Three Flavour Majorana Neutrinos with Magnetic Moments in a Supernova

The resonant transition effects MSW and NSFP for three flavour Majorana neutrinos in a supernova are considered, where the transition magnetic moments are likely to play a relevant role in neutrino physics. In this scenario, the deformed thermal neutrino distributions are obtained for different choices of the electron-tau mixing angle. Detailed predictions for the future large neutrino detectors are also given in terms of the ratio between the spectra of recoil electrons for deformed and undeformed spectra.Comment: 20 pages, LaTeX, 5 figures.p

The Maker Faire of Rome as a window of observation on the new perspectives for local economic development and the new urban entrepreneurial ecosystems

The rise of the Maker Movement – representing small businesses active in the digital fabrication and the creative industry field – is indicative of the emergence of a new type of urban economy and labour regulations in many cities. Trade fairs have been central to the dynamics of these makers as well as an institutional tool to build an economic reputation for the place hosting them. This paper draws upon a survey of exhibitors at, and interviews with organizers of, the Maker Faire of Rome 2015 to describe the features of this unfolding entrepreneurial world. The findings indicate that, although cities are once again the nexus of contemporary innovation trends, these are deeply intertwined with the surrounding socio-political context. Specifically, and in some contrast to the extant literature on creativity, the Rome case indicates the salience of Makers to those urban economies most in need of regeneration

Secure self-calibrating quantum random bit generator

Random bit generators (RBGs) are key components of a variety of information processing applications ranging from simulations to cryptography. In particular, cryptographic systems require "strong" RBGs that produce high-entropy bit sequences, but traditional software pseudo-RBGs have very low entropy content and therefore are relatively weak for cryptography. Hardware RBGs yield entropy from chaotic or quantum physical systems and therefore are expected to exhibit high entropy, but in current implementations their exact entropy content is unknown. Here we report a quantum random bit generator (QRBG) that harvests entropy by measuring single-photon and entangled two-photon polarization states. We introduce and implement a quantum tomographic method to measure a lower bound on the "min-entropy" of the system, and we employ this value to distill a truly random bit sequence. This approach is secure: even if an attacker takes control of the source of optical states, a secure random sequence can be distilled.Comment: 5 pages, 2 figure

A review of the immunomodulating components of maternal breast milk and protection against necrotizing enterocolitis

Breast milk contains immunomodulating components that are beneficial to newborns during maturation of their immune system. Human breast milk composition is influenced by an infant\u27s gestational and chronological age, lactation stage, and the mother and infant\u27s health status. Major immunologic components in human milk, such as secretory immunoglobulin A (IgA) and growth factors, have a known role in regulating gut barrier integrity and microbial colonization, which therefore protect against the development of a life-threatening gastrointestinal illness affecting newborn infants called necrotizing enterocolitis (NEC). Breast milk is a known protective factor in the prevention of NEC when compared with feeding with commercial formula. Breast milk supplements infants with human milk oligosaccharides, leukocytes, cytokines, nitric oxide, and growth factors that attenuate inflammatory responses and provide immunological defenses to reduce the incidence of NEC. This article aims to review the variety of immunomodulating components in breast milk that protect the infant from the development of NEC

"Magic" numbers in Smale's 7th problem

Smale's 7-th problem concerns N-point configurations on the 2-dim sphere which minimize the logarithmic pair-energy V_0(r) = -ln r averaged over the pairs in a configuration; here, r is the chordal distance between the points forming a pair. More generally, V_0(r) may be replaced by the standardized Riesz pair-energy V_s(r)= (r^{-s} -1)/s, which becomes - ln r in the limit s to 0, and the sphere may be replaced by other compact manifolds. This paper inquires into the concavity of the map from the integers N>1 into the minimal average standardized Riesz pair-energies v_s(N) of the N-point configurations on the 2-sphere for various real s. It is known that v_s(N) is strictly increasing for each real s, and for s<2 also bounded above, hence "overall concave." It is (easily) proved that v_{-2}(N) is even locally strictly concave, and that so is v_s(2n) for s<-2. By analyzing computer-experimental data of putatively minimal average Riesz pair-energies v_s^x(N) for s in {-1,0,1,2,3} and N in {2,...,200}, it is found that {v}_{-1}^x(N) is locally strictly concave, while v_s^x(N) is not always locally strictly concave for s in {0,1,2,3}: concavity defects occur whenever N in C^{x}_+(s) (an s-specific empirical set of integers). It is found that the empirical map C^{x}_+(s), with s in {-2,-1,0,1,2,3}, is set-theoretically increasing; moreover, the percentage of odd numbers in C^{x}_+(s), s in {0,1,2,3}, is found to increase with s. The integers in C^{x}_+(0) are few and far between, forming a curious sequence of numbers, reminiscent of the "magic numbers" in nuclear physics. It is conjectured that the "magic numbers" in Smale's 7-th problem are associated with optimally symmetric optimal-energy configurations.Comment: 109 pages, of which 30 are numerical data tables. Thoroughly revised version, to appear in J. Stat. Phys. under the different title: `Optimal N point configurations on the sphere: "Magic" numbers and Smale's 7th problem

