Ghost imaging lidar via sparsity constraints

For remote sensing, high-resolution imaging techniques are helpful to catch more characteristic information of the target. We extend pseudo-thermal light ghost imaging to the area of remote imaging and propose a ghost imaging lidar system. For the first time, we demonstrate experimentally that the real-space image of a target at about 1.0 km range with 20 mm resolution is achieved by ghost imaging via sparsity constraints (GISC) technique. The characters of GISC technique compared to the existing lidar systems are also discussed.Comment: 4pages, 3figure

Brzo otkrivanje uzročnika virusnog proljeva goveda u mlijeku iz spremnika pomoću kombinacije metoda umnožene rekombinazne polimeraze i test-traka za „lateral flow“ analizu

Bovine viral diarrhea virus (BVDV) is one of the most prevalent and economically important pathogens of ruminants, and leads to significant financial losses to the livestock industry worldwide. Development of rapid and accurate diagnostic methods is of great importance for the control and eradication of BVDV infection. The aim of this study was to develop a novel isothermal recombinase polymerase amplification (RPA) method combined with a lateral flow dipstick (LFD), for rapid detection of BVDV. RPA primers and a probe targeting the specific conserved 5′-UTR of BVDV genome were designed. The RPA amplification could be finished at a constant temperature of 38 0000C for 15 min, and the amplification product was easily visualized on a simple LFD within 5 min. The detection limit of this assay was 20 copies per reaction, and there was no cross-reactivity with other bovine infectious viruses, such as infectious bovine rhinotracheitis virus (IBRV), bovine enterovirus (BEV), bovine coronavirus (BcoV), bovine parainfluenza virus type 3 (BPIV-3), bovine ephemeral fever virus (BEFV) and bovine respiratory syncytial virus (BRSV). The assay performance on bulk tank milk was also evaluated, and the sensitivity and accuracy of BVDV LFD RPA was compared with real-time RT-PCR. Of 284 pool or bulk tank milk samples, 51 were found to be positive by RPA assay, whereas 52 were positive by real-time RT-PCR. The coincidence rate between LFD RPA and real-time RT-PCR was 97.54% (277/284).Uzročnik virusnog proljeva goveda (BVDV) jedan je od najčešćih i ekonomski važnih patogena preživača koji uzrokuje znatne financijske gubitke u stočarskoj industriji širom svijeta. Razvoj brzih i točnih dijagnostičkih metoda iznimno je važan za kontrolu i iskorjenjivanje zaraze BVDV-om. Cilj ovog istraživanja bio je razviti novu metodu za brzo otkrivanje BVDV-a baziranu na kombinaciji metoda umnožene rekombinazne polimeraze i test-traka za „lateral flow“ analizu. Oblikovane su početnice i probe za umnažanje rekombinazne polimeraze usmjerene na specifični konzervirani 5’-UTR u genomu BVDV-a. Umnažanje se moglo završiti pri konstantnoj temperaturi od 38 °C tijekom 15 minuta i produkt umnažanja je lako vizualiziran na jednostavnoj test-traci za „lateral flow“ analizu unutar 5 minuta. Test je ograničen na 20 kopija po reakciji, pri čemu nije bilo križne reaktivnosti s drugim goveđim zaraznim virusima kao što su infektivni rinotraheitis virusa goveda (IBRV), goveđi enterovirus (BEV), goveđi koronavirus (BcoV), virus goveđe parainfluence tipa 3 (BPIV-3), virus gljivične ephemeralne groznice (BEFV) i goveđi respiratorni sincicijski virus (BRSV). Učinkovitost kombinacije navedenih metoda istražena je i s obzirom na usporedbu osjetljivosti odnosno točnosti koja se dobiva uporabom RT-PCR metode. Od 284 skupna uzorka mlijeka iz spremnika, kombinacijom metoda umnožene rekombinazne polimeraze i test-traka za „lateral flow“ analizu utvrđen je 51 pozitivan uzorak, a RT-PCR 52 pozitivna uzorka. Stopa podudarnosti između navedenih metoda bila je 97,54 % (277/284)

Finite-time stochastic synchronization of fuzzy bi-directional associative memory neural networks with Markovian switching and mixed time delays via intermittent quantized control

