Self-Supervised Deep Visual Odometry with Online Adaptation

Self-supervised VO methods have shown great success in jointly estimating camera pose and depth from videos. However, like most data-driven methods, existing VO networks suffer from a notable decrease in performance when confronted with scenes different from the training data, which makes them unsuitable for practical applications. In this paper, we propose an online meta-learning algorithm to enable VO networks to continuously adapt to new environments in a self-supervised manner. The proposed method utilizes convolutional long short-term memory (convLSTM) to aggregate rich spatial-temporal information in the past. The network is able to memorize and learn from its past experience for better estimation and fast adaptation to the current frame. When running VO in the open world, in order to deal with the changing environment, we propose an online feature alignment method by aligning feature distributions at different time. Our VO network is able to seamlessly adapt to different environments. Extensive experiments on unseen outdoor scenes, virtual to real world and outdoor to indoor environments demonstrate that our method consistently outperforms state-of-the-art self-supervised VO baselines considerably.Comment: Accepted by CVPR 2020 ora

Mitigating shrinkage in ultra-high performance concrete using MgO expansion agents with different activity levels

To mitigate the shrinkage properties of ultra-high performance concrete (UHPC), MgO expansion agents (MEAs) with different activity levels (R-MEA, M-MEA, and S-MEA) were prepared and incorporated into UHPC. The effect of MEA activity on the mechanical properties and volumetric stability of UHPC were evaluated by using hydration heat tests, XRD-Rietveld quantitative analysis, MIP, X-CT and SEM. The results showed that MEA addition reduces the mechanical properties of UHPC, especially at high activity levels. However, it is beneficial for compensating early shrinkage. By combining MIP and X-CT analyses, it was found that MEA effectively increases the porosity of UHPC, with R-MEA (with the strongest activity) increasing it most. The w/b ratio had a greater effect on MEA hydration than the activity level. At lower w/b ratios, R-MEA reduced autogenous shrinkage even less effectively than M-MEA. Considering both the mechanical properties and shrinkage-reducing effect, it is recommended to prepare shrinkage-reducing UHPC with a w/b ratio of 0.18 and moderately reactive M-MEA

Genome-wide analysis of long non-coding RNAs (lncRNAs) in tea plants (Camellia sinensis) lateral roots in response to nitrogen application

Tea (Camellia sinensis) is one of the significant cash crops in China. As a leaf crop, nitrogen supply can not only increase the number of new shoots and leaves but also improve the tenderness of the former. However, a conundrum remains in science, which is the molecular mechanism of nitrogen use efficiency, especially long non-coding RNA (lncRNA). In this study, a total of 16,452 lncRNAs were identified through high-throughput sequencing analysis of lateral roots under nitrogen stress and control conditions, of which 9,451 were differentially expressed lncRNAs (DE-lncRNAs). To figure out the potential function of nitrogen-responsive lncRNAs, co-expression clustering was employed between lncRNAs and coding genes. KEGG enrichment analysis revealed nitrogen-responsive lncRNAs may involve in many biological processes such as plant hormone signal transduction, nitrogen metabolism and protein processing in endoplasmic reticulum. The expression abundance of 12 DE-lncRNAs were further verified by RT-PCR, and their expression trends were consistent with the results of RNA-seq. This study expands the research on lncRNAs in tea plants, provides a novel perspective for the potential regulation of lncRNAs on nitrogen stress, and valuable resources for further improving the nitrogen use efficiency of tea plants

Disrupted Cerebellar Connectivity With the Central Executive Network and the Default-Mode Network in Unmedicated Bipolar II Disorder

Objective: Bipolar disorder (BD) is a common psychiatric disease. Although structural and functional abnormalities of the cerebellum in BD patients have been reported by recent neuroimaging studies, the cerebellar-cerebral functional connectivity (FC) has not yet been examined. The present study aims to investigate the FC between the cerebellum and cerebrum, particularly the central executive network (CEN) and the default-mode network (DMN) in bipolar II disorder (BD II).Methods: Ninety-four patients with unmedicated BD II depression and 100 healthy controls (HCs) underwent the resting-state functional magnetic resonance imaging. Seed-based connectivity analyses were performed using cerebellar seeds previously identified as being involved in the CEN (bilateral Crus Ia) and DMN (bilateral Crus Ib).Results: Compared with HCs, BD II depression patients appeared decreased FC in the right Crus Ia-left dorsal lateral prefrontal cortex (dlPFC) and -left anterior cingulate cortex (ACC), the right Crus Ib-left medial prefrontal cortex (mPFC), -left middle temporal gyrus (MTG), and -left inferior temporal gyrus (ITG). No altered FC between the left Crus Ia or Crus Ib and the cerebral regions was found.Conclusions: Patients with BD II depression showed disrupted FC between the cerebellum and the CEN (mainly in the left dlPFC and ACC) and DMN (mainly in the left mPFC and temporal lobe), suggesting the significant role of the cerebellum-CEN and -DMN connectivity in the pathogenesis of BD

