A Virtual Simulation Experiment of Mechanics: Material Deformation and Failure Based on Scanning Electron Microscopy

This work presents a set of comprehensive virtual experiments to detect material deformation and failure. The most commonly used pieces of equipment in ...

wuhan university

The errors of low-cost inertial sensors, especially Micro-Electro Mechanical Systems (MEMS) ones, are highly dependent on environmental conditions such as the temperature. Thus, there is a need for the development of accurate and reliable thermal compensation models to reduce the impact of such thermal drift of the sensors. Since the conventional thermal calibration methods are typically time-consuming and costly, an efficient thermal calibration method to investigate the thermal drift of a full set of gyroscope and accelerometer errors (i.e., biases, scale factor errors and non-orthogonalities) over the entire temperature range in a few hours is proposed. The proposed method uses the idea of the Ramp method, which removes the time-consuming process of stabilizing the sensor temperature, and addresses its inherent problems with several improvements. We change the temperature linearly for a complete cycle and take a balanced strategy by making comprehensive use of the sensor measurements during both heating and cooling processes. Besides, an efficient 8-step rotate-and-static scheme is designed to further improve the calibration accuracy and efficiency. Real calibration tests showed that the proposed method is suitable for low-grade IMUs and for both lab and factory calibration due to its efficiency and sufficient accuracy.

Fast thermal calibration of low-grade inertial sensors and inertial measurement units.

This paper presents a method that trains the WiFi fingerprint database using sensor-based navigation solutions. Since micro-electromechanical systems (MEMS) sensors provide only a short-term accuracy but suffer from the accuracy degradation with time, we restrict the time length of available indoor navigation trajectories, and conduct post-processing to improve the sensor-based navigation solution. Different middle-term navigation trajectories that move in and out of an indoor area are combined to make up the database. Furthermore, we evaluate the effect of WiFi database shifts on WiFi fingerprinting using the database generated by the proposed method. Results show that the fingerprinting errors will not increase linearly according to database (DB) errors in smartphone-based WiFi fingerprinting applications.

Collaborative WiFi Fingerprinting Using Sensor-Based Navigation on Smartphones.

Indoor wireless localization using Bluetooth Low Energy (BLE) beacons has attracted considerable attention after the release of the BLE protocol. In this paper, we propose an algorithm that uses the combination of channel-separate polynomial regression model (PRM), channel-separate fingerprinting (FP), outlier detection and extended Kalman filtering (EKF) for smartphone-based indoor localization with BLE beacons. The proposed algorithm uses FP and PRM to estimate the target's location and the distances between the target and BLE beacons respectively. We compare the performance of distance estimation that uses separate PRM for three advertisement channels (i.e., the separate strategy) with that use an aggregate PRM generated through the combination of information from all channels (i.e., the aggregate strategy). The performance of FP-based location estimation results of the separate strategy and the aggregate strategy are also compared. It was found that the separate strategy can provide higher accuracy; thus, it is preferred to adopt PRM and FP for each BLE advertisement channel separately. Furthermore, to enhance the robustness of the algorithm, a two-level outlier detection mechanism is designed. Distance and location estimates obtained from PRM and FP are passed to the first outlier detection to generate improved distance estimates for the EKF. After the EKF process, the second outlier detection algorithm based on statistical testing is further performed to remove the outliers. The proposed algorithm was evaluated by various field experiments. Results show that the proposed algorithm achieved the accuracy of <2.56 m at 90% of the time with dense deployment of BLE beacons (1 beacon per 9 m), which performs 35.82% better than <3.99 m from the Propagation Model (PM) + EKF algorithm and 15.77% more accurate than <3.04 m from the FP + EKF algorithm. With sparse deployment (1 beacon per 18 m), the proposed algorithm achieves the accuracies of <3.88 m at 90% of the time, which performs 49.58% more accurate than <8.00 m from the PM + EKF algorithm and 21.41% better than <4.94 m from the FP + EKF algorithm. Therefore, the proposed algorithm is especially useful to improve the localization accuracy in environments with sparse beacon deployment.

Smartphone-Based Indoor Localization with Bluetooth Low Energy Beacons.

