Research on Object Tracking Technology for Orderless and Blurred Movement under Complex Scenes

University of Technology Sydney. Faculty of Engineering and Information Technology.Visual tracking is widely found in anomaly behaviour detection, self-driving, virtual reality. Recent researches reported that classic methods, including the Tracking-Learning-Detection method, the Particle Filter and the mean shift, were surpassed by deep learning in accuracy and correlation filtering in speed. However, correlation filtering can be affected by boundary effects. The conventional correlation filtering fixes the size of its detection window. When its detection window only captures partial target images due to large and sudden scale variations, the correlation filtering fails to locate the tracked target. When the target is undergoing violent shaking, motion blurs and orderless movements appear along with it. The conventional correlation filtering locks itself in the previous position of the target, and hence, the target is out of the sight of the correlation filtering. In this case, the correlation filtering drifts or fails to track. Therefore, this thesis topic is to track single-objects under complex scenes with attributes of motion blurs, orderless motions and scale variations. The main research innovation is listed as follows. (1) An approach for searching orderless movements is designed in a generative-discriminative tracking model. To address the uncertain orderless movements, a coarse-to-fine tracking framework is adopted. A spatio-temporal correlation is learned for the detection in the subsequent frames. Experiments are conducted on public databases with orderless motion attributes to validate the robustness of the proposed approach. (2) A template matching method is proposed for tracking objects with motion blurs. An effective target motion model is designed to provide supplementary appearance features. A robust similarity measure is proposed to address the outliers caused by motion blurs. Our approach outperforms other approaches in a public benchmark database with motion blurs. (3) An ensemble framework is designed to tackle scale variations. The scale of a target is estimated based on the Gaussian Particle Filtering. A high-confidence strategy is used to validate the reliability of tracking results. Our approach with hand-crafted or CNN features outperforms the methods based on correlation filtering and deep learning in databases with scale variations. To sum up, this thesis addresses boundary effects, model drifts, fixed search windows and easily interfered hand-crafted features of objects. Different trackers are proposed for tracking single-objects with orderless movements, motion blurs and scale variations. As future work, our methods can be extended to using a neural network to further improve single-object tracking models

A Surrogate-Assisted Extended Generative Adversarial Network for Parameter Optimization in Free-Form Metasurface Design

Metasurfaces have widespread applications in fifth-generation (5G) microwave communication. Among the metasurface family, free-form metasurfaces excel in achieving intricate spectral responses compared to regular-shape counterparts. However, conventional numerical methods for free-form metasurfaces are time-consuming and demand specialized expertise. Alternatively, recent studies demonstrate that deep learning has great potential to accelerate and refine metasurface designs. Here, we present XGAN, an extended generative adversarial network (GAN) with a surrogate for high-quality free-form metasurface designs. The proposed surrogate provides a physical constraint to XGAN so that XGAN can accurately generate metasurfaces monolithically from input spectral responses. In comparative experiments involving 20000 free-form metasurface designs, XGAN achieves 0.9734 average accuracy and is 500 times faster than the conventional methodology. This method facilitates the metasurface library building for specific spectral responses and can be extended to various inverse design problems, including optical metamaterials, nanophotonic devices, and drug discovery

Exciton Assisted Deeply Subwavelength Nano-Photonics

The wave nature of light sets a fundamental diffraction limit that challenges confinement and control of light in nanoscale structures with dimensions significantly smaller than the wavelength. Here, we demonstrate van der Waals MoS_2 nano-photonic devices with dimensions as small as ~ \lambda/16 (~60 nm at 1000 nm excitation wavelength). This deep subwavelength light confinement is achieved by exploiting the coupling between MoS_2 excitons and photons. We validate deep subwavelength light control via far- and near-field measurements. Our near-field measurements reveal detailed imaging of excitation, evolution, and guidance of fields in MoS_2 nanodevices, whereas our far-field study examines highly confined integrated photonics. Exciton-driven nano-photonics at a fraction of a wavelength demonstrated here could dramatically reduce the size of integrated photonic devices and opto-electronic circuits with potential applications in optical information science and engineering.Comment: 39 pages, 32 figure

