Can enlightenment be traced to specific neural correlates, cognition, or behavior? No, and (a qualified) Yes

The field of contemplative science is rapidly growing and integrating into the basic neurosciences, psychology, clinical sciences, and society-at-large. Yet the majority of current research in the contemplative sciences has been divorced from the soteriological context from which these meditative practices originate and has focused instead on clinical applications with goals of stress reduction and psychotherapeutic health. In the existing research on health outcomes of mindfulness-based clinical interventions, for example, there have been almost no attempts to scientifically investigate the goal of enlightenment. This is a serious oversight, given that such profound transformation across ethical, perceptual, emotional, and cognitive domains are taken to be the natural outcome and principle aim of mindfulness practice in the traditional Buddhist contexts from which these practices are derived. If short-term interventions as short as a few sessions are now beginning to produce neuroplastic changes, it may be that even in secular contexts, practitioners are already developing states and traits that are associated with progress toward enlightenment. In order to carefully assess the potential effects of meditative interventions it is of singular importance to ask whether enlightenment can be traced to specific neural correlates, cognition, or behavior

2018 MAX-C/ExoMars Mission: The Orleans Mars-Analogue Rock Collection for Instrument Testing

International audienceIn order to reply to the exobiological goals of the 2018 MAX-C/ExoMars mission, the Orléans-OSUC analogue rock collection and database contains well characterised Mars analogue rocks and minerals for use in instrument testing and in situ missions

The WISDOM Radar: Unveiling the Subsurface Beneath the ExoMars Rover and Identifying the Best Locations for Drilling

The search for evidence of past or present life on Mars is the principal objective of the 2020 ESA-Roscosmos ExoMars Rover mission. If such evidence is to be found anywhere, it will most likely be in the subsurface, where organic molecules are shielded from the destructive effects of ionizing radiation and atmospheric oxidants. For this reason, the ExoMars Rover mission has been optimized to investigate the subsurface to identify, understand, and sample those locations where conditions for the preservation of evidence of past life are most likely to be found. The Water Ice Subsurface Deposit Observation on Mars (WISDOM) ground-penetrating radar has been designed to provide information about the nature of the shallow subsurface over depth ranging from 3 to 10 m (with a vertical resolution of up to 3 cm), depending on the dielectric properties of the regolith. This depth range is critical to understanding the geologic evolution stratigraphy and distribution and state of subsurface H2O, which provide important clues in the search for life and the identification of optimal drilling sites for investigation and sampling by the Rover's 2-m drill. WISDOM will help ensure the safety and success of drilling operations by identification of potential hazards that might interfere with retrieval of subsurface samples

Prediction of incident cardiovascular events using machine learning and CMR radiomics.

OBJECTIVES: Evaluation of the feasibility of using cardiovascular magnetic resonance (CMR) radiomics in the prediction of incident atrial fibrillation (AF), heart failure (HF), myocardial infarction (MI), and stroke using machine learning techniques. METHODS: We identified participants from the UK Biobank who experienced incident AF, HF, MI, or stroke during the continuous longitudinal follow-up. The CMR indices and the vascular risk factors (VRFs) as well as the CMR images were obtained for each participant. Three-segmented regions of interest (ROIs) were computed: right ventricle cavity, left ventricle (LV) cavity, and LV myocardium in end-systole and end-diastole phases. Radiomics features were extracted from the 3D volumes of the ROIs. Seven integrative models were built for each incident cardiovascular disease (CVD) as an outcome. Each model was built with VRF, CMR indices, and radiomics features and a combination of them. Support vector machine was used for classification. To assess the model performance, the accuracy, sensitivity, specificity, and AUC were reported. RESULTS: AF prediction model using the VRF+CMR+Rad model (accuracy: 0.71, AUC 0.76) obtained the best result. However, the AUC was similar to the VRF+Rad model. HF showed the most significant improvement with the inclusion of CMR metrics (VRF+CMR+Rad: 0.79, AUC 0.84). Moreover, adding only the radiomics features to the VRF reached an almost similarly good performance (VRF+Rad: accuracy 0.77, AUC 0.83). Prediction models looking into incident MI and stroke reached slightly smaller improvement. CONCLUSIONS: Radiomics features may provide incremental predictive value over VRF and CMR indices in the prediction of incident CVDs. KEY POINTS: • Prediction of incident atrial fibrillation, heart failure, stroke, and myocardial infarction using machine learning techniques. • CMR radiomics, vascular risk factors, and standard CMR indices will be considered in the machine learning models. • The experiments show that radiomics features can provide incremental predictive value over VRF and CMR indices in the prediction of incident cardiovascular diseases

Testing the theory of immune selection in cancers that break the rules of transplantation

