Cores of bottom sediments of Lake Karakel (Northern Caucasus) were obtained in 2010 and 2014 to perform geochemical studies for reconstructing the regional paleoclimate of the late Holocene. Solid sam- ples of bottom sediments were scanned via micro-XRF with a step of 1 mm at the shared resource center of the Siberian Synchrotron and Terahertz Radiation Center. The contents of more than 20 elements were deter- mined. The scan profiles are used to construct a single reference section with correction for a sediment layer dated via radiocarbon analysis, and to create a sediment core age–depth model.
Polypedilum vanderplanki is a striking and unique example of an insect that can survive almost complete desiccation. Its genome and a set of dehydration-rehydration transcriptomes, together with the genome of Polypedilum nubifer (a congeneric desiccation-sensitive midge), were recently released. Here, using published and newly generated datasets reflecting detailed transcriptome changes during anhydrobiosis, as well as a developmental series, we show that the TCTAGAA DNA motif, which closely resembles the binding motif of the Drosophila melanogaster heat shock transcription activator (Hsf), is significantly enriched in the promoter regions of desiccation-induced genes in P. vanderplanki, such as genes encoding late embryogenesis abundant (LEA) proteins, thioredoxins, or trehalose metabolism-related genes, but not in P. nubifer Unlike P. nubifer, P. vanderplanki has double TCTAGAA sites upstream of the Hsf gene itself, which is probably responsible for the stronger activation of Hsf in P. vanderplanki during desiccation compared with P. nubifer To confirm the role of Hsf in desiccation-induced gene activation, we used the Pv11 cell line, derived from P. vanderplanki embryo. After preincubation with trehalose, Pv11 cells can enter anhydrobiosis and survive desiccation. We showed that Hsf knockdown suppresses trehalose-induced activation of multiple predicted Hsf targets (including P. vanderplanki-specific LEA protein genes) and reduces the desiccation survival rate of Pv11 cells fivefold. Thus, cooption of the heat shock regulatory system has been an important evolutionary mechanism for adaptation to desiccation in P. vanderplanki.
Diffusion imaging techniques such as DTI and HARDI are difficult to implement in infants because of their sensitivity to subject motion. A short acquisition time is generally preferred, at the expense of spatial resolution and signal-to-noise ratio. Before estimating the local diffusion model, most pre-processing techniques only register diffusion-weighted volumes, without correcting for intra-slice artifacts due to motion or technical problems. Here, we propose a fully automated strategy, which takes advantage of a high orientation number and is based on spherical-harmonics decomposition of the diffusion signal.Material and methods
The correction strategy is based on two successive steps: 1) automated detection and resampling of corrupted slices; 2) correction for eddy current distortions and realignment of misregistered volumes. It was tested on DTI data from adults and non-sedated healthy infants.Results
The methodology was validated through simulated motions applied to an uncorrupted dataset and through comparisons with an unmoved reference. Second, we showed that the correction applied to an infant group enabled to improve DTI maps and to increase the reliability of DTI quantification in the immature cortico-spinal tract.Conclusion
This automated strategy performed reliably on DTI datasets and can be applied to spherical single- and multiple-shell diffusion imaging.
Understanding neurocognitive mechanisms supporting the use of multiple languages is a key question in language science. Recent neuroimaging studies in monolinguals indicated that core language areas in human neocortex together with sensorimotor structures form a highly interactive system underpinning native language comprehension. While the experience of a native speaker promotes the establishment of strong action-perception links in the comprehension network, this may not necessarily be the case for L2 where, as it has been argued, the most a typical L2 speaker may get is a link between an L2 wordform and its L1 translation equivalent. Therefore, we investigated, whether the motor cortex of bilingual subjects shows differential involvement in processing action semantics of native and non-native words. We used high-density EEG to dynamically measure changes in the cortical motor system's activity, indexed by event-related desynchronisation (ERD) of the mu-rhythm, in response to passively reading L1 (German) and L2 (English) action words. Analysis of motor-related EEG oscillations at the sensor level revealed an early (starting ~150ms) and left-lateralised coupling between action and semantics during both L1 and L2 processing. Crucially, source-level activation in the motor areas showed that mu-rhythm ERD, while present for both languages, is significantly stronger for L1 words. This is the first neurophysiological evidence of rapid motor-cortex involvement during L2 action-semantic processing. Our results both strengthen embodied cognition evidence obtained previously in monolinguals and, at the same time, reveal important quantitative differences between L1 and L2 sensorimotor brain activity in language comprehension.