Planning for residential ‘value’? London’s densification policies and impacts

This paper considers the agency and influence of planning processes and densification policies on urban landscapes in London. Urban transformation through residential densification can bring opportunities for real estate development, combined with longer term investment and financial gains for local authorities through planning gain. However, the measurements and indicators used to define density and its impacts could be better understood both objectively and subjectively through the lens of an extended notion of ‘value’. Such experiences of density can be viewed bluntly as positive or negative. This research investigates nuanced dimensions of density and adopts a primarily qualitative approach, reflecting on relevant literature and wider policy context through a discourse analysis relating to densification in London. The idea of elements of ‘value’ is explored and evaluated in ongoing developments through a detailed case study of Nine Elms, London. Quantitative data on the residential real estate market is used to illustrate investment flows. Conclusions consider best practice policy recommendations in relation to understandings of ‘value’

The Iconographic Exploitation of the Urban Space for the Amplification of the Symbols of the Camorra. The Case of Spanish Quarters, Naples, Italy

This contribution is inspired by a current scenario regarding the city of Naples, Italy, where a strong popular uprising is underway against local institutions that are destroying the Camorra murals celebrating its “heroes” died in “war”. These events are very interesting to analyse the theme of the iconographic exploitation of urban space by the criminal part of society in order to amplify the identity symbols of a tribal structure such as the Camorra. While on the one hand the analysis aims to show the positive response of civil society and institutions in eradicating these celebra tory icons of evil, on the other hand the research intends to emphasise the profound and worrying systemic modification of public space according to subjective and nega tive canons that, however, are also shared by some intellectuals and even an adminis trative cour

Prospective and retrospective performance assessment of Advanced Driver Assistance Systems in imminent collision scenarios: the CMI-Vr approach

Structured abstract Introduction Prospective and retrospective performance assessment of Advanced Driver Assistance Systems (ADASs) is fundamental to pilot future enhancements for active safety devices. In critical road scenarios between two vehicles where ADAS activation enables collision mitigation only, currently available assessment methodologies rely on the reconstruction of the impact phase consequent to the specific intervention on braking and steering: the velocity change sustained by the vehicle in the collision ($$\Delta V$$ Δ V ) is retrieved, so that IR decrease for the vehicle occupants can be obtained by appropriate Injury Risk (IR) models. However, information regarding the ADAS performance is available only after the impact phase reconstruction and not just as when the criticality occurs in the pre-impact phase: the best braking and steering alternative cannot be immediately envisaged, since a direct correlation lacks between the braking/steering intervention and IR. Method This work highlights an ADAS performance assessment method based on the disaggregation of $$\Delta V$$ Δ V in the two pre-impact parameters closing velocity at collision ($$V_r$$ V r ) and impact eccentricity, represented by the Crash Momentum Index (CMI). Such a disaggregation leads to the determination of IR based solely on impact configuration between the vehicles, without directly considering the impact phase. The performance of diverse ADASs in terms of intervention logic are directly comparable based on the resulting impact configuration, associated with a single coordinate in the CMI-$$V_r$$ V r plane and a sole IR value as a consequence. Results The CMI-$$V_r$$ V r approach is employable for both purposes of prospective and retrospective performance assessment of ADAS devices. To illustrate the advantages of the methodology, a solution for prospective assessment based on the CMI-$$V_r$$ V r plane is initially proposed and applied to case studies: this provides direct suggestions regarding the most appropriate interventions on braking and steering for IR minimization, fundamental in the tuning or development phase of an ADAS. A method for retrospective assessment is ultimately contextualized in the EuroNCAP "Car-to-Car Rear moving" test for an Inter-Urban Autonomous Emergency Braking system, a device implemented on a significant portion of the circulating fleet. Conclusions Based on the evidenced highlights, it is demonstrated that the approach provides complementary information compared to well-established performance assessment methodologies in all stages of an ADAS life cycle, by suggesting a direct physical connection in the pre-impact phase between the possible ADAS interventions and the foreseeable injury outcomes

Mask-R 2 CNN: a distance-field regression version of Mask-RCNN for fetal-head delineation in ultrasound images

Background and objectives: Fetal head-circumference (HC) measurement from ultrasound (US) images provides useful hints for assessing fetal growth. Such measurement is performed manually during the actual clinical practice, posing issues relevant to intra- and inter-clinician variability. This work presents a fully automatic, deep-learning-based approach to HC delineation, which we named Mask-R2CNN. It advances our previous work in the field and performs HC distance-field regression in an end-to-end fashion, without requiring a priori HC localization nor any postprocessing for outlier removal. Methods: Mask-R2CNN follows the Mask-RCNN architecture, with a backbone inspired by feature-pyramid networks, a region-proposal network and the ROI align. The Mask-RCNN segmentation head is here modified to regress the HC distance field. Results: Mask-R2CNN was tested on the HC18 Challenge dataset, which consists of 999 training and 335 testing images. With a comprehensive ablation study, we showed that Mask-R2CNN achieved a mean absolute difference of 1.95 mm (standard deviation = ± 1.92 mm), outperforming other approaches in the literature. Conclusions: With this work, we proposed an end-to-end model for HC distance-field regression. With our experimental results, we showed that Mask-R2CNN may be an effective support for clinicians for assessing fetal growth