The nonlinear Schrödinger (NLS) equation describing the propagation of weakly rotational wave packets in an infinitely deep fluid in Lagrangian coordinates has been derived. The vorticity is assumed to be an arbitrary function of Lagrangian coordinates and quadratic in the small parameter proportional to the wave steepness. The vorticity effects manifest themselves in a shift of the wave number in the carrier wave and in variation in the coefficient multiplying the nonlinear term. In the case of vorticity dependence on the vertical Lagrangian coordinate only (Gouyon waves), the shift of the wave number and the respective coefficient are constant. When the vorticity is dependent on both Lagrangian coordinates, the shift of the wave number is horizontally inhomogeneous. There are special cases (e.g., Gerstner waves) in which the vorticity is proportional to the squared wave amplitude and nonlinearity disappears, thus making the equations for wave packet dynamics linear. It is shown that the NLS solution for weakly rotational waves in the Eulerian variables may be obtained from the Lagrangian solution by simply changing the horizontal coordinates.
Objective. Brain-computer interface (BCI) systems are known to be vulnerable to variabilities in background states of a user. Usually, no detailed information on these states is available even during the training stage. Thus there is a need in a method which is capable of taking background states into account in an unsupervised way. Approach. We propose a latent variable method that is based on a probabilistic model with a discrete latent variable. In order to estimate the model's parameters, we suggest to use the expectation maximization (EM) algorithm. The proposed method is aimed at assessing characteristics of background states without any corresponding data labeling. In the context of asynchronous motor imagery paradigm, we applied this method to the real data from twelve able-bodied subjects with open/closed eyes serving as background states. Main results. We found that the latent variable method improved classication of target states compared to the baseline method (in seven of twelve subjects). In addition, we found that our method was also capable of background states recognition (in six of twelve subjects). Signicance. Without any supervised information on background states, the latent variable method provides a way to improve classication in BCI by taking background states into account at the training stage and then by making decisions on target states weighted by posterior probabilities of background states at the prediction stage.
The issue of rogue wave lifetimes is addressed in this study, which helps to detail the general picture of this dangerous oceanic phenomenon. The direct numerical simulations of irregular wave ensembles are performed to obtain the complete accurate data on the rogue wave occurrence and evolution. Purely collinear wave systems, moderately crested, and short-crested sea states have been simulated by means of the high-order spectral method for the potential Euler equations. As rogue waves are transient and poorly reflect the physical eects, we join instant abnormally high waves in close locations and close time moments to new objects, rogue events, which helps to retrieve the abnormal occurrences more stably and more consistently from the physical point of view. The rogue event lifetime probability distributions are calculated based on the simulated wave data. They show the distinctive dierence between rough sea states with small directional bandwidth on one part, and small-amplitude sea states and short-crested states on the other part. The former support long-living rogue wave patterns (the corresponding probability distributions have heavy tails), though the latter possess exponential probability distributions of rogue event lifetimes and generally produce much shorter rogue wave events.
Bacterial cell wall is targeted by many antibiotics. Among them are lantibiotics, which realize their function via interaction with transmembrane lipid-II molecule — a chemically conserved part of the cell wall synthesis pathway. To investigate structural and dynamic properties of this molecule, we have performed a series of nearly microsecond-long molecular dynamics simulations (MD) of lipid-II and some of its analogs in zwitterionic single component and charged mixed model phospholipid bilayers (the reference and mimic of the bacterial plasmatic membrane, respectively). Extensive analysis revealed that lipid-II forms a unique “amphiphilic pattern” exclusively on the surface of the model bacterial membrane (and not in the reference bilayer). We hypothesize that conserved features of lipid-II along with characteristic modulation of the bacterial membrane provide a recognition spot for many lantibiotics. This putative recognition mechanism opens new opportunities for studies on lantibiotics action and design of novel armament against resistant bacterial strains.
