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Abstract Three-dimensional (3D) high-resolution large-volume imaging has remained a challenge. Translational rapid ultraviolet-excited sectioning tomography (TRUST) achieves rapid and cost-effective whole-organ subcellular imaging through iterative optical scanning and mechanical sectioning. However, the axial resolution is limited by the mechanical sectioning thickness or the UV light penetration depth in tissue. Here, assisted with high-and-low-frequency (HiLo) microscopy (HiLoTRUST), the optical sectioning thickness has been reduced from tens of micrometers to ~5.8 µm. In addition, HiLoTRUST has attained a finer mechanical sectioning thickness (10–15 µm) compared to TRUST (50 µm). For high-content imaging as in TRUST, we employed two additional UV light-emitting diodes (LEDs) specifically for uniform illumination. The full-color imaging ability and improved axial resolution of HiLoTRUST have been validated by two-dimensional (2D)/3D imaging of various mouse organs and human lung cancer specimens. HiLoTRUST offers a cost-effective, full-color, and high-resolution 3D imaging approach, showing its great potential in 3D histology applications.

Abstract Background Colorectal cancer (CRC) ranks as the third most common malignancies in the world, and periodic examination of the patient is advantageous in reducing the mortality of CRC. The first blood-based Septin9 gene methylation assay which recognized by the US FDA for CRC examination was Epi proColon. However, this assay was not broadly applied in the current clinical guideline because of its relatively lower sensitivity in the detection of early-stage CRC. Methods This study aimed at developing a new multiplex Septin9 methylation assay (ColonUSK) which simultaneously evaluates two CpG-rich subregions in the promoter of the Septin9 gene and an internal control in a single reaction. ColonUSK proved increased sensitivity, with a detection limit as low as 12pg of the positive DNA compared with the Septin9 assay targeting one CpG-rich subregion. 1366 subjects were prospectively recruited from four comprehensive hospitals in China in an opportunistic screening study for assessing its value in CRC detection. Blind testing was developed to evaluate ColonUSK in comparison with clinical examination using clinical gold standard such as colonoscopy. Results The assay demonstrates clinical sensitivity for diagnosing colorectal cancer (CRC) and advanced adenoma at rates of 77.34% and 25.26%, respectively. Furthermore, ColonUSK exhibits a high degree of specificity for non-CRC cases (95.95%) clinically. Significantly, the detection rate of cases in high-grade intraepithelial neoplasia increased to 54.29%. The value for the assay in the Kappa test was 0.76, showing a high degree of consistency between ColonUSK and clinical gold standard. Conclusions ColonUSK indicated moderate diagnostic value and could become a non-invasive detection way for CRC. The implementation of the ColonUSK assay has the capacity to markedly enhance CRC screening practices.

Abstract Astragaloside IV, a prime active component of Astragalus membranaceus, has potential as a neuroprotectant. We aimed to identify the active ingredients in A. membranaceus and assess if Astragaloside IV can improve cerebral ischemia-reperfusion injury (CIRI) cell apoptosis by reducing P-Src and P-GRK2 via ryanodine receptor (RyR) expression inhibition. We used bioinformatics analysis to examine the effects of A. membranaceus on ischemic stroke. We studied brain samples from middle cerebral artery occlusion (MCAO) mice treated with normal saline, Astragaloside IV, and sham mice for pathology and Western blot tests. We also tested PC12 cells in vitro with or without Astragaloside IV or GSK180736A using Western blotting and fluorescence assays. Our bioinformatics analysis suggested a possible association between A. membranaceus, calcium ion pathways, and apoptosis pathways. Western blot data indicated Astragaloside IV significantly decreased RyR, p-Src, and downstream phosphorylated GRK2, PLC, CaMKII, and IP3R levels in MCAO mice brains. Astragaloside IV also considerably inhibited pro-apoptotic and oxidative stress-associated proteins’ expression while boosting anti-apoptotic protein expression. The results suggest Astragaloside IV can inhibit RyR expression, subsequently reducing brain cell apoptosis.

This study aims to systematically investigate the deterioration of tensile properties, voltage variation, and voltage-strength theoretical model of CFRP/ conductive ECC composites under coupling effect of anode polarization, load and erosion environment. The effects of testing parameters including conductive ECC mixture type, electric current density, polarization time, tensile stress value, sulfate soak time, and sulfate attack-wet and dry cycle time were synthetically investigated. The experimental results indicated that the voltage increases approximately linearly with the increase of degradation time in the voltage-deterioration time curves. The stress-strain curve can be divided into three stages: the stress-strain linear increase stage, the strain hardening characteristic stage, and the decline stage during failure. The conductive ECC mixture type, polarization time, current density, tensile stress value, sulfate soak time, and sulfate attack-wet and dry cycle time all have significant effects the deterioration of tensile strength and the voltage change ratio of CFRP/ conductive ECC composite. More importantly, an innovative voltage-strength theoretical model was proposed, which can predict the relationship between voltage and material deterioration strength. The theoretical model is in good agreement not only with the experimental results of this study, but also with the results of other studies. The model proposed can be used to predict deterioration degree of materials in real time, which has very important guiding significance for impressed current cathodic protection-structural strengthening technology (ICCP-SS) technology. This study is expected to promote a more comprehensive understanding of the deterioration of mechanical properties and voltage-strength theoretical model of CFRP/conductive ECC composites for ICCP-SS technology.

With global climate change, linking vegetation phenology with net ecosystem productivity (NEP) is crucial for assessing vegetation carbon storage capacity and predicting terrestrial ecosystem changes. However, there have been few studies investigating the relationship between vegetation phenology and NEP in the middle and high latitudes of the Northern Hemisphere. This study comprehensively analyzed vegetation phenological changes and their climate drivers using satellite data. It also investigated the spatial distribution and climate drivers of NEP and further analyzed the sensitivity of NEP to vegetation phenology. The results indicated that the average land surface phenology (LSP) was dominated by a monotonic trend in the study area. LSP derived from different satellite products and retrieval methods exhibited relatively consistent responses to climate. The average SOS and POS for different retrieval methods showed a higher negative correlation with nighttime temperatures compared to daytime temperatures. The average EOS exhibited a higher negative correlation with daytime temperatures than a positive correlation. The correlations between VPD and the average SOS, POS, and EOS showed that the proportion of negative correlations was higher than that of positive correlations. The average annual NEP ranged from 0 to 1000 gC·m−2. The cumulative trends of NEP were mainly monotonically increasing, accounting for 61.04%, followed by monotonically decreasing trends, which accounted for 17.95%. In high-latitude regions, the proportion of positive correlation between VPD and NEP was predominant, while the proportion of negative correlation was predominant in middle-latitude regions. The positive and negative correlations between soil moisture and NEP (48.08% vs. 51.92%) were basically consistent in the study area. The correlation between SOS and POS with NEP was predominantly negative. The correlation between EOS and NEP was overall characterized by a greater proportion of negative correlations than positive correlations. The correlation between LOS and NEP exhibited a positive relationship in most areas. The sensitivity of NEP to vegetation phenological parameters (SOS, POS, and EOS) was negative, while the sensitivity of NEP to LOS was positive (0.75 gC·m−2/d for EVI vs. 0.63 gC·m−2/d for LAI vs. 0.30 gC·m−2/d for SIF). This study provides new insights and a theoretical basis for exploring the relationship between vegetation phenology and NEP under global climate change.