Sustained proliferation in cancer: mechanisms and novel therapeutic targets

Proliferation is an important part of cancer development and progression. This is manifest by altered expression and/or activity of cell cycle related proteins. Constitutive activation of many signal transduction pathways also stimulates cell growth. Early steps in tumor development are associated with a fibrogenic response and the development of a hypoxic environment which favors the survival and proliferation of cancer stem cells. Part of the survival strategy of cancer stem cells may manifested by alterations in cell metabolism. Once tumors appear, growth and metastasis may be supported by overproduction of appropriate hormones (in hormonally dependent cancers), by promoting angiogenesis, by undergoing epithelial to mesenchymal transition, by triggering autophagy, and by taking cues from surrounding stromal cells. A number of natural compounds (e.g., curcumin, resveratrol, indole-3-carbinol, brassinin, sulforaphane, epigallocatechin-3-gallate, genistein, ellagitannins, lycopene and quercetin) have been found to inhibit one or more pathways that contribute to proliferation (e.g., hypoxia inducible factor 1, nuclear factor kappa B, phosphoinositide 3 kinase/Akt, insulin-like growth factor receptor 1, Wnt, cell cycle associated proteins, as well as androgen and estrogen receptor signaling). These data, in combination with bioinformatics analyses, will be very important for identifying signaling pathways and molecular targets that may provide early diagnostic markers and/or critical targets for the development of new drugs or drug combinations that block tumor formation and progression

Impact of COVID-19 Nonpharmaceutical Interventions on Pneumococcal Carriage Prevalence and Density in Vietnam.

Nonpharmaceutical interventions (NPIs) implemented to contain SARS-CoV-2 have decreased invasive pneumococcal disease. Previous studies have proposed the decline is due to reduced pneumococcal transmission or suppression of respiratory viruses, but the mechanism remains unclear. We undertook a secondary analysis of data collected from a clinical trial to evaluate the impact of NPIs on pneumococcal carriage and density, drivers of transmission and disease, during the COVID-19 pandemic in Ho Chi Minh City, Vietnam. Nasopharyngeal samples from children aged 24 months were assessed in three periods - one pre-COVID-19 period (n = 1,537) and two periods where NPIs were implemented with increasing stringency (NPI period 1 [NPI-1, n = 307], and NPI period 2 [NPI-2, n = 262]). Pneumococci were quantified using lytA quantitative PCR and serotyped by DNA microarray. Overall, capsular, and nonencapsulated pneumococcal carriage and density were assessed in each NPI period compared with the pre-COVID-19 period using unadjusted log-binomial and linear regression. Pneumococcal carriage was generally stable after the implementation of NPIs. In contrast, overall pneumococcal carriage density decreased by 0.44 log10 genome equivalents/mL (95% confidence interval [CI]: 0.19 to 0.69) in NPI-1 and by 0.84 log10 genome equivalents/mL (95% CI: 0.55 to 1.13) in NPI-2 compared with the pre-COVID-19 period. Reductions in overall pneumococcal density were driven by reductions in capsular pneumococci, with no corresponding reduction in nonencapsulated density. As higher pneumococcal density is a risk factor for disease, the decline in density provides a plausible explanation for the reductions in invasive pneumococcal disease that have been observed in many countries in the absence of a substantive reduction in pneumococcal carriage. IMPORTANCE The pneumococcus is a major cause of mortality globally. Implementation of NPIs during the COVID-19 pandemic led to reductions in invasive pneumococcal disease in many countries. However, no studies have conducted a fully quantitative assessment on the impact of NPIs on pneumococcal carriage density, which could explain this reduction. We evaluated the impact of COVID-19 NPIs on pneumococcal carriage prevalence and density in 2,106 children aged 24 months in Vietnam and found pneumococcal carriage density decreased up to 91.5% after NPI introduction compared with the pre-COVID-19 period, which was mainly attributed to capsular pneumococci. Only a minor effect on carriage prevalence was observed. As respiratory viruses are known to increase pneumococcal carriage density, transmission, and disease, this work suggests that interventions targeting respiratory viruses may have the added benefit of reducing invasive pneumococcal disease and explain the reductions observed following NPI implementation

Chemically induced self-assembly of spherical and anisotropic inorganic nanocrystals

The self-assembly of inorganic nanoparticles is a research area of great interest aiming at the fabricationof unique mesostructured materials with intrinsic properties. Although many assembly strategies have been reportedover the years, chemically induced self-assembly remains one of the dominant approaches to achieve a high levelof nanoparticle organization. In this feature article we review the latest developments in assembly drivenby the active manipulation of nanoparticle surface

