Гарантоздатність як фундаментальний узагальнюючий та інтегруючий підхід

Представлені головні принципи та умови становлення і етапи розвитку фундаментальної теорії і практики узагальнюючих та інтегруючих концепцій гарантоздатності, починаючи з першої об’єднаної конференції двох наукових шкіл Дж. фон Неймана і Н. Вінера. Приведені основні положення розвитку теоретичних засад і результатів прикладних досліджень інтеграційних процесів безвідмовності (надійності), відмовостійкості та гарантоздатності інформаційно-управляючих комп’ютерних систем (ІУКС).Представлены главные принципы, условия становления и этапы развития фундаментальной теории и практики обобщающих и интегрирующих концепций гарантоспособности, начиная с первой объединённой конференции двух научных школ Дж. фон Неймана и Н. Винера. Приведены основные положения развития теоретических основ и результатов прикладных исследований интеграционных процессов безотказности (надёжности), отказоустойчивости и гарантоспособности информационно-управляющих компьютерных систем (ИУКС).The main principles and conditions of formation and stages of development of the fundamental theory and practice of the generalizing and integrating concepts of dependability were presented after the leadthrough the first joint conference of two scientific schools of J. von Neumann and N. Wiener. The basic aspects of development of theoretical principles and results of applied researches of integration processes of reliability (fail-safety)

Square root singularity in the viscosity of neutral colloidal suspensions at large frequencies

The asymptotic frequency $\omega$, dependence of the dynamic viscosity of neutral hard sphere colloidal suspensions is shown to be of the form $\eta_0 A(\phi) (\omega \tau_P)^{-1/2}$, where $A(\phi)$ has been determined as a function of the volume fraction $\phi$, for all concentrations in the fluid range, $\eta_0$ is the solvent viscosity and $\tau_P$ the P\'{e}clet time. For a soft potential it is shown that, to leading order steepness, the asymptotic behavior is the same as that for the hard sphere potential and a condition for the cross-over behavior to $1/\omega \tau_P$ is given. Our result for the hard sphere potential generalizes a result of Cichocki and Felderhof obtained at low concentrations and agrees well with the experiments of van der Werff et al, if the usual Stokes-Einstein diffusion coefficient $D_0$ in the Smoluchowski operator is consistently replaced by the short-time self diffusion coefficient $D_s(\phi)$ for non-dilute colloidal suspensions.Comment: 18 pages LaTeX, 1 postscript figur

Improving impact evaluations through randomised experiments : The challenge of the National Research Council report for European criminology

The National Research Council (NRC) report on Improving Evaluation of Anticrime Programs presents and discusses a wide array of techniques of evaluation. Although recognising the very high internal validity of randomised experiments, it considers, under certain conditions, quasi-experiments and observational studies as equally valid approaches. This conclusion is critically reviewed from a European perspective, where only a few randomised trials have been realised so far. It is argued that many critiques routinely addressed to randomised experiments, such as ethical concerns or low acceptance among practitioners, are either unfounded or can be adequately dealt with through imaginative adjustments. On the other hand, randomised controlled trials need to take the challenge of broadening the perspective, especially by looking at long-term effects that no other method can consider with comparable internal validity. Other recommendations include using innovative measures of re-offending, considering dynamic rather than static criteria of re-offending, and looking, beyond re-offending, at rehabilitation in other areas of life. Particular challenges are the possible placebo effects that evaluators in criminal justice have not yet found appropriate ways to deal with

Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures

Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predictive power of the existing algorithms has been limited by small sample sizes, lack of representativeness, data leakage, and/or overfitting. Here, we overcome these limitations with the largest multi-site sample size to date (N = 5365) to provide a generalizable ML classification benchmark of major depressive disorder (MDD) using shallow linear and non-linear models. Leveraging brain measures from standardized ENIGMA analysis pipelines in FreeSurfer, we were able to classify MDD versus healthy controls (HC) with a balanced accuracy of around 62%. But after harmonizing the data, e.g., using ComBat, the balanced accuracy dropped to approximately 52%. Accuracy results close to random chance levels were also observed in stratified groups according to age of onset, antidepressant use, number of episodes and sex. Future studies incorporating higher dimensional brain imaging/phenotype features, and/or using more advanced machine and deep learning methods may yield more encouraging prospects

