Development of 3-D Ice Accretion Measurement Method

A research plan is currently being implemented by NASA to develop and validate the use of a commercial laser scanner to record and archive fully three-dimensional (3-D) ice shapes from an icing wind tunnel. The plan focused specifically upon measuring ice accreted in the NASA Icing Research Tunnel (IRT). The plan was divided into two phases. The first phase was the identification and selection of the laser scanning system and the post-processing software to purchase and develop further. The second phase was the implementation and validation of the selected system through a series of icing and aerodynamic tests. Phase I of the research plan has been completed. It consisted of evaluating several scanning hardware and software systems against an established selection criteria through demonstrations in the IRT. The results of Phase I showed that all of the scanning systems that were evaluated were equally capable of scanning ice shapes. The factors that differentiated the scanners were ease of use and the ability to operate in a wide range of IRT environmental conditions

μ→eγ\mu \to e \gamma and μ→3e\mu \to 3e processes with polarized muons and supersymmetric grand unified theories

$\mu^{+} \to e^{+} \gamma$ and $\mu^{+} \to e^{+}e^{+}e^{-}$ processes are analyzed in detail with polarized muons in supersymmetric grand unified theories. We first present Dalitz plot distribution for $\mu^{+} \to e^{+}e^{+}e^{-}$ decay based on effective Lagrangian with general lepton-flavor-violating couplings and define various P- and T-odd asymmetries. We calculate branching ratios and asymmetries in supersymmetric SU(5) and SO(10) models taking into account complex soft supersymmetry breaking terms. Imposing constraints from experimental bounds on the electron, neutron and atomic electric dipole moments, we find that the T-odd asymmetry for $\mu^{+} \to e^{+}e^{+}e^{-}$ can be 15% in the SU(5) case. P-odd asymmetry with respect to muon polarization for $\mu^{+} \to e^{+} \gamma$ varies from -20% to -100% for the SO(10) model while it is $+100$ in the SU(5) case. We also show that the P-odd asymmetries in $\mu^{+} \to e^{+}e^{+}e^{-}$ and the ratio of $\mu^{+} \to e^{+}e^{+}e^{-}$ and $\mu^{+} \to e^{+} \gamma$ branching fractions are useful to distinguish different models.Comment: 52 pages, 15 figure

Application of Gauss's theorem to quantify localized surface emissions from airborne measurements of wind and trace gases

Airborne estimates of greenhouse gas emissions are becoming more prevalent with the advent of rapid commercial development of trace gas instrumentation featuring increased measurement accuracy, precision, and frequency, and the swelling interest in the verification of current emission inventories. Multiple airborne studies have indicated that emission inventories may underestimate some hydrocarbon emission sources in US oil- and gas-producing basins. Consequently, a proper assessment of the accuracy of these airborne methods is crucial to interpreting the meaning of such discrepancies. We present a new method of sampling surface sources of any trace gas for which fast and precise measurements can be made and apply it to methane, ethane, and carbon dioxide on spatial scales of  ∼ 1000 m, where consecutive loops are flown around a targeted source region at multiple altitudes. Using Reynolds decomposition for the scalar concentrations, along with Gauss's theorem, we show that the method accurately accounts for the smaller-scale turbulent dispersion of the local plume, which is often ignored in other average mass balance methods. With the help of large eddy simulations (LES) we further show how the circling radius can be optimized for the micrometeorological conditions encountered during any flight. Furthermore, by sampling controlled releases of methane and ethane on the ground we can ascertain that the accuracy of the method, in appropriate meteorological conditions, is often better than 10 %, with limits of detection below 5 kg h−1 for both methane and ethane. Because of the FAA-mandated minimum flight safe altitude of 150 m, placement of the aircraft is critical to preventing a large portion of the emission plume from flowing underneath the lowest aircraft sampling altitude, which is generally the leading source of uncertainty in these measurements. Finally, we show how the accuracy of the method is strongly dependent on the number of sampling loops and/or time spent sampling the source plume

Combining macula clinical signs and patient characteristics for age-related macular degeneration diagnosis: a machine learning approach

Background: To investigate machine learning methods, ranging from simpler interpretable techniques to complex (non-linear) “black-box” approaches, for automated diagnosis of Age-related Macular Degeneration (AMD). Methods: Data from healthy subjects and patients diagnosed with AMD or other retinal diseases were collected during routine visits via an Electronic Health Record (EHR) system. Patients’ attributes included demographics and, for each eye, presence/absence of major AMD-related clinical signs (soft drusen, retinal pigment epitelium, defects/ pigment mottling, depigmentation area, subretinal haemorrhage, subretinal fluid, macula thickness, macular scar, subretinal fibrosis). Interpretable techniques known as white box methods including logistic regression and decision trees as well as less interpreitable techniques known as black box methods, such as support vector machines (SVM), random forests and AdaBoost, were used to develop models (trained and validated on unseen data) to diagnose AMD. The gold standard was confirmed diagnosis of AMD by physicians. Sensitivity, specificity and area under the receiver operating characteristic (AUC) were used to assess performance. Results: Study population included 487 patients (912 eyes). In terms of AUC, random forests, logistic regression and adaboost showed a mean performance of (0.92), followed by SVM and decision trees (0.90). All machine learning models identified soft drusen and age as the most discriminating variables in clinicians’ decision pathways to diagnose AMD. C Conclusions: Both black-box and white box methods performed well in identifying diagnoses of AMD and their decision pathways. Machine learning models developed through the proposed approach, relying on clinical signs identified by retinal specialists, could be embedded into EHR to provide physicians with real time (interpretable) support

