Primitive digraphs with large exponents and slowly synchronizing automata

We present several infinite series of synchronizing automata for which the minimum length of reset words is close to the square of the number of states. All these automata are tightly related to primitive digraphs with large exponent.Comment: 23 pages, 11 figures, 3 tables. This is a translation (with a slightly updated bibliography) of the authors' paper published in Russian in: Zapiski Nauchnyh Seminarov POMI [Kombinatorika i Teorija Grafov. IV], Vol. 402, 9-39 (2012), see ftp://ftp.pdmi.ras.ru/pub/publicat/znsl/v402/p009.pdf Version 2: a few typos are correcte

Unexpected influence of substituents on the binding affinities of polycyclic aromatic hydrocarbons with a tetra-Au(I) metallorectangle

A tetra-gold supramolecular organometallic cage constructed with two pyrene-bis-imidazolylidene ligands and two carbazolyl-bis-alkynyl linkers (1) was studied as host for a series of substituted polycyclic aromatic hydrocarbons (PAHs). For the two smaller PAHs used (2-naphthalenol and 1-pyrenemethanol), the presence of the - OH groups at the periphery of the molecules did not enhance the binding affinity of the guest, compared with the unsubstituted PAHs. This observation indicated no hydrogen bonding of these two guests with the NH of the carbazole linker, as well as negligible dispersive interactions of the substituents with the π-system of 1. In the case of 3- perylenemethanol, the CH2OH group produced a significant increase in the binding affinity, vs perylene. Similarly, 3- methylperylene shows an increased binding affinity compared to perylene. MN15-L/def2-QZVP calculations gave Gibbs reaction energies for the displacement of perylene from the host by the substituted perylenes becoming more exergonic in the order: -1.6 (3-methylperylene) > -4.3 (3-ethylperylene) > -4.5 kcal/mol (3-perylenemethanol). The experimental and DFT results indicate that the peripheral dispersive interactions can make a significant contribution to the host-guest bonding energy, in addition to the conventional π–π stacking interactions. Our work highlights the importance of dispersive interactions in the contribution to the binding affinity of host-guest chemistry complexe

NOISE SHAPING IN SAR ADC

The successive approximation register (SAR) analog-to-digital converter (ADC) is currently the most popular type of ADC architecture, owing to its power efficiency. They are also used in multichannel systems, where power efficiency is of high importance because of the large number of simultaneously working channels. However, the SAR ADC architecture is not the most area efficient. In SAR ADCs, the binary weighted capacitive digital-to-analog converter (DAC) is used, which means that one additional bit of resolution costs double the increase of area. Oversampling and noise shaping are methods that allow an increase in resolution without an increase of area. In this paper we present the new SAR ADC architectures with a noise shaping. A first-order noise transfer function (NTF) with zero located nearly at one can be achieved. We propose two modifications of the architecture: with zero-only NTF and with the NTF with additional pole. The additional pole theoretically increases the efficiency of noise shaping to further 3 dB. The architectures were applied to the design of SAR ADCs in a 65 nm complementary metal-oxide semiconductor (CMOS) with OSR equal to 10. A 6-bit capacitive DAC was used. The proposed  architectures  provide nearly 4 additional bits in ENOB. The equalent input bandwitdth is equal to 200 kHz with the sampling rate equal to 4 MS/s

First homoleptic MIC and heteroleptic NHC-MIC coordination cages from 1,3,5-triphenylbenzene-bridged tris-MIC and tris-NHC ligands

The preparation of a triphenylbenzene-bridged tris-(1,2,3-triazolium) salt allowed us to obtain the first homoleptic tris-MIC cylinder-like cages of Ag and Au. The silver MIC-based cage reacts with the trisNHC-Ag analogue to form the corresponding heteroleptic NHC–MIC silver cage in an unusual reaction involving the simultaneous exchange of the tris-NHC and tris-MIC ligands.MINECO (CTQ2014-51999-P) and UJI (P11B2014-02).Published versio

Forecasting stock market returns over multiple time horizons

In this paper we seek to demonstrate the predictability of stock market returns and explain the nature of this return predictability. To this end, we introduce investors with different investment horizons into the news-driven, analytic, agent-based market model developed in Gusev et al. (2015). This heterogeneous framework enables us to capture dynamics at multiple timescales, expanding the model's applications and improving precision. We study the heterogeneous model theoretically and empirically to highlight essential mechanisms underlying certain market behaviors, such as transitions between bull- and bear markets and the self-similar behavior of price changes. Most importantly, we apply this model to show that the stock market is nearly efficient on intraday timescales, adjusting quickly to incoming news, but becomes inefficient on longer timescales, where news may have a long-lasting nonlinear impact on dynamics, attributable to a feedback mechanism acting over these horizons. Then, using the model, we design algorithmic strategies that utilize news flow, quantified and measured, as the only input to trade on market return forecasts over multiple horizons, from days to months. The backtested results suggest that the return is predictable to the extent that successful trading strategies can be constructed to harness this predictability.Comment: This is the version accepted for publication in a journal Quantitative Finance. A draft was posted here on 18 August 2015. 50 page

Predictable markets? A news-driven model of the stock market

We attempt to explain stock market dynamics in terms of the interaction among three variables: market price, investor opinion and information flow. We propose a framework for such interaction and apply it to build a model of stock market dynamics which we study both empirically and theoretically. We demonstrate that this model replicates observed market behavior on all relevant timescales (from days to years) reasonably well. Using the model, we obtain and discuss a number of results that pose implications for current market theory and offer potential practical applications.Comment: This is the version accepted for publication in a new journal Algorithmic Finance (http://algorithmicfinance.org). A draft was posted here on 29 Apri