Azimuthal and meridional asymmetries of the solar wind and quasiperiodic variations of intensity of Galactic Cosmic Rays (GCR)

The results of analysis of 27 day, annual and quasi-two year variation of galactic cosmic rays (GCR) are presented. The dependence of the periods of 27 day GCR variation on the energy of initial radiation is discovered, according to the data during 1980 of the World network of station in sufficiently wide range of the observed threshold energy. The dependence of the annual variation of GCR is established, according to the data of the Huancayo station in conforming with the change of the polarity of the General Magnetic Field of the Sun (GMFS)

Joint Learning of Intrinsic Images and Semantic Segmentation

Semantic segmentation of outdoor scenes is problematic when there are variations in imaging conditions. It is known that albedo (reflectance) is invariant to all kinds of illumination effects. Thus, using reflectance images for semantic segmentation task can be favorable. Additionally, not only segmentation may benefit from reflectance, but also segmentation may be useful for reflectance computation. Therefore, in this paper, the tasks of semantic segmentation and intrinsic image decomposition are considered as a combined process by exploring their mutual relationship in a joint fashion. To that end, we propose a supervised end-to-end CNN architecture to jointly learn intrinsic image decomposition and semantic segmentation. We analyze the gains of addressing those two problems jointly. Moreover, new cascade CNN architectures for intrinsic-for-segmentation and segmentation-for-intrinsic are proposed as single tasks. Furthermore, a dataset of 35K synthetic images of natural environments is created with corresponding albedo and shading (intrinsics), as well as semantic labels (segmentation) assigned to each object/scene. The experiments show that joint learning of intrinsic image decomposition and semantic segmentation is beneficial for both tasks for natural scenes. Dataset and models are available at: https://ivi.fnwi.uva.nl/cv/intrinsegComment: ECCV 201

Field-linked States of Ultracold Polar Molecules

We explore the character of a novel set of ``field-linked'' states that were predicted in [A. V. Avdeenkov and J. L. Bohn, Phys. Rev. Lett. 90, 043006 (2003)]. These states exist at ultralow temperatures in the presence of an electrostatic field, and their properties are strongly dependent on the field's strength. We clarify the nature of these quasi-bound states by constructing their wave functions and determining their approximate quantum numbers. As the properties of field-linked states are strongly defined by anisotropic dipolar and Stark interactions, we construct adiabatic surfaces as functions of both the intermolecular distance and the angle that the intermolecular axis makes with the electric field. Within an adiabatic approximation we solve the 2-D Schrodinger equation to find bound states, whose energies correlate well with resonance features found in fully-converged multichannel scattering calculations

Magnetic switching in granular FePt layers promoted by near-field laser enhancement

Light-matter interaction at the nanoscale in magnetic materials is a topic of intense research in view of potential applications in next-generation high-density magnetic recording. Laser-assisted switching provides a pathway for overcoming the material constraints of high-anisotropy and high-packing density media, though much about the dynamics of the switching process remains unexplored. We use ultrafast small-angle x-ray scattering at an x-ray free-electron laser to probe the magnetic switching dynamics of FePt nanoparticles embedded in a carbon matrix following excitation by an optical femtosecond laser pulse. We observe that the combination of laser excitation and applied static magnetic field, one order of magnitude smaller than the coercive field, can overcome the magnetic anisotropy barrier between "up" and "down" magnetization, enabling magnetization switching. This magnetic switching is found to be inhomogeneous throughout the material, with some individual FePt nanoparticles neither switching nor demagnetizing. The origin of this behavior is identified as the near-field modification of the incident laser radiation around FePt nanoparticles. The fraction of not-switching nanoparticles is influenced by the heat flow between FePt and a heat-sink layer

SARS-CoV-2 variants and their relevant mutational profiles: update summer 2021

: Since the beginning of the coronavirus disease 2019 (COVID-19) pandemic caused by it, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been undergoing a genetic diversification leading to the emergence of new variants. Nevertheless, a clear definition of the genetic signatures underlying the circulating variants is still missing. Here, we provide a comprehensive insight into mutational profiles characterizing each SARS-CoV-2 variant, focusing on spike mutations known to modulate viral infectivity and/or antigenicity. We focused on variants and on specific relevant mutations reported by GISAID, Nextstrain, Outbreak.info, Pango, and Stanford database websites that were associated with any clinical/diagnostic impact, according to published manuscripts. Furthermore, 1,223,338 full-length high-quality SARS-CoV-2 genome sequences were retrieved from GISAID and used to accurately define the specific mutational patterns in each variant. Finally, mutations were mapped on the three-dimensional structure of the SARS-CoV-2 spike protein to assess their localization in the different spike domains. Overall, this review sheds light and assists in defining the genetic signatures characterizing the currently circulating variants and their clinical relevance. IMPORTANCE Since the emergence of SARS-CoV-2, several recurrent mutations, particularly in the spike protein, arose during human-to-human transmission or spillover events between humans and animals, generating distinct worrisome variants of concern (VOCs) or of interest (VOIs), designated as such due to their clinical and diagnostic impacts. Characterizing these variants and their related mutations is important in tracking SAR-CoV-2 evolution and understanding the efficacy of vaccines and therapeutics based on monoclonal antibodies, convalescent-phase sera, and direct antivirals. Our study provides a comprehensive survey of the mutational profiles characterizing the important SARS-CoV-2 variants, focusing on spike mutations and highlighting other protein mutations

