Multi-Eruption Solar Energetic Particle Events Observed by SOHO/ERNE

In the last two decades of studying the Solar Energetic Particle (SEP) phenomenon, intensive emphasis has been put on how and when and where these SEPs are injected into interplanetary space. It is well known that SEPs are related to solar flares and CMEs. However, the role of each in the acceleration of SEPs has been under debate since the major role was taken from flares ascribed to CMEs step by step after the skylab mission, which started the era of CME spaceborn observations. Since then, the shock wave generated by powerful CMEs in between 2-5 solar radii is considered the major accelerator. The current paradigm interprets the prolonged proton intensity-time profile in gradual SEP events as a direct effect of accelerated SEPs by shock wave propagating in the interplanetary medium. Thus the powerful CME is thought of as a starter for the acceleration and its shock wave as a continuing accelerator to result in such an intensity-time profile. Generally it is believed that a single powerful CME which might or might not be associated with a flare is always the reason behind such gradual events.

In this work we use the Energetic and Relativistic Nucleus and Electrons ERNE instrument on board Solar and Heliospheric Observatory SOHO to present an empirical study to show the possibility of multiple accelerations in SEP events. In the beginning we found 18 double-peaked SEP events by examining 88 SEP events. The peaks in the intensity-time profile were separated by 3-24 hours. We divided the SEP events according to possible multiple acceleration into four groups and in one of these groups we find evidence for multiple acceleration in velocity dispersion and change in the abundance ratio associated at transition to the second peak. Then we explored the intensity-time profiles of all SEP events during solar cycle 23 and found that most of the SEP events are associated with multiple eruptions at the Sun and we call those events as Multi-Eruption Solar Energetic Particles (MESEP) events. We use the data available by Large Angle and Spectrometric Coronograph LASCO on board SOHO to determine the CME associated with such events and YOHKOH and GOES satellites data to determine the flare associated with such events. We found four types of MESEP according to the appearance of the peaks in the intensity-time profile in large variation of energy levels. We found that it is not possible to determine whether the peaks are related to an eruption at the Sun or not, only by examining the anisotropy flux, He/p ratio and velocity dispersion. Then we chose a rare event in which there is evidence of SEP acceleration from behind previous CME. This work resulted in a conclusion which is inconsistent with the current SEP paradigm. Then we discovered through examining another MESEP event, that energetic particles accelerated by a second CME can penetrate a previous CME-driven decelerating shock. Finally, we report the previous two MESEP events with new two events and find a common basis for second CME SEPs penetrating previous decelerating shocks. This phenomenon is reported for the first time and expected to have significant impact on modification of the current paradigm of the solar energetic particle events.

Membrane emulsification in preparation of single site catalyst

In the theory part the membrane emulsification was studied. Emulsions are used in many industrial areas. Traditionally emulsions are prepared by using high shear in rotor-stator systems or in high pressure homogenizer systems. In membrane emulsification two immiscible liquids are mixed by pressuring one liquid through the membrane into the other liquid. With this technique energy could be saved, more homogeneous droplets could be formed and the amount of surfactant could be decreased. Ziegler-Natta and single-site catalysts are used in olefin polymerization processes. Nowadays, these catalysts are prepared according to traditional mixing emulsification. More homogeneous catalyst particles that have narrower particle size distribution might be prepared with membrane emulsification. The aim of the experimental part was to examine the possibility to prepare single site polypropylene catalyst using membrane emulsification technique. Different membrane materials and solidification techniques of the emulsion were examined. Also the toluene-PFC phase diagram was successfully measured during this thesis work. This phase diagram was used for process optimization. The polytetrafluoroethylene membranes had the largest contact angles with toluene and also the biggest difference between the contact angles measured with PFC and toluene. Despite of the contact angle measurement results no significant difference was noticed between particles prepared using PTFE membrane or metal sinter. The particle size distributions of catalyst prepared in these tests were quite wide. This would probably be fixed by using a membrane with a more homogeneous pore size distribution. It is also possible that the solidification rate has an effect on the particle sizes and particle morphology. When polymeric membranes are compared PTFE is probably still the best material for the process as it had the best chemical durability.

