Distinguishing between Dirac and Majorana neutrinos in the presence of general interactions

We revisit the possibility of distinguishing between Dirac and Majorana neutrinos via neutrino-electron elastic scattering in the presence of all possible Lorentz-invariant interactions. Defining proper observables, certain regions of the parameter space can only be reached for Dirac neutrinos, but never for Majorana neutrinos, thus providing an alternative method to differentiate these two possibilities. We first derive analytically and numerically the most general conditions that would allow to distinguish Dirac from Majorana neutrinos, both in the relativistic and non-relativistic cases. Then, we apply these conditions to data on $\nu_\mu$-$e$ and $\bar{\nu}_e$-$e$ scatterings, from the CHARM-II and TEXONO experiments, and find that they are consistent with both types of neutrinos. Finally, we comment on future prospects of this kind of tests.Comment: Comments added, version to appear in JHE

Quantum Hall plateau transition in the lowest Landau level of disordered graphene

We investigate, analytically and numerically, the effects of disorder on the density of states and on the localization properties of the relativistic two dimensional fermions in the lowest Landau level. Employing a supersymmetric technique, we calculate the exact density of states for the Cauchy (Lorentzian) distribution for various types of disorders. We use a numerical technique to establish the localization-delocalization (LD) transition in the lowest Landau level. For some types of disorder the LD transition is shown to belong to a different universality class, as compared to the corresponding nonrelativistic problem. The results are relevant to the integer quantum Hall plateau transitions observed in graphene.Comment: 18 pages and 11 figure

Comparative Study on the Structures of Chinese and Korean Compound Words

The goal of the research was to compare the compound words in Chinese, an isolated language, and Korean, an agglutinative language. This research used library research. The researchers found that the main characteristics of the formation of Korean compound words were that the latter element was the central word. The method of word formation decided its lexical category. Moreover, most of the internal relationships of the compound words were connection and modification. While in Chinese, the endocentric compound noun decided the part of speech of the compound word, and could be the proceeding element or the latter element. Furthermore, Chinese contained no complicated morphological changes. It is concluded that Korean is a Subject–Object–Verb (SOV) language, where verb elements demonstrate a central feature of the compound verb are always a trailing part. Thus, there is no exocentric compound verb in Korean. By contrast, Chinese is a typical SVO language. When constituting the compound verbs, nouns or adjectives can function as the structural elements. Therefore, there is no permanent position for head words

Quantum oscillations in graphene in the presence of disorder and interactions

Quantum oscillations in graphene is discussed. The effect of interactions are addressed by Kohn's theorem regarding de Haas-van Alphen oscillations, which states that electron-electron interactions cannot affect the oscillation frequencies as long as disorder is neglected and the system is sufficiently screened, which should be valid for chemical potentials not very close to the Dirac point. We determine the positions of Landau levels in the presence of potential disorder from exact transfer matrix and finite size diagonalization calculations. The positions are shown to be unshifted even for moderate disorder; stronger disorder, can, however, lead to shifts, but this also appears minimal even for disorder width as large as one-half of the bare hopping matrix element on the graphene lattice. Shubnikov-de Haas oscillations of the conductivity are calculated analytically within a self-consistent Born approximation of impurity scattering. The oscillatory part of the conductivity follows the widely invoked Lifshitz-Kosevich form when certain mass and frequency parameters are properly interpreted.Comment: Appendix A was removed, as the content of it is already contained in Ref. 17. Thanks to M. A. H. Vozmedian

BMI, Gestational Weight Gain and Angiogenic Biomarker Profiles for Preeclampsia Risk