Childhood Atopic Diseases and Early Life Circumstances: An Ecological Study in Cuba

Background: Children are especially vulnerable during periods of resource shortage such as economic embargoes. They are likely to suffer most from poor nutrition, infectious diseases, and other ensuing short-term threats. Moreover, early life circumstances can have important consequences for long-term health. We examined the relationship between early childhood exposure to the Cuban economic situation in the nineties and the occurrence of atopic diseases later in childhood. Methodology/Principal Findings: A cross-sectional study of 1321 primary schoolchildren aged 4-14 was conducted in two Cuban municipalities. Asthma, allergic rhinoconjunctivitis and atopic dermatitis were diagnosed using the International Study of Asthma and Allergies in Childhood questionnaire. Children were divided into three groups of exposure to the economic situation in the nineties according to birth date: (1) unexposed; (2) exposed during infancy; (3) exposed during infancy and early childhood. Associations were assessed using multiple logistic regression models. Exposure during infancy had a significant inverse association with the occurrence of asthma (OR 0.56, 95% CI 0.33-0.94) and allergic rhinoconjunctivitis (OR 0.46, 95% CI 0.25-0.85). The associations were stronger after longer exposure, i.e. during infancy and early childhood, for asthma (OR 0.40, 95% CI 0.17-0.95) and allergic rhinoconjunctivitis (OR 0.29, 95% CI 0.11-0.77). No significant associations were found for atopic dermatitis. Conclusions/Significance: Exposure to the economic situation in the nineties during infancy and early childhood was inversely associated with asthma and allergic rhinoconjunctivitis occurrence later in childhood. We hypothesize that factors related to this period, such as infectious diseases and undernutrition, may have an attenuating effect on atopic disease development. The exact cause and underlying mechanisms need to be further elucidated

Biomarker discovery and redundancy reduction towards classification using a multi-factorial MALDI-TOF MS T2DM mouse model dataset

Diabetes like many diseases and biological processes is not mono-causal. On the one hand multifactorial studies with complex experimental design are required for its comprehensive analysis. On the other hand, the data from these studies often include a substantial amount of redundancy such as proteins that are typically represented by a multitude of peptides. Coping simultaneously with both complexities (experimental and technological) makes data analysis a challenge for Bioinformatics

No Alterations of Brain Structural Asymmetry in Major Depressive Disorder: An ENIGMA Consortium Analysis

OBJECTIVE: Asymmetry is a subtle but pervasive aspect of the human brain, and it may be altered in several psychiatric conditions. MRI studies have shown subtle differences of brain anatomy between people with major depressive disorder and healthy control subjects, but few studies have specifically examined brain anatomical asymmetry in relation to this disorder, and results from those studies have remained inconclusive. At the functional level, some electroencephalography studies have indicated left fronto-cortical hypoactivity and right parietal hypoactivity in depressive disorders, so aspects of lateralized anatomy may also be affected. The authors used pooled individual-level data from data sets collected around the world to investigate differences in laterality in measures of cortical thickness, cortical surface area, and subcortical volume between individuals with major depression and healthy control subjects. METHODS: The authors investigated differences in the laterality of thickness and surface area measures of 34 cerebral cortical regions in 2,256 individuals with major depression and 3,504 control subjects from 31 separate data sets, and they investigated volume asymmetries of eight subcortical structures in 2,540 individuals with major depression and 4,230 control subjects from 32 data sets. T1-weighted MRI data were processed with a single protocol using FreeSurfer and the Desikan-Killiany atlas. The large sample size provided 80% power to detect effects of the order of Cohen's d=0.1. RESULTS: The largest effect size (Cohen's d) of major depression diagnosis was 0.085 for the thickness asymmetry of the superior temporal cortex, which was not significant after adjustment for multiple testing. Asymmetry measures were not significantly associated with medication use, acute compared with remitted status, first episode compared with recurrent status, or age at onset. CONCLUSIONS: Altered brain macro-anatomical asymmetry may be of little relevance to major depression etiology in most cases

