Double diffusive convection during solidification of ammonium chloride - water (NH4CL-H20) mixture in a trapezoidal cavity

The effect of the initial concentration of ammonium chloride (sub eutectic: C \u3c 19.8 wt. % and eutectic Ce= 19.8 wt. %) and boundary temperatures (Tcold = -30 0C to -10 0C) on the solidification process is examined. Particle Image Velocimetry (PIV) is used in this study to measure the velocity fields in the melt during the solidification process. The distributions of temperatures at discrete locations in the solution and the boundary walls were measured. This study focuses on the solidification of an ammonium chloride-water (NH4Cl- H2O) solution in a trapezoidal cavity with one and two inclined cooling walls. The thermosolutal convective flow strongly influenced the rate of freezing. An increase in thermal driving force increased the rate of freezing. Increased initial concentration retarded the freezing process and primarily affected the structure of the solid and mush regions. The results of this study will contribute in understanding the phenomena and bridge the gap between the engineering aspect and physics background for the dynamics of solid phase formation during castings, ingots, and polymerization

Multivariate Cryptography with Mappings of Discrete Logarithms and Polynomials

In this paper, algorithms for multivariate public key cryptography and digital signature are described. Plain messages and encrypted messages are arrays, consisting of elements from a fixed finite ring or field. The encryption and decryption algorithms are based on multivariate mappings. The security of the private key depends on the difficulty of solving a system of parametric simultaneous multivariate equations involving polynomial or exponential mappings. The method is a general purpose utility for most data encryption, digital certificate or digital signature applications. For security protocols of the application layer level in the OSI model, the methods described in this paper are useful

Multivariate Polynomial and Exponential Mappings based Password Authentication Protocol

In this paper, a multivariate polynomial and exponential mappings based password protocol is presented. The method can be utilized in public domains. The key generator generates a vector, intended to be used as a password by the authentication protocol subsequently, such that when the vector is substituted and evaluated in certain fixed multivariate polynomials -- that may be listed in a public domain -- the value $0$ is found as a result of proper authentication. The public domain in this context could be internal to a large, and possibly distributed, system. The key generator can take hints from the owner of the password to generate the particular zero vector to suit the user. It may take into consideration biometric and any other user specific information at the time of key generation. The information collected by the key generator can be saved by the owner of the password for its possible retrieval upon requisition by the user, during the period of its validity, in case it is forgotten by the user

The genetic architecture of type 2 diabetes

The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of heritability. To test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole genome sequencing in 2,657 Europeans with and without diabetes, and exome sequencing in a total of 12,940 subjects from five ancestral groups. To increase statistical power, we expanded sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support a major role for lower-frequency variants in predisposition to type 2 diabetes

Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes

Hundreds of thousands of genetic variants have been reported to cause severe monogenic diseases, but the probability that a variant carrier develops the disease (termed penetrance) is unknown for virtually all of them. Additionally, the clinical utility of common polygenetic variation remains uncertain. Using exome sequencing from 77,184 adult individuals (38,618 multi-ancestral individuals from a type 2 diabetes case-control study and 38,566 participants from the UK Biobank, for whom genotype array data were also available), we apply clinical standard-of-care gene variant curation for eight monogenic metabolic conditions. Rare variants causing monogenic diabetes and dyslipidemias display effect sizes significantly larger than the top 1% of the corresponding polygenic scores. Nevertheless, penetrance estimates for monogenic variant carriers average 60% or lower for most conditions. We assess epidemiologic and genetic factors contributing to risk prediction in monogenic variant carriers, demonstrating that inclusion of polygenic variation significantly improves biomarker estimation for two monogenic dyslipidemias