As various inertial measurement units (IMUs) from different manufacturers appear every year, it is not affordable to evaluate every IMU through tests. Therefore, this paper presents an IMU evaluation method by grafting data from the tested IMU to the reference data from a higher-grade IMU. The signal grafting (SG) method has several benefits: (a) only one set of field tests with a higher-grade IMU is needed, and can be used to evaluate numerous IMUs. Thus, SG is effective and economic because all data from the tested IMU is collected in the lab; (b) it is a general approach to compare navigation performances of various IMUs by using the same reference data; and, finally, (c) through SG, one can first evaluate an IMU in the lab, and then decide whether to further test it. Moreover, this paper verified the validity of SG to both medium- and low-grade IMUs, and presents and compared two SG strategies, i.e., the basic-error strategy and the full-error strategy. SG provided results similar to field tests, with a difference of under 5% and 19.4%-26.7% for tested tactical-grade and MEMS IMUs. Meanwhile, it was found that dynamic IMU errors were essential to guarantee the effect of the SG method.

An IMU Evaluation Method Using a Signal Grafting Scheme.

Electronic maps (E-maps) provide people with convenience in real-world space. Although web map services can display maps on screens, a more important function is their ability to access geographical features. An E-map that is based on raster tiles is inferior to vector tiles in terms of interactive ability because vector maps provide a convenient and effective method to access and manipulate web map features. However, the critical issue regarding rendering tiled vector maps is that geographical features that are rendered in the form of map symbols via vector tiles may cause visual discontinuities, such as graphic conflicts and losses of data around the borders of tiles, which likely represent the main obstacles to exploring vector map tiles on the web. This paper proposes a tiled vector data model for geographical features in symbolized maps that considers the relationships among geographical features, symbol representations and map renderings. This model presents a method to tailor geographical features in terms of map symbols and 'addition' (join) operations on the following two levels: geographical features and map features. Thus, these maps can resolve the visual discontinuity problem based on the proposed model without weakening the interactivity of vector maps. The proposed model is validated by two map data sets, and the results demonstrate that the rendered (symbolized) web maps present smooth visual continuity.

Tiled vector data model for the geographical features of symbolized maps.

Replication factor C (RFC) is a multisubunit complex that opens the sliding clamp and loads it onto the DNA chain in an ATP-dependent manner and is thus critical for high-speed DNA synthesis. In yeast () and humans, biochemical studies and structural analysis revealed interaction patterns between the subunits and architectures of the clamp loaders. Mutations of  lead to loss of cell viability and defective replication. However, the functions of RFC subunits in higher plants are unclear, except for , and the interaction and arrangement of the subunits have not been studied. Here, we identified /+, /+, and /+ mutants in , and found that embryos and endosperm arrested at the 2/4-celled embryo proper stage and 6-8 nuclei stages, respectively. Subcellular localization analysis revealed that AtRFC1 and OsRFC1/4/5 proteins were localized in the nucleus, while AtRFC2/3/4/5 and OsRFC2/3 proteins were present both in the nucleus and cytoplasm. By using yeast two-hybrid (Y2H) and bimolecular fluorescence complementation (BiFC) techniques, we demonstrated the interactions of  and rice () RFC subunits, and proposed arrangements of the five subunits within the RFC complex, which were AtRFC5-AtRFC4-AtRFC3/2-AtRFC2/3-AtRFC1 and OsRFC5-OsRFC2-OsRFC3-OsRFC4-OsRFC1, respectively. In addition, AtRFC1 could interact with AtRFC2/3/4/5 in the presence of other subunits, while OsRFC1 directly interacted with the other four subunits. To further characterize the regions required for complex formation, truncated RFC proteins of the subunits were created. The results showed that C-termini of the RFC subunits are required for complex formation. Our studies indicate that the localization and interactions of RFCs in  and rice are distinctly discrepant.

Subunit Interaction Differences Between the Replication Factor C Complexes in  and Rice.

Although wireless fingerprinting has been well researched and widely used for indoor localization, its performance is difficult to quantify. Therefore, when wireless fingerprinting solutions are used as location updates in multi-sensor integration, it is challenging to set their weight accurately. To alleviate this issue, this paper focuses on predicting wireless fingerprinting location uncertainty by given received signal strength (RSS) measurements through the use of machine learning (ML). Two ML methods are used, including an artificial neural network (ANN)-based approach and a Gaussian distribution (GD)-based method. The predicted location uncertainty is evaluated and further used to set the measurement noises in the dead-reckoning/wireless fingerprinting integrated localization extended Kalman filter (EKF). Indoor walking test results indicated the possibility of predicting the wireless fingerprinting uncertainty through ANN the effectiveness of setting measurement noises adaptively in the integrated localization EKF.

Wireless Fingerprinting Uncertainty Prediction Based on Machine Learning.

