Hierarchical Convolutional Neural Networks for Vision-Based Feature Detection

University of Technology Sydney. Faculty of Engineering and Information Technology.This thesis is devoted to the problem of feature detection, an essential pre-requisite to machine vision applications. The key to feature detection rests with the development of effective algorithms, which could incorporate machine intelligence to achieve such attributes as accuracy in pixel-wise terms and robustness against structural and stochastic uncertainty. To this end, a hierarchical convolutional neural network (HCNN) with feature preservation, is proposed to present the probability map of feature candidates. Specifically, the abstraction of features in consideration is enhanced by bidirectional branch nets. The outputs of previous convolutional blocks are unified and concatenated to the current ones to reduce the visual impairment in the up/down-sampling stage and the overall information loss. Besides, an Intercontrast-based Iterative Thresholding (IIT) approach is developed for the proposed network hierarchy at the post-processing step, whereby patterns of interest are clustered within the probability map of identified features and generate a solid feature map. To effectively overcome uncertainty, network prediction is conducted by a customised variational inference. Here, deterministic weights are converted into a probability distribution with learnable hyperparameters to adapt the interference of outliers and alleviate overfitting. Furthermore, to incorporate Bayesian modelling into high-level tasks such as resource allocation, an additional module for Gaussian heatmap is developed to meticulously present the location of the geometrical target. Then, a physics-driven training scenario is designed to gradually shrink the benchmark kernel for continuous calibration to avoid local minima. In summary, the contributions of this thesis include 1. a new hierarchical network proposed for feature detection, whereby the abstractions of the image can be bidirectionally extracted to improve prediction performance, 2. unsupervised and gradient-sharing approaches incorporating Bayesian inference in the proposed network for enhancing its uncertainty handling capability, 3. a new training strategy for representation learning via spatial indexing to link the primary geometrical features with quantitative allocation, and 4. an average F-measure proposed for evaluation of robustness along with other metrics for performance evaluation. An extensive comparison with existing techniques is conducted using various datasets and evaluation criteria for evaluation. Experimental results demonstrate the crack detection merits of the proposed architecture over existing techniques applied to numerous images. To illustrate generality of the developed network architecture, additional tests are also conducted for various applications, including salient object detection, anthropometric and facial landmark detection, and measurement retrieval. The results obtained show the scalability and robustness of the proposed model to medium and high-level image processing tasks

Bayesian dense inverse searching algorithm for real-time stereo matching in minimally invasive surgery

This paper reports a CPU-level real-time stereo matching method for surgical images (10 Hz on 640 * 480 image with a single core of i5-9400). The proposed method is built on the fast ''dense inverse searching'' algorithm, which estimates the disparity of the stereo images. The overlapping image patches (arbitrary squared image segment) from the images at different scales are aligned based on the photometric consistency presumption. We propose a Bayesian framework to evaluate the probability of the optimized patch disparity at different scales. Moreover, we introduce a spatial Gaussian mixed probability distribution to address the pixel-wise probability within the patch. In-vivo and synthetic experiments show that our method can handle ambiguities resulted from the textureless surfaces and the photometric inconsistency caused by the Lambertian reflectance. Our Bayesian method correctly balances the probability of the patch for stereo images at different scales. Experiments indicate that the estimated depth has higher accuracy and fewer outliers than the baseline methods in the surgical scenario

Characterization and Control of Pore Structural Heterogeneity for Low-Thermal-Maturity Shale: A Case Study of the Shanxi Formation in the Northeast Zhoukou Depression, Southern North China Basin

