Erratum After publication of the original article [1] it was brought to our attention that some of the authors’ final corrections were not incorporated in the online version of the paper. 1. In the ‘Background’ section, third paragraph, “Wold Health Organisation” has been corrected to “World Health Organisation”. 2. In Table 1, under column ‘Description of variables’ , “Respondents’ higest educ...

Recent research demonstrated that mutation-based fault localization techniques are relatively accurate and practical. However, these methods have never been compared and have only been assessed with simple hand-seeded faults. Therefore, their actual practicality is questionable when it comes to real-wold faults. To deal with this limitation we asses and compare the two main mutation-based fault...

simultaneous thermal analysis (sta) method has been applied to study decomposition reactions of ap under a flowing nitrogen atmosphere and static air. results obtained indicate that a phase transformation occurs prior to the decomposition reaction. decomposition takes place exothermally in two stages, first stage of decomposition could be suppressed by the controlled heating programme. addition...

in the 1960's noboru iwahori and hideya matsumoto, eiichi abe and kazuo suzuki, and michael stein discovered that chevalley groups $g=g(phi,r)$ over a semilocal ring admit remarkable gauss decomposition $g=tuu^-u$, where $t=t(phi,r)$ is a split maximal torus, whereas $u=u(phi,r)$ and $u^-=u^-(phi,r)$ are unipotent radicals of two opposite borel subgroups $b=b(phi,r)$ and $b^-=b^-(phi,r)$ contai...

We propose a semi-supervised generative model, SeGMA, which learns joint probability distribution of data and their classes is implemented in typical Wasserstein autoencoder framework. choose mixture Gaussians as target latent space, provides natural splitting into clusters. To connect Gaussian components with correct classes, we use small amount labeled classifier induced by the distribution. ...

Generative models dealing with modeling a joint data distribution are generally autoencoder, or GAN based. Both have pros and cons, generating blurry images being unstable in training. We propose new generative model resembling classical transforming Gaussian noise into space without adversarial optimization. Training of the proposed is two-step procedure. First, we train an autoencoder-based a...

let $n,t_1,...,t_k$ be distinct positive integers. a toeplitz graph $g=(v, e)$ denoted by $t_n$ is a graph, where $v ={1,...,n}$ and $e= {(i,j) : |i-j| in {t_1,...,t_k}}$.in this paper, we present some results on decomposition of toeplitz graphs.

the main objective of this study is to swing krull intersection theorem in primary decomposition of rings and modules to the primary decomposition of soft rings and soft modules. to fulfill this aim several notions like soft prime ideals, soft maximal ideals, soft primary ideals, and soft radical ideals are introduced for a soft ring over a given unitary commutative ring. consequently, the p...

background: despite the enhancement in health outcomes worldwide, health inequity and inequality is one of the most relevant topics both for health policy and public health. this research was designed to decompose the health inequality of people living in shiraz, south-west iran. methods: data were obtained from a multistage-sample survey conducted in shiraz from april to may 2012, to find dete...