Klever: Verification Framework for Critical Industrial C Programs

Automatic software verification tools help to find hard-to-detect faults in programs checked against specified requirements non-interactively. Besides, they can prove program correctness formally under certain assumptions. These capabilities are vital for verification of critical industrial programs like operating system kernels and embedded software. However, such programs can contain hundreds or thousands of KLOC that prevent obtaining valuable verification results in any reasonable time when checking non-trivial requirements. Also, existing tools do not provide widely adopted means for environment modeling, specification of requirements, verification of many versions and configurations of target programs, and expert assessment of verification results. In this paper, we present the Klever software verification framework, designed to reduce the effort of applying automatic software verification tools to large and critical industrial C programs.Comment: 53 page

Alpha Band Resting-State EEG Connectivity Is Associated With Non-verbal Intelligence

The aim of the present study was to investigate whether EEG resting state connectivity correlates with intelligence. One-hundred and sixty five participants took part in the study. Six minutes of eyes closed EEG resting state was recorded for each participant. Graph theoretical connectivity metrics were calculated separately for two well-established synchronization measures [weighted Phase Lag Index (wPLI) and Imaginary Coherence (iMCOH)] and for sensor- and source EEG space. Non-verbal intelligence was measured with Raven’s Progressive Matrices. In line with the Neural Efficiency Hypothesis, path lengths characteristics of the brain networks (Average and Characteristic Path lengths, Diameter and Closeness Centrality) within alpha band range were significantly correlated with non-verbal intelligence for sensor space but no for source space. According to our results, variance in non-verbal intelligence measure can be mainly explained by the graph metrics built from the networks that include both weak and strong connections between the nodes

The Y-chromosome C3* star-cluster attributed to Genghis Khan\u27s descendants is present at high frequency in the Kerey clan from Kazakhstan

In order to verify the possibility that the Y-chromosome C3* star-cluster attributed to Genghis Khan and his patrilineal descendants is relatively frequent in the Kereys, who are the dominant clan in Kazakhstan and in Central Asia as a whole, polymorphism of the Y-chromosome was studied in Kazakhs, represented mostly by members of the Kerey clan. The Kereys showed the highest frequency (76.5%) of individuals carrying the Y-chromosome variant known as C3* star-cluster ascribed to the descendants of Genghis Khan. C3* star-cluster haplotypes were found in two sub-clans, Abakh-Kereys and Ashmaily-Kereys, diverged about 20-22 generations ago according to the historical data. Median network of the Kerey star-cluster haplotypes at 17 STR loci displays a bipartite structure, with two subclusters defined by the only difference at DYS448 locus. It is noteworthy that there is a strong correspondence of these subclusters with the Kerey sub-clans affiliation. The data obtained suggest that the Kerey clan appears to be the largest known clan in the world descending from a common Y-chromosome ancestor. Possible ways of Genghis Khan‟s relation to the Kereys are discussed

Attitudes towards genetic testing: The role of genetic literacy, motivated cognition, and socio-demographic characteristics

Understanding reasons for why people choose to have or not to have a genetic test is essen tial given the ever-increasing use of genetic technologies in everyday life. The present study explored the multiple drivers of people’s attitudes towards genetic testing. Using the Interna tional Genetic Literacy and Attitudes Survey (iGLAS), we collected data on: (1) willingness to undergo testing; (2) genetic literacy; (3) motivated cognition; and (4) demographic and cultural characteristics. The 37 variables were explored in the largest to-date sample of 4311 participants from diverse demographic and cultural backgrounds. The results showed that 82% of participants were willing to undergo genetic testing for improved treatment; and over 73%—for research. The 35 predictor variables together explained only a small propor tion of variance: 7%—in the willingness to test for Treatment; and 6%—for Research. The strongest predictors of willingness to undergo genetic testing were genetic knowledge and deterministic beliefs. Concerns about data misuse and about finding out unwanted health related information were weakly negatively associated with willingness to undergo genetic testing. We also found some differences in factors linked to attitudes towards genetic testing across the countries included in this study. Our study demonstrates that decision-making regarding genetic testing is influenced by a large number of potentially interacting factors. Further research into these factors may help consumers to make decisions regarding genetic testing that are right for their specific circumstances

Test-Retest Reliability of Behavioural and ERP Measures in Maths-Related Processing

