Computational fluid dynamics challenges for hybrid air vehicle applications

This paper begins by comparing turbulence models for the prediction of hybrid air vehicle (HAV) flows. A 6 : 1 prolate spheroid is employed for validation of the computational fluid dynamics (CFD) method. An analysis of turbulent quantities is presented and the Shear Stress Transport (SST) k-ω model is compared against a k-ω Explicit Algebraic Stress model (EASM) within the unsteady Reynolds-Averaged Navier-Stokes (RANS) framework. Further comparisons involve Scale Adaptative Simulation models and a local transition transport model. The results show that the flow around the vehicle at low pitch angles is sensitive to transition effects. At high pitch angles, the vortices generated on the suction side provide substantial lift augmentation and are better resolved by EASMs. The validated CFD method is employed for the flow around a shape similar to the Airlander aircraft of Hybrid Air Vehicles Ltd. The sensitivity of the transition location to the Reynolds number is demonstrated and the role of each vehicle£s component is analyzed. It was found that the ¦ns contributed the most to increase the lift and drag

INTEGRATING OPTICAL AND RADAR IMAGERY TO ENHANCE RIVER DROUGHT MONITORING

Drought events are growingly affecting European and Italian territories, hampering local environments and biodiversity, such as the ones relying on rivers for their subsistence. Monitoring of rivers is becoming an important issue to face drought crisis and may be exploited with different tools. Among the most commons, satellite imagery is exploited to map water coverage, basing on optical or radar sources. This work proposes a combination of the two sensors to overcome possible limitations of the single dataset exploitation, reaching a reliable result. The methodology is applied to a stretch of Po River in Lombardy region (Italy). Through Google Earth Engine platform, optical satellite Sentinel-2 and radar satellite Sentinel-1 data are processed. The combination of the radar data and of the optical spectral indices is carried out through a pixel-based supervised classification, with a Random Forest classifier. Maps of water coverage are obtained, numerical outcomes of water surface evaluation are recorded and validated by the mean of reference hydrometric data. A multitemporal analysis is then reported, aiming to prove the efficiency of the procedure. All iterations show reliable accuracies and correlation among water surface estimation and water table measurements in two sections of interest. In perspective, the proposed methodology will be implemented in tools for supporting drought monitoring to be integrated in environmental public administration policies

Analysis of Hybrid Air Vehicles using Computational Fluid Dynamics

This paper presents an aerodynamic study of bodies related to lighter than air vehicles, using Computational Fluid Dynamics. The work begins with the validation of the CFD method using a 6:1 prolate spheroid. The validated method is then employed for the study of the flow around a shape similar to the Airlander aircraft of Hybrid Air Vehicles Ltd. An overview of the flow around is presented, supported by pressure survey, flow visualisation and transitional flow effects. The sensitivity of the transition location to the Reynolds number is also demonstrated, and the role of each component of the vehicle is analysed in terms of its effect on the flow-field, the lift and drag, and stability in pitch. It was found that the fins contributed the most to increase the lift and drag coefficients

SEMI-AUTOMATED PRODUCTION AND FILTERING OF SATELLITE DERIVED WATER QUALITY PARAMETERS

This paper describes the semi-automated procedure implemented for the production of Water Quality Parameters (WQP) maps obtained processing Sentinel-3 and Landsat-8 imagery in the framework of SIMILE Interreg project. The processing chain includes the use of the C2RCC processor to obtain Chl-a (Chlorophyll-a) and TSM (Total Suspended Matter) and the Barsi method to produce maps of water surface temperature. The maps were filtered to exclude anomalous values due for example to clouds, water reflection (such as glint), or mixed pixels and compared to in-situ data. The filtering included an outlier rejection performed with the 36 rule. The values singled out as local anomalies where checked with respect to possible local behaviours, such as the presence of very small gulfs and inflow/outflow streams and providing guidelines with visual examples, to support the operator. The idea of a procedure as much as possible automated and guided is to foster the WQP maps production after the end of SIMILE project

