86 research outputs found
Normal Transformer: Extracting Surface Geometry from LiDAR Points Enhanced by Visual Semantics
High-quality estimation of surface normal can help reduce ambiguity in many
geometry understanding problems, such as collision avoidance and occlusion
inference. This paper presents a technique for estimating the normal from 3D
point clouds and 2D colour images. We have developed a transformer neural
network that learns to utilise the hybrid information of visual semantic and 3D
geometric data, as well as effective learning strategies. Compared to existing
methods, the information fusion of the proposed method is more effective, which
is supported by experiments.
We have also built a simulation environment of outdoor traffic scenes in a 3D
rendering engine to obtain annotated data to train the normal estimator. The
model trained on synthetic data is tested on the real scenes in the KITTI
dataset. And subsequent tasks built upon the estimated normal directions in the
KITTI dataset show that the proposed estimator has advantage over existing
methods
7-Fluoro-6-nitroÂquinazolin-4(3H)-one
The quinazolinone unit of the title compound, C8H4FN3O3, is essentially planar, with a maximum deviation of 0.0538â
(14)â
Ă
for the O atom. The nitro group is twisted by 12.0â
(3)° from the mean plane of the quinazolinone ring system. The crystal structure is stabilized by interÂmolecular NâHâŻO, CâHâŻN and CâHâŻO hydrogen bonds
Robust Speed Tracking Control for a Micro Turbine as a Distributed Energy Resource via Feedback Domination and Disturbance Observer
Synchronization of General Complex Networks with Hybrid Couplings and Unknown Perturbations
The issue of synchronization for a class of hybrid coupled complex networks with mixed delays (discrete delays and distributed delays) and unknown nonstochastic external perturbations is studied. The perturbations do not disappear even after all the dynamical nodes have reached synchronization. To overcome the bad effects of such perturbations, a simple but all-powerful robust adaptive controller is designed to synchronize the complex networks even without knowing a priori the functions and bounds of the perturbations. Based on Lyapunov stability theory, integral inequality Barbalat lemma, and Schur Complement lemma, rigorous proofs are given for synchronization of the complex networks. Numerical simulations verify the effectiveness of the new robust adaptive controller
A specialized metabolic network selectively modulates Arabidopsis root microbiota
Plant specialized metabolites have ecological functions, yet the presence of numerous uncharacterized biosynthetic genes in plant genomes suggests that many molecules remain unknown. We discovered a triterpene biosynthetic network in the roots of the small mustard plant Arabidopsis thaliana. Collectively, we have elucidated and reconstituted three divergent pathways for the biosynthesis of root triterpenes, namely thalianin (seven steps), thalianyl medium-chain fatty acid esters (three steps), and arabidin (five steps). A. thaliana mutants disrupted in the biosynthesis of these compounds have altered root microbiota. In vitro bioassays with purified compounds reveal selective growth modulation activities of pathway metabolites toward root microbiota members and their biochemical transformation and utilization by bacteria, supporting a role for this biosynthetic network in shaping an Arabidopsis-specific root microbial community
Screening and identification of the dominant antigens of the African swine fever virus
African swine fever is a highly lethal contagious disease of pigs for which there is no vaccine. Its causative agent African swine fever virus (ASFV) is a highly complex enveloped DNA virus encoding more than 150 open reading frames. The antigenicity of ASFV is still unclear at present. In this study, 35 proteins of ASFV were expressed by Escherichia coli, and ELISA was developed for the detection of antibodies against these proteins. p30, p54, and p22 were presented as the major antigens of ASFV, positively reacting with all five clinical ASFV-positive pig sera, and 10 pig sera experimentally infected by ASFV. Five proteins (pB475L, pC129R, pE199L, pE184L, and pK145R) reacted well with ASFV-positive sera. The p30 induced a rapid and strong antibody immune response during ASFV infection. These results will promote the development of subunit vaccines and serum diagnostic methods against ASFV
Large expert-curated database for benchmarking document similarity detection in biomedical literature search
Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe
Natural product discovery: studies on the phenolic antioxidants from Smilax Glyciphylla and the synthesis and formation of Guaiane Sesquiterpenoids.
