Optimal surface profile design of deployable mesh reflectors via a force density strategy

Based on a force density method coupled with optimal design of node positions, a novel approach for optimal surface profile design of mesh reflectors is presented. Uniform tension is achieved by iterations on coefficients of force density. The positions of net nodes are recalculated in each iteration so that the faceting RMS error of the reflector surface is minimized. Applications of both prime focus and offset configurations are demonstrated. The simulation results show the effectiveness of the proposed approach

A chemoenzymatic route to the (+)-form of the amaryllidaceae alkaloid narseronine

The enzymatically derived and enantiopure cis-1,2-dihydrocatechol 1 has been converted, over 14 one-pot operations, into the (+)-form of the alkaloid narseronine (2). The present study, which complements earlier work that established a route from metabolite 1 to enantiomer (–)-2, involves an N-bromosuccinimide/tri-n-butyltin hydride-mediated cyclisation reaction to construct the unsaturated B-ring lactone of the target compound.We thank the Australian Research Council and the Institute of Advanced Studies for generous financial support

The effect of soil resistivity on the LV surge environment

Student Number : 0418388R - MSc(Eng) research report - School of Electrical and Information Engineering - Faculty of Engineering and the Built EnvironmentDue to the high soil resistivities and high frequency of lightning strikes in South Africa, the background theory about the effect of soil resistivity on the LV surge environment is important, but the present local and international standards do not give reasonable explanations for this effect. The previously published experimental results and research results related to this effect were investigated. From these investigations, it can be shown that the soil resistivity can affect surge generation, surge propagation and surge attenuation significantly. Also, soil resistivity plays a main role in the lightning surges caused by both direct strikes and indirect strikes, which can cause severe damage to the LV distribution system. Soil resistivity also has a significant impact on the resistance of an earth electrode

Robusni algoritam praćenja mjerenjem smjera pomoću strukturiranog potpunog Kalmanovog filtra zasnovanog na metodi najmanjih kvadrata

A nonlinear approach called the robust structured total least squares kalman filter (RSTLS-KF) algorithm is proposed for solving tracking inaccuracy caused by outliers in bearings-only multi-station passive tracking. In that regard, the robust extremal function is introduced to the weighted structured total least squares (WSTLS) location criterion, and then the improved Danish equivalent weight function is built on the basis, which can identify outliers automatically and reduce the weight of the polluted data. Finally, the observation equation is linearized according to the RSTLS location result with the structured total least norm (STLN) solution. Hence location and velocity of the target can be given by the Kalman filter. Simulation results show that tracking performance of the RSTLS-KF is comparable or better than that of conventional algorithms. Furthermore, when outliers appear, the RSTLS-KF is accurate and robust, whereas the conventional algorithms become distort seriously.U ovome radu predložen je nelinearni pristup za rješavanje netočnosti uzrokovanih netipčnim vrijednostima kod praćenja mjerenjem smjera pasivnim senzorima s više stanica. Pristup je zasnovan na robusnom strukturiranom potpunom Kalmanovom filtru zasnovanom na metodi najmanjih kvadrata. Pomoću predložene metode moguće je estimirati položaj i brzinu praćenog objekta. Simulacijski rezultati pokazuju da je učinkovitost predloženog algoritma jednaka ili bolja od konvencionalnih algoritama. Nadalje, u prisustvu netipčnih vrijednosti mjerenja, predloženi algoritam zadržava točnost i robusnost, dok konvencionalni algoritmi pokazuju pogreške u estimaciji

Chemoenzymatic Total Syntheses of Some Biologically Relevant Scaffolds in Homochiral Form

Since time immemorial certain plants and/or extracts thereof have been used for the treatment of various diseases. The utility of such materials is normally attributed to the specific chemical components within the source plants. For this reason, chemists have sought to isolate the active principals for evaluation and the more efficacious ones have been the subject of synthetic studies. Since biological activity is normally embodied in one but not the other enantiomeric form of homochiral natural products, the selective synthesis of such species has become an important aspect of such endeavours. The use of chirons for such purposes has often provided a very effective means of obtaining a given enantiomeric form of the target compound. Since various enantiomerically pure cis-1,2-dihydrocatechols (such as compounds 3c and 3d) have become available in large quantity via the whole-cell biotransformation of certain halogenated arenes they have become particularly important starting materials in natural product synthesis. This is all the more so with the recognition that the “hidden symmetry elements” embodied within such chirons can allow for the generation of either enantiomeric form of a target compound from a single enantiomeric form of such starting materials, a process sometimes termed enantiodivergent synthesis. In this thesis, approaches to the syntheses of the biologically significant systems such as ent-kirkamide, (+)-lycorine, and (+)-narseronine are described by using enzymatically generated cis-1,2-dihydrocatechols.Specifically, the first chapter of this thesis analyses the current state-of-play with respect to the generation of cis-1,2-dihydrocatechols of the general form 3 and their application in chemical synthesis, especially as this applies to the assembly of biologically active natural products and related systems. The approaches employed in establishing a near-to-complete total synthesis of ent-kirkamide from (1S,2S)-3-bromocyclohexa-3,5-diene-1,2-diol (3c) and its iodo-counterpart 3d are described in Chapter Two. This is preceded by a commentary on the origins, structural elucidation and biological properties of the natural product (viz. kirkamide) along with a description of the only total synthesis of this compound reported to date. A chemoenzymatic approach to the total synthesis of (+)-lycorine using (1S,2S)-3-bromocyclohexa-3,5-diene-1,2-diol (3c) as starting material is discussed in the third chapter. This is preceded by a description of the synthetic approaches (reported by others) to either the (+)- or (–)-form of lycorine. The work reported in the fourth chapter on the successful synthesis of (+)-narseronine from the bromobenzene-derived metabolite 3c serves to emphasize the utility of cis-1,2-dihydrocatechols as chiral building blocks. Since earlier work within the Banwell Group had resulted in the development of a synthesis of (–)-narseronine from the same starting material, the present work serves to emphasize the capacity for undertaking enantiodivergent syntheses using the “pseudo-symmetric” cis-1,2-dihydrocatechol 3c as starting material