An excess power statistic for detection of burst sources of gravitational radiation

We examine the properties of an excess power method to detect gravitational waves in interferometric detector data. This method is designed to detect short-duration (< 0.5 s) burst signals of unknown waveform, such as those from supernovae or black hole mergers. If only the bursts' duration and frequency band are known, the method is an optimal detection strategy in both Bayesian and frequentist senses. It consists of summing the data power over the known time interval and frequency band of the burst. If the detector noise is stationary and Gaussian, this sum is distributed as a chi-squared (non-central chi-squared) deviate in the absence (presence) of a signal. One can use these distributions to compute frequentist detection thresholds for the measured power. We derive the method from Bayesian analyses and show how to compute Bayesian thresholds. More generically, when only upper and/or lower bounds on the bursts duration and frequency band are known, one must search for excess power in all concordant durations and bands. Two search schemes are presented and their computational efficiencies are compared. We find that given reasonable constraints on the effective duration and bandwidth of signals, the excess power search can be performed on a single workstation. Furthermore, the method can be almost as efficient as matched filtering when a large template bank is required. Finally, we derive generalizations of the method to a network of several interferometers under the assumption of Gaussian noise.Comment: 22 pages, 6 figure

The Cosmic Microwave Background and Particle Physics

In forthcoming years, connections between cosmology and particle physics will be made increasingly important with the advent of a new generation of cosmic microwave background (CMB) experiments. Here, we review a number of these links. Our primary focus is on new CMB tests of inflation. We explain how the inflationary predictions for the geometry of the Universe and primordial density perturbations will be tested by CMB temperature fluctuations, and how the gravitational waves predicted by inflation can be pursued with the CMB polarization. The CMB signatures of topological defects and primordial magnetic fields from cosmological phase transitions are also discussed. Furthermore, we review current and future CMB constraints on various types of dark matter (e.g. massive neutrinos, weakly interacting massive particles, axions, vacuum energy), decaying particles, the baryon asymmetry of the Universe, ultra-high-energy cosmic rays, exotic cosmological topologies, and other new physics.Comment: 43 pages. To appear in Annual Reviews of Nuclear and Particle Scienc

Dynamics & Predictions in the Co-Event Interpretation

Sorkin has introduced a new, observer independent, interpretation of quantum mechanics that can give a successful realist account of the 'quantum microworld' as well as explaining how classicality emerges at the level of observable events for a range of systems including single time 'Copenhagen measurements'. This 'co-event interpretation' presents us with a new ontology, in which a single 'co-event' is real. A new ontology necessitates a review of the dynamical & predictive mechanism of a theory, and in this paper we begin the process by exploring means of expressing the dynamical and predictive content of histories theories in terms of co-events.Comment: 35 pages. Revised after refereein

Managing toxicities associated with immune checkpoint inhibitors: consensus recommendations from the Society for Immunotherapy of Cancer (SITC) Toxicity Management Working Group.

Cancer immunotherapy has transformed the treatment of cancer. However, increasing use of immune-based therapies, including the widely used class of agents known as immune checkpoint inhibitors, has exposed a discrete group of immune-related adverse events (irAEs). Many of these are driven by the same immunologic mechanisms responsible for the drugs\u27 therapeutic effects, namely blockade of inhibitory mechanisms that suppress the immune system and protect body tissues from an unconstrained acute or chronic immune response. Skin, gut, endocrine, lung and musculoskeletal irAEs are relatively common, whereas cardiovascular, hematologic, renal, neurologic and ophthalmologic irAEs occur much less frequently. The majority of irAEs are mild to moderate in severity; however, serious and occasionally life-threatening irAEs are reported in the literature, and treatment-related deaths occur in up to 2% of patients, varying by ICI. Immunotherapy-related irAEs typically have a delayed onset and prolonged duration compared to adverse events from chemotherapy, and effective management depends on early recognition and prompt intervention with immune suppression and/or immunomodulatory strategies. There is an urgent need for multidisciplinary guidance reflecting broad-based perspectives on how to recognize, report and manage organ-specific toxicities until evidence-based data are available to inform clinical decision-making. The Society for Immunotherapy of Cancer (SITC) established a multidisciplinary Toxicity Management Working Group, which met for a full-day workshop to develop recommendations to standardize management of irAEs. Here we present their consensus recommendations on managing toxicities associated with immune checkpoint inhibitor therapy