The work within this thesis is positioned in the field of natural product (NP) chemistry and covers three main integrated studies along with some additional explorations. These studies not only included the isolation and characterisation of NP but also involved total syntheses of various NP and related derivatives and detailed mechanistic studies into potential routes of formation in nature. Given my naturally emerging zest for natural products, I have begun this thesis with a detailed discussion of the numerous syntheses of Taxol. This exemplar highlights not only why the field of natural products is so important, but also highlights the ever growing significance of total and semi-syntheses. The first major study investigated the phenolic profile and antioxidant activity of the leaves of the Australian native plant Smilax glyciphylla. Along with the sweet principle glycyphyllin A, seven phenolic compounds including two new dihydrochalcone rhamnosides, glycyphyllin B and C, and five known flavonoids were isolated from the ethanolic extract of the leaves of Smilax glyciphylla for the first time. The structures of these compounds were characterised by spectroscopic methods including UV, HRMS, 1D and 2D NMR. In vitro antioxidant capacity tests employing the FRAP and DPPH assays indicated that three of the isolated compounds exhibited potent antioxidant activity and are the key phenolics responsible for the high antioxidant activity of the leaf extract of S. glyciphylla. The second major study focused on the synthesis of guaiane type sesquiterpenoids via the diastereoselective epoxidation of guaiol and realized by manipulating the types of remote protecting groups on the isopropanoyl side chain, choice of solvent and epoxidising reagent. This stragety allowed for a concise stereoselective synthesis of a range of guaiane-type sesquiterpenoids including the natural products guaia-4(5)-en-11-ol, guaia-5(6)-en-11-ol, and aciphyllene and epimers of the recently isolated natural products, 1-epi-guaia-4(5)-en-11-ol, 1-epi-aciphyllene and 1-epi-melicodenone C and E in up to 31% yield within 11 steps. The third study explored the autoxidation of α-guaiene and the mechanisms involved. Over a dozen sesquiterpenoids including natural rotundone, corymbolone and the C7 epimers of natural chabrolidione A and several unstable hydroperoxide intermediates were isolated from the autoxidation products of α-guaiene. Their structures were elucidated on the basis of spectroscopic data along with the synthesis of authentic compounds. Detailed mechanistic studies have allowed many of the mechanisms involved in the formation of these downstream oxidation products to be elucidated. Together with the above main studies, several deuterium labelled precursors including dâ-α- guaiene, dâ
-(2R/2S)-rotundols, dâ
-α-bulnesone, dâ-α-bulnesene and dâ
-2R-bulnesol were synthesised and used as internal standards to develop a robust analytical method (SIDA) to monitor the transformation of certain precursors to the sesquiterpneoid fragrances rotundone and 2R-bulnesol. A total of five publications support my research works herein and are included as the main research chapters of this thesis.Thesis (Ph.D.) -- University of Adelaide, School of Agriculture, Food and Wine, 201
Unearthing a sesterterpene biosynthetic repertoire in the Brassicaceae through genome mining reveals convergent evolution.
Robust Speed Tracking Control for a Micro Turbine as a Distributed Energy Resource via Feedback Domination and Disturbance Observer
Micro turbine (MT) is characterized with complex dynamics, parameter uncertainties, and variable working conditions. In this paper, a novel robust controller is investigated for a single-shaft micro turbine as a distributed energy resource by integrating a feedback domination control technique and a feedforward disturbance compensation. An active estimation process of the mismatched disturbances is firstly enabled by constructing a disturbance observer. Secondly, we adopt a feedback domination technique, rather than popularly used feedback linearization methods, to handle the system nonlinearities. In an explicit way, the composite controllers are then derived by recursive design based on Lyapunov theory while a global input-to-state stability can be guaranteed. Abundant comparison simulation results are provided to demonstrate the effectiveness of the proposed scheme, which not only perform an improved closed-loop control performance comparing to all existing results, but also render a simple control law which will ease its practical implementation
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