Тенденції розвитку туристичної галузі в умовах глобальної нестабільності

Розглянуто питання розвитку світової туристичної галузі в умовах нестабільності та перспективи розвитку туризму на Україні.The problems of the global tourism industry in terms of instability and prospects for the development of tourism in Ukraine are discussed in the article.Рассмотрены вопросы развития мировой туристической отрасли в условиях нестабильности и перспективы развития туризма на Украине

Finding Low Degree Annihilators for a Boolean Function Using Polynomial Algorithms

Low degree annihilators for Boolean functions are of great interest in cryptology because of algebraic attacks on LFSR-based stream ciphers. Several polynomial algorithms for construction of low degree annihilators are introduced in this paper. The existence of such algorithms is studied for the following forms of the function representation: algebraic normal form (ANF), disjunctive normal form (DNF), conjunctive normal form (CNF), and arbitrary formula with the Boolean operations of negation, conjunction, and disjunction. For ANF and DNF of a Boolean function $f$ there exist polynomial algorithms that find the vector space $A_d (f)$ of all annihilators of degree $\leqslant d$. For CNF this problem is NP-hard. Nevertheless author introduces one polynomial algorithm that constructs some subspace of $A_d (f)$ having formula that represents $f$

The nucleotide sequence of bacteriophage T 5 leucine tRNA

AbstractUniformly 32P-labeled bacteriophage T5 leucine tRNA has been isolated by two-dimensional gel electrophoresis from phage-infected E. coli cells. Its nucleotide sequence has been determined by conventional techniques using TLC on cellulose for oligonucleotide fractionation:pGGGGCUAUGCUGGAACDGmGDAGACAAUACGGCCUUAGm;6UΨCCGUAGCUUAAA UGCGUGGGAGT'ΨCGAGUCUCCCUAGCCCCACCAoh.This tRNA has anticodon sequence UAG, which can presumably recognize all the four leucine-specific codons (CUN). The main feature of T5 tRNALeu is the absence of the A10-C25 and C31-Ψ39 pairing in the D and anticodon stems, respectively

Cloning and DNA sequence of the 5'-exonuclease gene of bacteriophage T5

AbstractThe nucleotide sequence of the BalI-PstI fragment of T5 DNA, 1347 bp in length, coding for 5'-exonuclease (D15 gene), has been determined. A coding region of the gene contains 873 bp and is preceded by a typical Shine-Dalgarno sequence. The D15 gene belongs to a cluster, consisting of at least 3 genes, in which a termination codon of a preceding gene overlaps an initiation codon of the following one. The sequence contains an open reading frame for 291 amino acid residues. The molecular mass of the 5'-exonuclease calculated from the predicted amino acid sequence is 33400 Da

Genetic engineering of peptide hormones : II. Possible polymorphism of preprolactin in cattle. Data of molecular cloning

Primary structure is determined of an insertion of a clone isolated from the library of hypophyseal cDNA of cattle by hybridization with a probe specific for prolactin. Analysis of nucleotide sequences showed that in the process of cloning, reorganization occurred in structure of preprolactin cDNA, including an inversion of the 5'-terminal and deletion of the central section of cDNA. Nevertheless, from structure of cDNA, nucleotide sequences can be deduced of extended 5'- and 3'-terminal sections of preprolactin mRNA in cattle with lengths of 257 and 551 nucleotide residues, respectively. When these sequences are compared to those established previously, some differences were found in primary structure. The most important of them is the presence of an additional codon which codes alanine at the position (-22) of the signal peptide. It is suggested that heterogeneity of preprolactin mRNA of cattle in the section coding the signal peptide is the result of alternative splicing, as was shown for preprolactin mRNA in rats

RuDaCoP: The Dataset for Smartphone-based Intellectual Pedestrian Navigation

This paper presents the large and diverse dataset for development of smartphone-based pedestrian navigation algorithms. This dataset consists of about 1200 sets of inertial measurements from sensors of several smartphones. The measurements are collected while walking through different trajectories up to 10 minutes long. The data are accompanied by the high accuracy ground truth collected with two foot-mounted inertial measurement units and post-processed by the presented algorithms. The dataset suits both for training of intellectual pedestrian navigation algorithms based on learning techniques and for development of pedestrian navigation algorithms based on classical approaches. The dataset is accessible at http://gartseev.ru/projects/ipin2019