Objective: In May 2009, after considering short and long-term maternal/child outcomes, the Institute of Medicine (IOM) revised recommendations for gestational weight gain (GWG); however preeclampsia was dismissed due to insufficient evidence. Our objective was to evaluate preeclampsia risk by angiogenic-biomarker profile by both BMI and GWGadherence. Given numerous studies showing adipose tissue\u27s ability to stimulate angiogenesis, we hypothesized that overweight/obese (OW-OB) women and over-gainers (OG) would have altered angiogenic profiles as compared to underweight/normal-weight (UN) women and under-/appropriate-gainers (U-AG), respectively. Methods: Between 5/04-1/06, serial serum specimens collected from 94 women at high preeclampsia risk between 22-36 weeks. Soluble fms-like tyrosine kinase-1 (sFlt1), placental growth factor (PlGF) and soluble endoglin (sEng) measured by ELISA. BMI and GWG adherence categories determined by 1990 IOM recommendations. Within-women correlation and right-skewness handled by estimating linear mixed models for ln-transformed biomarkers and then exponentiating on ln scale (i.e.geometric means). T-test compared means in 3 windows. Results: Analytic sample included 82 subjects (342 specimens) without multiples or pregnancy-related hypertension diagnosis. Mean sFlt1 lower in all windows in OW-OB compared to U-N - significant only at 22-26wks [506.2 (95% CI 438.1-584.9) vs 745.5 (95% CI 595.9-932.6) p=0.04] and in OG compared to U-AG with significant comparisons (p=0.05) [22-26wks: 492.1 (95% CI 420.1-576.3) vs 691.3 (95% CI 574.0-832.6); 27-30 wks: 570.1 (95% CI 488.1-665.9) vs 788.8 (95% CI 656.8-947.4)]. Mean PIGF lower in all windows in OW-OB compared to U-N [22-26wks: 430.5 (95% CI 359.0-516.3) vs 588.6 (95% CI 444.3-779.7) p=0.06; 27-30wks: 475.8 (95% CI 398.7-567.8) vs 811.8 (95% CI 614.3-1072.9) p=0.005; 31-36wks: 428.5 (95% CI 358.0-513.0) vs 724.6 (95% CI 548.5-957.1) p=0.01] and in OG compared to U-AG with no significant comparisons. Mean ratio [(sFlt1+sEng):PIGF] trended higher in OW-OB compared to U-N women at 27-30 and 31-36 wks and in OG compared to UAG at 31-36wks; however no windows with significant comparisons. Conclusion: Findings suggest trends that OW-OB BMI and excessive GWG associated with angiogenic biomarker profiles consistent with higher preeclampsia risk. Exploratory study limited by small numbers. BMI and GWG as potentially modifiable factors merit furtherinvestigation for preeclampsia risk alteration. Presented at the Society of Gynecologic Investigation 2011 Annual Meeting, March 2011, Miami Beach, Florida

Does class size matter? An in-depth assessment of the effect of class size in software defect prediction

In the past 20 years, defect prediction studies have generally acknowledged the effect of class size on software prediction performance. To quantify the relationship between object-oriented (OO) metrics and defects, modelling has to take into account the direct, and potentially indirect, effects of class size on defects. However, some studies have shown that size cannot be simply controlled or ignored, when building prediction models. As such, there remains a question whether, and when, to control for class size. This study provides a new in-depth examination of the impact of class size on the relationship between OO metrics and software defects or defect-proneness. We assess the impact of class size on the number of defects and defect-proneness in software systems by employing a regression-based mediation (with bootstrapping) and moderation analysis to investigate the direct and indirect effect of class size in count and binary defect prediction. Our results show that the size effect is not always significant for all metrics. Of the seven OO metrics we investigated, size consistently has significant mediation impact only on the relationship between Coupling Between Objects (CBO) and defects/defect-proneness, and a potential moderation impact on the relationship between Fan-out and defects/defect-proneness. Based on our results we make three recommendations. One, we encourage researchers and practitioners to examine the impact of class size for the specific data they have in hand and through the use of the proposed statistical mediation/moderation procedures. Two, we encourage empirical studies to investigate the indirect effect of possible additional variables in their models when relevant. Three, the statistical procedures adopted in this study could be used in other empirical software engineering research to investigate the influence of potential mediators/moderators.Comment: Accepted to Empirical Software Engineering (to appear). arXiv admin note: text overlap with arXiv:2104.1234

Statistical Models of Runway Incursions Based on Runway Intersections and Taxiways

According to the Federal Aviation Administration (FAA), the number of runway incursions are rising. The configuration of runways and taxiways at airports has been identified by the FAA as possibly being related to the number of incursions. In this paper, the relationship between airport geometry factors and the number of runway incursions at specific United States airports is explored using statistical analyses. Airport operations data from the FAA Air Traffic Activity System, runway incursion data from the FAA Aviation Safety Information Analysis and Sharing System from 2009 through 2013, and airport geometry data created using airport geometry features from the FAA airport diagrams were collected. The 30 busiest airports with intersecting runways and the 30 busiest airports without intersecting runways were compared. As expected, the analysis of the data show that at alpha = 0.05 level, runway incursions occur at a more frequent rate for airports with intersecting runways compared to airports with no intersecting runways. In the second phase of statistical analysis, the number of incursions per 100,000 operations at the 63 busiest United States airports was analyzed using four airport geometry factors as independent variables in regression analysis. The resulting regression equation was significant at the alpha = 0.05 level and contained two independent variables: the number of crossing taxiways per runway and the number of runway intersections per runway. The equation and each variable in the equation are statistically significant and the equation explains 17.3% of the variation in incursions per 100,000 operations