Achieving light-induced manipulation of controlled self-assembly in nanosized structures is essential for developing artificially dynamic smart materials. Herein, we demonstrate an approach using a non-photoresponsive hydrogen-bonded (H-bonded) macrocycle to control the self-assembly and disassembly of nanostructures in response to light. The present system comprises a photoacid (merocyanine, 1-MEH), a pseudorotaxane formed by two H-bonded macrocycles, dipyridinyl acetylene, and zinc ions. The operation of such a system is examined according to the alternation of self-assembly through proton transfer, which is mediated by the photoacid upon exposure to visible light. The host–guest complexation between the macrocycle and bipyridium guests was investigated by NMR spectroscopy, and one of the guests with the highest affinity for the ring was selected for use as one of the components of the system, which forms the host–guest complex with the ring in a 2:1 stoichiometry. In solution, a dipyridine and the ring, having no interaction with each other, rapidly form a complex in the presence of 1-MEH when exposed to light and thermally relax back to the free ring without entrapped guests after 4 h. Furthermore, the addition of zinc ions to the solution above leads to the formation of a polypseudorotaxane with its morphology responsive to photoirradiation. This work exemplifies the light-controlled alteration of self-assembly in non-photoresponsive systems based on interactions between the guest and the H-bonded macrocycle in the presence of a photoacid.

Developing optomechanical systems with large-aperture output beams is increasingly important for deep space exploration, homeland defense, and modern warfare. However, the assembly process for such systems is becoming more challenging due to their complexity and size. Considering that traditional computer-aided assembly methods for optomechanical systems primarily prioritize debugging and testing, often overlooking the importance of feasibility analysis and verification in the assembly process, this paper presents a digital assembly method for large aperture optomechanical systems that integrates virtual assembly technology with misalignment error detection technology. By combining these two technologies, the proposed method aims to enhance the assembly process by providing a more comprehensive approach that includes feasibility analysis and verification, in addition to debugging and testing. Firstly, virtual assembly technology is utilized to simulate and validate the assembly process design of optomechanical systems. Secondly, a second-order sensitivity matrix method is proposed to achieve higher accuracy in solving misalignment compared to traditional methods. The new method is validated through simulation experiments on an off-axis beam expander system, showing superior solving accuracy compared to traditional approaches. Lastly, an actual assembly and adjustment platform is constructed, and the obtained assembly result exhibits a wavefront aberration RMS value better than 0.016λ (λ=632.8nm).

PurposeThis study aimed to investigate the relationship between the ratio of c-reactive protein to albumin (CAR) and pediatric septic arthritis (PSA).MethodsClinical and laboratory data were collected. Receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive ability of CAR in identifying PSA. Multivariable logistic regression analyses was performed to calculate adjusted odds ratio (OR) with 95% confidence interval (CI).ResultsWe included 305 patients with PSA (CAR ≤ 0.447, 182 patients; CAR > 0.447, 123 patients) between September 2013 and November 2022. ROC analysis showed that CAR performed best in diagnosing PSA, with an area under curve (AUC) value of 0.828. After adjusted for potential confounders, we found that high CAR was associated with PSA (OR = 6.85, 95% CI: 2.30–20.40, p = 0.001). In sensitivity analyses, subgroups analyses, and propensity score matching, the results remain stable.ConclusionsThe CAR (>0.447) at admission was an independent risk factor for PSA. It is worthy to further investigate this association.

This study proposes a vessel position prediction method using attention spatiotemporal graph convolutional networks, which addresses the issue of low prediction accuracy due to less consideration of inter-feature dependencies in current vessel trajectory prediction methods. First, the method cleans the vessel trajectory data and uses the Time-ratio trajectory compression algorithm to compress the trajectory data, avoiding data redundancy and providing feature points for vessel trajectories. Second, the Spectral Temporal Graph Neural Network (StemGNN) extracts the correlation matrix that describes the relationship between multiple variables as a priori matrix input to the prediction model. Then the vessel trajectory prediction model is constructed, and the attention mechanism is added to the spatial and temporal dimensions of the trajectory data based on the spatio-temporal graph convolutional network at the same time as the above operations are performed on different time scales. Finally, the features extracted from different time scales are fused through the full connectivity layer to predict the future trajectories. Experimental results show that this method achieves higher accuracy and more stable prediction results in trajectory prediction. The attention-based spatio-temporal graph convolutional networks effectively capture the spatio-temporal correlations of the main features in vessel trajectories, and the spatio-temporal attention mechanism and graph convolution have certain interpretability for the prediction results.

Cemented carbide used in the rotor of a mud pulser is subjected to the scouring action of solid particles and corrosive mud media for a long time, which causes abrasive wear and electrochemical corrosion. To improve the wear and corrosive resistance of cemented carbide, samples with different cobalt content (WC-5Co, WC-8Co, and WC-10Co) receive deep cryogenic treatment (DCT) at −196 °C for 2.5 h. An optical metalloscope (OM) and X-ray diffractometer (XRD) are used to observe the phase changes of cemented carbides, and the XRD is also used to observe the change in residual stress on the cemented carbide’s surface. A scanning electron microscope (SEM) is used to characterize the wear and electrochemical corrosion surface microstructure of cemented carbides (untreated and DCT). The results show that the DCT promotes the precipitation of the η phase, and the diffraction peak of ε-Co tends to intensify. Compared with the untreated, the wear rates of WC-5Co, WC-8Co, and WC-10Co can be reduced by 14.71%, 37.25%, and 41.01% by DCT, respectively. The wear form of the cemented carbides is mainly the extrusion deformation of Co and WC shedding. The precipitation of the η phase and the increase in WC residual compressive stress by DCT are the main reasons for the improvement of wear resistance. The electrochemical corrosion characteristic is the dissolution of the Co phase. DCT causes the corrosion potential of cemented carbide to shift forward and the corrosion current density to decrease. The enhancement of the corrosion resistance of cemented carbide caused by DCT is due to the Co phase transition, η phase precipitation, and the increase in the compressive stress of cemented carbide.