Quantification of Proteins and Cells: Luminometric Nonspecific Particle-Based Methods

New luminometric particle-based methods were developed to quantify protein and to count cells. The developed methods rely on the interaction of the sample with nano- or microparticles and different principles of detection. In fluorescence quenching, timeresolved luminescence resonance energy transfer (TR-LRET), and two-photon excitation fluorescence (TPX) methods, the sample prevents the adsorption of labeled protein to the particles. Depending on the system, the addition of the analyte increases or decreases the luminescence. In the dissociation method, the adsorbed protein protects the Eu(III) chelate on the surface of the particles from dissociation at a low pH. The experimental setups are user-friendly and rapid and do not require hazardous test compounds and elevated temperatures. The sensitivity of the quantification of protein (from 40 to 500 pg bovine serum albumin in a sample) was 20-500-fold better than in most sensitive commercial methods. The quenching method exhibited low protein-to-protein variability and the dissociation method insensitivity to the assay contaminants commonly found in biological samples. Less than ten eukaryotic cells were detected and quantified with all the developed methods under optimized assay conditions. Furthermore, two applications, the method for detection of the aggregation of protein and the cell viability test, were developed by utilizing the TR-LRET method. The detection of the aggregation of protein was allowed at a more than 10,000 times lower concentration, 30 μg/L, compared to the known methods of UV240 absorbance and dynamic light scattering. The TR-LRET method was combined with a nucleic acid assay with cell-impermeable dye to measure the percentage of dead cells in a single tube test with cell counts below 1000 cells/tube.

Utilization of Particle Image velocimetry in PPOOLEX condensation experiments

Particle Image Velocimetry, PIV, is an optical measuring technique to obtain velocity information of a flow in interest. With PIV it is possible to achieve two or three dimensional velocity vector fields from a measurement area instead of a single point in a flow. Measured flow can be either in liquid or in gas form. PIV is nowadays widely applied to flow field studies. The need for PIV is to obtain validation data for Computational Fluid Dynamics calculation programs that has been used to model blow down experiments in PPOOLEX test facility in the Lappeenranta University of Technology. In this thesis PIV and its theoretical background are presented. All the subsystems that can be considered to be part of a PIV system are presented as well with detail. Emphasis is also put to the mathematics behind the image evaluation. The work also included selection and successful testing of a PIV system, as well as the planning of the installation to the PPOOLEX facility. Already in the preliminary testing PIV was found to be good addition to the measuring equipment for Nuclear Safety Research Unit of LUT. The installation to PPOOLEX facility was successful even though there were many restrictions considering it. All parts of the PIV system worked and they were found out to be appropriate for the planned use. Results and observations presented in this thesis are a good background to further PIV use.

Generating Aesthetically Pleasing Images in a Virtual Environment using Particle Swarm Optimization

This research focuses on generating aesthetically pleasing images in virtual environments using the particle swarm optimization (PSO) algorithm. The PSO is a stochastic population based search algorithm that is inspired by the flocking behavior of birds. In this research, we implement swarms of cameras flying through a virtual world in search of an image that is aesthetically pleasing. Virtual world exploration using particle swarm optimization is considered to be a new research area and is of interest to both the scientific and artistic communities. Aesthetic rules such as rule of thirds, subject matter, colour similarity and horizon line are all analyzed together as a multi-objective problem to analyze and solve with rendered images. A new multi-objective PSO algorithm, the sum of ranks PSO, is introduced. It is empirically compared to other single-objective and multi-objective swarm algorithms. An advantage of the sum of ranks PSO is that it is useful for solving high-dimensional problems within the context of this research. Throughout many experiments, we show that our approach is capable of automatically producing images satisfying a variety of supplied aesthetic criteria.

Sensitivity of direct radiative forcing by mineral dust to particle characteristics

Airborne dust affects the Earth's energy balance — an impact that is measured in terms of the implied change in net radiation (or radiative forcing, in W m-2) at the top of the atmosphere. There remains considerable uncertainty in the magnitude and sign of direct forcing by airborne dust under current climate. Much of this uncertainty stems from simplified assumptions about mineral dust-particle size, composition and shape, which are applied in remote sensing retrievals of dust characteristics and dust-cycle models. Improved estimates of direct radiative forcing by dust will require improved characterization of the spatial variability in particle characteristics to provide reliable information dust optical properties. This includes constraints on: (1) particle-size distribution, including discrimination of particle subpopulations and quantification of the amount of dust in the sub-10 µm to <0.1 µm mass fraction; (2) particle composition, specifically the abundance of iron oxides, and whether particles consist of single or multi-mineral grains; (3) particle shape, including degree of sphericity and surface roughness, as a function of size and mineralogy; and (4) the degree to which dust particles are aggregated together. The use of techniques that measure the size, composition and shape of individual particles will provide a better basis for optical modelling.