Knowledge Matters: Radiology Report Generation with General and Specific Knowledge

Automatic radiology report generation is critical in clinics which can relieve experienced radiologists from the heavy workload and remind inexperienced radiologists of misdiagnosis or missed diagnose. Existing approaches mainly formulate radiology report generation as an image captioning task and adopt the encoder-decoder framework. However, in the medical domain, such pure data-driven approaches suffer from the following problems: 1) visual and textual bias problem; 2) lack of expert knowledge. In this paper, we propose a knowledge-enhanced radiology report generation approach introduces two types of medical knowledge: 1) General knowledge, which is input independent and provides the broad knowledge for report generation; 2) Specific knowledge, which is input dependent and provides the fine-grained knowledge for report generation. To fully utilize both the general and specific knowledge, we also propose a knowledge-enhanced multi-head attention mechanism. By merging the visual features of the radiology image with general knowledge and specific knowledge, the proposed model can improve the quality of generated reports. Experimental results on two publicly available datasets IU-Xray and MIMIC-CXR show that the proposed knowledge enhanced approach outperforms state-of-the-art image captioning based methods. Ablation studies also demonstrate that both general and specific knowledge can help to improve the performance of radiology report generation.Comment: Medical Image Analysi

PhotoRedshift-MML: a multimodal machine learning method for estimating photometric redshifts of quasars

We propose a Multimodal Machine Learning method for estimating the Photometric Redshifts of quasars (PhotoRedshift-MML for short), which has long been the subject of many investigations. Our method includes two main models, i.e. the feature transformation model by multimodal representation learning, and the photometric redshift estimation model by multimodal transfer learning. The prediction accuracy of the photometric redshift was significantly improved owing to the large amount of information offered by the generated spectral features learned from photometric data via the MML. A total of 415,930 quasars from Sloan Digital Sky Survey (SDSS) Data Release 17, with redshifts between 1 and 5, were screened for our experiments. We used |{\Delta}z| = |(z_phot-z_spec)/(1+z_spec)| to evaluate the redshift prediction and demonstrated a 4.04% increase in accuracy. With the help of the generated spectral features, the proportion of data with |{\Delta}z| < 0.1 can reach 84.45% of the total test samples, whereas it reaches 80.41% for single-modal photometric data. Moreover, the Root Mean Square (RMS) of |{\Delta}z| is shown to decreases from 0.1332 to 0.1235. Our method has the potential to be generalized to other astronomical data analyses such as galaxy classification and redshift prediction. The algorithm code can be found at https://github.com/HongShuxin/PhotoRedshift-MML .Comment: 10 pages, 8 figures, accepted for publication in MNRA

Porous bulk superhydrophobic nanocomposites for extreme environments

Robust superhydrophobic materials providing protections from harsh weather events such as hurricanes, high temperatures, and humid/frigid conditions have proven challenging to achieve. Here, we report a porous bulk nanocomposite comprising carbon nanotube (CNT)-reinforced polytetrafluoroethylene (PTFE). The nanocomposites are prepared using a templated approach by infusing a CNT/PTFE dispersion into a sponge followed by thermal annealing and decomposition of the sponge template. Importantly, an excess accretion of CNT/PFFE particle mixture on the sponge resulted in nanocomposites with unique and hierarchical porous microstructure, featuring nanochannels near the surface connected to microscale pores inside. The superhydrophobic nanocomposite could resist liquid jets impacting at a velocity of �85.4 m s1 (Weber number of �202,588) and exhibits excellent high-temperature resistance as well as mechanochemical robustness. The porous nanocomposites display excellent icephobicity both with and without infusion with polydimethylsiloxane/silicone oil. These properties should facilitate exploitation as stiff/strong structural polymeric foams used in a variety of fields