222 research outputs found
COURSE-KEEPING CONTROL FOR DIRECTIONALLY UNSTABLE LARGE TANKERS USING THE MIRROR-MAPPING TECHNIQUE
This study examines the course-keeping control of directionally unstable large oil tankers involving a pole in the right half plane. Treated as an unstable plant in control engineering, tankers are theoretically and experimentally investigated during the controller design process. First, the unstable plant is mirror-mapped to its corresponding stable minimum phase plant using the mirror-mapping technique, which enables an easy controller design. Then, a linear proportional-differential and a first-order filter controller is designed based on the closed-loop gain shaping algorithm, which requires only one controller parameter to be properly selected based on the system’s characteristics. Numerical simulation results confirmed that the designed controller can successfully stabilise an unstable plant subjected to external wind and wave disturbances. The controller designed with the proposed method is suitable for course-keeping control of directionally unstable large tankers. The controller design method is simple with an uncomplicated structure that can easily be implemented in engineering endeavours. Moreover, the rudder motion is small and soft
Improved Model for Beam-Wave Interaction with Ohmic Losses and Reflections of Sheet Beam Traveling Wave Tubes
In this article, an improved model for the beam-wave interaction of sheet beam in traveling wave tubes (TWTs) considering ohmic losses and reflections is presented. The ohmic losses are obtained by field analysis and equivalent method. The space charge magnetic field is derived from the active Helmholtz's equation. An algorithm to obtain the S-matrix by the equivalent circuit method is presented. The relativistic Boris method is applied to accelerate macroparticles. The exchanged power is computed by the work the electromagnetic field applied to the macroparticles. The theoretical model is applied for validation to a G-band staggered double vane TWT and validated in comparison with CST Particle Studio and simulations without losses and reflections. The convergence of this algorithm is also discussed. The simulation time of the model is substantial faster than 3-D particle-in-cell (PIC) simulations
A grazing Gomphotherium in Middle Miocene Central Asia, 10 million years prior to the origin of the Elephantidae
Feeding preference of fossil herbivorous mammals, concerning the coevolution of mammalian and floral ecosystems, has become of key research interest. In this paper, phytoliths in dental calculus from two gomphotheriid proboscideans of the middle Miocene Junggar Basin, Central Asia, have been identified, suggesting that Gomphotherium connexum was a mixed feeder, while the phytoliths from G. steinheimense indicates grazing preference. This is the earliest-known proboscidean with a predominantly grazing habit. These results are further confirmed by microwear and isotope analyses. Pollen record reveals an open steppic environment with few trees, indicating an early aridity phase in the Asian interior during the Mid-Miocene Climate Optimum, which might urge a diet remodeling of G. steinheimense. Morphological and cladistic analyses show that G. steinheimense comprises the sister taxon of tetralophodont gomphotheres, which were believed to be the general ancestral stock of derived “true elephantids”; whereas G. connexum represents a more conservative lineage in both feeding behavior and tooth morphology, which subsequently became completely extinct. Therefore, grazing by G. steinheimense may have acted as a behavior preadaptive for aridity, and allowing its lineage evolving new morphological features for surviving later in time. This study displays an interesting example of behavioral adaptation prior to morphological modification
Characterization of deep sub-wavelength nanowells by imaging the photon state scattering spectra
Optical-matter interactions and photon scattering in a sub-wavelength space are of great interest in many applications, such as nanopore-based gene sequencing and molecule characterization. Previous studies show that spatial distribution features of the scattering photon states are highly sensitive to the dielectric and structural properties of the nanopore array and matter contained on or within them, as a result of the complex optical-matter interaction in a confined system. In this paper, we report a method for shape characterization of subwavelength nanowells using photon state spatial distribution spectra in the scattering near field. Far-field parametric images of the near-field optical scattering from sub-wavelength nanowell arrays on a SiN substrate were obtained experimentally. Finite-difference time-domain simulations were used to interpret the experimental results. The rich features of the parametric images originating from the interaction of the photons and the nanowells were analyzed to recover the size of the nanowells. Experiments on nanoholes modified with Shp2 proteins were also performed. Results show that the scattering distribution of modified nanoholes exhibits significant differences compared to empty nanoholes. This work highlights the potential of utilizing the photon status scattering of nanowells for molecular characterization or other virus detection applications
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Methodological implementation of mixed linear models in multi-locus genome-wide association studies
The mixed linear model has been widely used in genome-wide association studies (GWAS), but its application to multi-locus GWAS analysis has not been explored and assessed. Here, we implemented a fast multi-locus random-SNP-effect EMMA (FASTmrEMMA) model for GWAS. The model is built on random single nucleotide polymorphism (SNP) effects and a new algorithm. This algorithm whitens the covariance matrix of the polygenic matrix K and environmental noise, and specifies the number of nonzero eigenvalues as one. The model first chooses all putative quantitative trait nucleotides (QTNs) with ≤ 0.005 P-values and then includes them in a multi-locus model for true QTN detection. Owing to the multi-locus feature, the Bonferroni correction is replaced by a less stringent selection criterion. Results from analyses of both simulated and real data showed that FASTmrEMMA is more powerful in QTN detection and model fit, has less bias in QTN effect estimation and requires a less running time than existing single- and multi-locus methods, such as empirical Bayes, settlement of mixed linear model under progressively exclusive relationship (SUPER), efficient mixed model association (EMMA), compressed MLM (CMLM) and enriched CMLM (ECMLM). FASTmrEMMA provides an alternative for multi-locus GWAS
Photo scattering signal amplification in gold-viral particle ligation towards fast infection screening
The polarization states of scattered photons can be used to map or image the anisotropic features of a nanostructure. However, the scattering strength depends heavily on the refractivity contrast in the near field under measurement, which limits the imaging sensitivity for viral particles which have little refractivity contrast with their nano-ambientes. In this paper, we show the photon scattering signal strength can be magnified by introducing a more abrupt change of refractivity at the virus particle using antibody-conjugated gold nanoparticles (AuNPs), allowing the presence of such viruses to be detected. Using two different deep learning methods to minimize scattering noise, the photon states scattering signal of a AuNPs ligated virus is enhanced significantly compared to that of a bare virus particle. This is confirmed by Finite Difference Time Domain (FDTD) numerical simulations. The sensitivity of the polarization state scattering spectra from a virus-gold particle doublet is 5.4 times higher than that of a conventional microscope image
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