The rapid expansion and implementation of digital technologies are profoundly changing our lifestyles, production methods, and modes of exchange. However, whether or not such change can help promote the sustainability of urban socio-environmental systems has not been fully investigated. In this paper, we propose a comprehensive framework that utilizes the spatial Durbin model to investigate whether and how the digital economy contributes to low-carbon urban development, using the panel data of 276 Chinese cities from 2011 to 2018. This framework systematically identifies triple dimensions of low-carbon transition taking place throughout the whole value chain system, i.e. green innovation, production reshaping, and consumption upgrading. The finding reveals that the digital economy in a city exerts a significant mitigating effect on carbon emissions in both local and neighboring cities. It is also observed that digital economy activities play a significant role in alleviating urban carbon emissions due to their capacity to stimulate green innovation and promote sustainable patterns of production and consumption. The robustness of these findings is assessed through the consideration of endogeneity and substitution of the explained and explanatory variables. This paper contributes to a systematic understanding of the linkage between the revolution of digitalization within economic systems and the transition towards sustainability within environmental systems. It also provides valuable insights to policymakers on strategies to promote and accelerate low-carbon development.

The effect of Mn content on the microstructure evolution and mechanical properties of Al–Cu–Mg–x Mn alloys at ambient temperature was investigated. The findings show that in the Mn-containing alloys at the as-cast state, the blocky primary T(Al20Cu2Mn3) phase coexisting with the Al2Cu phase appeared. With the increase in Mn content, the majority of the Al2Cu phase dissolved, nd a minor amount of the T phase remained at the grain boundary after solution treatment. The rod-like TMn (Al20Cu2Mn3) nanoprecipitate was simultaneously distributed at grain boundaries and the interiors, while a high density of needle-like θ″ (Al3Cu) nanoprecipitate was also observed in the T6 state. Further increases in Mn content promoted the dispersion of the TMn phase and inhibited the growth and transformation of the θ″ phase. Tensile test results show that 0.7 wt.% Mn alloy had excellent mechanical properties at ambient temperature with ultimate tensile strength, yield strength, and fracture elongation of 498.7 MPa, 346.2 MPa, and 19.2%, respectively. The subsequent calculation of strengthening mechanisms elucidates that precipitation strengthening is the main reason for the increase in yield strength of Mn-containing alloys.

Currently, in most traditional VSLAM (visual SLAM) systems, static assumptions result in a low accuracy in dynamic environments, or result in a new and higher level of accuracy but at the cost of sacrificing the real–time property. In highly dynamic scenes, balancing a high accuracy and a low computational cost has become a pivotal requirement for VSLAM systems. This paper proposes a new VSLAM system, balancing the competitive demands between positioning accuracy and computational complexity and thereby further improving the overall system properties. From the perspective of accuracy, the system applies an improved lightweight target detection network to quickly detect dynamic feature points while extracting feature points at the front end of the system, and only feature points of static targets are applied for frame matching. Meanwhile, the attention mechanism is integrated into the target detection network to continuously and accurately capture dynamic factors to cope with more complex dynamic environments. From the perspective of computational expense, the lightweight network Ghostnet module is applied as the backbone network of the target detection network YOLOv5s, significantly reducing the number of model parameters and improving the overall inference speed of the algorithm. Experimental results on the TUM dynamic dataset indicate that in contrast with the ORB–SLAM3 system, the pose estimation accuracy of the system improved by 84.04%. In contrast with dynamic SLAM systems such as DS–SLAM and DVO SLAM, the system has a significantly improved positioning accuracy. In contrast with other VSLAM algorithms based on deep learning, the system has superior real–time properties while maintaining a similar accuracy index.

IntroductionInvasive alien plants (IAPs) are major hazards to biodiversity, human health, and the agricultural economy. As one of the most aggressive species of IAPs, the distribution area of Centaurea solstitialis L. has increased exponentially in the past two years since its invasion into Xinjiang, China, in July 2014. Predicting the potential geographic distributions (PGDs) of C. solstitialis in China can provide theoretical support for preventing the continued spread of this weed.MethodsIn this study, based on 5,969 valid occurrence records of C. solstitialis and 33 environmental variables, we constructed an ensemble model to predict suitable habitats for C. solstitialis under climate change scenarios.ResultsOur results showed that the mean true skill statistic (TSS) values, area under the receiver operating characteristic (ROC) curve (AUC), and Cohen’s Kappa (KAPPA) for the ensemble model were 0.954, 0.996, and 0.943, respectively. The ensemble model yielded more precise predictions than those of the single model. Temperature seasonality (Bio4), minimum temperature of the coldest month (Bio6), precipitation of the driest month (Bio14), and human influence index (HII) have significantly disrupted the PGDs of C. solstitialis in China. The total (high) suitability habitat area of C. solstitialis in China was 275.91 × 104 (67.78 × 104) km2, accounting for 71.26 (7.06)% of China. The PGDs of C. solstitialis in China under the current climate were mainly in East China (Shandong, Jiangsu, Shanghai, Zhejiang, and Anhui), Central China (Henan, southwestern Shanxi, southern Shaanxi, southern Gansu, Hubei, Hunan, Jiangxi, Chongqing, and Guizhou), and South China (southern Tibet, eastern Sichuan, Yunnan, Guangxi, Guangdong, Fujian, and Taiwan). Under future climate scenarios, the total suitability habitat area for C. solstitialis will expand, whereas the high suitability habitat area will decrease.DiscussionThe main manifestation is that the shift of southeast China into a moderate suitability habitat, and the total suitability habitats will be extended to northwest China. More focus needs to be placed on preventing further spread of C. solstitialis in northwest China.

The ever-growing demands for renewable energy sources motivate the development of energy storage systems. Among them, supercapacitors are received increasing attention due to their high power density, long cycle life, fast recharge rate, and almost no maintenance. Nevertheless, their application is hindered by severe self-discharge behaviors, especially in wearable and energy storage devices. In recent years, tremendous excellent works have been reported to conquer this shortcoming through various creative strategies. Herein, we gives a timely spotlight on breakthroughs in the self-discharge mechanism investigations of supercapacitors and the corresponding suppression strategies. The self-discharge mechanisms of various supercapacitors were introduced first, followed by a summary of the strategies from materials (i.e., electrode, electrolyte, and separator) to system and protocol optimization, furthermore, the connection between them, existing issues, and possible directions for future research are discussed.

We used network pharmacology to predict the correlation between the pathway of Bushenhuoxue formula in the treatment of vascular dementia and carried out experiments to verify the correlation between drug composition and disease. By screening the active components and key targets through various databases and drawing the topological network diagram, we obtained 502 effective compound targets, 601 disease targets, 95 disease-related compound targets, and 162 pathways. The pathway related to vascular dementia may be neurodegeneration-multiple diseases, PI3K-Akt signaling pathway, Mitogen-activated protein kinase signaling pathway, or HIF-1 signaling pathway. By detecting the learning and memory ability of vascular dementia rats, the morphology of the hippocampus under the electron microscope, the degree of neuronal damage, and autophagy-related proteins, the results showed that the Bushenhuoxue formula could improve the neuronal injury induced by ischemia in the hippocampus, down-regulate the level of autophagy, and thereby improve learning and memory. Therefore, the Bushenhuoxue formula may improve the ischemic injury of neurons by regulating the mechanism of neuronal autophagy.

