and A.Bourmistrova

This paper present a methodology to achieve three dimensional shape optimization of damping liners attached to vibrating panels. It is the initial stage of the development of a flexible CAE design tool to optimize such liners in automotive panels. Noise, vibration and harshness are critical aspects in modern vehicle refinement and passenger perception of quality. Vibration from engine, powertrain and road sources are transmitted through the vehicle structure and excite body panels that add to the tactile vibrations felt by passengers and the noise level. To reduce this, damping materials are commonly attached to panels as uniform layers to absorb and dissipate vibration energy. A redistribution of damping material based on the dynamic response characteristics of the panels constitutes a more efficien

The relationship between successional vascular plant assemblages and associated microbial communities on coal mine spoil heaps

The aim of the study was to investigate the relationships between the vascular plant species and the associated soil microbial properties at various stages of vegetation development on unclaimed hard coal mine spoil heaps in Upper Silesia (south Poland). The spontaneous vegetation, soil chemistry as well as the activity and structure of microbial communities were recorded on this specific habitat. The colliery heaps were divided into four age classes and the plant species composition and cover abundance were recorded on established plots (2 m × 2 m). The soil microbial activity under the vegetation patches was assessed using fluorescein diacetate hydrolytic activity (FDHA) and the soil microbial biomass and community composition were determined by phospholipid fatty acid (PLFA) biomarkers. Total microbial biomass in soils from the older vegetation plots was significantly higher than those in soils from the younger plots. In all studied samples, microbial communities consisted primarily of bacteria with the dominance of Gram negative bacteria over Gram positive and aerobic microorganisms were more dominant than anaerobic ones. Statistical analysis revealed a correlation between the type of vegetation and microbial community structure

SAWA experiment ? properties of mineral dust aerosol as seen by synergic lidar and sun-photometer measurements

International audienceWe propose a method of retrieving basic information on mineral dust aerosol particles from synergic sun-photometer and multi-wavelength lidar measurements as well as from the observations of lidar light depolarisation. We use this method in a case study of mineral dust episode in Central Europe. Lidar signals are inversed with a modified Klett-Fernald algorithm. Aerosol optical depth measured with the sun-photometer allows to reduce uncertainties in the inversion procedure through which we estimate vertical profile of aerosol extinction. Next we assume that aerosol particles may be represented by ensemble of randomly oriented, identical spheroids. Having calculated vertical profiles of aerosol extinction coefficients for lidar wavelengths, we compute the profiles of local Angstrom exponent. We use laser beam depolarisation together with the calculated Angstrom exponents to estimate the shapes (aspect ratios) and sizes of the spheroids. Numerical calculations are performed with the transition matrix (T-matrix) algorithm by M. Mishchenko. The proposed method was first used during SAWA measurement campaign in Warsaw, spring 2005, to characterise the particles of desert dust, drifting over Poland with a southern-eastern wind (13?14 April). Observations and T-matrix calculations show that mode radii of spheroids representative for desert aerosols' particles are in the range of 0.15?0.3 ?m, while their aspect ratios are lower than 0.7 or larger than 1.7

Microscopic description of the surface dipole plasmon in large Na_N clusters (950 < N < 12050)

Fully microscopic RPA/LDA calculations of the dipole plasmon for very large neutral and charged sodium clusters, Na_N^Z+, in the size range 950 < N < 12050 are presented for the first time. 60 different sizes are considered altogether, which allows for an in-depth investigation of the asymptotic behavior of both the width and the position of the plasmon.Comment: Latex/Revtex, 4 pages with 4 Postscript figures, accepted for publication in Physical Review

Repeated-Measures Latent Profile Analyses of Intervention Fidelity to a Teacher-Delivered Intervention Program for Children At Elevated Risk for Emotional and Behavioral Disorders