Using laboratory and field measurements to constrain a single habit shortwave optical parameterization for cirrus

A single habit parameterization for the shortwave optical properties of cirrus is presented. The parameterization utilizes a hollow particle geometry, with stepped internal cavities as identified in laboratory and field studies. This particular habit was chosen as both experimental and theoretical results show that the particle exhibits lower asymmetry parameters when compared to solid crystals of the same aspect ratio. The aspect ratio of the particle was varied as a function of maximum dimension, D, in order to adhere to the same physical relationships assumed in the microphysical scheme in a configuration of the Met Office atmosphere-only global model, concerning particle mass, size and effective density. Single scattering properties were then computed using T-Matrix, Ray Tracing with Diffraction on Facets (RTDF) and Ray Tracing (RT) for small, medium, and large size parameters respectively. The scattering properties were integrated over 28 particle size distributions as used in the microphysical scheme. The fits were then parameterized as simple functions of Ice Water Content (IWC) for 6 shortwave bands. The parameterization was implemented into the GA6 configuration of the Met Office Unified Model along with the current operational long-wave parameterization. The GA6 configuration is used to simulate the annual twenty-year short-wave (SW) fluxes at top-of-atmosphere (TOA) and also the temperature and humidity structure of the atmosphere. The parameterization presented here is compared against the current operational model and a more recent habit mixture model.

The effect of a single supernova explosion on the cuspy density profile of a small-mass dark matter halo

Some observations of galaxies, and in particular dwarf galaxies, indicate a presence of cored density profiles in apparent contradiction with cusp profiles predicted by dark matter N-body simulations. We constructed an analytical model, using particle distribution functions (DFs), to show how a supernova (SN) explosion can transform a cusp density profile in a small-mass dark matter halo into a cored one. Considering the fact that an SN efficiently removes matter from the centre of the first haloes, we study the effect of mass removal through an SN perturbation in the DFs. We find that the transformation from a cusp into a cored profile occurs even for changes as small as 0.5 per cent of the total energy of the halo, which can be produced by the expulsion of matter caused by a single SN explosion.

Single-step chemical synthesis of ferrite hollow nanospheres

We report a single-step chemical synthesis of iron oxide hollow nanospheres with 9.3 nm in diameter. The sample presents a narrow particle diameter distribution and chemical homogeneity. The hollow nature of the particles is confirmed by HRTEM and HAADF STEM analysis. Electron and x-ray diffraction show that the outer material component is constituted by 2 nm ferrite crystals. Mossbauer data provide further evidence for the formation of iron oxide with high structural disorder, magnetically ordered at 4.2 K and superparamagnetism at room temperature. An unusual magnetic behavior under an applied field is reported, which can be explained by the large fraction of atoms existing at both inner and outer surfaces.

Dimensional Compactification and Two-Particle Binding

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Universal zero-bias conductance for the single-electron transistor

The thermal dependence of the zero-bias conductance for the single electron transistor is the target of two independent renormalization-group approaches, both based on the spin-degenerate Anderson impurity model. The first approach, an analytical derivation, maps the Kondo-regime conductance onto the universal conductance function for the particle-hole symmetric model. Linear, the mapping is parametrized by the Kondo temperature and the charge in the Kondo cloud. The second approach, a numerical renormalization-group computation of the conductance as a function the temperature and applied gate voltages offers a comprehensive view of zero-bias charge transport through the device. The first approach is exact in the Kondo regime; the second, essentially exact throughout the parametric space of the model. For illustrative purposes, conductance curves resulting from the two approaches are compared.

Multifractal characterization of saprolite particle-size distributions after topsoil removal

Multifractal analysis is now increasingly used to characterize soil properties as it may provide more information than a single fractal model. During the building of a large reservoir on the Parana River (Brazil), a highly weathered soil profile was excavated to a depth between 5 and 8 m. Excavation resulted in an abandoned area with saprolite materials and, in this area, an experimental field was established to assess the effectiveness of different soil rehabilitation treatments. The experimental design consisted of randomized blocks. The aim of this work was to characterize particle-size distributions of the saprolite material and use the information obtained to assess between-block variability. Particle-size distributions of the experimental plots were characterized by multifractal techniques. Ninety-six soil samples were analyzed routinely for particle-size distribution by laser diffractometry in a range of scales, varying from 0.390 to 2000 mu m. Six different textural classes (USDA) were identified with a clay content ranging from 16.9% to 58.4%. Multifractal models described reasonably well the scaling properties of particle-size distributions of the saprolite material. This material exhibits a high entropy dimension, D-1. Parameters derived from the left side (q > 0) of the f(alpha) spectra, D-1, the correlation dimension (D-2) and the range (alpha(0)-alpha(q+)), as well as the total width of the spectra (alpha(max) - alpha(min)) all showed dependence on the clay content. Sand, silt and clay contents were significantly different among treatments as a consequence of soil intrinsic variability. The D, and the Holder exponent of order zero, alpha(0), were not significantly different between treatments; in contrast, D-2 and several fractal attributes describing the width of the f(alpha) spectra were significantly different between treatments. The only parameter showing significant differences between sampling depths was (alpha(0) - alpha(q+)). Scale independent fractal attributes may be useful for characterizing intrinsic particle-size distribution variability. (c) 2006 Elsevier B.V. All rights reserved.