Previous research documents that men and women can accurately judge male physical strength from gait, but also that the sexes differ in attractiveness judgments of strong and weak male walkers. Women’s (but not men’s) attractiveness assessments of strong male walkers are higher than for weak male walkers. Here, we extend this research to assessments of strong and weak male walkers in Chile, Germany, and Russia. Men and women judged videos of virtual characters, animated with the walk movements of motion-captured men, on strength and attractiveness. In two countries (Germany and Russia), these videos were additionally presented at 70% (slower) and 130% (faster) of their original speed. Stronger walkers were judged to be stronger and more attractive than weak walkers, and this effect was independent of country (but not sex). Women tended to provide higher attractiveness judgments to strong walkers, and men tended to provide higher attractiveness judgments to weak walkers. In addition, German and Russian participants rated strong walkers most attractive at slow and fast speed. Thus, across countries men and women can assess male strength from gait, although they tended to differ in attractiveness assessments of strong and weak male walkers. Attractiveness assessments of male gait may be influenced by society-specific emphasis on male physical strength.
We present a novel method for the extraction of neuronal components showing cross-frequency phase synchronization.
In general the method can be applied for the detection of phase interactions between components with frequencies f1 and f2, where f2 ≈ rf1 and r is some integer. We refer to the method as cross-frequency decomposition (CFD), which consists of the following steps: (a) extraction of f1-oscillations with the spatio-spectral decomposition algorithm (SSD); (b) frequency modification of the f1-oscillations obtained with SSD; and (c) finding f2-oscillations synchronous with f1-oscillations using least-squares estimation.
Our simulations showed that CFD was capable of recovering interacting components even when the signal-to-noise ratio was as low as 0.01. An application of CFD to the real EEG data demonstrated that cross-frequency phase synchronization between alpha and beta oscillations can originate from the same or remote neuronal populations.
CFD allows a compact representation of the sets of interacting components. The application of CFD to EEG data allows differentiating cross-frequency synchronization arising due to genuine neurophysiological interactions from interactions occurring due to quasi-sinusoidal waveform of neuronal oscillations.
CFD is a method capable of extracting cross-frequency coupled neuronal oscillations even in the presence of strong noise.
Copyright © 2011 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
This paper presents an overview of studies on the correlations of teacher pay to regional economics and to regional factors affecting the size of teacher salaries. It describes the basic pay indicators for teachers in the regions: absolute salary, teacher pay level as compared to the average regional salary, and ratio of salary to the cost of a fixed set of goods and services and to the per capita gross regional product. Based on calculations that used open government databases, a classification of regions by teacher pay level was developed. Regions of the country turned out to belong to seven different clusters. Recommendations on teacher remuneration were developed for each of these clusters and common risks and challenges were identified.
Nannopus palustris Brady, 1880 is a free-living widely distributed harpacticoid copepod, which has been formerly assumed to be a single, cosmopolitan but highly variable species. We compared several geographically distant N. palustris populations in terms of their morphology and genetics. Populations from the White Sea (WS), the North Sea (NS), the Black Sea (BS) and two sympatric morphs from South Carolina, USA (SC notched and SC straight morphs), were considered. The NS, BS and to a lesser extent SC notched specimens were morphologically similar and partly coincided to the ‘canonical’ description of the species. By contrast, WS population showed remark able anatomical and morphometric peculiarities that correspond to some earlier descriptions. Genetic analyses of mitochondrial (cytochrome b) and nuclear (28S rDNA) genes demonstrated the significant distinctness among WS, both SC and (NS+BS) populations, the latter two being genetically indistinguishable. Concordance between mitochondrial and nuclear gene trees and morphological data supports that N. palustris is in fact composed of several pseudo-sibling species, which are genetically and morphologically divergent. Neither correlation between genetic divergence and geographical distance nor significant intrapopulation diversity was found for these species. Taxonomic status, distribution and phylogenetic relationships of the species within the Nannopus genus need to be reconsidered. A further subdivision of species complexes might have important implications for the analysis of biodiversity of benthic copepods and consequently for the interpretation of their (species-specific) ecological function.