For the aero-spiral bevel gears，the temperature of flank surface will be greatly increased in the high speed and heavy load conditions. It is necessary to consider the modal condition with the temperature field in designing early. Based on the traditional linear modal theory，the modal analysis model of aero-spiral bevel gears is established，what is considering the influence of rotational speed and temperature field on the stiffness. According to the model，the modal analysis of a driven gear of an aero-spiral bevel gear is carried out. The results show that the speed has a great influence on the stiffness of the gear，and which is not necessarily negative，and the uneven distribution of temperature field also affects the results of the modal analysis. The pitch diameter vibration mode is the main mode what is affected by the speed and temperature field.

Rapid multicolor three-dimensional (3D) imaging for centimeter-scale specimens with subcellular resolution remains a challenging but captivating scientific pursuit. Here, we present a fast, cost-effective, and robust multicolor whole-organ 3D imaging method assisted with ultraviolet (UV) surface excitation and vibratomy-assisted sectioning, termed translational rapid ultraviolet-excited sectioning tomography (TRUST). With an inexpensive UV light-emitting diode (UV-LED) and a color camera, TRUST achieves widefield exogenous molecular-specific fluorescence and endogenous content-rich autofluorescence imaging simultaneously while preserving low system complexity and system cost. Formalin-fixed specimens are stained layer by layer along with serial mechanical sectioning to achieve automated 3D imaging with high staining uniformity and time efficiency. 3D models of all vital organs in wild-type C57BL/6 mice with the 3D structure of their internal components (e.g., vessel network, glomeruli, and nerve tracts) can be reconstructed after imaging with TRUST to demonstrate its fast, robust, and high-content multicolor 3D imaging capability. Moreover, its potential for developmental biology has also been validated by imaging entire mouse embryos (~2 days for the embryo at the embryonic day of 15). TRUST offers a fast and cost-effective approach for high-resolution whole-organ multicolor 3D imaging while relieving researchers from the heavy sample preparation workload.

Solanum viarum has become extensively invasive owing to international trade, climate change, and land–use change. As it is classified as a quarantine weed by countries such as the U.S. and Mexico, it is critical to understand the prevailing historical dispersal, ecological niche dynamics, and distribution patterns. We reconstructed the historical invasion countries and analyzed the ecological niche shift of S. viarum. Using MaxEnt based on the conservativeness of ecological niches, we studied variations in the potential geographical distributions (PGDs) of S. viarum in ecosystems and variations in suitability probabilities along latitudinal gradients. The invasion history in six continents involved three phases: lag (before 1980), spread (1980–2010), and equilibrium (2010–present). The ecological niche remains conserved. The area of S. viarum PGDs had increased by 259 km2; the PGDs will expand to reach a maximum in the 2050s, SSP5–8.5. The PGDs of S. viarum will migrate to higher latitudes under the same future climate scenarios. The latitudes subject to high threats range from 20° to 30° in forest and cropland ecosystems, 15.5° to 27.5° (northern hemisphere) and 33.1° to 42.8° (southern hemisphere) in grassland ecosystems, and 20° to 35° in urban ecosystems. Global change has led to an increased threat of S. viarum at high latitudes. These findings provide a theoretical basis to monitor and control S. viarum.

Non-coding RNAs (ncRNAs) have attracted wide attention in the field of ionizing radiation (IR). They have been found to be involved in cell development, proliferation, differentiation, and apoptosis in both clinical radiotherapy and radiation protection studies. Despite the production of an increasing number of relevant reports in recent years, the molecular mechanisms involved are yet to be clearly understood. In the last few years, ncRNAs have received a lot of research attention, especially microRNAs, long noncoding RNAs, and circular RNAs, which have a well-known association with the development of human disease and are closely related to the biological phenotypic changes caused by IR. With recent developments of research methods, these ncRNAs might play a significant regulatory role in future radiation protection and radiotherapy. This review will summarize the research progress of various types of ncRNAs as biomarkers of IR and potential new targets for radiotherapy, aiming to provide references for future research and the formulation of new strategies.

Ovarian surface epithelium (OSE) undergoes recurring ovulatory rupture and OSE stem cells rapidly generate new cells for the repair. How the stem cell activation is triggered by the rupture and promptly turns on proliferation is unclear. Our previous study has identified that Protein C Receptor (Procr) marks OSE progenitors. In this study, we observed decreased adherent junction and selective activation of YAP signaling in Procr progenitors at OSE rupture site. OSE repair is impeded upon deletion of Yap1 in these progenitors. Interestingly, Procr+ progenitors show lower expression of Vgll4, an antagonist of YAP signaling. Overexpression of Vgll4 in Procr+ cells hampers OSE repair and progenitor proliferation, indicating that selective low Vgll4 expression in Procr+ progenitors is critical for OSE repair. In addition, YAP activation promotes transcription of the OSE stemness gene Procr. The combination of increased cell division and Procr expression leads to expansion of Procr+ progenitors surrounding the rupture site. These results illustrate a YAP-dependent mechanism by which the stem/progenitor cells recognize the murine ovulatory rupture, and rapidly multiply their numbers, highlighting a YAP-induced stem cell expansion strategy.

According to the need of power system for GEO satellite,the plan design and simulation based on Maximum Power Point Tracking (MPPT) technology were designed and simulated.It could reduce the power loss in power transport line and made full use of the output power of solar array.Based on the research and simulation for solar array,the simulation of all the power system was fi nished.The result of simulation provides that it can complete the MPPT function and stabilize the bus voltage.Last,the new plan and the traditional one were compared,which shows the advantage of the new plan and lays a foundation for next power system.

Abstract Background The concurrent ipsilateral Tillaux fracture with medial malleolar fracture in adolescents commonly suffer from high-energy injury, making treatment more difficult. The aim of this study was to discuss the mechanism on injury, diagnosis, and treatment of this complex fracture pattern. Methods The charts and radiographs of six patients were reviewed. The function was assessed by the American Orthopedic Foot and Ankle Society ankle-hindfoot scores. Results The mean age at operation was 12.8 years. The mean interval from injury to operation was 7.7 days. Five Tillaux fractures and all medial malleolar fractures were shown on AP plain radiographs. One Tillaux fracture and two cases with avulsion of posterolateral tibial aspect were confirmed in axial computerized tomography. There was talar subluxation laterally with medial space widening in three and syndesmotic disruption in one. There were five patients sustaining ipsilateral distal fibular fractures. All fractures, except nonunion in two medial malleolar fractures and in one Tillaux fracture, healed within 6–8 weeks. There was one case of osteoarthritis of ankle joint. The average AOFAS score was 88.7. Conclusions Computerized tomography is helpful in identifying the fracture pattern. Anatomic reduction and internal fixation of Tillaux and medial malleolar fracture was recommended to restore the articular surface congruity and ankle stability.

