Calixarene alpha-ketoacetylenes: versatile platforms for reaction with hydrazine nucleophile

Late stage diversification of calix[4]arenes and thiacalix[4]arenes with heterocycles remains a significant synthetic challenge and hampers further exploitation of the scaffolds. Here we describe the development of a short and facile synthetic route to conformationally diverse novel calix[4]arene and thiacalix[4]arene ynones using a palladium cross coupling approach (5% Pd(II) + 10% Cu(I)) with benzoyl chloride. Their successful conversion to heterocycles to afford pyrazoles was demonstrated through treatment with hydrazine. Functionalisation is calixarene conformation and linker independent enabling access to a library of structures

Novel relativistic plasma excitations in a gated two-dimensional electron system

The microwave response of a two-dimensional electron system (2DES) covered by a conducting top gate is investigated in the relativistic regime for which the 2D conductivity $\sigma_{2 \rm{D}} > c/2\pi$. Weakly damped plasma waves are excited in the gated region of the 2DES. The frequency and amplitude of the resulting plasma excitations show a very unusual dependence on the magnetic field, conductivity, gate geometry and separation from the 2DES. We show that such relativistic plasmons survive for temperatures up to 300 K, allowing for new room-temperature microwave and terahertz applications.Comment: 9 pages, 7 figure

Neural Architecture Search by Estimation of Network Structure Distributions

The influence of deep learning is continuously expanding across different domains, and its new applications are ubiquitous. The question of neural network design thus increases in importance, as traditional empirical approaches are reaching their limits. Manual design of network architectures from scratch relies heavily on trial and error, while using existing pretrained models can introduce redundancies or vulnerabilities. Automated neural architecture design is able to overcome these problems, but the most successful algorithms operate on significantly constrained design spaces, assuming the target network to consist of identical repeating blocks. While such approach allows for faster search, it does so at the cost of expressivity. We instead propose an alternative probabilistic representation of a whole neural network structure under the assumption of independence between layer types. Our matrix of probabilities is equivalent to the population of models, but allows for discovery of structural irregularities, while being simple to interpret and analyze. We construct an architecture search algorithm, inspired by the estimation of distribution algorithms, to take advantage of this representation. The probability matrix is tuned towards generating high-performance models by repeatedly sampling the architectures and evaluating the corresponding networks, while gradually increasing the model depth. Our algorithm is shown to discover non-regular models which cannot be expressed via blocks, but are competitive both in accuracy and computational cost, while not utilizing complex dataflows or advanced training techniques, as well as remaining conceptually simple and highly extensible.Comment: 16 pages, 4 figures, 3 table

Efficient Vector Quantization for Fast Approximate Nearest Neighbor Search

Increasing sizes of databases and data stores mean that the traditional tasks, such as locating a nearest neighbor for a given data point, become too complex for classical solutions to handle. Exact solutions have been shown to scale poorly with dimensionality of the data. Approximate nearest neighbor search (ANN) is a practical compromise between accuracy and performance; it is widely applicable and is a subject of much research. Amongst a number of ANN approaches suggested in the recent years, the ones based on vector quantization stand out, achieving state-of-the-art results. Product quantization (PQ) decomposes vectors into subspaces for separate processing, allowing for fast lookup-based distance calculations. Additive quantization (AQ) drops most of PQ constraints, currently providing the best search accuracy on image descriptor datasets, but at a higher computational cost. This thesis work aims to reduce the complexity of AQ by changing a single most expensive step in the process – that of vector encoding. Both the outstanding search performance and high costs of AQ come from its generality, therefore by imposing some novel external constraints it is possible to achieve a better compromise: reduce complexity while retaining the accuracy advantage over other ANN methods. We propose a new encoding method for AQ – pyramid encoding. It requires significantly less calculations compared to the original “beam search” encoding, at the cost of an increased greediness of the optimization procedure. As its performance depends heavily on the initialization, the problem of choosing a starting point is also discussed. The results achieved by applying the proposed method are compared with the current state-of-the-art on two widely used benchmark datasets – GIST1M and SIFT1M, both generated from a real-world image data and therefore closely modeling practical applications. AQ with pyramid encoding, in addition to its computational benefits, is shown to achieve similar or better search performance than competing methods. However, its current advantages seem to be limited to data of a certain internal structure. Further analysis of this drawback provides us with the directions of possible future work

МИХАИЛ ЛИФШИЦ И ЭВАЛЬД ИЛЬЕНКОВ: НЕЗАВЕРШЕННЫЙ ДИАЛОГ ПО ПРОБЛЕМЕ ИДЕАЛЬНОГО

The problem of the ideal was raised in Soviet Marxism by E. V. Ilyenkov and after his tragic death became the content of a special study in the last theoretical work of M. A. Lifshitz "Dialogue with Evald Ilyenkov". Lifshitz's research of this problem was put in the context of the relationship between classical and post-classical philosophical thought, which gave the researcher the opportunity to discuss its main aspects in detail. Among these aspects are the question of a single field of consciousness, the contradiction of finite consciousness and the search for "metasonsciousness" caused by it, as well as the problem of consciousness of consciousness, which leads Lifshitz to the problem of the nature of the ideal, which is the subject of his friendly polemic with Ilyenkov. The article provides a comparative analysis of their positions on this problem, which shows that their positions are directly related to the features of the development of the classical philosophical heritage by outstanding thinkers of the Soviet era. Turning to the fact that the problem of the ideal was reached from Plato to Hegel inclusive, allowed Ilyenkov and Lifshitz to develop original and complementary versions of the solution of this basic philosophical problem, which can still stimulate the solution of individual scientific and technical problems that are fundamentally dependent on it. In the final part of the article, its author formulates a lesson to be learned, which is hidden in the differences between Lifshitz and Ilyenkov.Проблема идеального была поднята в советском марксизме Э. В. Ильенковым и после его трагического ухода из жизни стала содержанием специального исследования в последней теоретической работе М. А. Лифшица «Диалог с Эвальдом Иль-енковым». Исследование этой проблемы было поставлено Лифшицем в контекст отношения классической и постклассической философской мысли, что дало исследователю возможность развернуто обсудить ее главные аспекты. В числе таких аспектов – вопрос о едином поле сознания, противоречие конечного сознания и вызванные им поиски «метасознания», а также проблема сознательности сознания, которая выводит Лифшица на проблему природы идеального, составляющую предмет его дружеской полемики с Ильенковым. В статье проводится сравнительный анализ их позиций по этой проблеме, который показывает, что выдвинутые ими положения напрямую связаны с особенностями освоения выдающимися мыслителями советской эпохи классического философского наследия. Обращение к тому, что по проблеме идеального было достигнуто от Платона до Гегеля включительно, позволило Ильенкову и Лифшицу разработать оригинальные и дополняющие одна другую версии решения этой основной философской проблемы, способ-ной и сегодня стимулировать решение принципиально зависимых от нее частных научно-технических проблем. В заключительной части статьи ее автор формулирует подлежащий освоению урок, который таят в себе разногласия между ее героями