Renormalization group evolution induced leptogenesis in the minimal seesaw model with the trimaximal mixing and mu-tau reflection symmetry

In this paper, we consider the imbedding of the popular and well-motivated trimaximal mixing and μ–τ reflection symmetry (which can help us shape the forms of the neutrino mass matrix) in the minimal seesaw model (which contains much fewer parameters than the general seesaw model) with two TeV-scale right-handed neutrinos (for realizing a low-scale seesaw) of nearly degenerate masses (for realizing a resonant leptogenesis). However, either for the trimaximal mixing scenario (which is realized through the Form Dominance approach here) or for the μ–τ reflection symmetry scenario, leptogenesis cannot proceed. To address this issue, we consider the possibility that the special forms of the neutrino mass matrix for the trimaximal mixing and μ–τ reflection symmetry are slightly broken by the renormalization group evolution effect, thus allowing leptogenesis to proceed. It is found that in the normal case of the neutrino mass ordering, the baryon asymmetry thus generated can reproduce the observed value. For completeness, we have also extended our analysis to the scenario that two right-handed neutrinos are not nearly degenerate any more. Unfortunately, in this scenario the final baryon asymmetry is smaller than the observed value by several orders of magnitude.

Understanding the Effect of a Soft Drinks Industry Levy on Consumer Well-Being in the UK: First Estimates

This paper is a first attempt to provide a quantitative evaluation of consumer well-being resulting from the UK Soft Drinks Industry Levy introduced in April 2018. Using a model setup that encompasses both a normal case and a Giffen case for sugary drinks consumption, a computational exercise is performed to quantify the welfare social loss for a variety of household incomes. The model demonstrates that the introduction of a soft drinks levy results in a non-trivial welfare loss, particularly in terms of monetary value and weight effect. We also find that the wealthiest individuals in society are affected positively by this levy, whilst the poorest segment of the population are adversely affected, especially in the presence of a binding nutritional constraint.

Automated Keratoconus Detection by 3D Corneal Images Reconstruction

This paper presents a technique for the detection of keratoconus via the construction of a 3D eye images from 2D frontal and lateral eye images. Keratoconus is a disease that affects the cornea. Normal case eyes have a round-shaped cornea, while patients who suffer from keratoconus have a cone-shaped cornea. Early diagnosis can decrease the risk of eyesight loss. Our aim is to create a method of fully automated keratoconus detection using digital-camera frontal and lateral eye images. The presented technique accurately determines case severity. Geometric features are extracted from 2D images to estimate depth information used to build 3D images of the cornea. The proposed methodology is easy to implement and time-efficient. 2D images of the eyes (frontal and lateral) are used as input, and 3D images from which the curvature of the cornea can be detected are produced as output. Our method involves two main steps: feature extraction and depth calculation. Machine learning from the 3D images dataset Dataverse, specifically taken by the Cornea/Anterior Segment OCT SS-1000 (CASIA), was performed. Results show that the method diagnosed the four stages of keratoconus (severe, moderate, mild, and normal) with an accuracy of 97.8%, as compared to manual diagnosis done by medical experts.

Scaling Membership of Byzantine Consensus

Scaling Byzantine Fault Tolerant (BFT) systems in terms of membership is important for secure applications with large participation such as blockchains. While traditional protocols have low latency, they cannot handle many processors. Conversely, blockchains often have hundreds to thousands of processors to increase robustness, but they typically have high latency or energy costs. We describe various sources of unscalability in BFT consensus protocols. To improve performance, many BFT protocols optimize the “normal case,” where there are no failures. This can be done in a modular fashion by wrapping existing BFT protocols with a building block that we call alliance . In normal case executions, alliance can scalably determine if the initial conditions of a BFT consensus protocol predetermine the outcome, obviating running the consensus protocol. We give examples of existing protocols that solve alliance. We show that a solution based on hypercubes and MAC s has desirable scalability and performance in normal case executions, with only a modest overhead otherwise. We provide important optimizations. Finally, we evaluate our solution using the ns3 simulator and show that it scales up to thousands of processors and compare with prior work in various network topologies.