A more fine-grained measure towards animal welfare: a study with regards to gender differences in Spanish students

The environmental issue is nowadays taking more importance in the environmental awareness all around the world, and in this field, animal consideration is more and more spread. A highlighted part in globalisation is the animal welfare awareness. This article presents a study comparing attitudes towards animals among secondary and university students in reference to gender. It was carried out on 1394 Spanish participants from 11 to 26 years. The instrument used in the study is the reviewed version of the Animal Welfare Attitude Scale which was renamed as “Animal Welfare Attitude-Revised Scale” (AWA-R Scale), with a Cronbach a reliability value of 0.85. It is subdivided into four components namely C1: animal abuse for pleasure or due to ignorance; C2: leisure with animals; C3: farm animals; and C4: animal abandonment. These components have been deeply detailed by a confirmatory factor analysis (CFA), which highly contributes to define the position of participants for the different dimensions of animal welfare. It is concluded that significant differences exist between males’ and females’ attitudes in all components of the AWA-R Scale. It is also suggested that two social characteristics—people’s attitudes towards animals and towards environmental protection—are, at the very least, coexistent and may indeed be interdependent. These differences between gender in matters of socialisation could thus be reflected in environmental attitudes, and also in others related to them, i.e. animal welfare attitudes

Point Mutations in Aβ Result in the Formation of Distinct Polymorphic Aggregates in the Presence of Lipid Bilayers

A hallmark of Alzheimer's disease (AD) is the rearrangement of the β-amyloid (Aβ) peptide to a non-native conformation that promotes the formation of toxic, nanoscale aggregates. Recent studies have pointed to the role of sample preparation in creating polymorphic fibrillar species. One of many potential pathways for Aβ toxicity may be modulation of lipid membrane function on cellular surfaces. There are several mutations clustered around the central hydrophobic core of Aβ near the α-secretase cleavage site (E22G Arctic mutation, E22K Italian mutation, D23N Iowa mutation, and A21G Flemish mutation). These point mutations are associated with hereditary diseases ranging from almost pure cerebral amyloid angiopathy (CAA) to typical Alzheimer's disease pathology with plaques and tangles. We investigated how these point mutations alter Aβ aggregation in the presence of supported lipid membranes comprised of total brain lipid extract. Brain lipid extract bilayers were used as a physiologically relevant model of a neuronal cell surface. Intact lipid bilayers were exposed to predominantly monomeric preparations of Wild Type or different mutant forms of Aβ, and atomic force microscopy was used to monitor aggregate formation and morphology as well as bilayer integrity over a 12 hour period. The goal of this study was to determine how point mutations in Aβ, which alter peptide charge and hydrophobic character, influence interactions between Aβ and the lipid surface. While fibril morphology did not appear to be significantly altered when mutants were prepped similarly and incubated under free solution conditions, aggregation in the lipid membranes resulted in a variety of polymorphic aggregates in a mutation dependent manner. The mutant peptides also had a variable ability to disrupt bilayer integrity

The Effect of Service on Research Performance: A Study on Italian Academics in Management

Academics all over the world are feeling the increasing pressure to attain satisfactory research performance. Since research is not the only activity required of academics, though, the debate on how it may be coupled with other knowledge transfer activities like teaching, patenting, and dissemination has been captivating scholars interested in higher education. Literature is surprisingly silent about the interplay between research performance and other roles and tasks that faculty are expected to carry out, namely academic citizenship, intended as the service that they provide to their institution, to the scientific community, and to the larger society. Through a negative binomial regression conducted on 692 Italian academics in management, this paper investigates both the direct and moderating effect exerted by academic citizenship on the relationship between research performance in two subsequent evaluation exercises, thus advancing our knowledge of the relationship between research and service. Findings show that institutional service acts as a pure moderator, discipline-based service is a quasi-moderator, while public service exerts only a direct negative effect on research performance. In light of the emergent interplay between research and service, the necessity to boost reflection on academic citizenship is discussed and suggestions for its acknowledgement and advancement are formulated

Semiconductor Spintronics

Spintronics refers commonly to phenomena in which the spin of electrons in a solid state environment plays the determining role. In a more narrow sense spintronics is an emerging research field of electronics: spintronics devices are based on a spin control of electronics, or on an electrical and optical control of spin or magnetism. This review presents selected themes of semiconductor spintronics, introducing important concepts in spin transport, spin injection, Silsbee-Johnson spin-charge coupling, and spindependent tunneling, as well as spin relaxation and spin dynamics. The most fundamental spin-dependent nteraction in nonmagnetic semiconductors is spin-orbit coupling. Depending on the crystal symmetries of the material, as well as on the structural properties of semiconductor based heterostructures, the spin-orbit coupling takes on different functional forms, giving a nice playground of effective spin-orbit Hamiltonians. The effective Hamiltonians for the most relevant classes of materials and heterostructures are derived here from realistic electronic band structure descriptions. Most semiconductor device systems are still theoretical concepts, waiting for experimental demonstrations. A review of selected proposed, and a few demonstrated devices is presented, with detailed description of two important classes: magnetic resonant tunnel structures and bipolar magnetic diodes and transistors. In most cases the presentation is of tutorial style, introducing the essential theoretical formalism at an accessible level, with case-study-like illustrations of actual experimental results, as well as with brief reviews of relevant recent achievements in the field.Comment: tutorial review; 342 pages, 132 figure