We report isolation, sequencing, and electrophysiological characterization of OSK3 (α-KTx 8.8 in Kalium and Uniprot databases), a potassium channel blocker from the scorpion Orthochirus scrobiculosus venom. Using the voltage clamp technique, OSK3 was tested on a wide panel of 11 voltage-gated potassium channels expressed in Xenopus oocytes, and was found to potently inhibit Kv1.2 and Kv1.3 with IC50 values of ~ 331 nM and ~ 503 nM, respectively. OdK1 produced by the scorpion Odontobuthus doriae differs by just two C-terminal residues from OSK3, but shows marked preference to Kv1.2. Based on the charybdotoxin-potassium channel complex crystal structure, a model was built to explain the role of the variable residues in OdK1 and OSK3 selectivity.
In this article we aim to highlight the problems related to the structure and stability of the comparatively thin current sheets that were relatively recently discovered by space missions in the magnetospheres of the Earth and planets, as well as in the solar wind. These magnetoplasma structures are universal in collisionless cosmic plasmas and can play a key role in the processes of storage and release of energy in the space environment. The development of a self-consistent theory for these sheets in the Earth’s magnetosphere, where they were first discovered, has a long and dramatic history. Solution of the problem of the thin current sheet structure and stability become possible in the framework of a kinetic quasi-adiabatic approach required to explain their embedding and metastability properties. It was found that the structure and stability of current structures are completely determined by the nonlinear dynamics of plasma particles. Theoretical models have been developed to predict many properties of these structures and interpret many experimental observations in planetary magnetospheres and the heliosphere.
The paper discusses conflicts in perceptions of GM crops illustrating the complexities of GM debates and applications of the concept of sustainable development. The concept consists of three discourses that both opponents and supporters of GM crops refer to in their analyses: environmentalism, social and economic development and the two sub-issues of sustainable development—biodiversity loss and food security. This creates a unique situation when both proponents and opponents of GM food use the same framework of sustainable development to support their arguments and do not reach a common ground. This will be illustrated by a review of the arguments brought by these two groups.
The dynamics of the system of cities in Russia in 1989–2010 is analyzed based on the population census data in 1989, 2002, and 2010, as well as the current population register. The extent of the decline or less often of the increase of the population size are considered for cities of different sizes for each intercensal period (1989–2002 and 2002–2010) and factors contributing to this are noted. The change in the populationsize of cities is analyzed, depending on their size and geographical location, expressed in the distance to the center of the federal subject. It turned out that in the 1990s and in the 2000s, the population of cities of different sizes, but located at a distance of up to 50 km from the regional center increased, and at greater distances the dynamics were not so welldefined. The dependence of the growth/decline of the population of cities on their size is more variable: the population of cities of different sizes both grew and declined. The dynamics of the natural increase and migration increase of cities with different sizes of population show that the higher the population size the greater the importance of migration increase as a compensator of natural decrease.
Non-homogeneous Markov chain models can represent biologically important regions of DNA sequences. The statistical pattern that is described by these models is usually weak and was found primarily because of strong biological indications. The general method for extracting similar patterns is presented in the current paper. The algorithm incorporates cluster analysis, multiple alignment and entropy minimization. The method was first tested using the set of DNA sequences produced by Markov chain generators. It was shown that artificial gene sequences, which initially have been randomly set up along the multiple alignment panels, are aligned according to the hidden triplet phase. Then the method was applied to real protein-coding sequences and the resulting alignment clearly indicated the triplet phase and produced the parameters of the optimal 3-periodic non-homogeneous Markov chain model. These Markov models were already employed in the GeneMark gene prediction algorithm, which is used in genome sequencing projects. The algorithm can also handle the case in which the sequences to be aligned reveal different statistical patterns, such as Escherichia co/i protein-coding sequences belonging to Class II and Class III. The algorithm accepts a random mix of sequences from different classes, and is able to separate them into two groups (clusters), align each cluster separately, and define a non-homogeneous Markov chain model for each sequence cluster.
The spatiotemporal coupling of brainwaves is commonly quantified using the amplitude or phase of signals measured by electro- or magnetoencephalography (EEG/MEG). To enhance the temporal resolution for coupling delays down to millisecond level, a new power correlation (PC) method is proposed and tested.
The cross-correlations of any two brainwave powers at two locations are calculated sequentially through a measurement using the convolution theorem. For noise suppression, the cross-correlation series is moving-average filtered, preserving the millisecond resolution in the cross-correlations, but with reduced noise. The coupling delays are determined from the delays of the cross-correlation peaks.