Teachers have difficulty delivering Tier-2 intervention programs for preschoolers at elevated risk for socioemotional and behavioral disorders with high intervention fidelity (Durlak, 2010; Sutherland et al., 2018). Several proximal factors that impact program fidelity have been identified, which may undermine program effects (Domitrovich et al., 2008; McLeod et al., 2022; Sutherland et al., 2018). Therefore, researchers have identified strategies, such as practice-based coaching, to improve intervention fidelity and support teachers (Hemmeter et al., 2015; Synder et al., 2015). Most of the field\u27s knowledge of these topics is limited to variable-centered approaches (Fettig et al., 2022; Low et al., 2016). However, variable-centered approaches, as opposed to person-centered approaches, ignore the possibility that there may be underlying subgroups of teachers that can be identified based on their level of intervention fidelity. As such, the current study aimed to utilize a person-centered approach to identify whether there are distinct profiles of teachers based on their patterns in the level of intervention fidelity throughout practice-based coaching. Additionally, the study aimed to understand whether proximal factors and program outcomes are associated with profile membership. To achieve these aims, a secondary analysis of a multi-site cluster randomized control trial of the BEST in CLASS program, a Tier-2 teacher-delivered intervention for children at risk for emotional and behavioral disorders, was conducted (Conroy et al., 2018; Sutherland et al., 2018a). Data was drawn from teachers (n = 85) and children (n = 195) assigned to the BEST in CLASS study condition. To identify whether there are underlying subgroups of teacher-child dyads based on teachers’ patterns of intervention fidelity during coaching, two Repeated-Measure Latent Profile Analyses (RM-LPA) were conducted. The first RM-LPA using subscale-level adherence data as indicator variables across five time points revealed two distinct subgroups: Average Adherence and Above Average Adherence. Likewise, results from the second RM-LPA using competence subscale scores at the same five time points also found two distinct subgroups (“Average Competence” and “Above Average Competence”). Notably, no significant differences were found between the two adherence subgroups based on proximal factors or intervention outcomes. In contrast, subgroup membership based on competence scores was significantly associated with classroom climate and initial levels of challenging child behavior. Additionally, the “Above Average Competence” subgroup displayed significantly lower levels of challenging child behavior and teacher-child conflict at post-test than the “Average Competence” subgroup. However, no differences in teacher-child closeness were observed. The current study\u27s results support the existence of distinct subgroups of teachers who vary in their patterns of intervention fidelity while receiving practice-based coaching. Findings also suggest that proximal factors and intervention outcomes are associated with subgroup membership, mainly based on levels of competence. These findings may help inform efforts to tailor coaching and professional development for teachers based on their unique needs

A Psychometric Evaluation of the BEST in CLASS Adherence and Competence Scale

It is critical to utilize treatment integrity instruments to support the evaluation of evidence-based programs in early classroom contexts. However, in the early childhood field, guidelines for collecting treatment integrity data are underdeveloped. Consequently, most treatment integrity instruments employed in the field solely assess adherence, vary in design features and have little psychometric evidence supporting their use. As such, this represents a gap in the field that might slow efforts to implement evidence-based programs. The current study examines the score reliability and validity of an observational treatment integrity instrument (The BEST in CLASS Adherence and Competence Scale [BiCACS]; Sutherland et al., 2014). The BiCACS is designed to assess adherence and competence of the practices found in the BEST in CLASS program, a teacher-delivered evidence-based program for children at-risk for emotional and behavioral disorders. Data were drawn from observations of 179 teachers who were randomized to BEST in CLASS (n = 89) or business-as-usual (n = 90) and 416 children (n = 211 in the BEST in CLASS condition; n = 205 in the business-as-usual condition) at risk for emotional and behavioral disorders. Based on double-coded observations (25% of sample) the mean single-measure intraclass correlation (ICC[2,1]) was .74 (SD = 0.06) for the Adherence items and .46 (SD = 0.14) for the Competence items. The ICC(2,1) for the Adherence and Competence subscales were .81 and .43, respectively. Findings also suggested initial evidence of convergent and discriminant validity at the BiCACS item and subscale levels. The magnitude of correlations among the BiCACS items suggests that the adherence and Competence items overlap the most with items within the same subscale, but also measure distinct BEST in CLASS practices. At the subscale level, the correlation among the Adherence and Competence items are more related to each other than their correlations with scores on measures of child responsiveness, child engagement, closeness, and conflict of student-teacher relationships. Validity evidence at the subscale level suggests that the BiCACS can distinguish between intervention groups and detect change over time. The reliability and validity findings support the use of the BiCACS as a program evaluation instrument. Although, future research is still needed to replicate these findings and test the construct validity of the BiCACS with other instruments that assess adherence and competence. Still, results provide valuable information about the psychometric properties of a treatment integrity instrument used in early classroom contexts and inform the growing knowledge of this area in the field

ACE-ASIA - Regional climatic and atmospheric chemical effects of Asian dust and pollution

Although continental-scale plumes of Asian dust and pollution reduce the amount of solar radiation reaching the earth's surface and perturb the chemistry of the atmosphere, our ability to quantify these effects has been limited by a lack of critical observations, particularly of layers above the surface. Comprehensive surface, airborne, shipboard, and satellite measurements of Asian aerosol chemical composition, size, optical properties, and radiative impacts were performed during the Asian Pacific Regional Aerosol Characterization Experiment (ACE-Asia) study. Measurements within a massive Chinese dust storm at numerous widely spaced sampling locations revealed the highly complex structure of the atmosphere, in which layers of dust, urban pollution, and biomass-burning smoke may be transported long distances as distinct entities or mixed together. The data allow a first-time assessment of the regional climatic and atmospheric chemical effects of a continental-scale mixture of dust and pollution. Our results show that radiative flux reductions during such episodes are sufficient to cause regional climate change

On the determination of a cloud condensation nuclei from satellite : Challenges and possibilities

