body response. The results visualized that the transplanted bio-composites were integrated with the surrounding tissues, as seen at the macro-level as a square cube surrounded by a fibrotic tissue growing over . The hisImplant integration with the healing tendon relies on autologous cells function during tissue regeneration, and the augment facilitated the improvement of this recovery step. In the current study, we aimed to evaluate the stability of the bio-composite augment. We analyzed the produced bio composite film both in vitro  and in vFirst, we evaluated in vitro the stability of the collagen-alginate hydrogel bio composition device under different storage conditions . The bioA biocompatibility study recently showed the properties of the bio-composite for cells growth and differentiation in vitro with no sign of cytotoxicity for period of up to 11 weeks . The curThe rats were analyzed for their recovery, and the animals displayed the disruption of the left rotator cuff function, as shown in The mechanisms underlying tendon healing encompass the step of macrophages recruitment, followed by fibrous tissue formation and the regulation of ECM remodeling. The presence of fibro-proliferation is proven and angiogenesis lead to tissue remodeling during the wound’s healing. Such steps were observed during the current in vivo rotor cuff tendon augmentation and subcutaneous transplant. These findings emphasize the biocompatibility of the bio-composite and its safety, which is a principal quality for clinical use. Therefore, it is concluded that the analyzed material meets the ISO standard for biocompatibility.Sarchophyton ehrenbergi [Coral collagen fibers were isolated by mechanical extraction from the soft coral renbergi ,13,17. Tw/v) alginate solution was produced by dissolving sodium alginate  in distilled water. The isolated collagen fibers were arranged in various orientations on a frame to provide the mechanical properties to the biocomposite. The collagen fibers were embedded in alginate and then inserted into a dialysis membrane . The membrane was sealed, flattened, and soaked for 24 h in a calcium-containing solution at physiological concentration (0.02 M CaCl2). Calcium divalent cations mediate cross-linking between the polysaccharide chains of the alginate, which become a hydrogel  at a wide range of temperatures  as indicated in each experiment.2 was placed over the repaired supraspinatus tendon and sutured down to the supraspinatus with Vicryl 4-0 . Finally, an additional subcutaneous implantation was performed, using a similar bio composite film scaffold that was placed under the skin at the back of the neck. The wound was closed in layers: the subcutaneous layer was closed with Vicryl 3-0  and the skin was sutured with Vicryl 3-0 . The operated rats were followed up by observation until awakening from anaesthesia and daily monitored after surgery for well-being and physiological recovery. The follow up was carried out by the visual monitoring of the rats’ activity  with the approval of Tel Aviv University Institutional Animal Care and Use Committee Number 01-18076. The rats underwent a unilateral detachment of the right supraspinatus tendon, and were subjected to repair and augmentation with a bio composite scaffold implant as described in the following surgical procedure of rotator cuff augmentation or sub-cutaneous implantation sites. Rats were anesthetized with 5% isoflurane inhalation (maintained at 2–3% during surgery) and injected with Rimadyl (NSAID) prior to surgery. All the animals were subjected to identical unilateral supraspinatus detachment and repair. The animals were operated on the right shoulder, where a 1.5 cm skin incision was performed over the anterolateral border of the glen humeral joint. The deltoid was exposed and the supraspinatus tendon was identified . The supvity see  and weigThe rats were sacrificed and the transplanted bio-composite films, which served as tendon augment or for subcutaneous implantation, were extracted and processed for histology. These analysed transplants were removed and fixed in 4% paraformaldehyde, embedded in paraffin and 5 µm thick sections were stained with haematoxylin eosin (HE) or Masson Trichrome (MT) to highlight the fibrous tissue. The slides were observed and photographed on a light microscope .The biocompatibility of the collagen-alginate bio composite film was previously assessed in vitro, showing that the scaffold meets the terms of the IS0 10993-5 standards for cytotoxicity. In the in vitro study, mesenchymal stem cells succeeded in migrating and colonizing the scaffold, grew and proliferated, and formed tissue-like structures along and between the collagen fibers . In the


The first-order theory of rewriting is a decidable theory for linear variable-separated rewrite systems. The decision procedure is based on tree automata techniques and recently we completed a formalization in the Isabelle proof assistant. In this paper we present a certificate language that enables the output of software tools implementing the decision procedure to be formally verified. To show the feasibility of this approach, we present FORT-h, a reincarnation of the decision tool FORT with certifiable output, and the formally verified certifier FORTify.