Simulations showed that the new method detects reliably power cross-correlations with millisecond accuracy. Moreover, in MEG measurements on three healthy volunteers, the method showed average alpha–alpha coupling delays of around 0–20 ms between the occipital areas of two hemispheres. Lower-frequency brainwaves vs. alpha waves tended to have a larger lag; higher-frequency waves vs. alpha waves showed delays with large deviations.
Comparison with existing methods
The use of signal power instead of its square root (amplitude) in the cross-correlations improves noise cancellation. Compared to signal phase, the signal power analysis time delays do not have periodic ambiguity. In addition, the novel method allows fast calculation of cross-correlations.
The PC method conveys novel information about brainwave dynamics. The method may be extended from sensor-space to source-space analysis, and can be applied also for electroencephalography (EEG) and local field potentials (LFP).
Detection of recombination events in a bacterial genome is both important from the evolutionary point of view, and of practical interest. Indeed, homologous recombination (HR) plays a major role in the exchange of antigenic determinants between strains. There exist statistical methods to detect recently recombined segments in whole-genome sequences that use a high local density of substitutions as a signal of HR events with a source outside considered strains. However, it is difficult to detect the HR events within a set of strains, which represent whole species diversity, due to a low number of substitutions in recombined segments and high level of diversity of strains. Here, we analyzed HR in 20 Escherichia coli (E. coli) strains to define what fraction of segments with a high substitution rate were introduced in a genome by HR. For detection of HR, we used the segmentation, performed by the adaptive weights smoothing (AWS) algorithm. It detects sharp changes in the structure of observed data analyzing only qualitative structural information. We validated the approach on simulated data, applied it to the analysis of E. coli strains, and determined the recombination rates between phylogroups.
Recent years of research have shown that the complex temporal structure of ongoing oscillations is scale-free and characterized by long-range temporal correlations. Detrended fluctuation analysis (DFA) has proven particularly useful, revealing that genetic variation, normal development, or disease can lead to differences in the scale-free amplitude modulation of oscillations. Furthermore, amplitude dynamics is remarkably independent of the time-averaged oscillation power, indicating that the DFA provides unique insights into the functional organization of neuronal systems. To facilitate understanding and encourage wider use of scaling analysis of neuronal oscillations, we provide a pedagogical explanation of the DFA algorithm and its underlying theory. Practical advice on applying DFA to oscillations is supported by MATLAB scripts from the Neurophysiological Biomarker Toolbox (NBT) and links to the NBT tutorial website http://www.nbtwiki.net/. Finally, we provide a brief overview of insights derived from the application of DFA to ongoing oscillations in health and disease, and discuss the putative relevance of criticality for understanding the mechanism underlying scale-free modulation of oscillations.
The key-problems of design, examination, laboratory' and flight testing of the attitude determination and control system (ADCS) dedicated for a microsatellite arc considered. The system consists of three pairs of the reaction wheels, three magnetorquers, set of Sun sensors, three-axis magnetometer and a control unit. ADCS, on one hand, is subjected to the high accuracy and reliability requirements, and, on the other hand, power consumption, total mass and volume limitations. It is meant for the LEO satellite with mass between 10 and 50 kg. The problems are solved within several steps, i.e. preliminary study of the satellite dynamics using asymptotical and numerical techniques, hardware and software design, testing of each actuator and sensor and the whole ACS on the test-bench dedicated specially for such a laboratory simulation. Finally flight testing has been carried out to validate ADCS functioning. In this paper both dynamics of the microsatellite with ADCS and mock-up of ADCS operation are studied. Reaction wheels control law parameters are chosen to provide the maximum degree of stability. The evolution of the reaction wheels angular momentum is also studied and the problem of the desaturation with use of the magnetorquers is solved. Attitude accuracy is estimated in terms of closed-form formulae. Some aspects of in-flight ADCS exploitation onboard the Russian microsatellite "Chibis-M" developed, designed and fabricated by the Institute of Space Research of RAS and orbited from SC "Progress" on 25th of January, 2012 are presented. Flight showed a good correspondence between analytical, numerical and laboratory' study with in-flight testing.