Neuronal activity in the subthalamic nucleus (STN) of patients with Parkinson's disease (PD) is characterised by excessive neuronal synchronization, particularly in the beta frequency range. However, less is known about the temporal dynamics of neuronal oscillations in PD. In this respect long-range temporal correlations (LRTC) are of special interest as they quantify the neuronal dynamics on different timescales and have been shown to be relevant for optimal information processing in the brain. While the presence of LRTC has been demonstrated in cortical data, their existence in deep brain structures remains an open question. We investigated (i) whether LRTC are present in local field potentials (LFP) recorded bilaterally from the STN at wakeful rest in ten patients with PD after overnight withdrawal of levodopa (OFF) and (ii) whether LRTC can be modulated by levodopa treatment (ON). Detrended fluctuation analysis was utilised in order to quantify the temporal dynamics in the amplitude fluctuations of LFP oscillations. We demonstrated for the first time the presence of LRTC (extending up to 50 s) in the STN. Importantly, the ON state was characterised by significantly stronger LRTC than the OFF state, both in beta (13-35 Hz) and high-frequency (> 200 Hz) oscillations. The existence of LRTC in subcortical structures such as STN provides further evidence for their ubiquitous nature in the brain. The weaker LRTC in the OFF state might indicate limited information processing in the dopamine-depleted basal ganglia. The present results implicate LRTC as a potential biomarker of pathological neuronal processes in PD.
Modeling of tsunamis in glacial fjords prompts us to evaluate applicability of the crosssectionally averaged nonlinear shallow water equations to model propagation and runup of long waves in asymmetrical bays and also in fjords with two heads. We utilize the Tuck-Hwang transformation, initially introduced for the plane beaches and currently generalized for bays with arbitrary cross section, to transform the nonlinear governing equations into a linear equation. The solution of the linearized equation describing the runup at the shore line is computed by taking into account the incident wave at the toe of the last sloping segment. We verify our predictions against direct numerical simulation of the 2-D shallow water equations and show that our solution is valid both for bays with an asymmetric L-shaped cross section, and for fjords with two heads—bays with a W-shaped cross section
The long wave run-up on two types of slopes is investigated numerically within the framework of nonlinear shallow water theory using the CLAWPACK software. One of the slopes represents a plane slope widely used in the laboratory and numerical experiments; the second is the so-called “non-reflecting” slope (h ∼ x4/3, where h is the basin depth and x is the distance from the shoreline). In the case of very low wave amplitudes when there is no wave breaking, the run-up height is greater on the non-reflecting beach than that on the plane slope. As the wave amplitude increases, the breaking effects have the stronger impact in the case of non-reflecting beach and the run-up height becomes smaller.
Autism spectrum conditions (ASC) are characterised by deficits in understanding and expressing emotions and are frequently accompanied by alexithymia, a difficulty in understanding and expressing emotion words. Words are differentially represented in the brain according to their semantic category and these difficulties in ASC predict reduced activation to emotion-related words in limbic structures crucial for affective processing. Semantic theories view 'emotion actions' as critical for learning the semantic relationship between a word and the emotion it describes, such that emotion words typically activate the cortical motor systems involved in expressing emotion actions such as facial expressions. As ASC are also characterised by motor deficits and atypical brain structure and function in these regions, motor structures would also be expected to show reduced activation during emotion-semantic processing. Here we used event-related fMRI to compare passive processing of emotion words in comparison to abstract verbs and animal names in typically-developing controls and individuals with ASC. Relatively reduced brain activation in ASC for emotion words, but not matched control words, was found in motor areas and cingulate cortex specifically. The degree of activation evoked by emotion words in the motor system was also associated with the extent of autistic traits as revealed by the Autism Spectrum Quotient. We suggest that hypoactivation of motor and limbic regions for emotion-word processing may underlie difficulties in processing emotional language in ASC. The role that sensorimotor systems and their connections might play in the affective and social-communication difficulties in ASC is discussed.
The geographical and seasonal distributions of kinematic and nonlinear parametersof long internal waves obtained on a base of GDEM climatology in the Baltic Sea region are examined. The considered parameters (phase speed of long internal wave, dispersion, quadratic and cubicnonlinearity parameters) of the weakly-nonlinear Korteweg-de Vries-type models (in particular, Gardner model), can be used for evaluations of the possible polarities, shapes of solitary internal waves, their limiting amplitudes and propagation speeds. The key outcome is an express estimate of the expected internal wave parameters for different regions of the Baltic Sea. The central kinematic characteristic is the near-bottom velocity in internal waves in areas where the density jump layers are located in the vicinity of seabed. In such areas internal waves are the major driver of sediment resuspension and erosion processes and may be also responsible for destroying the laminated structure of sedimentation regime (that frequently occurs in certain areas of the Baltic Sea).