Reliable and continuous navigation solutions are essential for high-accuracy location-based services. Currently, the real-time kinematic (RTK) based Global Positioning System (GPS) is widely utilized to satisfy such requirements. However, RTK's accuracy and continuity are limited by the insufficient number of the visible satellites and the increasing length of base-lines between reference-stations and rovers. Recently, benefiting from the development of precise point positioning (PPP) and BeiDou satellite navigation systems (BDS), the issues existing in GPS RTK can be mitigated by using GPS and BDS together. However, the visible satellite number of GPS + BDS may decrease in dynamic environments. Therefore, the inertial navigation system (INS) is adopted to bridge GPS + BDS PPP solutions during signal outage periods. Meanwhile, because the quality of BDS geosynchronous Earth orbit (GEO) satellites is much lower than that of inclined geo-synchronous orbit (IGSO) satellites, the predicted observation residual based robust extended Kalman filter (R-EKF) is adopted to adjust the weight of GEO and IGSO data. In this paper, the mathematical model of the R-EKF aided GEO/IGSO/GPS PPP/INS tight integration, which uses the raw observations of GPS + BDS, is presented. Then, the influences of GEO, IGSO, INS, and R-EKF on PPP are evaluated by processing land-borne vehicle data. Results indicate that (1) both GEO and IGSO can provide accuracy improvement on GPS PPP; however, the contribution of IGSO is much more visible than that of GEO; (2) PPP's accuracy and stability can be further improved by using INS; (3) the R-EKF is helpful to adjust the weight of GEO and IGSO in the GEO/IGSO/GPS PPP/INS tight integration and provide significantly higher positioning accuracy.

Robust Kalman Filter Aided GEO/IGSO/GPS Raw-PPP/INS Tight Integration.

Semantically rich indoor models are increasingly used throughout a facility's life cycle for different applications. With the decreasing price of 3D sensors, it is convenient to acquire point cloud data from consumer-level scanners. However, most existing methods in 3D indoor reconstruction from point clouds involve a tedious manual or interactive process due to line-of-sight occlusions and complex space structures. Using the multiple types of data obtained by RGB-D devices, this paper proposes a fast and automatic method for reconstructing semantically rich indoor 3D building models from low-quality RGB-D sequences. Our method is capable of identifying and modelling the main structural components of indoor environments such as space, wall, floor, ceilings, windows, and doors from the RGB-D datasets. The method includes space division and extraction, opening extraction, and global optimization. For space division and extraction, rather than distinguishing room spaces based on the detected wall planes, we interactively define the start-stop position for each functional space (e.g., room, corridor, kitchen) during scanning. Then, an interior elements filtering algorithm is proposed for wall component extraction and a boundary generation algorithm is used for space layout determination. For opening extraction, we propose a new noise robustness method based on the properties of convex hull, octrees structure, Euclidean clusters and the camera trajectory for opening generation, which is inapplicable to the data collected in the indoor environments due to inevitable occlusion. A global optimization approach for planes is designed to eliminate the inconsistency of planes sharing the same global plane, and maintain plausible connectivity between the walls and the relationships between the walls and openings. The final model is stored according to the CityGML3.0 standard. Our approach allows for the robust generation of semantically rich 3D indoor models and has strong applicability and reconstruction power for complex real-world datasets.

Fast and Automatic Reconstruction of Semantically Rich 3D Indoor Maps from Low-quality RGB-D Sequences.

Di(2-ethylhexyl)phthalate (DEHP) is a typical endocrine-disrupting chemical and reproductive toxicant. Although previous studies have attempted to describe the mechanism by which DEHP exposure results in reproductive dysfunction, few studies focused on puberty, a critical period of reproductive development, and the increased susceptibility to injury in adolescents. To elucidate the mechanism underpinning the testicular effects of DEHP in puberty, we sought to investigate the JAZF1/TR4 pathway in the testes of pubertal rats. Specifically, we focused on the role of the JAZF1/TR4 pathway in male reproduction, including the genes JAZF1, TR4, Sperm 1, and Cyclin A1. In the present study, rats were exposed to increasing concentrations of DEHP (0, 250, 500, and 1000 mg/kg/day) by oral gavages for 30 days. Then we assayed testicular zinc and oxidative stress levels. Our results indicated that DEHP exposure could lead to oxidative stress and decrease the contents of testicular zinc. Additionally, significant morphological changes and cell apoptosis were observed in testes exposed to DEHP, as identified by hematoxylin and eosin staining and the terminal deoxynucleotidyl transferase-mediated nick and labeling assay. By measuring the expression levels of the above relevant genes by qPCR, we found the DEHP-induced increased expression of JAZF1 and decreased expression of TR4, Sperm 1, and Cyclin A1. Therefore, we have demonstrated that in vivo exposure to DEHP might induce reproductive toxicity in pubertal male rats through the JAZF1/TR4 pathway and oxidative stress.