Effects of Steel Slag Powder and Expansive Agent on the Properties of Ultra-High Performance Concrete (UHPC): Based on a Case Study

In view of the performance requirements of mass ultra-high performance concrete (UHPC) for the Pang Gong bridge steel cable tower in China, the UHPC incorporating of steel slag powder and hybrid expansive agents is optimized and prepared. The effects of steel slag powder and hybrid expansive agents on the hydration characteristics and persistent shrinkage of UHPC are investigated. The results indicate that 15 wt.% steel slag powder and 5 wt.% hybrid expansive agents can effectively reduce the drying shrinkage deformation of UHPC with a slight decrease of strength. Heat flow calorimetry results show that the incorporation of steel slag powder and expansive agents decreases the hydration heat at three days. Moreover, the obtained adiabatic temperature rise of UHPC is 59.5 °C and the total shrinkage value at 180 days is 286 με. The hydration heat release changes of large volume UHPC in the steel-concrete section of cable tower is agreed with the result of adiabatic temperature rise in the laboratory

The Influence of Mixing Degree between Coarse and Fine Particles on the Strength of Offshore and Coast Foundations

The variability in strata of foundation soil in marine environments makes it tedious to design foundations for offshore structures. Hence, it is essential to investigate and evaluate the strength properties of this type of soil. This study investigates the variability of the soil strata (which is quantified by the index of the mixing degree between coarse and fine particles) and its influence on the stability of the soil by mixing coarse and fine particles at varying proportions. A series of discrete element method triaxial shear tests were conducted on binary geotechnical mixtures with a varying proportion of coarse content (25%, 50% and 75%) and different mixing degrees (ranging from 0.0 to 1.0). The macroscopic results show that the peak shear strength increases with an increase in mixing degree, and the increase is more obvious with increasing coarse content, while the critical shear strength is independent of the mixing degree. The main evaluation of the number, mean normal force and distribution of the coarse–fine (cf) contact helps to clarify the meso-mechanisms that result in the variations in peak shear strength and critical shear strength with mixing degree. The increase in the peak strength may primarily be due to the increased number and globalized distribution of coarse–fine contact. However, the decreased contact force of coarse–fine contact counterbalances the strength gain due to the increased number and globalized distribution, which maintain the stability of the critical strength

Effect of Electrochemical Pre-Oxidation for Mitigating Ultrafiltration Membrane Fouling Caused by Extracellular Organic Matter

Algal extracellular organic matter (EOM) will cause grievous membrane fouling during the filtration of algae-laden water; hence, boron-doped diamond (BDD) anodizing was selected as the pretreatment process before the ultrafiltration, and the EOM fouling mitigation mechanism and the purification efficiency were systematically investigated. The results showed that BDD oxidation could significantly alleviate the decline of membrane flux and reduce membrane fouling, and the effect was more notable with an increase in oxidation time. Less than 10% flux loss happened when oxidation duration was 100 min. The dominant fouling model was gradually replaced by standard blocking. BDD anodizing preferentially oxidizes hydrophobic organic matter and significantly reduces the DOC concentration in EOM. The effluent DOC was reduced to less than 1 mg/L when 100 min of BDD anodizing was applied. After the pre-oxidation of BDD, the zeta potential and interfacial free energy, including the cohesive and adhesive free energy, were all constantly increasing, which implied that the pollutants would agglomerate and deposit, and the repulsion between foulants and the ultrafiltration membrane was augmented with the extensive oxidation time. This further confirms the control of BDD on membrane fouling. In addition, the BDD anodizing coupled ultrafiltration process also showed excellent performance in removing disinfection by-product precursors

An INS-UWB Based Collision Avoidance System for AGV

As a highly automated carrying vehicle, an automated guided vehicle (AGV) has been widely applied in various industrial areas. The collision avoidance of AGV is always a problem in factories. Current solutions such as inertial and laser guiding have low flexibility and high environmental requirements. An INS (inertial navigation system)-UWB (ultra-wide band) based AGV collision avoidance system is introduced to improve the safety and flexibility of AGV in factories. An electronic map of the factory is established and the UWB anchor nodes are deployed in order to realize an accurate positioning. The extended Kalman filter (EKF) scheme that combines UWB with INS data is used to improve the localization accuracy. The current location of AGV and its motion state data are used to predict its next position, decrease the effect of control delay of AGV and avoid collisions among AGVs. Finally, experiments are given to show that the EKF scheme can get accurate position estimation and the collisions among AGVs can be detected and avoided in time