Particle Competition and Cooperation in Networks for Semi-Supervised Learning with Concept Drift

Concept drift is a problem of increasing importance in machine learning and data mining. Data sets under analysis are no longer only static databases, but also data streams in which concepts and data distributions may not be stable over time. However, most learning algorithms produced so far are based on the assumption that data comes from a fixed distribution, so they are not suitable to handle concept drifts. Moreover, some concept drifts applications requires fast response, which means an algorithm must always be (re) trained with the latest available data. But the process of labeling data is usually expensive and/or time consuming when compared to unlabeled data acquisition, thus only a small fraction of the incoming data may be effectively labeled. Semi-supervised learning methods may help in this scenario, as they use both labeled and unlabeled data in the training process. However, most of them are also based on the assumption that the data is static. Therefore, semi-supervised learning with concept drifts is still an open challenge in machine learning. Recently, a particle competition and cooperation approach was used to realize graph-based semi-supervised learning from static data. In this paper, we extend that approach to handle data streams and concept drift. The result is a passive algorithm using a single classifier, which naturally adapts to concept changes, without any explicit drift detection mechanism. Its built-in mechanisms provide a natural way of learning from new data, gradually forgetting older knowledge as older labeled data items became less influent on the classification of newer data items. Some computer simulation are presented, showing the effectiveness of the proposed method.

Synthesis and electrochemical behavior of single-crystal magnetite nanoparticles

Water-dispersed magnetite nanoparticle synthesis from iron(II) chloride in dimethyl sulfoxide (DMSO)-water solution at different DMSO-water ratios in alkaline medium was reported. TEM and XRD results suggest a single-crystal formation with mean particle size in the range 4-27 nm. Magnetic nanoparticles are formed by the oxidative hydrolysis reaction from green rust species that leads to FeOOH formation, followed by autocatalysis of the adsorbed available Fe(II) on the FeOOH surfaces. The available hydroxyl groups seem to be dependent on the DMSO-water ratio due to strong molecular interactions presented by the solvent mixture. Goethite phase on the magnetite surface was observed by XRD data only for sample synthesized in the absence of DMSO. In addition, cyclic voltammetry with carbon paste electroactive electrode (CV-CPEE) results reveal two reduction peaks near 0 and +400 mV associated with the presence of iron(III) in different chemical environments related to the surface composition of magnetite nanoparticles. The peak near +400 mV is related to a passivate thin layer surface such as goethite on the magnetite nanoparticle, assigned to the intensive hydrolysis reaction due to strong interactions between DMSO-water molecules in the initial solvent mixture that result in a hydroxyl group excess in the medium. Pure magnetite phase was only observed in the samples prepared at 30% (30W) and 80% (80W) water in DMSO in agreement with the structured molecular solvent cluster formation. The goethite phase present on the, magnetite nanoparticle surface like a thin passivate layer only was detectable using CV-CPEE, which is a very efficient, cheap, and powerful tool for surface characterization, and it is able to determine the passivate oxyhydroxide or oxide thin layer presence on the nanoparticle surface.

Measurement of neutral strange particle production in the underlying event in proton-proton collisions at √s=7 TeV

Measurements are presented of the production of primary KS0 and Λ particles in proton-proton collisions at √s=7 TeV in the region transverse to the leading charged-particle jet in each event. The average multiplicity and average scalar transverse momentum sum of KS0 and Λ particles measured at pseudorapidities |η|<2 rise with increasing charged-particle jet pT in the range 1-10 GeV/c and saturate in the region 10-50 GeV/c. The rise and saturation of the strange-particle yields and transverse momentum sums in the underlying event are similar to those observed for inclusive charged particles, which confirms the impact-parameter picture of multiple parton interactions. The results are compared to recent tunes of the pythia Monte Carlo event generator. The pythia simulations underestimate the data by 15%-30% for KS0 mesons and by about 50% for Λ baryons, a deficit similar to that observed for the inclusive strange-particle production in non-single-diffractive proton-proton collisions. The constant strange- to charged-particle activity ratios with respect to the leading jet pT and similar trends for mesons and baryons indicate that the multiparton-interaction dynamics is decoupled from parton hadronization, which occurs at a later stage. © 2013 CERN, for the CMS Collaboration Published by the American Physical Society under the terms of the Creative Commons Attribution 3.0 License. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.