We are concerned in this paper with the finite-time synchronization problem for fuzzy bi-directional associative memory neural networks with Markovian switching, discrete-time delay in leakage terms, continuous-time and infinitely distributed delays in transmission terms. After detailed analysis, we come up with an intermittent quantized control for the concerned bi-directional associative memory neural network. By designing an elaborate Lyapunov-Krasovskii functional, we prove under certain additional conditions that the controlled network is stochastically synchronizable in finite time: The 1st moment of every trajectory of the error network system associated to the concerned controlled network tends to zero as time approaches a finite instant (the settling time) which is given explicitly, and remains to be zero constantly thereupon. In the meantime, we present a numerical example to illustrate that the synchronization control designed in this paper is indeed effective. Since the concerned fuzzy network includes Markovian jumping and several types of delays simultaneously, and it can be synchronized in finite time by our suggested control, as well as the suggested intermittent control is quantized which could reduce significantly the control cost, the theoretical results in this paper are rich in mathematical implication and have wide potential applicability in the real world

Piezoelectrically Mediated Reversible Addition-Fragmentation Chain Transfer Polymerization

A well-controlled piezoelectrically mediated reversible addition-fragmentation chain transfer polymerization (piezo-RAFT) was carried out under ultrasound agitation with piezoelectric ZnO nanoparticles as the mechano-chemical trans-ducer. The resulting polymer had predictable molecular weight, high end-group fidelity, low dispersity, and capacity for chain extension. This chemistry was further adopted in curing composite resins to circumvent the light penetration limit of UV curing. This work opened a new avenue of piezoelectrically mediated chemistry and showed its good potential in curing applications

Initial-boundary value problem of fifth-order Korteweg-de Vries equation posed on half line with nonlinear boundary values

Abstract In this paper, we study the initial boundary problem of fifth-order Korteweg-de Vries equation with nonlinear boundary values. First, we establish a so-called sharp boundary trace regularity associated with the linearized fifth-order Korteweg-de Vries equation. Then, aided by the sharp boundary trace regularity, we verify that initial-boundary value problem of fifth-order Korteweg-de Vries equation with nonlinear boundary conditions is locally well-posed when initial and boundary values are properly chosen.</jats:p

Global well-posedness of initial-boundary value problem of fifth-order KdV equation posed on finite interval

We have established the existence and uniqueness of the local solution for (0.1)∂tu+∂x5u−u∂xu=0,00,u(x,0)=φ(x),00,\left\{\begin{array}{ll}{\partial }_{t}u+{\partial }_{x}^{5}u-u{\partial }_{x}u=0,& 0\lt x\lt 1,\hspace{1.0em}t\gt 0,\\ u\left(x,0)=\varphi \left(x),& 0\lt x\lt 1,\\ u\left(0,t)={h}_{1}\left(t),u\left(1,t)={h}_{2}\left(t),\hspace{0.33em}{\partial }_{x}u\left(1,t)={h}_{3}\left(t),& \\ {\partial }_{x}u\left(0,t)={h}_{4}\left(t),\hspace{0.33em}{\partial }_{x}^{2}u\left(1,t)={h}_{5}\left(t),& t\gt 0,\end{array}\right. in the study of Zhao and Zhang [Non-homogeneous boundary value problem of the fifth-order KdV equations posed on a bounded interval, J. Math. Anal. Appl. 470 (2019), 251–278]. A question arises naturally: Can the local solution be extended to a global one? This article will address this question. First, through a series of logical deductions, a global a priori estimate is established, and then the local solution is naturally extended to a global solution

Almost Surely Exponential Convergence Analysis of Time Delayed Uncertain Cellular Neural Networks Driven by Liu Process via Lyapunov–Krasovskii Functional Approach

As with probability theory, uncertainty theory has been developed, in recent years, to portray indeterminacy phenomena in various application scenarios. We are concerned, in this paper, with the convergence property of state trajectories to equilibrium states (or fixed points) of time delayed uncertain cellular neural networks driven by the Liu process. By applying the classical Banach’s fixed-point theorem, we prove, under certain conditions, that the delayed uncertain cellular neural networks, concerned in this paper, have unique equilibrium states (or fixed points). By carefully designing a certain Lyapunov–Krasovskii functional, we provide a convergence criterion, for state trajectories of our concerned uncertain cellular neural networks, based on our developed Lyapunov–Krasovskii functional. We demonstrate under our proposed convergence criterion that the existing equilibrium states (or fixed points) are exponentially stable almost surely, or equivalently that state trajectories converge exponentially to equilibrium states (or fixed points) almost surely. We also provide an example to illustrate graphically and numerically that our theoretical results are all valid. There seem to be rare results concerning the stability of equilibrium states (or fixed points) of neural networks driven by uncertain processes, and our study in this paper would provide some new research clues in this direction. The conservatism of the main criterion obtained in this paper is reduced by introducing quite general positive definite matrices in our designed Lyapunov–Krasovskii functional