This article is devoted to the study of the population’s ethnic structure in regions of Russia and former RSFSR (Russian Soviet Federative Socialist Republic) as well as the temporal dynamics of major ethnic groups by means of mathematical and cartographic modelling. Integrated indicators are developed to estimate ethnic diversity in regions of Russia and former RSFSR (ethnic diversity index and its modification – ethnic diversity index adjusted for the ability to speak Russian), and cluster analysis is performed to offer typological classification of Russian regions based on their ethnic composition. Maps are created on the basis of the derived indicators and typological classification. Finally, the estimates of the share of major ethnic groups up to 2030 are provided.
Invagination of epithelial sheets is an important type of morphogenetic deformation. Primary invagination during gastrulation in the sea urchin provides one of the simplest and best-studied examples. The specific mechanisms of invagination remain unclear in spite of numerous observations. The problem of plane-stress deformation of an initially circular layer exposed to a constant internal pressure is considered. Active forces developed by cells are characterized by an active moment. The rheology of a layer is described by a Maxwell-type viscoelasticity equation, which links the passive bending moment with the curvature of the layer. The presence of a passive moment threshold below which bending is purely elastic is taken into account. The active moment is defined as a function of coordinates and time that is nonzero in a certain limited region. The function is assumed to gradually increase, reach a steady state, and then decline gradually. Both constant- and alternating-sign spatial distributions of the active moment are considered. Numerical simulation showed that among all of the considered variants a realistic sequence of shapes can only be obtained if the layer is viscoelastic, there is a finite threshold for the passive bending moment, and the distribution of the active moment is of an alternating-sign type. The sign of the active moment differs between the inner and outer areas of the active region, tending to bend the sheet inward in the inner area and outward in the outer area. This study made it possible to reach several conclusions on the nature of the macroscopic organization of invagination and to outline avenues of research into the cellular mechanisms that are capable of developing the corresponding forces.
The problem of deformation of a planar embryonic epithelium layer that is unloaded after a short period of uniaxial stretching with subsequent fixation in the stretched state for different periods of time is solved. The initial conditions for solving this problem are derived from the previously discussed problem of the uniform stretching of a tissue fragment (explant) with subsequent fixation of the obtained length. In this study we used the previously developed continuum model that describes the stress–strain state of epithelial tissue taking the parameters that characterize the shape of the cells and their stress state into account, as well as the active stresses they exert when they interact with each other. The experimentally observed continuation of the deformation of a stretched tissue after the external force has ceased to act is described theoretically as a result of active cell reactions to mechanical stress. The duration of explant fixation is shown to have a strong effect on its further elongation and on the pattern of cell activity.
A continuum model of the embryonic epithelial tissue with account for the active deformations and rearrangements of the cells is proposed. The stress tensor is represented as the sum of the stresses undergone by the cell directly and the tensor of active stresses that arise owing to contracting cellular protrusions anchored on the surface of neighboring cells and developing in response to cell reshaping (deformation). The strain rate tensor includes three components: elastic and two inelastic related to the active deformation of the cells and their rearrangement. The first of these components depends on the stresses in the cells and the reached cellular deformation level, whereas the second is determined by the active stresses. The problem of reaction of a thin sheet to a rapid stretching is solved and agreement with experimental data is obtained.
In September, 2015, the UN General Assembly established the Sustainable Development Goals (SDGs). The SDGs specify 17 universal goals, 169 targets, and 230 indicators leading up to 2030. We provide an analysis of 33 health-related SDG indicators based on the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015).
We applied statistical methods to systematically compiled data to estimate the performance of 33 health-related SDG indicators for 188 countries from 1990 to 2015. We rescaled each indicator on a scale from 0 (worst observed value between 1990 and 2015) to 100 (best observed). Indices representing all 33 health-related SDG indicators (health-related SDG index), health-related SDG indicators included in the Millennium Development Goals (MDG index), and health-related indicators not included in the MDGs (non-MDG index) were computed as the geometric mean of the rescaled indicators by SDG target. We used spline regressions to examine the relations between the Socio-demographic Index (SDI, a summary measure based on average income per person, educational attainment, and total fertility rate) and each of the health-related SDG indicators and indices.
