Recurrence intervals between earthquakes strongly depend on history

We study the statistics of the recurrence times between earthquakes above a certain magnitude M$in California. We find that the distribution of the recurrence times strongly depends on the previous recurrence time$\tau_0$. As a consequence, the conditional mean recurrence time$\hat \tau(\tau_0)$between two events increases monotonically with$\tau_0$. For$\tau_0$well below the average recurrence time$\ov{\tau}, \hat\tau(\tau_0)$is smaller than$\ov{\tau}$, while for$\tau_0>\ov{\tau}$,$\hat\tau(\tau_0)$is greater than$\ov{\tau}$. Also the mean residual time until the next earthquake does not depend only on the elapsed time, but also strongly on$\tau_0$. The larger$\tau_0$ is, the larger is the mean residual time. The above features should be taken into account in any earthquake prognosis.Comment: 5 pages, 3 figures, submitted to Physica

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

MEDIUM TERM PARAMETERS OF SOCIO-ECONOMIC, BUDGETARY AND FINANCIAL DEVELOPMENT FORECASTING FOR THE RUSSIAN FEDERATION AND KEY MACROECONOMIC RISKS MANAGEMENT

The topic of the study is relevant due to the fact that abrupt changes in the economy and in the financial system, particularly those caused by the coronavirus pandemic, have changed all existing development forecasts. At the same time, a whole range of new risks for the financial system appeared. In this regard, the development of a forecast for the development of the financial sector in various scenarios, taking into account risks and opportunities, seems to be the most important task for the Russian economy. The purpose of the study is to develop a medium-term forecast for the development of the financial sector in the Russian Federation. The subject of this research is the dynamics of the development of the financial system of the Russian Federation in the medium term. The research method or methodology is based on the study of key current and retrospective data on the state of the financial sector of the Russian Federation, highlighting the most important risks for the financial sector and building a medium-term forecast. As a result of the work carried out, the key components of the budgetary sphere, financial and credit markets have been analyzed, and the impact of the deterioration in the external environment has been assessed. Thus, the work presents the assessments of the prerequisites for the forecast and developed three possible scenarios for the development of the financial sector in Russia. The scientific novelty of the research lies in producing unique forecasts for the development of the financial sector in Russia. The recommendations obtained as a result of the study indicate the need to develop mechanisms for responding to certain risks for the financial system, taking into account the possible consequences of such an impact presented in the forecast. The project was carried out as part of research work by the Laboratory for Structural Research of the IAER at the Russian Presidential Academy of National Economy and Public Administration in 2021