The application of deep learning techniques in background subtraction for VHR optical remote sensing videos holds the potential to facilitate multiple intelligent remote sensing processing tasks. However, existing methods on background subtraction for VHR optical remote sensing videos are still facing technical challenges. First, conventional CNN and other networks are limited by performance constraints. Second, existing background subtraction methods are mostly trained by natural videos due to the lack of VHR optical remote sensing video datasets. Third, VHR optical remote sensing videos have large scene sizes. In our article, we design a novel deep learning network via fully utilizing GAN and domain adaptation, which has the ability to measure and minimize the discrepancy between feature distributions of natural videos and VHR optical remote sensing videos so that the background subtraction performance for VHR optical remote sensing videos is improved significantly. Numerous experiments are conducted on the CDnet 2014 dataset and VHR optical remote sensing video dataset. Tremendous experiments demonstrate that our proposed method achieves an average FM of 0.8533, which reveals excellent performance on background subtraction.

Event extraction is an important research direction in the field of natural language processing (NLP) applications including information retrieval (IR). Traditional event extraction is realized with two methods: the pipeline and the joint extraction methods. The pipeline method determines the event by triggering word recognition to further implement event extraction and is prone to error cascading. The joint extraction method applies deep learning to implement the completion of the trigger word and the argument role classification task. Most studies with the joint extraction method adopt the CNN or RNN network structure. However, in the case of event extraction, deeper understanding of complex contexts is required. Existing studies do not make full use of syntactic relations. This paper proposes a novel event extraction model, which is built upon a Tree-LSTM network and a Bi-GRU network and carries syntactically related information. It is illustrated that this method simultaneously uses Tree-LSTM and Bi-GRU to obtain a representation of the candidate event sentence and identify the event type, which results in a better performance compared to the ones that use chain structured LSTM, CNN or only Tree-LSTM. Finally, the hidden state of each node is used in Tree-LSTM to predict a label for candidate arguments and identify/classify all arguments of an event. Lab results show that the proposed event extraction model achieves competitive results compared to previous works.

Topography significantly complicates the radiative transfer process of vegetation and further causes variation in reflectance observed by remote sensors. Leaf area index (LAI) inversion based on reflectance data is subsequently influenced by topography. Neglecting the topographic effects may lead to large biases when estimating LAI over rugged terrain. How the topography influences the LAI inversion process has rarely been explored. In this article, the topographic effects on LAI inversion over sloped terrain are quantitatively investigated and analyzed based on a dataset generated from the discrete anisotropy radiative transfer model. An artificial neural network (ANN) model is established to represent the flat surface LAI inversion algorithms. Then, the reflectance of sloped terrain is input into the ANN model to obtain the biased LAI inversion values. The results reveal that topography effects on LAI inversion are related to canopy density and generally lead to an underestimation except for sparse canopies. The mean relative bias could reach 51% when the slope angle reaches 60°. The variation trends of inverted LAI are closely related to the local incident angle. The different levels of bias in reflectance at red and near-infrared bands lead to different patterns of inversion errors for different canopies densities. Finally, we compared the existing strategies (geometric correction and topographic correction strategies) designed for LAI inversion over sloped terrain. It is found that these strategies apply in different situations. The results are helpful in understanding the topographic effects and further finding a better strategy for LAI inversion over sloped terrain.

Summary: Three-dimensional (3D) histology is vitally important to characterize disease-induced tissue heterogeneity at the individual cell level. However, it remains challenging for both high-throughput 3D imaging and volumetric reconstruction. Here we propose a label-free, cost-effective, and ready-to-use 3D histological imaging technique, termed microtomy-assisted autofluorescence tomography with ultraviolet excitation (MATE). With the combination of block-face imaging and serial microtome sectioning, MATE can achieve rapid and label-free imaging of paraffin-embedded whole organs at an acquisition speed of 1 cm3 per 4 h with a voxel resolution of 1.2 × 1.2 × 10 μm3. We demonstrate that MATE enables simultaneous visualization of cell nuclei, fiber tracts, and blood vessels in mouse/human brains without tissue staining or clearing. Moreover, diagnostic features, including nuclear size and packing density, can be quantitatively extracted with high accuracy. MATE is augmented to the current slide-based 2D histology, holding great promise to facilitate histopathological interpretation at the organelle level.

Previous studies have focused on the changes of tumour cells in immune escape, and less is known about the effect of tumour microenvironment (TME) on immune escape. Tumour-associated fibroblasts (TAF) is an important part of the TME and has special physiological and biochemical characteristics, but the specific mechanism has not been clarified. In order to investigate the effect of TAF on the expression of PD-L1 in gastric cancer cells, gastric cancer cell lines MNK45, SGC7901 were non-contact co-culturing with TAF 1, 3 and 7 d via transwell. PD-L1 mRNA and protein expression were detected using qRT-PCR and FCM. Then, 95 cases of gastric cancer tissues were selected and evaluated PD-L1 and TAF expressions by immunohistochemical examination. The results showed that the mRNA and protein expression of PD-L1 in the experiment group were significantly higher than that in the control group. PD-L1 expression was associated with massive lymphocyte infiltration, diffuse/mixed histology and intratumoral TAFs in gastric cancers. In conclusion, TAFs promoted the growth in gastric cancer cell lines by increased the PD-L1 expression.

The boll weevil, Anthonomus grandis Boheman (Coleoptera: Curculionidae), is an invasive alien species that can damage cotton plants and cause huge economic losses in the cotton industry. Currently, A. grandis is mainly distributed in the American continent. However, few studies have indicated the distribution and modification of its suitable global habitats after undergoing climate change. Based on the 339 distribution records of A. grandis and eight bioclimatic variables, we used the optimal MaxEnt model to predict the potential global distribution of A. grandis under the current (1970–2000) and future climatic scenarios (SSP5-8.5). The annual mean temperature (bio1) and isothermality (bio3) were the two most important bioclimatic variables, which indicates that the survival of A. grandis is extremely sensitive to temperature fluctuations. Under the current scenario, the highly suitable habitats were mainly distributed in America (the USA, Mexico, Brazil, Argentina, Paraguay, and Uruguay), Africa (South Africa, Ethiopia, and Mozambique), Asia (Pakistan, India, Thailand, Burma, and China), and Oceania (Australia). In future scenarios (SSP5-8.5), the potential suitable global habitats reached the highest level in America, Africa, Asia, and Oceania in the 2090s. Our study provides a meaningful reference for researchers, quarantine officers, and governments to devise suitable management control strategies for A. grandis.