New methods and approaches for carrying out comprehensive measurements of hazardous waves (tsunami, storm surges) and background wave climate with telemetrically related group of ground, surface and underwater based robots are discussed. The design and equipment list of the ground robot are considered. It includes three various types of movers, an add-on for the installation of devices on the mobile platform and the hardware part. Ground robot was tested in 2016 on the coast of Sakhalin Island, cape Svobodny. Based on test results there were made conclusions on the possibility of increasing mobility of the ground robot and expanding its use. Specially designed underwater robot collects data using a video inspection system and a hydrostatic wave recorder with a string sensor. It has the ability to adjust the position of the center of gravity to increase stability when driving on steep slopes of the seabed. The surface robot was designed for conducting detailed bathymetry measurements of investigated water areas by means of a multi-beam echo sounder. Underwater and surface-based robots were tested in July 2017 on Sakhalin Island. Both robotic systems were merged into the united local network. The results of their operation were obtained to verify the data from measuring systems of the ground robot. In 2018, it is planned to conduct a series of tests involving the three robots and merging them into a local network to manage and process data in real-time.
Digit ratio (2D:4D) is a putative marker for prenatal testosterone and is correlated with performance in many sports. Low 2D:4D has been linked to strength but the evidence is mixed and strength is also influenced by mass, testosterone, and behavioural factors. It has been hypothesised that the 2D:4D-strength correlation may be strongest in challenge conditions when short-term changes occur in steroid hormones.
We tested this suggestion in men.
We used a cross-over study design with a challenge (an aggressive video of rugby tackles) and control (a blank screen) condition.
89 healthy men.
Finger lengths (2nd and 4th for both hands), hand-grip strength (HGS), testosterone (T), cortisol (C), aggression (Buss-Perry Aggression Questionnaire) and personality type (Ten Item Personality Measure). In both conditions participants provided saliva samples (for hormone assays).
In the challenge condition there was a highly significant increase in HGS, and modest changes in T, physical aggression and emotional stability. HGS correlated negatively with left hand 2D:4D. In a multiple regression, left hand 2D:4D was negatively related to HGS and emotional stability was positively related to HGS. In the control condition HGS was not correlated with 2D:4D. In a multiple regression, BMI, physical aggression, and emotional stability were significantly related to HGS.
2D:4D is a negative correlate of strength in challenge situations. This finding may in part explain associations between 2D:4D and sports performance.
Neuronal oscillations have been shown to be associated with perceptual, motor and cognitive brain operations. While complex spatio-temporal dynamics are a hallmark of neuronal oscillations, they also represent a formidable challenge for the proper extraction and quantification of oscillatory activity with non-invasive recording techniques such as EEG and MEG. In order to facilitate the study of neuronal oscillations we present a general-purpose pre-processing approach, which can be applied for a wide range of analyses including but not restricted to inverse modeling and multivariate single-trial classification. The idea is to use dimensionality reduction with spatio-spectral decomposition (SSD) instead of the commonly and almost exclusively used principal component analysis (PCA). The key advantage of SSD lies in selecting components explaining oscillations-related variance instead of just any variance as in the case of PCA. For the validation of SSD pre-processing we performed extensive simulations with different inverse modeling algorithms and signal-to-noise ratios. In all these simulations SSD invariably outperformed PCA often by a large margin. Moreover, using a database of multichannel EEG recordings from 80 subjects we show that pre-processing with SSD significantly increases the performance of single-trial classification of imagined movements, compared to the classification with PCA pre-processing or without any dimensionality reduction. Our simulations and analysis of real EEG experiments show that, while not being supervised, the SSD algorithm is capable of extracting components primarily relating to the signal of interest often using as little as 20% of the data variance, instead of > 90% variance as in case of PCA. Given its ease of use, absence of supervision, and capability to efficiently reduce the dimensionality of multivariate EEG/MEG data, we advocate the application of SSD pre-processing for the analysis of spontaneous and induced neuronal oscillations in normal subjects and patients.
Numerical modeling of dispersive shock waves called solibore in a stratified fluid is conducted. The theoretical model is based on extended version of the Korteweg-de Vries equation which takes into account the effects of cubic nonlinearity and Earth rotation. This model is now very popular in the physical oceanography. Initial conditions for simulations correspond to the real observed internal waves of shock-like shape in the Pechora Sea, the Arctic. It is shown that a sharp drop (like kink in the soliton theory) in the depth of the thermocline is conserved at a distance of one–three kilometers, and then it is transformed into dispersive shock waves (shock wave with undulations).