Значение специфических инфекций у беременных в развитии хронической плацентарной недостаточности

ПЛАЦЕНТАРНАЯ НЕДОСТАТОЧНОСТЬБЕРЕМЕННОСТИ ОСЛОЖНЕНИЯПОЛОВЫМ ПУТЕМ ПЕРЕДАВАЕМЫЕ БОЛЕЗНИИНФЕКЦИ

Electric Dipole Moments of Neutron and Electron in Two-Higgs-Doublet Model with Maximal CPCP violation

We study the electric dipole moments(EDM) of the neutron and the electron in the two-Higgs-doublet model, in the case that $CP$ symmetry is violated maximally in the neutral Higgs sector. We take account of the Weinberg's operator O_{3g}=GG\t G as well as the operator $O_{qg}=\bar q\sigma\tilde Gq$ for the neutron, and the Barr-Zee diagrams for the electron. It is found that the predicted neutron EDM could be considerably reduced by the destructive contribution of the two Higgs scalars to get the lower value than the experimental bound. As to the electron EDM, the predicted value is smaller in one order than the experimental one.Comment: 15pages, UWThPh-1994-48, AUE-08-94, US-94-06. The post-script files of figures will be sent by request by electric mai

Pd Nanoparticles and Thin Films for Room Temperature Hydrogen Sensor

We report the application of palladium nanoparticles and thin films for hydrogen sensor. Electrochemically grown palladium particles with spherical shapes deposited on Si substrate and sputter deposited Pd thin films were used to detect hydrogen at room temperature. Grain size dependence of H2sensing behavior has been discussed for both types of Pd films. The electrochemically grown Pd nanoparticles were observed to show better hydrogen sensing response than the sputtered palladium thin films. The demonstration of size dependent room temperature H2sensing paves the ways to fabricate the room temperature metallic and metal–metal oxide semiconductor sensor by tuning the size of metal catalyst in mixed systems. H2sensing by the Pd nanostructures is attributed to the chemical and electronic sensitization mechanisms

Clinical Aspects of Feline Retroviruses: A Review

Feline leukemia virus (FeLV) and feline immunodeficiency virus (FIV) are retroviruses with global impact on the health of domestic cats. The two viruses differ in their potential to cause disease. FeLV is more pathogenic, and was long considered to be responsible for more clinical syndromes than any other agent in cats. FeLV can cause tumors (mainly lymphoma), bone marrow suppression syndromes (mainly anemia), and lead to secondary infectious diseases caused by suppressive effects of the virus on bone marrow and the immune system. Today, FeLV is less commonly diagnosed than in the previous 20 years; prevalence has been decreasing in most countries. However, FeLV importance may be underestimated as it has been shown that regressively infected cats (that are negative in routinely used FeLV tests) also can develop clinical signs. FIV can cause an acquired immunodeficiency syndrome that increases the risk of opportunistic infections, neurological diseases, and tumors. In most naturally infected cats, however, FIV itself does not cause severe clinical signs, and FIV-infected cats may live many years without any health problems. This article provides a review of clinical syndromes in progressively and regressively FeLV-infected cats as well as in FIV-infected cats

Calibration of the charge and energy loss per unit length of the MicroBooNE liquid argon time projection chamber using muons and protons

We describe a method used to calibrate the position- and time-dependent response of the MicroBooNE liquid argon time projection chamber anode wires to ionization particle energy loss. The method makes use of crossing cosmic-ray muons to partially correct anode wire signals for multiple effects as a function of time and position, including cross-connected TPC wires, space charge effects, electron attachment to impurities, diffusion, and recombination. The overall energy scale is then determined using fully-contained beam-induced muons originating and stopping in the active region of the detector. Using this method, we obtain an absolute energy scale uncertainty of 2% in data. We use stopping protons to further refine the relation between the measured charge and the energy loss for highly-ionizing particles. This data-driven detector calibration improves both the measurement of total deposited energy and particle identification based on energy loss per unit length as a function of residual range. As an example, the proton selection efficiency is increased by 2% after detector calibration

Reconstruction and measurement of (100) MeV energy electromagnetic activity from π0 arrow γγ decays in the MicroBooNE LArTPC

We present results on the reconstruction of electromagnetic (EM) activity from photons produced in charged current νμ interactions with final state π0s. We employ a fully-automated reconstruction chain capable of identifying EM showers of (100) MeV energy, relying on a combination of traditional reconstruction techniques together with novel machine-learning approaches. These studies demonstrate good energy resolution, and good agreement between data and simulation, relying on the reconstructed invariant π0 mass and other photon distributions for validation. The reconstruction techniques developed are applied to a selection of νμ + Ar → μ + π0 + X candidate events to demonstrate the potential for calorimetric separation of photons from electrons and reconstruction of π0 kinematics

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector.

The development and operation of liquid-argon time-projection chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies

Convolutional Neural Networks Applied to Neutrino Events in a Liquid Argon Time Projection Chamber

We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level

Noise Characterization and Filtering in the MicroBooNE Liquid Argon TPC

The low-noise operation of readout electronics in a liquid argon time projection chamber (LArTPC) is critical to properly extract the distribution of ionization charge deposited on the wire planes of the TPC, especially for the induction planes. This paper describes the characteristics and mitigation of the observed noise in the MicroBooNE detector. The MicroBooNE's single-phase LArTPC comprises two induction planes and one collection sense wire plane with a total of 8256 wires. Current induced on each TPC wire is amplified and shaped by custom low-power, low-noise ASICs immersed in the liquid argon. The digitization of the signal waveform occurs outside the cryostat. Using data from the first year of MicroBooNE operations, several excess noise sources in the TPC were identified and mitigated. The residual equivalent noise charge (ENC) after noise filtering varies with wire length and is found to be below 400 electrons for the longest wires (4.7 m). The response is consistent with the cold electronics design expectations and is found to be stable with time and uniform over the functioning channels. This noise level is significantly lower than previous experiments utilizing warm front-end electronics.Comment: 36 pages, 20 figure

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

The development and operation of Liquid-Argon Time-Projection Chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.Comment: Preprint to be submitted to The European Physical Journal