Wuyi Mountain in Southeast China is the origin of black tea and oolong tea. It is also considered the ‘treasure trove of tea cultivars’ because of its rich tea germplasm resources. In the present study, the population structure and genetic diversity of 137 tea germplasms from Wuyi Mountain and its adjacent areas were analyzed by SNPs. The information index (I), observed heterozygosity (Ho), expected heterozygosity (He) and fixation index (F) polymorphisms of the selected SNPs were high, stable and reliable. Ho had an average of 0.389, while He had an average of 0.324, indicating that Wuyi Mountain tea germplasms had rich genetic diversity. The AMOVA results showed that genetic variation came mainly from intrapopulation variation, accounting for 66% of the total variation. The differences in the Fst and Nei values of tea germplasm between Wuyi Mountain and its adjacent areas are similar to the geographical differences. Multiple analyses based on high-quality SNPs found that the landraces of tea plants on Wuyi Mountain had different genetic backgrounds from the wild-type landraces and the landraces of Wuyi Mountain tea plants underwent population differentiation. This study provides a basis for the effective protection and utilization of tea germplasms on Wuyi Mountain and lays a foundation for identifying potential parents to optimize tea cultivation.

Summary: Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer death worldwide. However, the pathogenesis of HCC is complicated, and the drugs used for HCC treatment are limited. The following protocol combines a genetically engineered mouse model (GEMM) with a sleeping beauty system to establish an in vivo liver tumorigenesis model. By using this model, the impact of genes of interest in liver tumorigenesis and progression can be studied. This model can also be applied to develop new therapeutic drugs for HCC.For complete details on the use and execution of this protocol, please refer to He et al. (2020).

Summary: Sequential chromatin immunoprecipitation (ChIP) is commonly used to investigate DNA-protein and protein-protein interactions to a specific genomic region. However, it can be tricky to achieve a robust and reproducible signal with sequential ChIP. Here, we provide an optimized two-step ChIP protocol to quantify the in vivo associates of multiple proteins with the same DNA regulatory element.For complete details on the use and execution of this protocol, please refer to He et al. (2020).

Abstract Background The objectives of this study were to examine nutrient intakes of tuberculosis (TB) patients and to identify their associated factors. Methods In this cross-sectional study, 300 adult TB patients were surveyed in two impoverished counties in China. Nutrient intakes were evaluated through two consecutive 24-h dietary recalls and compared with the Chinese Dietary Reference Intakes (DRIs) 2013. The potential socio-demographic and behavioral factors were analyzed using multivariate logistic model to identify strong influential factors. Results We found that mean daily energy intake was 1655.0 kcal (SD: 619.3 kcal) and 1360.3 kcal (SD: 552.1 kcal) for male and female patients, respectively. The mean daily energy intake was significantly lower than that has been recommended by DRI (i.e., 2250 and 1800 kcal for males and females, respectively), with 87.4% of the male patients and 59.9% of female patients failed to consume adequate energy. The protein intakes were 44.6 g (SD: 18.2 g) and 35.9 g (SD: 12.3 g) for male and female patients, respectively, which were lower than the recommended values by DRI (i.e., 65 and 55 g for males and females, respectively). Most male (90.8%) and female (58.4%) TB patients had insufficient daily protein intake. Further analyses suggested that mean daily intakes of many micronutrients, were insufficient, while for most of patients, intakes of vitamin E and sodium were sufficient. We identified that unemployment was a risk factor for low energy intake (p

Audio-visual speech recognition (AVSR) can significantly improve performance over audio-only recognition for small or medium vocabularies. However, current AVSR, whether hybrid or end-to-end (E2E), still does not appear to make optimal use of this secondary information stream as the performance is still clearly diminished in noisy conditions for large-vocabulary systems. We, therefore, propose a new fusion architecture—the decision fusion net (DFN). A broad range of time-variant reliability measures are used as an auxiliary input to improve performance. The DFN is used in both hybrid and E2E models. Our experiments on two large-vocabulary datasets, the Lip Reading Sentences 2 and 3 (LRS2 and LRS3) corpora, show highly significant improvements in performance over previous AVSR systems for large-vocabulary datasets. The hybrid model with the proposed DFN integration component even outperforms oracle dynamic stream-weighting, which is considered to be the theoretical upper bound for conventional dynamic stream-weighting approaches. Compared to the hybrid audio-only model, the proposed DFN achieves a relative word-error-rate reduction of 51% on average, while the E2E-DFN model, with its more competitive audio-only baseline system, achieves a relative word error rate reduction of 43%, both showing the efficacy of our proposed fusion architecture.

This paper presents a discrete-time design of robust composite nonlinear controller to achieve fast and accurate set-point tracking for motor servo systems subject to actuator saturation and disturbances. The basic idea here is to use a combination of linear and nonlinear control, together with a disturbance rejection mechanism based on extended state observer. The linear control part is designed to yield a fast response, and the nonlinear part serves to reduce the overshoot, while the extended state observer estimates simultaneously the state vector and the unknown disturbance for control and compensation. The closed-loop stability is analyzed using the Lyapunov theory. Practical application in a permanent magnet synchronous motor position servo system is given to demonstrate the effectiveness of the proposed control scheme.

N6-methyladenosine (m6A) plays crucial roles in a diverse range of physiological and pathological processes, and it is believed that it tremendously promotes neoplasia and progression. However, knowledge of the molecular characteristics of m6A modification, its prognostic value, and the infiltration of immune cell populations in head and neck squamous cell carcinoma (HNSCC) is still insufficient. Therefore, a pan-cancer genomic analysis was systematically performed here by examining m6A regulators at the molecular level within 33 multiple cancer types, and the correlations between the expression of m6A molecules were researched using datasets from The Cancer Genome Atlas (TCGA). Based on the above analysis, insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2) is upregulated in HNSCC and may serve as an independent prognostic factor of overall survival, thus showing potential as a prognostic biomarker in HNSCC. Genetic alteration analyses elucidated the reasons for the abnormal upregulation of IGF2BP2 in HNSCC. As a result, IGF2BP2 was selected for further univariate and multivariate analyses. The functions of the related genes were annotated through gene set enrichment analysis, and the activation states of multiple biological pathways were shown by gene set variation analysis. We found that LRRC59 and STIP1 may act as IGF2BP2-associated genes to have a regulatory function in the m6A modification. In addition, we found that the status of immune cell infiltration was correlated with the level of IGF2BP2 gene expression. Our results provide supplementation at the molecular level for epigenetic regulation in HNSCC and insight into effective immunotherapy targets and strategies.

Microdosimetry is a tool for the investigation of microscopic energy deposition of ionizing radiation. This work used Caenorhabditis elegans as a model to estimate the microdosimetric deposition level at the 60 Co gamma radiation. Monte Carlo software PHITS was employed to establish irradiated nematodes model. The dose deposition of the entire body and gonad irradiated to 100 Gy was calculated. The injury levels of radiation were evaluated by the detection of biological indicators. The result of microdosimetric experiment suggested that the dose of whole body of nematodes was estimated to be 99.9 ± 57.8 Gy, ranging from 19.6 to 332.2 Gy. The dose of gonad was predicted to be 129.4 ± 558.8 Gy (9.5-6597 Gy). The result of biological experiment suggested that there were little changes in the length of nematodes after irradiation. However, times of head thrash per minute and the spawning yield in 3 consecutive days decreased 27.1% and 94.7%, respectively. Nematodes in the irradiated group displayed heterogeneity. Through contour analysis, trends of behavior kinematics and reproductive capacity of irradiated nematodes proved to be consistent with the dose distribution levels estimated by microdosimetric model. Finally, C . elegans presented a suitable combined model of microdosimetry and biology for studying radiation.