Research into test-retest stability of emotional and cognitive responses has focused on behavioural and ERP components in relation to very well-established paradigms (such as oddball, mismatch negativity, continuous performance task, etc.). However, there is a lack of evidence for more integrative paradigms that contain a variety of tasks in a single paradigm. The aim of the present study was to investigate the test-retest reliability for behavioural and ERP components (cue-locked P300 and task-locked P600) in a paradigm composed of three different error-recognition tasks: lexical, arithmetic, and algebraic. Participants completed the paradigm on two occasions, two weeks apart on average. We examined the between-session correlations and mean-level differences. The results showed moderate-to-strong between-session stability for accuracies (r = [.29-.69]), reaction times (r = [.48-.81]), and ERP P300 and P600 responses (r = [.70-.79] and r = [.45-.85], respectively). Overall, results indicated that there was more homogeneity of the estimates at the ERP level than in stability estimates at the behavioural level. The study highlights the importance of studying neural mechanisms involved in emotional and cognitive processing in addition to studying behavioural output

Genetic Literacy and Attitudes Survey (iGLAS): International Population-Wide Assessment Instrument

Genetics represents the fastest developing discipline in the history of scientific enquiry. Genetic advances have implications for individuals and society, including matters related to law, ethics, education, medicine and philosophy. As such, it will be important for all people to be able to engage with genetic research, not just at the point that it becomes personally applicable, such as in medical treatment, but also more generally across many social domains. Given the ever-increasing impact of genetics on daily life, it is important to have a tool to evaluate what people know, think and feel about genetics and for this tool to be applicable across society. Previous studies have mainly focused on genetic literacy in medical domains with less attention paid to other applications. They have also largely focused on well-defined populations, such as undergraduate students and young adults. To overcome these limitations of previous research in this area, a consortium of psychologists, geneticists, lawyers, educationalists and ethicists have developed the International Genetic Literacy and Attitudes Survey (iGLAS). This paper presents the development, piloting and validation of this instrument. The resulting iGLAS provides a flexible, informative and quick tool for evaluating public knowledge and perceptions of genetics. In particular, it provides a tool that can be used across all demographics, allowing for tailored research with specific groups of interest

Nonlinear surface waves in left-handed materials

We study both linear and nonlinear surface waves localized at the interface separating a left-handed medium (i.e. the medium with both negative dielectric permittivity and negative magnetic permeability) and a conventional (or right-handed) dielectric medium. We demonstrate that the interface can support both TE- and TM-polarized surface waves - surface polaritons, and we study their properties. We describe the intensity-dependent properties of nonlinear surface waves in three different cases, i.e. when both the LH and RH media are nonlinear and when either of the media is nonlinear. In the case when both media are nonlinear, we find two types of nonlinear surface waves, one with the maximum amplitude at the interface, and the other one with two humps. In the case when one medium is nonlinear, only one type of surface wave exists, which has the maximum electric field at the interface, unlike waves in right-handed materials where the surface-wave maximum is usually shifted into a self-focussing nonlinear medium. We discus the possibility of tuning the wave group velocity in both the linear and nonlinear cases, and show that group-velocity dispersion, which leads to pulse broadening, can be balanced by the nonlinearity of the media, so resulting in soliton propagation.Comment: 9 pages, 10 figure

Phenological shifts of abiotic events, producers and consumers across a continent

Ongoing climate change can shift organism phenology in ways that vary depending on species, habitats and climate factors studied. To probe for large-scale patterns in associated phenological change, we use 70,709 observations from six decades of systematic monitoring across the former Union of Soviet Socialist Republics. Among 110 phenological events related to plants, birds, insects, amphibians and fungi, we find a mosaic of change, defying simple predictions of earlier springs, later autumns and stronger changes at higher latitudes and elevations. Site mean temperature emerged as a strong predictor of local phenology, but the magnitude and direction of change varied with trophic level and the relative timing of an event. Beyond temperature-associated variation, we uncover high variation among both sites and years, with some sites being characterized by disproportionately long seasons and others by short ones. Our findings emphasize concerns regarding ecosystem integrity and highlight the difficulty of predicting climate change outcomes. The authors use systematic monitoring across the former USSR to investigate phenological changes across taxa. The long-term mean temperature of a site emerged as a strong predictor of phenological change, with further imprints of trophic level, event timing, site, year and biotic interactions.Peer reviewe