We use aerosol size distributions measured in the size range from 0.01 to 10+ μm during Transport and Chemical Evolution over the Pacific (TRACE-P) and Aerosol Characterization Experiment-Asia (ACE-Asia), results of chemical analysis, measured/modeled humidity growth, and stratification by air mass types to explore correlations between aerosol optical parameters and aerosol number concentration. Size distributions allow us to integrate aerosol number over any size range expected to be effective cloud condensation nuclei (CCN) and to provide definition of a proxy for CCN (CCNproxy). Because of the internally mixed nature of most accumulation mode aerosol and the relationship between their measured volatility and solubility, this CCNproxy can be linked to the optical properties of these size distributions at ambient conditions. This allows examination of the relationship between CCNproxy and the aerosol spectral radiances detected by satellites. Relative increases in coarse aerosol (e.g., dust) generally add only a few particles to effective CCN but significantly increase the scattering detected by satellite and drive the Angstrom exponent (α) toward zero. This has prompted the use of a so-called aerosol index (AI) on the basis of the product of the aerosol optical depth and the nondimensional α, both of which can be inferred from satellite observations. This approach biases the AI to be closer to scattering values generated by particles in the accumulation mode that dominate particle number and is therefore dominated by sizes commonly effective as CCN. Our measurements demonstrate that AI does not generally relate well to a measured proxy for CCN unless the data are suitably stratified. Multiple layers, complex humidity profiles, dust with very low α mixed with pollution, and size distribution differences in pollution and biomass emissions appear to contribute most to method limitations. However, we demonstrate that these characteristic differences result in predictable influences on AI. These results suggest that inference of CCN from satellites will be challenging, but new satellite and model capabilities could possibly be integrated to improve this retrieval

Regional variation of organic functional groups in aerosol particles on four U.S. east coast platforms during the International Consortium for Atmospheric Research on Transport and Transformation 2004 campaign

Submicron atmospheric aerosol samples were collected during the International Consortium for Atmospheric Research on Transport and Transformation (ICARTT) 2004 campaign on four platforms: Chebogue Point (Nova Scotia, Canada), Appledore Island (Maine), the CIRPAS Twin Otter over Ohio, and the NOAA R/V Ronald H. Brown in the Gulf of Maine. Saturated aliphatic C-C-H, unsaturated aliphatic C=C−H, aromatic C=C−H, organosulfur C-O-S, carbonyl C=O, and organic hydroxyl C-OH functional groups were measured by calibrated Fourier Transform Infrared (FTIR) spectroscopy at all four sampling platforms. The ratio of molar concentrations of carbonyl C=O to saturated aliphatic C-C-H groups was nearly constant at each sampling platform, with the Twin Otter samples having the lowest ratio at 0.1 and the three more coastal platforms having ratios of 0.4 and 0.5. Organic mass (OM) to organic carbon (OC) ratios follow similar trends for the four platforms, with the Twin Otter having the lowest ratio of 1.4 and the coastal platforms having slightly higher values typically between 1.5 and 1.6. Organosulfur compounds were occasionally observed. Collocated organic aerosol sampling with two Aerodyne aerosol mass spectrometers for OM, a Sunset Laboratory thermo-optical analysis instrument for OC, and an ion chromatography-particle into liquid sampler (IC-PILS) for speciated carboxylic acids provided comparable results for most of the project, tracking the time series of FTIR OM, OC, and carbonyl groups, respectively, and showing simultaneous peaks of similar magnitude during most of the project. The FTIR/IC-PILS comparison suggests that about 9% of the carbonyl groups found in submicron organic particles on the Twin Otter are typically associated with low molecular weight carboxylic acids

An overview of the first decade of PollyNET : an emerging network of automated Raman-polarization lidars for continuous aerosol profiling

© Author(s) 2016. This work is distributed under the Creative Commons Attribution 3.0 LicenseA global vertically resolved aerosol data set covering more than 10 years of observations at more than 20 measurement sites distributed from 63° N to 52° S and 72° W to 124° E has been achieved within the Raman and polarization lidar network PollyNET. This network consists of portable, remote-controlled multiwavelength-polarization-Raman lidars (Polly) for automated and continuous 24/7 observations of clouds and aerosols. PollyNET is an independent, voluntary, and scientific network. All Polly lidars feature a standardized instrument design with different capabilities ranging from single wavelength to multiwavelength systems, and now apply unified calibration, quality control, and data analysis. The observations are processed in near-real time without manual intervention, and are presented online at http://polly.tropos.de/. The paper gives an overview of the observations on four continents and two research vessels obtained with eight Polly systems. The specific aerosol types at these locations (mineral dust, smoke, dust-smoke and other dusty mixtures, urban haze, and volcanic ash) are identified by their Ångström exponent, lidar ratio, and depolarization ratio. The vertical aerosol distribution at the PollyNET locations is discussed on the basis of more than 55 000 automatically retrieved 30 min particle backscatter coefficient profiles at 532 nm as this operating wavelength is available for all Polly lidar systems. A seasonal analysis of measurements at selected sites revealed typical and extraordinary aerosol conditions as well as seasonal differences. These studies show the potential of PollyNET to support the establishment of a global aerosol climatology that covers the entire troposphere.Peer reviewe