Millicharged neutrino with anomalous magnetic moment in rotating magnetized matter

New exact solutions of the modified Dirac equation describing a neutrino with nontrivial electromagnetic properties in extreme background conditions are obtained. Within the quasi-classical treatment the effective Lorentz force that describes the neutrino propagation in the magnetized rotating matter is introduced. We predict the effect of the spatial separation of different types of relativistic neutrinos and antineutrinos (different in flavors and energies) by the magnetized rotating matter of a star. Low energy neutrinos can be even trapped inside the star. We also predict two new phenomena: a new type of the neutrino electromagnetic radiation (termed "Light of (milli)Charged Neutrino", $LC\nu$) and a new mechanism of the star angular velocity shift due to neutrinos escaping the star (termed "Neutrino Star Turning" mechanism, $\nu S T$). The possible impact of the $\nu S T$ mechanism on a supernova explosion yields a new astrophysical limit on the neutrino millicharge $q_{\nu}<1.3\times10^{-19}e_0$. In addition, the $\nu S T$ mechanism can be also used to explain the origin of pulsar "anti-glitches" and ordinary glitches as well.Comment: 18 pages, minor typos corrected and several references adde

PROBING AND CONTROLLING FLUID RHEOLOGY AT MICROSCALE WITH MAGNETIC NANORODS

This Dissertation is focused on the development of new methods for characterization and control of fluid rheology using magnetic nanorods. This Dissertation consists of five chapters. In the first chapter, we review current microrheologial methods and develop a Magnetic Rotational Spectroscopy (MRS) model describing nanorod response to a rotating magnetic field. Using numerical modeling, we analyze the effects of materials parameters of nanorods and fluids on the MRS characteristic features. The model is designed for a specific experimental protocol. We introduce and examine physical parameters which can be measured experimentally. The model allows identification of MRS features enabling the calculation of fluid viscosity. The MRS of Non-Newtonian fluids with exponentially increasing viscosity is discussed for the first time. In the second chapter, we review the techniques for magnetic nanorods synthesis. We describe a setup and experimental protocol to synthesize nickel nanorods with the desired geometrical properties, in particular, with the controlled length to diameter ratio. We review magnetic systems used for manipulation of magnetic nanoparticles. A multifunctional magnetic rotator is introduced and described in detail in this chapter. We believe that this multifunctional magnetic system will be useful not only for micro and nanorheological studies, but will find much broader applications requiring remotely controlled manipulation of micro and nanoobjects. In the third chapter, we describe the MRS experiments and use the model developed in the first chapter for characterization of magnetic properties of synthesized nickel nanorods. The same setup is used to measure viscosity of microdroplets. We show that the diffraction pattern from the suspension of nickel nanorods aligned in a magnetic field can be rotated by a spinning magnetic field. This effect opens up an opportunity for the MRS using much smaller nanorods. Another practical application of the controlled diffraction patterns is discussed: the use of this pattern in medical optofluidic devices producing stationary illuminating spots, for example, in endoscopes. In the fourth chapter, we report on a new MRS method which can be used for the in-situ (or in-vivo) rheological measurements of fluids and polymer systems when the fluid viscosity increases exponentially with time. We use this method to measure the exponential change of the viscosity of HEMA (2-hydroxyethyl-methacrylate) undergoing photopolymerization. Remarkably, an exponential increase of viscosity can be traced beyond the point when the polymer system undergoes transition to a gel and the gel domains start to appear. We expect that this method will open up new horizons in the quantitative rheological analysis of fluids inside living cells, microorganisms, and aerosol droplets with thickeners. In the fifth chapter, we describe a physical principle of self-assembly of magnetic nanorods into droplets of different sizes. These droplets can be formed on demand using magneto-static interactions between magnetic nanorods and a magnetic field gradient. We theoretically and experimentally confirmed that the cluster of nanorods at the top of the droplet is acting as a cone-shape solid body deforming the top part of the droplet when moving towards the magnet. The developed model allows one to selectively concentrate a finite amount of magnetic nanorods at the free surface and print multiple microdroplets on demand

Что делать архитектору с историей архитектуры?

The article considers the aspects of teaching of history and theory of architecture and the relations between humanity and design subjects. The touch point of design and history may consist in consideration of the tasks, which have been facing the architecture throughout its history, and their solutions. The educational result of the course should be not only students’ historical knowledge, but also their ability to analyze projects regardless of the time of their construction.Публикация посвящена преподаванию истории и теории архитектуры и взаимоотношениям гуманитарных предметов с проектными дисциплинами. Точкой соприкосновения проектирования и истории может стать обсуждение задач, стоящих перед архитектурой на протяжении ее истории и способов их решения. Образовательным результатом курса истории должно стать не просто знание исторического материала, но и умение студента самостоятельно анализировать проекты и постройки независимо от времени их возведения

Permafrost hydrology in changing climatic conditions: seasonal variability of stable isotope composition in rivers in discontinuous permafrost

Role of changing climatic conditions on permafrost degradation and hydrology was investigated in the transition zone between the tundra and forest ecotones at the boundary of continuous and discontinuous permafrost of the lower Yenisei River. Three watersheds of various sizes were chosen to represent the characteristics of the regional landscape conditions. Samples of river flow, precipitation, snow cover, and permafrost ground ice were collected over the watersheds to determine isotopic composition of potential sources of water in a river flow over a two year period. Increases in air temperature over the last forty years have resulted in permafrost degradation and a decrease in the seasonal frost which is evident from soil temperature measurements, permafrost and active-layer monitoring, and analysis of satellite imagery. The lowering of the permafrost table has led to an increased storage capacity of permafrost affected soils and a higher contribution of ground water to river discharge during winter months. A progressive decrease in the thickness of the layer of seasonal freezing allows more water storage and pathways for water during the winter low period making winter discharge dependent on the timing and amount of late summer precipitation. There is a substantial seasonal variability of stable isotopic composition of river flow. Spring flooding corresponds to the isotopic composition of snow cover prior to the snowmelt. Isotopic composition of river flow during the summer period follows the variability of precipitation in smaller creeks, while the water flow of larger watersheds is influenced by the secondary evaporation of water temporarily stored in thermokarst lakes and bogs. Late summer precipitation determines the isotopic composition of texture ice within the active layer in tundra landscapes and the seasonal freezing layer in forested landscapes as well as the composition of the water flow during winter months

Crop leaves high-resolution images analysis and segmentation by a convolutional neural network under small sampling condition

The authors propose an algorithm for analysing and segmenting high-resolution images of cultivated plant leaves by a convolutional neural network of deep learning in conditions of small samples. The algorithm implemented in the hardware and software complex includes images preprocessing procedures with the elimination of distortions if they are present, data augmentation to increase the number of variations, classification of signs by textural characteristics in order to identify diseases with subsequent segmentation of images of affected leaves