The Extension of a Method of Risk Analysis from Aeronautics to Medicine. Application to Endoscopic Surgery

The 6-4-3-5 method of risk analysis from Aeronautics is adapted and extended to Medicine with emphasis on Endoscopic Surgery. The new main risk factors are identified and the corresponding risk severity is evaluated. In the complete method “6”represents the number of persons in the evaluating team,“4” gives the used weights 1; 2; 3; 4; “3” is the number of variants required to each person from the evaluating team and “5” indicates the time for evaluation (five minutes). The risk is defined as a product between the probability of an event and the event severity, S, taking one of the values 1; 2; 3; 4. The value S = 1 represents the normal case and S = 4 corresponds to the maximum damage, for example, dead people resulting in one aviation accident. Three more simple variants are also given.

Perfect State Transfer on Cayley Graphs over Dihedral Groups: The Non-Normal Case

Recently, perfect state transfer (PST for short) on graphs has attracted great attention due to their applications in quantum information processing and quantum computations. Many constructions and results have been established through various graphs. However, most of the graphs previously investigated are abelian Cayley graphs. Necessary and sufficient conditions for Cayley graphs over dihedral groups having perfect state transfer were studied recently. The key idea in that paper is the assumption of the normality of the connection set. In those cases, viewed as an element in a group algebra, the connection set is in the center of the group algebra, which makes the situations just like in the abelian case. In this paper, we study the non-normal case. In this case, the discussion becomes more complicated. Using the representations of the dihedral group $D_n$, we show that ${\rm Cay}(D_n,S)$ cannot have PST if $n$ is odd. For even integers $n$, it is proved that if ${\rm Cay}(D_n,S)$ has PST, then $S$ is normal.

Optimization Audicor for Normal and Abnormal Heart Sounds Characteristic

Heart Sounds are important things in the human body that can deliver information related to the heart condition. However, a recorded signal such as PCG and ECG that getting through Audicor still contain unexpected components or noise while the recording process happens it makes the result data from Audicor cannot directly use to recognize the condition of the heart. This research presents signal processing and data analysis to suppress the noise of the heart sounds that getting while the process of recording data happens. The cleaned heart sound will be processed in feature extraction by using FFT and PCA that capable to produce the feature both of the normal and abnormal heart sounds. For the normal case, we get the data from some healthy volunteers recorded by using Audicor. While the abnormal heart sound we focus to observe the data that contain Ventricular Septal Defect (VSD) that getting from a partner hospital. As a result, feature both normal and abnormal heart sounds can be separated.

Kekerasan Simbolik (Studi Relasi Pendidik Dan Peserta Didik )

The background of this research is the existence of the symbolic domain, related between the teacher and the student. The symbolic violence that occurs is not expelled from the dynamics of education in Indonesia. This case is encouraged by the domination’s role, capital, domain, habitus which owned by an educator. Furthermore, the form of symbolic violence works through the mechanism of aufernisasi and sensorisasi, and it happened in the relation of the teacher and student. The symbolic violence is not something easy to be known, because it is running by the symbols of the discourse which the student areas the hegemony object, that is dominated by the produced meaning, based the domain of the subject, who has the domination. This research is a discourse analysis study, and the data is compelled by the verbal communication through the observation, the note, and the record. The result of this research is found that in the learning process, the student is headed in a single space and imposed to obey the rules of the educator. indeed, this relation is normal case, however, in this situation, the awareness is necessary for that it potentially become the symbolic violence.

Lowering Coupling in Distributed Applications With Compliance and Conformance

The interaction of applications in distributed system raises an integration problem that application-developing methods need to solve, even if the initial specifications change, which is actually the normal case. Current integration technologies, such as Web Services and RESTful APIs, solve the interoperability problem but usually entail more coupling than required by the interacting applications, since they share data schemas between applications, even if they do not actually exercise all the features of those schemas. The fundamental problem of application integration is therefore how to provide at most the minimum coupling possible while ensuring at least the minimum interoperability requirements. This chapter proposes compliance and conformance as the concepts to achieve this goal by sharing only the subset of the features of the data schema that applications actually use, with the goal of supporting a new architectural style, structural services, which seeks to combine the advantages of both SOA and REST.