Di(2-ethylhexyl)phthalate induces reproductive toxicity via JAZF1/TR4 pathway and oxidative stress in pubertal male rats.

Dynamical decoupling (DD) is an active and effective method for suppressing decoherence of a quantum system from its environment. In contrast to the nominal biaxial DD, this work presents a uniaxial decoupling protocol that requires a significantly reduced number of pulses and a much lower bias field satisfying the "magic" condition. We show this uniaxial DD protocol works effectively in a number of model systems of practical interest, e.g., a spinor atomic Bose-Einstein condensate in stray magnetic fields (classical noise), or an electron spin coupled to nuclear spins (quantum noise) in a semiconductor quantum dot. It requires only half the number of control pulses and a 10-100 times lower bias field for decoupling as normally employed in the above mentioned illustrative examples, and the overall efficacy is robust against rotation errors of the control pulses. The uniaxial DD protocol we propose shines new light on coherent controls in quantum computing and quantum information processing, quantum metrology, and low field nuclear magnetic resonance.

Uniaxial Dynamical Decoupling for an Open Quantum System.

The hydroxyproline-containing proteins (HCPs) among secretory and vacuolar proteins play important roles in growth and development of higher plants. Many hydroxyproline-rich glycoproteins (HRGPs), including Arabinogalactan proteins (AGPs), extensins (EXTs), and proline-rich proteins (PRPs), are identified as HCPs by bioinformatics approaches. The experimental evidence for validation of novel proline hydroxylation sites is vital for understanding their functional roles. In this study, the 62 HCPs containing 114 hydroxyproline (O, Hyp) residues were identified, and it was found that hydroxylation of proline residues in the HCPs could either constitute attachment sites for glycans or have other biological function in rice. The glycomodules of AO, OA, OG, VO, LO, and OE were abundant in the 62 HCPs. Further analysis showed that the 22 of 62 HCPs contained both signal peptides and transmembrane domains, and the 19 HCPs only contained transmembrane domains, while 21 HCPs contained neither. This study indicated the feasibility of mass spectrometry-based proteomics combined with bioinformatics approaches for the large-scale characterization of Hyp sites from complex protein digest mixtures. Furthermore, the expression of AGPs in rice was detected by using β-GlcY reagent and JIM13 antibody. The results displayed that the AGPs were widely distributed in different tissues and organs of rice, especially expressed highly in lateral root, pollen and embryo. In conclusion, our study revealed that the HCPs and Hyp residues in rice were ubiquitous and that these Hyps could be candidates for linking to glycans, which laid the foundation for further studying the functions of HCPs and hydroxylation of proline residues in rice.

Identification of Hydroxyproline-Containing Proteins and Hydroxylation of Proline Residues in Rice.

Inorganic nanosheets are endowed with many two-dimensional (2D) morphological features including ultra-high specific surface area, ultra-thin thickness, easy functionalization, and so on. They push forward an immense influence on effective cancer diagnosis and therapy, overcoming the inherent limitations of traditional treatment methods. However, long-term toxicity and poor biocompatibility are the critical issues for most inorganic nanosheets, which hinder their further oncological applications and clinical translations. Muscovite, also named white mica (WM), an aluminosilicate, is a major component of traditional Chinese medicine, which can be exfoliated into 2D nanosheets and expected to be a potential drug carrier. In this study, WM powder was exfoliated to prepare WM nanosheets (WMNs) through a polyamine intercalation method. In addition, doxorubicin hydrochloride (Dox) was loaded to WMNs  physical adsorption and electrostatic interaction to prepare Dox-loaded WMNs (Dox@WMNs). Then, we studied that Dox@WMNs released Dox in phosphate buffer saline. We also studied the cellular uptake and cytotoxicity of Dox@WMNs . The results illustrated that Dox@WMNs cumulatively released Dox much faster and more at acidic pH (6.0 and 4.6) compared with that at physiological pH. In addition, WMNs showed selective cytotoxicity. Within a certain concentration range, WMNs were cytotoxic to Hela cells but non-cytotoxic to RAW 264.7 cells. Compared with cytotoxicity at pH 7.4, the cytotoxicity of Dox@WMNs was significantly enhanced at pH 6.4 and 4.6. WMNs mainly promoted the immunostimulatory polarization of RAW 264.7 cells into M1 macrophages.