Aiming at the trajectory generation and optimization of mobile robots in complex and uneven environments, a hybrid scheme using mutual learning and adaptive ant colony optimization (MuL-ACO) is proposed in this paper. In order to describe the uneven environment with various obstacles, a 2D-H map is introduced in this paper. Then an adaptive ant colony algorithm based on simulated annealing (SA) is proposed to generate initial trajectories of mobile robots, where based on a de-temperature function of the simulated annealing algorithm, the pheromone volatilization factor is adaptively adjusted to accelerate the convergence of the algorithm. Moreover, the length factor, height factor, and smooth factor are considered in the comprehensive heuristic function of ACO to adapt to uneven environments. Finally, a mutual learning algorithm is designed to further smooth and shorten initial trajectories, in which different trajectory node sequences learn from each other to acquire the shortest trajectory sequence to optimize the trajectory. In order to verify the effectiveness of the proposed scheme, MuL-ACO is compared with several well-known and novel algorithms in terms of running time, trajectory length, height, and smoothness. The experimental results show that MuL-ACO can generate a collision-free trajectory with a high comprehensive quality in uneven environments.

Summary: The development of aggregation-induced emission (AIE) building block and deciphering its luminescence mechanism are of great significance. Here a feasible strategy for the construction of AIE unit based on E-Z isomerization (EZI) of exocyclic C=N double bond is proposed. Taking [1,2,4]thiadiazole[4,3-a]pyridine (TZP) derivative as an example, its aryl-substituted derivative (TZPP) shows obvious AIE character. The analysis of spectral data and theoretical calculations indicates that fast structural relaxation of TZPP in the emissive state plays a key role in a low fluorescence quantum yield in dilute solution, which should be caused by the small energy gap between locally excited (LE) state and twisted intramolecular charge transfer state. When in solid state, the bright emission with LE state characteristic reappears due to the large shift barrier of geometry transformation. As a potential building block for AIEgens with special heterocyclic structure, these findings would open up opportunities for developing various functional materials.

Summary: The Hippo signaling pathway maintains organ size and tissue homeostasis via orchestration of cell proliferation and apoptosis. How this pathway triggers cell apoptosis remains largely unexplored. Here, we identify NR4A1 as a target of the Hippo pathway that mediates the pro-apoptotic and anti-tumor effects of the Hippo pathway whereby YAP regulates the transcription, phosphorylation, and mitochondrial localization of NR4A1. NR4A1, in turn, functions as a feedback inhibitor of YAP to promote its degradation, thereby inhibiting the function of YAP during liver regeneration and tumorigenesis. Our studies elucidate a regulatory loop between NR4A1 and YAP to coordinate Hippo signaling activity during liver regeneration and tumorigenesis and highlight NR4A1 as a marker of Hippo signaling, as well as a therapeutic target for hepatocellular carcinoma.

Gap probability theory provides a theoretical equation to calculate fractional vegetation cover (FVC). However, the main algorithms used in present FVC products generation are still the linear mixture model and machine learning methods. The reason to limit the gap probability theory applied in the product algorithm is the availability and accuracy of leaf area index (LAI) and clumping index (CI) products. With the improvement of the LAI and CI products, it is necessary to assess whether the algorithm based on gap probability theory using the present products can improve the accuracy of FVC products. In this study, we generated the FVC estimates based on the gap probability theory (FVCgap) with a resolution of 500 m every 8 days for Europe. FVCgap estimates were validated with field FVC measurements of ImagineS from 2013 to 2015 for crop types. Two existing FVC products, Geoland2 Version1 (GEOV1) and Multisource data Synergized Quantitative remote sensing production system (MuSyQ), were used to inter-compare with the FVCgap estimates. FVCgap estimates showed a better agreement with field FVC measurements, with lowest root mean square error (RMSE) (0.1211) and bias (0.0224), than GEOV1 and MuSyQ FVC products. The inter-annual and seasonal variations of FVCgap estimates were also showed the most consistent with field measurements.

Sequence labeling is a common machine-learning task which not only needs the most likely prediction of label for a local input but also seeks the most suitable annotation for the whole input sequence. So it requires the model that is able to handle both the local spatial features and temporal-dependence features effectively. Furthermore, it is common for the length of the label sequence to be much shorter than the input sequence in some tasks such as speech recognition and handwritten text recognition. In this paper, we propose a kind of novel deep neural network architecture which combines convolution, pooling and recurrent in a unified framework to construct the convolutional recurrent neural network (CRNN) for sequence labeling tasks with variable lengths of input and output. Specifically, we design a novel CRNN to achieve the joint extraction of local spatial features and long-distance temporal-dependence features in sequence, introduce pooling along time to achieve a transform of long input to short output which will also reduce he model's complexity, and adopt Connectionist Temporal Classification (CTC) layer to achieve an end-to-end pattern for sequence labeling. Experiments on phoneme sequence recognition and handwritten character sequence recognition have been conducted and the results show that our method achieves great performance while having a more simplified architecture with more efficient training and labeling procedure.

Kompetitive allele-specific PCR (KASP) is a cost-effective single-step SNP genotyping technology, With an objective to enhance the marker repertoire and develop high efficient KASP-SNP markers in Chinese cabbage, we re-sequenced four Chinese cabbage doubled haploid (DH) lines, Y177-47, Y635-10, Y510-1 and Y510-9, and generated a total of more than 38.5 billion clean base pairs. A total of 827,720 SNP loci were identified with an estimated density of 3,217 SNPs/Mb. Further, a total of 387,354 SNPs with at least 30 bp to the next most adjacent SNPs on either side were selected as resource for KASP markers. From this resource, 258 (96.27%) of 268 SNP loci were successfully transformed into KASP-SNP markers using a Roche LightCycler 480-II instrument. Among these markers, 221 (85.66%) were co-dominant markers, 220 (85.27%) were non-synonymous SNPs, and 257 (99.6%) were newly developed markers. In addition, 53 markers were applied for genotyping of 34 Brassica rapa accessions. Cluster analysis separated these 34 accessions into three clusters based on heading types. The millions of SNP loci, a large set of resource for KASP markers, as well as the newly developed KASP markers in this study may facilitate further genetic and molecular breeding studies in Brassica rapa.