Modification of cancer cells likely to reduce their immunogenicity, including loss or down-regulation of MHC molecules, is now well documented and has become the main support for the concept of immune surveillance. The evidence that these modifications, in fact, result from selection by the immune system is less clear, since the possibility that they may result from reorganized metabolism associated with proliferation or from cell de-differentiation remains. Here, we (a) survey old and new transplantation experiments that test the possibility of selection and (b) survey how transmissible tumours of dogs and Tasmanian devils provide naturally evolved tests of immune surveillance

Strong Magnetic Field Fluctuations within Filamentary Auroral Density Cavities Interpreted as VLF Saucer Sources

The Geoelectrodynamics and Electro-Optical Detection of Electron and SuprathermalIon Currents (GEODESIC) sounding rocket encountered more than 100 filamentary densitycavities associated with enhanced plasma waves at ELF (3 kHz) and VLF (310 kHz)frequencies and at altitudes of 800990 km during an auroral substorm. These cavities weresimilar in size (20 m diameter in most cases) to so-called lower-hybrid cavities (LHCs)observed by previous sounding rockets and satellites; however, in contrast, many of theGEODESIC cavities exhibited up to tenfold enhancements in magnetic wave powerthroughout the VLF band. GEODESIC also observed enhancements of ELF and VLFelectric fields both parallel and perpendicular to the geomagnetic field B0 within cavities,though the VLF E field increases were often not as large proportionally as seen in themagnetic fields. This behavior is opposite to that predicted by previously published theoriesof LHCs based on passive scattering of externally incident auroral hiss. We argue thatthe GEODESIC cavities are active wave generation sites capable of radiating VLF wavesinto the surrounding plasma and producing VLF saucers, with energy supplied by cold,upward flowing electron beams composing the auroral return current. This interpretation issupported by the observation that the most intense waves, both inside and outside cavities,occurred in regions where energetic electron precipitation was largely inhibited orabsent altogether. We suggest that the wave-enhanced cavities encountered by GEODESICwere qualitatively different from those observed by earlier spacecraft because of thefortuitous timing of the GEODESIC launch, which placed the payload at apogee within asubstorm-related return current during its most intense phase, lasting only a few minutes

Law, Social Norms and Welfare as Means of Public Administration: Case Study of Mahalla Institutions in Uzbekistan

Despite numerous challenges, since its independence, Uzbekistan, with the exception of the May 2005 Andijan events, has enjoyed extraordinary political stability and not recorded any considerable cases of interethnic or interfaith conflict, regime change or civil war, whereas neighboring Kyrgyzstan, labeled an “island of democracy” by the Western world, has experienced numerous conflicts and chaos, ranging from “color revolutions” to ethnic conflict. However, for understanding Uzbekistan’s ability to cope with internal and external challenges, little recourse is made to the post-independence discourse on public administration known as “mahalla reforms”. In spite of the significant existing body of literature on the mahalla, there has been little systematic scholarly investigation of the role of mahalla in maintaining political stability and security in Uzbekistan. Previous studies did not provide an account of how the law, social norms and welfare come to interplay in the mahalla system and how this influences the public administration developments in Uzbekistan. This paper begins to redress this lacuna by analyzing public-administration reforms in post-independence Uzbekistan, namely mahalla reforms, with an effort to show how political and social stability is established through mahalla, and to what extent those reforms have affected the position of individuals vis-à-vis the public-administration system. In undertaking this task, the paper employs three theoretical concepts: the theory of norms, the welfare-pentagon model and the theory of social control. In this paper, I argue that public-administration reforms since 1991 have transformed mahalla into a comprehensive system of social control; and therefore, mahalla can be places of democratic involvement or sites of authoritarianism in Uzbekistan

The Effect of Mindfulness-based Programs on Cognitive Function in Adults: A Systematic Review and Meta-analysis

Mindfulness-based programs (MBPs) are increasingly utilized to improve mental health. Interest in the putative effects of MBPs on cognitive function is also growing. This is the first meta-analysis of objective cognitive outcomes across multiple domains from randomized MBP studies of adults. Seven databases were systematically searched to January 2020. Fifty-six unique studies (n = 2,931) were included, of which 45 (n = 2,238) were synthesized using robust variance estimation meta-analysis. Meta-regression and subgroup analyses evaluated moderators. Pooling data across cognitive domains, the summary effect size for all studies favored MBPs over comparators and was small in magnitude (g = 0.15; [0.05, 0.24]). Across subgroup analyses of individual cognitive domains/subdomains, MBPs outperformed comparators for executive function (g = 0.15; [0.02, 0.27]) and working memory outcomes (g = 0.23; [0.11, 0.36]) only. Subgroup analyses identified significant effects for studies of non-clinical samples, as well as for adults aged over 60. Across all studies, MBPs outperformed inactive, but not active comparators. Limitations include the primarily unclear within-study risk of bias (only a minority of studies were considered low risk), and that statistical constraints rendered some p-values unreliable. Together, results partially corroborate the hypothesized link between mindfulness practices and cognitive performance. This review was registered with PROSPERO [CRD42018100904]

iMARS Phase 2

The file attached is the Published/publisher’s pdf version of the articl