Targeted Gene Panel Sequencing for Early-onset Inflammatory Bowel Disease and Chronic Diarrhea

Background: In contrast to adult-onset inflammatory bowel disease (IBD), where many genetic loci have been shown to be involved in complex disease etiology, early-onset IBD (eoIBD) and associated syndromes can sometimes present as monogenic conditions. As a result, the clinical phenotype and ideal disease management in these patients often differ from those in adult-onset IBD. However, due to high costs and the complexity of data analysis, high-throughput screening for genetic causes has not yet become a standard part of the diagnostic work-up of eoIBD patients. Methods: We selected 28 genes of interest associated with monogenic IBD and performed targeted panel sequencing in 71 patients diagnosed with eoIBD or early-onset chronic diarrhea to detect causative variants. We compared these results to whole-exome sequencing (WES) data available for 25 of these patients. Results: Target coverage was significantly higher in the targeted gene panel approach compared with WES, whereas the cost of the panel was considerably lower (approximately 25% of WES). Disease-causing variants affecting protein function were identified in 5 patients (7%), located in genes of the IL10 signaling pathway (3), WAS (1), and DKC1 (1). The functional effects of 8 candidate variants in 5 additional patients (7%) are under further investigation. WES did not identify additional causative mutations in 25 patients. Conclusions: Targeted gene panel sequencing is a fast and effective screening method for monogenic causes of eoIBD that should be routinely established in national referral centers.info:eu-repo/semantics/publishedVersio

The microphytobenthos of Königshafen — spatial and seasonal distribution on a sandy tidal flat

A microphytobenthic species composition of a tidal flat in the northern Wadden Sea was analysed regarding cell numbers and biomass (in carbon units). The three sampling sites differed in tidal inundation from 15 cm to about 90 cm water depth at high tide. The sediment was sandy at all three stations. A cluster analysis revealed a separation of the benthic diatoms into three areas: aNereis-Corophium-belt, a seagrass-bed and theArenicola-flat. Small epipsammic diatoms were most abundant and dominated the microalgal biomass. A microphytobenthic “spring bloom” even started beneath the ice cover of the flat in January. Lowest values of cell numbers and biomass of benthic microalgae were found in summer. Highest values were measured in the uppermost area (Nereis-Corophium-belt), and only here was an autumnal increase of benthic microalgae found. Further cluster analysis within each of the three areas revealed seasonal differences although the majority of species were present all year round. Many species were most abundant in spring, and some showed a bimodal distribution (spring-autumn) in the year of investigatio

Potential Bands of Sentinel-2A Satellite for Classification Problems in Precision Agriculture

Various indices are used for assessing vegetation and soil properties in satellite remote sensing applications. Some indices, such as normalized difference vegetation index (NDVI) and normalized difference water index (NDWI), are capable of simply differentiating crop vitality and water stress. Nowadays, remote sensing capabilities with high spectral, spatial and temporal resolution are available to analyse classification problems in precision agriculture. Many challenges in precision agriculture can be addressed by supervised classification, such as crop type classification, disease and stress (e.g., grass, water and nitrogen) monitoring. Instead of performing classification based on designated indices, this paper explores direct classification using different bands information as features. Land cover classification by using the recently launched Sentinel-2A image is adopted as a case study to validate our method. Four approaches of featured band selection are compared to classify five classes (crop, tree, soil, water and road) with the support vector machines (SVMs) algorithm, where the first approach utilizes traditional empirical indices as features and the latter three approaches adopt specific bands (red, near infrared and short wave infrared) related to indices, specific bands after ranking by mutual information (MI), and full bands of on board sensors as features, respectively. It is shown that a better classification performance can be achieved by directly using the selected bands after MI ranking compared with the one using empirical indices and specific bands related to indices, while the use of all 13 bands can marginally improve the classification accuracy than MI based one. Therefore, it is recommended that this approach can be applied for specific Sentinel-2A image classification problems in precision agriculture