Blood-Sucking Fly <I>Icosta ardeae</I> – Its Distribution and Probable Role in Circulation of West-Nile FeverVirus

Communication comprises materials on distribution of blood-sucking fly, Icosta ardeae, in the territory of the Russian Federation and bordering states. Based on the analysis of literature data, collection assets, and personal investigations assumed has been the fact that this species is more widely spread in the local fauna than it was anticipated earlier. The fly parasitizes on the birds of 11 species, orders - ciconiiformes (storks), shore (wading) birds, Gruiformes, and fowl-like birds (Galliformes). More often I. ardeae is seen among bitterns – 43 % of the findings, abundance index –5,9. Therewith, put forward is the suggestion concerning the role of the species and other Hippoboscidae in the process of persistence and distribution of West-Nile fever virus. Studies of this group of insects can be of use for identification of mechanisms that benefit natural foci extension and development as regards various infectious diseases

Computing Individual Discrete Logarithms Faster in GF(pn)(p^n) with the NFS-DL Algorithm

International audienceThe Number Field Sieve (NFS) algorithm is the best known method to compute discrete logarithms (DL) in finite fields $\mathbb{F}_{p^n}$, with $p$ medium to large and $n \geq 1$ small. This algorithm comprises four steps: polynomial selection, relation collection, linear algebra and finally, individual logarithm computation. The first step outputs two polynomials defining two number fields, and a map from the polynomial ring over the integers modulo each of these polynomials to $\mathbb{F}_{p^n}$. After the relation collection and linear algebra phases, the (virtual) logarithm of a subset of elements in each number field is known. Given the target element in $\mathbb{F}_{p^n}$, the fourth step computes a preimage in one number field. If one can write the target preimage as a product of elements of known (virtual) logarithm, then one can deduce the discrete logarithm of the target. As recently shown by the Logjam attack, this final step can be critical when it can be computed very quickly. But we realized that computing an individual DL is much slower in medium-and large-characteristic non-prime fields $\mathbb{F}_{p^n}$ with $n \geq 3$, compared to prime fields and quadratic fields $\mathbb{F}_{p^2}$. We optimize the first part of individual DL: the \emph{booting step}, by reducing dramatically the size of the preimage norm. Its smoothness probability is higher, hence the running-time of the booting step is much improved. Our method is very efficient for small extension fields with $2 \leq n \leq 6$ and applies to any $n > 1$, in medium and large characteristic

Competitive Situation in the Russian Federation: Modern Trends and Development Problems

The most important element constituting the basis for the functioning of the modern economy of Russia and ensuring the ongoing development of market relations is the competition, understood in a broad sense as a process of rivalry between economic agents, leading to a change in product handling conditions on the relevant market. 2015 was held in Russia under the influence of a number of factors, which contain signs of an economic crisis, which is a condition that affects the development of key segments of the domestic economy and determines Russian policy. Mutual sanctions from the European Union and Russia have caused some changes not only in the economy of the country as a whole, but also in the economy of its individual regions. The Russian economy was faced with the need for a very short time to make a leap in increasing the competitiveness of its products, as well as import substitution, which would normally take many years. In such conditions, the key role of the state is to support not only large branches of the economy and the defense sector, but also to develop a strategy for developing competitive relations in the sphere of small and medium-sized businesses. The article examines the main problems of ensuring Russia's competitiveness, the reasons for the low efficiency of the national innovation system