The Shanxi Formation layers in the northeast of the Zhoukou Depression, Southern North China Basin, mainly consist of dark mudstone interbed with tight stone and widely developed coal seam, which is a promising target for unconventional oil and gas exploration. A series of geochemical and geological methods were used to analyze the characterization and controls of the pores structural heterogeneity in low-thermal-maturity shale. These methods include the Rock-Eval analysis, total organic carbon (TOC) analysis, scanning electron microscope observation with an energy-dispersive spectrometer (SEM-EDS), X-ray diffraction, and low-pressure N2 adsorption. Based on these measurements, the pore diameter, specific surface area (SSA), and fractal dimension (D) were calculated, and then, the pore structure heterogeneity was analyzed. The result shows the pores of Shanxi Formation shale are mainly interparticle pores with low porosity and low permeability, and the pore structure is highly complex. The average fractal dimension of the micropore and the macropore are both 2.77, but that of the mesopore is 2.65, indicating a less-complex mesopore structure than the micropore and macropore. The S2, S1, and TOC exhibit no clear correlation with SSA and fractal dimension of pores, which proved the little impact of organic matter on the heterogeneity of pore structure in the low-maturity shale of the research area. The illite has a strong effect on the pore structural heterogeneity of Shanxi Formation shale. The samples with high content of illite show higher SSA, better physical properties, and low fractal dimension, reflecting low pore structural heterogeneity. However, the quartz and clay minerals show a slight correlation with SSA and no obvious relationship with the fractal dimension, indicating a little effect of them on the pore structure heterogeneity. The pore structural heterogeneity decreases along with the increase in porosity, while the permeability influenced by a variety of reasons under the compaction shows a poor relationship with SSA and fractal dimension. On the whole, the pore structural heterogeneity decreases for low-thermal-maturity shale with high content of illite and high porosity, which should be considered to be the better unconventional oil and gas reservoir in the research area

SRSF5‐Mediated Alternative Splicing of M Gene is Essential for Influenza A Virus Replication: A Host‐Directed Target Against Influenza Virus

Abstract: Splicing of influenza A virus (IAV) RNA is an essential process in the viral life cycle that involves the co‐opting of host factors. Here, it is demonstrated that induction of host serine and arginine‐rich splicing factor 5 (SRSF5) by IAV facilitated viral replication by enhancing viral M mRNA splicing. Mechanistically, SRSF5 with its RRM2 domain directly bounds M mRNA at conserved sites (M mRNA position 163, 709, and 712), and interacts with U1 small nuclear ribonucleoprotein (snRNP) to promote M mRNA splicing and M2 production. Mutations introduced to the three binding sites, without changing amino acid code, significantly attenuates virus replication and pathogenesis in vivo. Likewise, SRSF5 conditional knockout in the lung protects mice against lethal IAV challenge. Furthermore, anidulafungin, an approved antifungal drug, is identified as an inhibitor of SRSF5 that effectively blocks IAV replication in vitro and in vivo. In conclusion, SRSF5 as an activator of M mRNA splicing promotes IAV replication and is a host‐derived antiviral target

The complete mitochondrial genome of an important root crop cassava (Manihot esculenta)

Manihot esculenta (M. esculenta) is the most important root crop in the world, which has high potential carbohydrate production and adaptability to diverse environments. In this study, we assembled the complete mitochondrial (mt) DNA sequence of M. esculenta into a circular genome of length 682,840 bp, comprising of 32 protein-coding genes, 17 tRNA genes, and three rRNA genes. A neighbour-joining phylogenetic tree was constructed based on 25 plant species and 23 conserved protein-coding genes, suggesting that M. esculenta is evolutionarily close to the Salicaceae plants (Populus tremula and Salix suchowensis) in the same Malpighiales order. The complete mt genome of M. esculenta will provide more desirable information for better understanding the genomic breeding of cassava

The Impact of Green Open Space on Community Attachment—A Case Study of Three Communities in Beijing

With the development of urbanization in China, the quality of urban life and community attachment have attracted increasing attention of the governments and society. Existing research on community attachment has mainly examined how individual characteristics affect community attachment, such as their length of residence and socioeconomic status. However, some scholars have become interested in exploring the effects of green open space on community attachment. This research examined whether the distribution of green open space in communities had significant effects on community attachment, and both the impact and path were also investigated. Through a questionnaire survey, relevant data in three communities of Beijing were collected. The impact of green open space layout on community attachment was evaluated by using hierarchical regression, and the impact path was examined by using a structural equation model. The results showed that green open space in a community had significant effects on the community attachment, with centralized green open space layout having a greater effect than that of dispersed green open space. Moreover, the more complex the shape of green open space is, the greater the impact is. The degree of satisfaction with the green open space had direct effects on the community attachment. The accessibility and perceived area of green open space could indirectly have an impact on the community attachment by affecting the degree of satisfaction with the green open space. Nevertheless, residents’ perceived importance of green open space could affect the community attachment directly and indirectly, as it affects the degree of satisfaction