Significant factors of the successful lean six-sigma implementation

© 2017 International Journal of Mathematical, Engineering and Management Sciences. Based on an extensive literature review we have selected factors critical for Lean Six Sigma implementation success. Four variables were selected to be used as output variables measuring this project success: project on time completion, achievement of financial goals, sigma level achieved (that was measured using Defects per Million Opportunities, DPMO), and overall project success. Using empirical data from 256 Lean Six Sigma Projects, we present the model developed and identify significant factors for Lean Six Sigma implementation success. Empirical results, which were collected during Lean Six Sigma implementation in 39 business units of an Automotive Sector Company in North America and Europe, were analysed using Multivariate Analysis of Variance (MANOVA) and General Linear Model (GLM). Two main factors were found as positively linked with the different aspects of project success: the competency of the Black Belts team and the management support to the project

The impact of psychosis on the course of cognition: a prospective, nested case-control study in individuals at clinical high-risk for psychosis

BACKGROUND: Although cognitive deficits in patients with schizophrenia are rooted early in development, the impact of psychosis on the course of cognitive functioning remains unclear. In this study a nested case-control design was used to examine the relationship between emerging psychosis and the course of cognition in individuals ascertained as clinical high-risk (CHR) who developed psychosis during the study (CHR + T). METHOD: Fifteen CHR + T subjects were administered a neurocognitive battery at baseline and post-psychosis onset (8.04 months, s.d. = 10.26). CHR + T subjects were matched on a case-by-case basis on age, gender, and time to retest with a group of healthy comparison subjects (CNTL, n = 15) and two groups of CHR subjects that did not transition: (1) subjects matched on medication treatment (i.e. antipsychotics and antidepressants) at both baseline and retesting (Meds-matched CHR + NT, n = 15); (2) subjects unmedicated at both assessments (Meds-free CHR + NT, n = 15). RESULTS: At baseline, CHR + T subjects showed large global neurocognitive and intellectual impairments, along with specific impairments in processing speed, verbal memory, sustained attention, and executive function. These impairments persisted after psychosis onset and did not further deteriorate. In contrast, CHR + NT subjects demonstrated stable mild to no impairments in neurocognitive and intellectual performance, independent of medication treatment. CONCLUSIONS: Cognition appears to be impaired prior to the emergence of psychotic symptoms, with no further deterioration associated with the onset of psychosis. Cognitive deficits represent trait risk markers, as opposed to state markers of disease status and may therefore serve as possible predictors of schizophrenia prior to the onset of the full illness

Contributions of early cortical processing and reading ability to functional status in individuals at clinical high risk for psychosis

Background: There is a growing recognition that individuals at clinical high risk need intervention for functional impairments, along with emerging psychosis, as the majority of clinical high risk (CHR) individuals show persistent deficits in social and role functioning regardless of transition to psychosis. Recent studies have demonstrated reduced reading ability as a potential cause of functional disability in schizophrenia, related to underlying deficits in generation of mismatch negativity (MMN). The present study extends these findings to subjects at CHR. Methods: The sample consisted of 34 CHR individuals and 33 healthy comparison subjects (CNTLs) from the Recognition and Prevention (RAP) Program at the Zucker Hillside Hospital in New York. At baseline, reading measures were collected, along with MMN to pitch, duration, and intensity deviants, and measures of neurocognition, and social and role (academic/work) functioning. Results: CHR subjects showed impairments in reading ability, neurocognition, and MMN generation, relative to CNTLs. Lower-amplitude MMN responses were correlated with worse reading ability, slower processing speed, and poorer social and role functioning. However, when entered into a simultaneous regression, only reduced responses to deviance in sound duration and volume predicted poor social and role functioning, respectively. Conclusions: Deficits in reading ability exist even prior to illness onset in schizophrenia and may represent a decline in performance from prior abilities. As in schizophrenia, deficits are related to impaired MMN generation, suggesting specific contributions of sensory-level impairment to neurocognitive processes related to social and role function. (C) 2015 Elsevier B.V. All rights reserved