In 2015, the median health-related SDG index was 59∙3 (95% uncertainty interval 56∙8–61∙8) and varied widely by country, ranging from 85∙5 (84∙2–86∙5) in Iceland to 20∙4 (15∙4–24∙9) in Central African Republic. SDI was a good predictor of the health-related SDG index (r²=0∙88) and the MDG index (r²=0∙92), whereas the non-MDG index had a weaker relation with SDI (r²=0∙79). Between 2000 and 2015, the health-related SDG index improved by a median of 7∙9 (IQR 5∙0–10∙4), and gains on the MDG index (a median change of 10∙0 [6∙7–13∙1]) exceeded that of the non-MDG index (a median change of 5∙5 [2∙1–8∙9]). Since 2000, pronounced progress occurred for indicators such as met need with modern contraception, under-5 mortality, and neonatal mortality, as well as the indicator for universal health coverage tracer interventions. Moderate improvements were found for indicators such as HIV and tuberculosis incidence, minimal changes for hepatitis B incidence took place, and childhood overweight considerably worsened.Interpretation
GBD provides an independent, comparable avenue for monitoring progress towards the health-related SDGs. Our analysis not only highlights the importance of income, education, and fertility as drivers of health improvement but also emphasises that investments in these areas alone will not be sufficient.
Although considerable progress on the health-related MDG indicators has been made, these gains will need to be sustained and, in many cases, accelerated to achieve the ambitious SDG targets. The minimal improvement in or worsening of health-related indicators beyond the MDGs highlight the need for additional resources to effectively address the expanded scope of the health-related SDGs
Quantitatively characterizing the intracellular carbon flux distribution provides useful information for both fundamental and applied investigations into the cellular metabolism at the system level, such as the roles of different metabolic pathways and individual reactions, metabolic state characterization, metabolic differences between the strains, and clues regarding strategies for producer-strain improvement. A variety of methods have been developed to characterize the metabolic state of the cell by determining its intracellular flux distribution, and together, they are called metabolic flux analysis (MFA) or fluxomics. These methods, in addition to other X-omics technologies (i.e., genomics, transcriptomics, proteomics, and metabolomics) constitute a recent arsenal of the system biology estimation approaches. One of the most well-developed approaches for intracellular carbon flux estimation in vivo in (quasi) steady-state conditions is 13C-MFA, which uses substrates that are labeled with a heavy carbon (13C). Applying 13C-MFA requires the coordination of experts in biochemistry, applied mathematics and nuclear magnetic resonance (NMR) or mass spectrometry. Therefore, the authors have prepared a three-part review highlighting the different but equally important aspects of 13C-MFA. In the first part, which is presented below, the focus is on the basic principles of 13C-MFA, such as stoichiometric model development, labeling experiments and experimental data extraction. The principles of the labeling experiments modeling and quantitative carbon flux estimation and statistics are discussed in the second part. The final part reviews recent achievements in fundamental and applied investigations of bacterial metabolism achieved using 13C-MFA.
At present, 13C-MFA is a primary method for quantitatively characterizing intracellular carbon fluxes in cells in vivo under steady-state conditions. The method has been successfully used to investigate both the fundamental characteristics of prokaryotic and eukaryotic cell metabolism and to improve producer strains for more than twenty years. This publication is the last in a set of reviews that describe various aspects of the method. Here, the authors highlight recent achievements that involved using 13C-MFA to elucidate bacterial metabolism. Analyses of well-characterized bacterial model strains revealed that central metabolism robustness is provided by a set of alternative metabolic pathways; these analyses also helped develop a better understanding of the physiological significance of these pathways and identified previously unknown functions of well-studied metabolic pathways. Several examples of 13C-MFA-based fundamental investigations of poorly characterized bacteria are also analyzed. In applied investigations, flux analysis of strains that produce amino acids, vitamins and antibiotics indicated targets for modifications, suggested unconventional metabolic engineering approaches, and, most importantly, confirmed their utility. In the last section of this article, 13C-MFA prospects, including the monitoring of the dynamics of metabolic flux distribution during culture growth, are discussed.
The paper presents analysis of a new kind of educational courses based on multidisciplinary approach. The course synthesizes the methodologies and advances of regional studies and regional geography, cultural and cross-cultural studies and communication, oriental studies, civilization studies, second language acquisition and second language teaching. The course is a part of a wider language program elaborated and implemented at NRU HSE (Saint Petersburg) and bases essentially on the inclusive strategies of Arab countries study, primarily language learning techniques (Arabic). It requires preliminary commandment of elementary course of Arabic. This study aims to analyze a year’s experience of constructing the Arab countries studies course and its teaching process, and to evaluate the merits and demerits of its aspects, taking into account the peculiarities of the academic activity, language skills, basic dictionary, and comparative analysis of several similar courses.