Spatio-Temporal Evolution and Coupled Coordination of LUCC and ESV in Cities of the Transition Zone, Shenmu City, China

This study investigates the spatial-temporal evolution and the interconnectedness of land use/cover change (LUCC) and ecosystem service value (ESV). Such analysis can offer theoretical guidance and support decision-making for sustainable land resource development and ecological preservation in ecologically vulnerable cities within the Loess Plateau-Maowusu Desert transition zone. Utilizing Landsat data spanning 2000–2020, the paper examines the synergistic relationship between ESV and land use intensity in Shenmu City through bivariate spatial autocorrelation and the coupled coordination degree (CCD) model. Our findings indicate that the area of construction land in Shenmu City experienced the most significant change between 2000 and 2020, with a dynamism rate of 76.8%. This shift resulted in a decrease in the total ESV, from RMB 10.059 billion in 2000 to RMB 9.906 billion in 2020. The bivariate spatial autocorrelation analysis reveals a significant positive spatial correlation between ESV and land use intensity, while the CCD levels for both demonstrate a fluctuating yet overall upward trend over the 20-year period. The paper uncovers the spatial-temporal evolution of LUCC and ESV in Shenmu City along with their interconnected dynamics. The research outcomes can contribute valuable insights for reinforcing land resource utilization and promoting sustainable regional development within cities in the Loess Plateau-Maowusu Desert transition zone

Body Fat Percentage and Normal-Weight Obesity in the Chinese Population: Development of a Simple Evaluation Indicator Using Anthropometric Measurements

Few studies explore the associations between body fat percentage (BFP) prediction and evaluation indicators for Chinese with normal-weight obesity. We aimed to explore convenient and cost-free BFP evaluation indicators to routinely monitor BFP status in Chinese patients with normal-weight obesity. Participants (N = 164) were divided into three groups according to body mass index (BMI) and BFP: normal-weight lean, normal-weight obese, and overweight and obese. Differences in body composition and circumference were compared to examine the relationship between BFP and circumference, determine a simple evaluation indicator reflecting BFP, and identify cutoff values for normal-weight obesity circumference. Significant differences in body composition and circumference were observed among the three groups. The correlation between thigh/height, hip/height, (hip + waist)/height, and BFP was stronger than that with BMI. The (hip + waist)/height ratio was the indicator most reflective of BFP (95% confidence interval: 3.004–9.018, p = 0.013), and a ratio above 1.115 (95% confidence interval: 0.936–0.992, p < 0.001) was predictive of normal-weight obesity. Furthermore, we suggest that the upper value for a normal BMI in Chinese individuals be lowered to 23.4 kg/m2 (95% confidence interval: 0.984–0.999, p < 0.001). The (hip + waist)/height ratio can be used with body mass index for a more accurate evaluations of BFP abnormalities and health risks

Cadmium stannate conductive layer with high optical transmittance and tunable work function

200 nm cadmium stannate (Cd _2 SnO _4 ) transparent conductive layer films with a sheet resistance of 6.35 Ω/sq and resistivity of 1.27 × 10 ^−4 Ω · cm are deposited by magnetron sputtering coupling with adjustable target bias voltage followed by 620 °C 30 min annealing. The lowest resistivity of Cd _2 SnO _4 films reported before was 1.28 × 10 ^−4 Ω · cm, achieved with 510 nm Cd _2 SnO _4 . The average transmission rate of 200 nm sputtering Cd _2 SnO _4 films between 400–800 nm is 94%. The deposition rate increase target bias voltage can the and electrical performance of Cd _2 SnO _4 films. The surface work function of Cd _2 SnO _4 films is also tunable by target bias voltage. The Cd _2 SnO _4 phonon spectrum and phonon density of states combined with Raman microscope shows the Cd _2 SnO _4 films with most ideal electric properties has a identical phonon response. XPS shows the chemical component of as-deposited Cd _2 SnO _4 films and Cd _2 SnO _4 films after annealing with 120 V target bias voltage is Cd _2.03 SnO _6.36 and Cd _1.25 SnO _4.15 , respectively, which is contrary to the general conclusions that interstitial cadmium atoms and oxygen vacancies are the main self-doping defects in Cd _2 SnO _4 films