Gene Expression Profiling of Preovulatory Follicle in the Buffalo Cow: Effects of Increased IGF-I Concentration on Periovulatory Events

The preovulatory follicle in response to gonadotropin surge undergoes dramatic biochemical, and morphological changes orchestrated by expression changes in hundreds of genes. Employing well characterized bovine preovulatory follicle model, granulosa cells (GCs) and follicle wall were collected from the preovulatory follicle before, 1, 10 and 22 h post peak LH surge. Microarray analysis performed on GCs revealed that 450 and 111 genes were differentially expressed at 1 and 22 h post peak LH surge, respectively. For validation, qPCR and immunocytochemistry analyses were carried out for some of the differentially expressed genes. Expression analysis of many of these genes showed distinct expression patterns in GCs and the follicle wall. To study molecular functions and genetic networks, microarray data was analyzed using Ingenuity Pathway Analysis which revealed majority of the differentially expressed genes to cluster within processes like steroidogenesis, cell survival and cell differentiation. In the ovarian follicle, IGF-I is established to be an important regulator of the above mentioned molecular functions. Thus, further experiments were conducted to verify the effects of increased intrafollicular IGF-I levels on the expression of genes associated with the above mentioned processes. For this purpose, buffalo cows were administered with exogenous bGH to transiently increase circulating and intrafollicular concentrations of IGF-I. The results indicated that increased intrafollicular concentrations of IGF-I caused changes in expression of genes associated with steroidogenesis (StAR, SRF) and apoptosis (BCL-2, FKHR, PAWR). These results taken together suggest that onset of gonadotropin surge triggers activation of various biological pathways and that the effects of growth factors and peptides on gonadotropin actions could be examined during preovulatory follicle development

Impact of primary kidney disease on the effects of empagliflozin in patients with chronic kidney disease: secondary analyses of the EMPA-KIDNEY trial

Background: The EMPA KIDNEY trial showed that empagliflozin reduced the risk of the primary composite outcome of kidney disease progression or cardiovascular death in patients with chronic kidney disease mainly through slowing progression. We aimed to assess how effects of empagliflozin might differ by primary kidney disease across its broad population. Methods: EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA). Patients were eligible if their estimated glomerular filtration rate (eGFR) was 20 to less than 45 mL/min per 1·73 m2, or 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher at screening. They were randomly assigned (1:1) to 10 mg oral empagliflozin once daily or matching placebo. Effects on kidney disease progression (defined as a sustained ≥40% eGFR decline from randomisation, end-stage kidney disease, a sustained eGFR below 10 mL/min per 1·73 m2, or death from kidney failure) were assessed using prespecified Cox models, and eGFR slope analyses used shared parameter models. Subgroup comparisons were performed by including relevant interaction terms in models. EMPA-KIDNEY is registered with ClinicalTrials.gov, NCT03594110. Findings: Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and followed up for a median of 2·0 years (IQR 1·5–2·4). Prespecified subgroupings by primary kidney disease included 2057 (31·1%) participants with diabetic kidney disease, 1669 (25·3%) with glomerular disease, 1445 (21·9%) with hypertensive or renovascular disease, and 1438 (21·8%) with other or unknown causes. Kidney disease progression occurred in 384 (11·6%) of 3304 patients in the empagliflozin group and 504 (15·2%) of 3305 patients in the placebo group (hazard ratio 0·71 [95% CI 0·62–0·81]), with no evidence that the relative effect size varied significantly by primary kidney disease (pheterogeneity=0·62). The between-group difference in chronic eGFR slopes (ie, from 2 months to final follow-up) was 1·37 mL/min per 1·73 m2 per year (95% CI 1·16–1·59), representing a 50% (42–58) reduction in the rate of chronic eGFR decline. This relative effect of empagliflozin on chronic eGFR slope was similar in analyses by different primary kidney diseases, including in explorations by type of glomerular disease and diabetes (p values for heterogeneity all >0·1). Interpretation: In a broad range of patients with chronic kidney disease at risk of progression, including a wide range of non-diabetic causes of chronic kidney disease, empagliflozin reduced risk of kidney disease progression. Relative effect sizes were broadly similar irrespective of the cause of primary kidney disease, suggesting that SGLT2 inhibitors should be part of a standard of care to minimise risk of kidney failure in chronic kidney disease. Funding: Boehringer Ingelheim, Eli Lilly, and UK Medical Research Council