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A highly potent antitumor saponin from Ornithogalum saudersiae, OSW-1, was totally synthesized for the first time. OSW-1 was derived from commercially available dehydroisoandrosterone, L-arabinose and D-xylose in 27 steps with the longest linear sequence being 14 steps and in 6% yield. Experimental results showed that all of the protecting groups were removed smoothly and cleanly in one step by using Pd(MeCN)(sub 2)Cl(sub 2) as a catalyst to produce OSW-1 in excellent yield.

This paper focuses on studying the differentially private consensus problem in multiagent networks under a quantized communication environment, where the exact real-value state is not available for transmission due to the range limitation of digital channels. We first extend the differentially private consensus model to the case of a quantized communication environment integrated with a dynamic encoding/decoding scheme and propose a differentially private communication algorithm utilizing the quantized state with a bounded quantizer instead of the exact real-value state to reach an agreement while protecting the initial or current states of the participants from information disclosure. Then, the convergence analysis of mean square consensus in the case of an unbounded quantizer is given to explain the sufficiency of the extended model and convergence conditions. To overcome the uncertainty of saturation in the case of a bounded quantizer, we also give a statistical analysis on the boundedness of quantization that the bounded quantizer with a finite number of bits can remain unsaturated with a desired high probability under certain conditions. Furthermore, we provide the statistical analysis on the convergent accuracy, which shows that the agreement value just converges to a random variable that falls in the neighboring range of the initial state average and the expectation of the agreement value is equal to the initial state average exactly. In addition, we provide the differential privacy analysis for individual agents and the whole network, and then establish the potential relationship between the dynamic encoding/decoding scheme and the differential privacy mechanism. Finally, the simulation results visually show that the proposed algorithm and the main theoretical results are effective and correct. [ABSTRACT FROM AUTHOR]

A very efficient glycosylation method for sapogenins is discussed. The glycosyl trichloroacetimidates were chosen as glycosyl donors. Diosgenin, dehydroisoandrosterone, cholesterol, pregnadiene and allyl oleanate were the acceptors. The benzoyl-protected glycosyl imidates, readily prepared from the corresponding 1-OH sugars were reasonably stable.

This paper studies the global asymptotic and exponential stability of the equilibrium point of discrete-time delayed Hopfield neural networks (DHNN) with large impulse effects. The present results characterize the aggregated effects of impulse and stability property of the impulse-free Hopfield neural networks on the stability of the considered system. The feasible upper bound of impulses is also estimated. It is shown that the discrete-time impulsive DHNN might preserve global exponential stability of the impulse-free DHNN even if the impulses have enlarging effects on the states of neurons. [ABSTRACT FROM PUBLISHER]

This paper discusses the application of digital information management tools in the context of financial control. In Bulgaria, such research is innovative as it is the first time that digital transformation in crucial financial control institutions, which influence the formation of the revenue part of the state budget and the spending of public funds, has been studied. The study aims to answer the research question of to what extent the application of digital tools in financial control improves its effectiveness. It analyses how modern technologies improve the efficiency and accuracy of information used in financial control institutions. The authors examine the impact of digital tools, such as database management systems, business analytics platforms, and electronic document management tools, on collecting, analyzing, and managing financial and non-financial information. The study uses descriptive statistics and a correlation analysis, which significantly contributes to establishing the relationship between implemented digital tools and improvements in financial control procedures. The results show that despite the conditions created for digitalization in financial control institutions, digital tools are used to a limited extent in the information management process. The study emphasizes the need for continuous investment in digital technologies and training to maximize the benefits of their application in financial control. [ABSTRACT FROM AUTHOR]

Digital twin railway is a pivotal foundation for the intelligent construction and maintenance of railway engineering projects within extensive open spaces. Its essence is the integrated representation and association management of multi-granularity spatiotemporal data, executable analysis models, and professional knowledge. These elements are characterized by the prominent characteristics of multi-source, heterogeneity, and massive volume. However, current decentralized and independent management strategies often neglect the dynamic coupling relationships between them, and numerous multi-path joins and conversion aggregation operations exist across various spatial scale applications. Consequently, this results in challenges such as the inability to dynamically couple data-model-knowledge and conduct global association retrieval, thereby limiting the potential for real-time analysis and intelligent application capabilities. To address these problems, we first constructed a tripartite graph model (DMK--Graph model) that explicitly associates temporal, spatial, and interactive relationships. Subsequently, an association management architecture was proposed, accompanied by a global association graph index (DMK--Graph index) and a global-local indexing mechanism. Finally, a prototype system for railway data-model-knowledge association management was developed. The effectiveness of the distributed association management method was demonstrated by employing a case study of high-temperature safety risk analysis in railway tunnel engineering with multi-physics field coupling. [ABSTRACT FROM AUTHOR]

The paper proposes a novel algorithm to get the encryption matrix. Firstly, a chaotic sequence generated by Chebyshev chaotic neural networks is converted into a series of low-order integer matrices from which available encryption matrices are selected. Then, a higher order encryption matrix relating real world application is constructed by means of tensor production method based on selected encryption matrices. The results show that the proposed algorithm can produce a 'one-time pad cipher' encryption matrix with high security; and the encryption results have good chaos and autocorrelation with the natural frequency of the plaintext being hidden and homogenized. [ABSTRACT FROM AUTHOR]

This index covers all technical items - papers, correspondence, reviews, etc. - that appeared in this periodical during the year, and items from previous years that were commented upon or corrected in this year. Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name. The primary entry includes the co-authors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination. The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author's name, the publication abbreviation, month, and year, and inclusive pages. Note that the item title is found only under the primary entry in the Author Index. [ABSTRACT FROM AUTHOR]