Non-alcoholic fatty liver (NAFLD) is a metabolic disorder related to a chronic lipid accumulation within the hepatocytes. This disease is the most common liver disorder worldwide, and it is estimated that it is present in up to 25% of the world’s population. However, the real prevalence of this disease and the associated disorders is unknown mainly because reliable and applicable diagnostic tools are lacking. It is known that the level of albumin, a pleiotropic protein synthesized by hepatocytes, is correlated with the correct function of the liver. The development of a complementary tool that allows direct, sensitive, and label-free monitoring of albumin secretion in hepatocyte cell culture can provide insight into NAFLD’s mechanism and drug action. With this aim, we have developed a simple integrated plasmonic biosensor based on gold nanogratings from periodic nanostructures present in commercial Blu-ray optical discs. This sensor allows the direct and label-free monitoring of albumin in a 2D fatty liver disease model under flow conditions using a highly-specific polyclonal antibody. This technology avoids both the amplification and blocking steps showing a limit of detection within pM range (≈0.26 ng/mL). Thanks to this technology, we identified the optimal fetal bovine serum (FBS) concentration to maximize the cells’ lipid accumulation. Moreover, we discovered that the hepatocytes increased the amount of albumin secreted on the third day from the lipids challenge. These data demonstrate the ability of hepatocytes to respond to the lipid stimulation releasing more albumin. Further investigation is needed to unveil the biological significance of that cell behavior. The chronic accumulation of fat within the liver, known as non-alcoholic fatty liver (NAFL), increased exponentially in the last 10 years. Over 25% of the global population is affected by NAFL, although it is underdiagnosed  + B, where A is the maximal signal, B is the minimum, C is the concentration producing 50% of the maximal signal, and D is the slope at the inflection point of the sigmoid curve. The calculation of the limit of detection (LOD) and the limit of quantification (LOQ) was based on ELISA methodology . For a sDetection of secreted albumin from the in vitro model of fatty liver was performed under fluidic conditions. Supernatants of controls and fatty liver was collected on day 0, 1, and 3. Each sample was interrogated by individual 2-channel nanoplasmonic sensing platforms and later fitted from the corresponding calibration curve for quantification. Nevertheless, the albumin secretion remains constant at FBS content of 0 and 10%. In the case of 2% FBS condition, we independently evaluate albumin secretion of samples in cell media with and without fat to confirm that the signal’s increment is selective in detecting the protein without added effect from the fat supplement media supplements b. We valThe in vitro data presented reflect both the phenotypical and functional changes in fatty hepatocytes in vivo. The viability and metabolic activity decrease upon challenge with NEFAs while the albumin production increases due to adaptation to the new environment. The simple label-free integrated plasmonic biosensor based on Blu-ray discs nanogratings allowed us to monitor albumin secretion overtime in an in vitro fatty liver model. The plasmonic biosensor represents a useful tool to study the evolution of the disease in vitro. Moreover, we took advantage of the cost-effective Blu-ray disc to achieve the fabrication of high throughput sensors. This prototype is customizable, and it has been employed as a multi-analyte detection system in cell culture supernatant media, with a LOD in the pM order without any amplification or pretreatment of the sample. Due to its high versatility and the straightforward integration in lab-on-a-chip devices, the presented plasmonic nanomaterial is a promising candidate for developing monitoring platforms for cell cultures.