Tissue homeostasis and regeneration in the Drosophila midgut is regulated by a diverse array of signaling pathways including the Hippo pathway. Hippo signaling restricts intestinal stem cell (ISC) proliferation by sequestering the transcription co-factor Yorkie (Yki) in the cytoplasm, a factor required for rapid ISC proliferation under injury-induced regeneration. Nonetheless, the mechanism of Hippo-mediated midgut homeostasis and whether canonical Hippo signaling is involved in ISC basal proliferation are less characterized. Here we identify Lola as a transcription factor acting downstream of Hippo signaling to restrict ISC proliferation in a Yki-independent manner. Not only that Lola interacts with and is stabilized by the Hippo signaling core kinase Warts (Wts), Lola rescues the enhanced ISC proliferation upon Wts depletion via suppressing Dref and SkpA expressions. Our findings reveal that Lola is a non-canonical Hippo signaling component in regulating midgut homeostasis, providing insights on the mechanism of tissue maintenance and intestinal function.

Simultaneous Localization and Mapping (SLAM) is an essential feature in many applications of mobile vehicles. To solve the problem of poor positioning accuracy, single use of mapping scene, and unclear structural characteristics in indoor and outdoor SLAM, a new framework of tight coupling of dual lidar inertial odometry is proposed in this paper. Firstly, through external calibration and an adaptive timestamp synchronization algorithm, the horizontal and vertical lidar data are fused, which compensates for the narrow vertical field of view (FOV) of the lidar and makes the characteristics of vertical direction more complete in the mapping process. Secondly, the dual lidar data is tightly coupled with an Inertial Measurement Unit (IMU) to eliminate the motion distortion of the dual lidar odometry. Then, the value of the lidar odometry after correcting distortion and the pre-integrated value of IMU are used as constraints to establish a non-linear least-squares objective function. Joint optimization is then performed to obtain the best value of the IMU state values, which will be used to predict the state of IMU at the next time step. Finally, experimental results are presented to verify the effectiveness of the proposed method.

Orthotropic steel decks are widely used in the construction of steel bridges. Although there are many fatigue-evaluation methods stipulated by codes, unexpected fatigue cracks are still detected in some bridges. To justify whether the local finite element model commonly used in fatigue investigations on orthotropic decks can correctly instruct engineering practices, the Arlequin framework is applied in this paper to determine the full fatigue stress under traffic loads. The convergence on and validity of this application for orthotropic decks are checked. Results show that the Arlequin model for deck-fatigue analysis established in this paper tends to be an efficient method for complete fatigue stress acquisition, whereby the vulnerable sites of orthotropic steel decks under traffic loads are defined. Vehicles near the flexible components, such as hangers or cables, can have adverse effects on the fatigue durability of decks. Additionally, the total number of vehicles and their arrangement concentration also affect fatigue performance. Complex traffic conditions cannot be fully loaded in local models. Regardless of the gross bridge mechanics and deck deformation, the fatigue stress range is underestimated by about 30–40%. Such a difference in fatigue assessment seems to explain the premature cracks observed in orthotropic steel decks.

One of the top concerns for travelers when choosing public transportation is whether they can reach their destination in limited time and monetary cost on the basis of ensured reliability. However, the existing literature shows no studies on how to evaluate bi-objective multimodal accessibility under travel time uncertainty. In order to fill this research gap, this paper creates a multimodal super network based on smart card data in which the transfers among taxi, bus, and subway modes are developed and applied. Next, we propose a two-stage opportunity accessibility model to calculate bi-objective multimodal accessibility under travel time uncertainty. Then we propose a multimodal reliability path finding model and a reliability boundary convergence algorithm to solve this problem. Finally, we conduct a large-scale real-world case study. It is found that the impedance heterogeneity between different modes is significant, and multimodal travel has better accessibility than a unimodal one. Although multimodal accessibility decreases as the reliability increases, the advantage of multimodal over unimodal accessibility increases with reliability, and it can be improved up to 14.61% by multimodal transfers. This model can effectively guide traffic management departments to improve traffic accessibility in terms of time and cost and advise commuters to choose living places.

The inductive displacement sensor is widely used in active magnetic bearing (AMB) systems to detect rotor displacement in real time, and the performance of the sensor directly affects the performance of AMB. At present, most theoretical studies on the working principle of inductive displacement sensor are based on a traditional mathematical model, ignoring the influence of the core magnetic resistance and core eddy current, which will lead to a certain error between the theoretical analysis of the sensor output characteristics and the actual situation. In this regard, based on the theory of electromagnetic field and circuit, an improved theoretical model of the inductive sensor was established in this paper by introducing the complex permeability, by which the influence of core eddy current on magnetic field can be taken into account. In order to verify the improved model, an eight-pole radial self-inductive displacement sensor with an air gap of 1 mm was designed. Then the electromagnetic field of the designed sensor was simulated by a finite element software and the GW LCR-6100 measuring instrument was used to measure the changes of the inductance and resistance of the designed sensor core coils with the rotor displacement at 20–100 kHz. The results demonstrated that there is a good linear relationship between the impedance change of the sensor coils and the rotor displacement within the measurement range of −0.4 ~ +0.4 mm. At the same time, compared with the traditional model, the sensitivity of the improved theoretical model is closer to the results from FEM and experiment, and the accuracy of the sensitivity of the improved theoretical model can be approximately doubled, despite there are certain differences with the experimental situation. Therefore, the improved theoretical model considering complex permeability is of great significance for studying the influence of core eddy current on the coil impedance of sensor.

High-quality Normalized Difference Vegetation Index (NDVI) time series are essential in studying vegetation phenology, dynamic monitoring, and global change. Gap filling is the most important issue in reconstructing NDVI time series from satellites with high spatial resolution, e.g., the Landsat series and Chinese GaoFen-1/6 series. Due to the sparse revisit frequencies of high-resolution satellites, traditional reconstruction approaches face the challenge of dealing with large gaps in raw NDVI time series data. In this paper, a climate incorporated gap-filling (CGF) method is proposed for the reconstruction of Landsat historical NDVI time series data. The CGF model considers the relationship of the NDVI time series and climate conditions between two adjacent years. Climate variables, including downward solar shortwave radiation, precipitation, and temperature, are used to characterize the constrain factors of vegetation growth. Radial basis function networks (RBFNs) are used to link the NDVI time series between two adjacent years with variabilities in climatic conditions. An RBFN predicted a background NDVI time series in the target year, and the observed NDVI values in this year were used to adjust the predicted NDVI time series. Finally, the NDVI time series were recursively reconstructed from 2018 to 1986. The experiments were performed in a heterogeneous region in the Qilian Mountains. The results demonstrate that the proposed method can accurately reconstruct and generate continuous 30 m 8-day NDVI time series using Landsat observations. The CGF method outperforms traditional time series reconstruction methods (e.g., the harmonic analysis of time series (HANTS) and Savitzky-Golay (SG) filter methods) when the raw time series is contaminated with large gaps, which widely exist in Landsat images.