Preparation and  Antitumor Study of Two-Dimensional Muscovite Nanosheets.

Albumin, a multifunctional protein, is widely used to prepare nanocarriers. Hyaluronic acid (HA) is a natural glycosaminoglycan that can specifically bind receptors, such as cluster of differentiation-44. Therefore, HA is commonly used as ligands for the surface modification of versatile nanocarriers. The combined utilization of albumin and HA as nanocarriers shows outstanding superiorities including efficient targeting, reducible particle size, pH and/or hyaluronidase sensitive drug release, combining capacity for various drugs, biocompatibility, non-immunogenicity, biodegradability and high stability. However, to the best of our knowledge, HA and albumin based nanoparticles have not been reviewed for drug delivery so far. This review involves the introduction of the essential information of HA and albumin as well as a brief presentation of the preparation methods of HA and albumin based nanocarriers. Moreover, the application of HA and albumin based nanoparticles as drug delivery carriers in tumors, joints, vitreum and skin tissue is systematically discussed with the potential and prospect in combined therapy and theranostics. In addition, the unique advantages of the HA and albumin based nanoparticles and their contributions to the improvement of drug delivery systems are further expounded in detail.

Hyaluronic acid and albumin based nanoparticles for drug delivery.

 To explore the changes in lipids in exosomes of hormone-sensitive and hormone-resistant prostate cancer cells and develop an inexpensive and rapid technique for screening lipid-based biomarkers of prostate cancer.  Exosomes were extracted from LnCap, PC and DU-145 cells, and their lipid composition was analyzed quantitatively using high-throughput mass spectrometry. Exosomes released by LnCap prostate cancer cells were also purified using a modified procedure based on polyethylene glycol (PEG) precipitation.  Exosomes extracted from LnCap cells contained higher proportions of phosphatidyl choline, phosphatidyl ethanolamine and phosphatidyl inositol lipids than whole LnCap cells. Lysophosphatidylcholine, a harmful intermediate product of phosphatidylcholine metabolism , was not found in LnCap cells but in exosomes. Phospholipids were different in exosomes from LnCap, PC3 and DU-145 prostate cancer cells. The main lipid pathways involved, i.e., glycerophospholipid metabolism, autophagy, and ferroptosis pathways, were also different in these cells. Exosomes isolated by this modified PEG precipitation technique were similar in purity to those obtained using a commercial kit.  This study demonstrates that phosphatidylcholine and its harmful product lysophosphatidylcholine may play important roles in hormone-sensitive prostate cancer. Phospholipid exosome metabolism was changed in hormone-sensitive and hormone-resistant prostate cancer cells. The LPC, lipid pathway of autophagy and ferroptosis may act as therapeutic targets. The possibility of purifying prostate cancer cell exosomes using modified PEG precipitation is suitable for cancer screening.

Changes in phospholipid metabolism in exosomes of hormone-sensitive and hormone-resistant prostate cancer cells.

Double fertilization is a key determinant of grain yield, and the failure of fertilization during hybridization is one important reason for reproductive isolation. Therefore, fertilization has a very important role in the production of high-yield and well-quality hybrid of rice. Here, we used RNA sequencing technology to study the change of the transcriptome during double fertilization with the help of the mutant  () that failed to finish fertilization process and led to seed abortion. The results showed that 1669 genes were related to the guided growth of pollen tubes, 332 genes were involved in the recognition and fusion of the male-female gametes, and 430 genes were associated with zygote formation and early free endosperm nuclear division. Among them, the genes related to carbohydrate metabolism; signal transduction pathways were enriched in the guided growth of pollen tubes, the genes involved in the photosynthesis; fatty acid synthesis pathways were activated by the recognition and fusion of the male-female gametes; and the cell cycle-related genes might play an essential role in zygote formation and early endosperm nuclear division. Furthermore, among the 1669 pollen tube-related genes, it was found that 7  (), 1  (), and 15  () were specifically expressed in anther, while 2 , 7 , and 5  in pistil, showing obvious unequal distribution which implied they might play different roles in anther and pistil during fertilization. These studies laid a solid foundation for revealing double fertilization mechanism of rice and for the follow-up investigation.

You Li

School of Civil Engineering

wuhan university

A Virtual Simulation Experiment of Mechanics: Material Deformation and Failure Based on Scanning Electron Microscopy

You Li

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}School of Civil Engineering

wuhan university

A Virtual Simulation Experiment of Mechanics: Material Deformation and Failure Based on Scanning Electron Microscopy

School of Civil Engineering