The Bipolar Prodrome Symptom Interview and Scale-Prospective (BPSS-P): description and validation in a psychiatric sample and healthy controls

Objective: The aim of the present study was to investigate the psychometric properties of the Bipolar Prodrome Symptom Interview and Scale-Prospective (BPSS-P), the first specific interview for emerging bipolar disorder (BD) symptoms. Methods: A total of 205 youth aged 12-23 years and/or their caregivers underwent BPSS-P interviews: 129 patients with mood spectrum disorders [ depression spectrum disorder (n = 77), mood disorder not otherwise specified (NOS) (n = 27), BD-NOS (n = 14), bipolar I disorder (BD-I)/bipolar II disorder (BD-II)/cyclothymia (n = 11), 34 with non-mood spectrum disorders, and 42 healthy controls (HCs)]. We used Cronbach\u27s alpha to assess internal consistency; intra-class correlation (ICC) for inter-rater reliability; Spearman\u27s rho for convergent validity with the Young Mania Rating Scale (YMRS), General Behavior Inventory-10-item Mania Form (GBI-M-10), and Cyclothymic-Hypersensitive Temperament (CHT) scale; and analysis of variance for discriminatory power between diagnostic groups. Results: Internal consistency was good to very good for the BPSS-P Mania (Cronbach\u27s alpha = 0.87), Depression (Cronbach\u27s alpha = 0.89), and General Symptom indices (Cronbach\u27s alpha = 0.74). Inter-rater reliability was high for the BPSS-P Total score (ICC = 0.939), and BPSS-P Mania (ICC = 0.934), Depression (ICC = 0.985), and General (ICC = 0.981) indices. Convergent validity was large (rho \u3e= 0.50) between the BPSS-P Mania Index and YMRS, GBI-M-10, and CHT; BPSS-P Depression Index and Montgomery-Asberg Depression Rating Scale (MADRS) and CHT; and BPSS-P General Index and GBI-M-10 and CHT. Expectedly, convergent validity was small (rho = 0.10 to \u3c 0.30) between the BPSS-P Mania Index and MADRS, and BPSS-P Depression Index and YMRS. Furthermore, the BPSS-P and its subscales discriminated each patient group from HCs and from non-mood spectrum patients (except for the BPSS-P General Index). Moreover, the BPSS-P Total score discriminated BD-I/BD-II/cyclothymia from depression spectrum patients, and the BPSS-Mania Index differentiated all three bipolar spectrum groups from depression spectrum patients. Conclusions: The BPSS-P has good to excellent psychometric properties. Its use across multiple settings and predictive validity requires further investigation

Mechanical Strength of 17 134 Model Proteins and Cysteine Slipknots

A new theoretical survey of proteins' resistance to constant speed stretching is performed for a set of 17 134 proteins as described by a structure-based model. The proteins selected have no gaps in their structure determination and consist of no more than 250 amino acids. Our previous studies have dealt with 7510 proteins of no more than 150 amino acids. The proteins are ranked according to the strength of the resistance. Most of the predicted top-strength proteins have not yet been studied experimentally. Architectures and folds which are likely to yield large forces are identified. New types of potent force clamps are discovered. They involve disulphide bridges and, in particular, cysteine slipknots. An effective energy parameter of the model is estimated by comparing the theoretical data on characteristic forces to the corresponding experimental values combined with an extrapolation of the theoretical data to the experimental pulling speeds. These studies provide guidance for future experiments on single molecule manipulation and should lead to selection of proteins for applications. A new class of proteins, involving cystein slipknots, is identified as one that is expected to lead to the strongest force clamps known. This class is characterized through molecular dynamics simulations.Comment: 40 pages, 13 PostScript figure