Surveys of environmental microbial communities using metagenomic approach produce vast volumes of multidimensional data regarding the phylogenetic and functional composition of the microbiota. Faced with such complex data, a metagenomic researcher needs to select the means for data analysis properly. Data visualization became an indispensable part of the exploratory data analysis and serves a key to the discoveries. While the molecular-genetic analysis of even a single bacterium presents multiple layers of data to be properly displayed and perceived, the studies of microbiota are significantly more challenging. Here we present a review of the state-of-art methods for the visualization of metagenomic data in a multi-level manner: from the methods applicable to an in-depth analysis of a single metagenome to the techniques appropriate for large-scale studies containing hundreds of environmental samples.
Climate, fire, and human activities strongly affected the development of vegetation communities during the Holocene, yet the relative importance of these individual factors remains unclear in many areas. This paper presents new multi-proxy records of environmental change for the Meshchera Lowlands (the central part of the East European Plain) during the Holocene. Changes in regional vegetation during the Mid- and Late Holocene were influenced by climate, fire regime and human impact, as indicated by pollen, plant macrofossil, charcoal and testate amoebae analysis from several peat cores, along with reconstruction of tree cover from pollen assemblages. Since 8500 cal yr BP, the vegetation history represented a series of consecutive phases of birch, birch-pine and pine-broadleaf forests, with introduction of spruce after 2500 cal yr BP. Maximal abundance of broadleaf tree species was detected from 4700 to 2000 cal yr BP. Vegetation dynamics were strongly influenced by human activity since 1400 cal yr BP. High fire frequency was recorded for the periods 8500–4500 cal yr BP and 3500–2000 cal yr BP, when the fire return interval varied from 40 to 80 years. Since 2000 cal yr BP, the fire return period exceeded 500 years suggesting a significant decline in fire frequency during the last two millennia.
The article assesses the dynamics of migration effectiveness by Russian regions over a long time period. Russian and foreign studies have found that people with migration experience change their place of residence more easily compared with those who have never moved. Migrants are divided into two main groups, namely, newcomers and long-time residents who have lived in a migration destination for a long time, and a transitional group from newcomers to long-time residents. Moscow, St. Petersburg, and their oblasts are subjects where migrants adapt the best. For a long time, in most Far Eastern and Siberian subjects (except for the Khanty-Mansi Autonomous Okrug and Yamalo-Nenets Autonomous Okrug), the large number of migrants who departed a region were compensated by large number of arriving migrants. The collapse of the Soviet Union and subsequent socioeconomic crisis have shown that population outflow occurs primarily in regions with the highest share of new settlers. Attempts to force the development of areas with harsh natural conditions and low adaptation by the population led to a massive return migration. Ensuring the adaptation of new settlers and their transition to long-time residents, rather than a high number of arrivals, is important for regional migration policy. Adaptation largely depends on the level of socioeconomic development of regions and particular localities.
Based on the data on addresses of real estate buyers, we assess the investment activity of residents of Russian regions and cities in the primary housing market of the Moscow capital region (MCR) compared to the activity of their labor migrations to the MCR. The objects of our analysis are 149 Russian cities and 80 remaining parts of regions. This enabled us to analyze the specifics of migration and investment behavior for the first time, taking into account differentiation between cities and rural areas, between size classes of cities, and between individual large cities. This enabled us to fill in the gap in assessing the mobility of inputs, i.e., capital and labor. A sharp contrast between settlements of different sizes was revealed in the nature of their interaction with the MCR agglomeration. The intensity of labor migration to the Moscow agglomeration is decreasing rapidly and monotonically with increasing settlement size. The activity of nonresident homebuyers, depending on the population of the city of their residence, varies nonmonotonically, reaching its highest level for cities with populations of 250000–500000 people for Moscow’s housing market and 100000–500000 people in Moscow oblast. Small towns and rural areas (except for the Khanty–Mansi and Yamalo–Nenets autonomous okrugs) are a source of labor for the Moscow agglomeration and show low investment activity in the capital’s housing market. Million-plus cities provide a negligible inflow of labor migrants and are characterized by moderate activity in the MCR housing market, close to the national average. Compared to the premium housing and labor market of the City of Moscow, investment and migration flows to Moscow oblast are shifted to smaller settlements and lower-income regions. The attraction of Moscow oblast rapidly decreases with distance, extending to first- and second-order neighbors, while Moscow’s influence is nationwide.