ACTRIS efforts for Sentinel 5 Precursor validation

2020 ◽  
Author(s):  
Lucia Mona ◽  
Nikolaos Papagiannopoulus ◽  
Gelsomina Pappalardo ◽  
Ulla Wandinger ◽  
Giuseppe D'Amico ◽  
...  
Keyword(s):  
State Of The Art ◽  
Aerosol Layer ◽  
Additional Information ◽  
Cloud Radar ◽  
Vertical Profiling ◽  
First Results ◽  
Multi Wavelength ◽  
Spatio Temporal ◽  
Aerosol Type

<p>The Sentinel 5 Precursor products, call for an accurate validation. Europe can be nowadays regarded as a leader in ground-based vertical profiling observations. ACTRIS (Aerosols, Clouds, and Trace gases Research InfraStructure Network) is an EC funded infrastructure integrating European ground-based stations equipped with advanced atmospheric equipment. Among these, EARLINET (European Aerosol Research Lidar NETwork) and Cloudnet are well-established networks providing vertical profiles of aerosol and clouds with high vertical and temporal resolution. A network of ground-based stations has the ability to provide the spatio-temporal development of aerosol and cloud fields and offers a unique opportunity for the validation of observations from space. In this project, state-of-the-art instrumentations for observing aerosol and clouds will be used for validation purposes: multi-wavelength lidar (EARLINET) and Doppler cloud radar (Cloudnet).</p><p>Characterization of aerosol and cloud fields over the stations is provided by the use of EARLINET and Cloudnet data. Additional information is provided by AERONET data where available. Differences will be reported as a function of aerosol load, aerosol and cloud height, aerosol type, cloud type and underneath surface.</p><p>First results of validation efforts performed within ACTRIS in terms of a quantitative evaluation of the accuracy of S5P aerosol and cloud products will be reported. This activity is done under the EC-ACTS: Earlinet and Cloudnet - Aerosol and Clouds Teams for Sentinel-5P Validation unfunded project, which comprises 3 EARLINET/Cloudnet stations [Potenza (IT), Leipzig (DE) and Cabauw (NL)]; 3 EARLINET stations [Granada (ES), Athens (GR) and Bucharest (RO)] and 2 Cloudnet sites [Mace Head (IE) and Sodankylä (FI)].</p><p>In particular, the first results will be about the S5P Aerosol Layer Height (mandatory product) and Aerosol Optical Depth (optional product) and whenever available the AAI-based columnar Aerosol Type product.</p>

Treatment system response to transient AOX (adsorbable organic halogen) loadings

1997 ◽  
Vol 35 (2-3) ◽  
pp. 85-91
Author(s):  
D. A. Barton ◽  
J. D. Woodruff ◽  
T. M. Bousquet ◽  
A. M. Parrish
Keyword(s):  
Paper Industry ◽  
Model Development ◽  
Operating Conditions ◽  
System Response ◽  
Additional Information ◽  
Organic Halogen ◽  
Aox Removal ◽  
Variable Operating Conditions ◽  
Plant Shutdown

If promulgated as proposed, effluent guidelines for the U.S. pulp and paper industry will impose average monthly and maximum daily numerical limits of discharged AOX (adsorbable organic halogen). At this time, it is unclear whether the maximum-day variability factor used to establish the proposed effluent guidelines will provide sufficient margin for mills to achieve compliance during periods of normal but variable operating conditions within the pulping and bleaching processes. Consequently, additional information is needed to relate transient AOX loadings with final AOX discharges. This paper presents a simplistic dynamic model of AOX decay during treatment. The model consists of hydraulic characterization of an activated sludge process and a first-order decay coefficient for AOX removal. Data for model development were acquired by frequent collection of influent and effluent samples at a bleach kraft mill during a bleach plant shutdown and startup sequence.

scholarly journals Documentary data and the study of past droughts: a global state of the art

2018 ◽  
Vol 14 (12) ◽  
pp. 1915-1960 ◽  
Author(s):  
Rudolf Brázdil ◽  
Andrea Kiss ◽  
Jürg Luterbacher ◽  
David J. Nash ◽  
Ladislava Řezníčková
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
Drought Indices ◽  
Documentary Evidence ◽  
Climatic Trends ◽  
Instrumental Observations ◽  
Spatio Temporal ◽  
Epigraphic Evidence ◽  
Administrative Evidence

Abstract. The use of documentary evidence to investigate past climatic trends and events has become a recognised approach in recent decades. This contribution presents the state of the art in its application to droughts. The range of documentary evidence is very wide, including general annals, chronicles, memoirs and diaries kept by missionaries, travellers and those specifically interested in the weather; records kept by administrators tasked with keeping accounts and other financial and economic records; legal-administrative evidence; religious sources; letters; songs; newspapers and journals; pictographic evidence; chronograms; epigraphic evidence; early instrumental observations; society commentaries; and compilations and books. These are available from many parts of the world. This variety of documentary information is evaluated with respect to the reconstruction of hydroclimatic conditions (precipitation, drought frequency and drought indices). Documentary-based drought reconstructions are then addressed in terms of long-term spatio-temporal fluctuations, major drought events, relationships with external forcing and large-scale climate drivers, socio-economic impacts and human responses. Documentary-based drought series are also considered from the viewpoint of spatio-temporal variability for certain continents, and their employment together with hydroclimate reconstructions from other proxies (in particular tree rings) is discussed. Finally, conclusions are drawn, and challenges for the future use of documentary evidence in the study of droughts are presented.

scholarly journals Fluorescence Fluctuation Spectroscopy enables quantification of potassium channel subunit dynamics and stoichiometry

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Giulia Tedeschi ◽  
Lorenzo Scipioni ◽  
Maria Papanikolaou ◽  
Geoffrey W. Abbott ◽  
Michelle A. Digman
Keyword(s):  
Plasma Membrane ◽  
Protein Diffusion ◽  
Ion Diffusion ◽  
Fluorescence Fluctuation Spectroscopy ◽  
Biophysical Characterization ◽  
Kv Channels ◽  
Subunit Stoichiometry ◽  
Spatio Temporal ◽  
Voltage Sensing Domain

AbstractVoltage-gated potassium (Kv) channels are a family of membrane proteins that facilitate K+ ion diffusion across the plasma membrane, regulating both resting and action potentials. Kv channels comprise four pore-forming α subunits, each with a voltage sensing domain, and they are regulated by interaction with β subunits such as those belonging to the KCNE family. Here we conducted a comprehensive biophysical characterization of stoichiometry and protein diffusion across the plasma membrane of the epithelial KCNQ1-KCNE2 complex, combining total internal reflection fluorescence (TIRF) microscopy and a series of complementary Fluorescence Fluctuation Spectroscopy (FFS) techniques. Using this approach, we found that KCNQ1-KCNE2 has a predominant 4:4 stoichiometry, while non-bound KCNE2 subunits are mostly present as dimers in the plasma membrane. At the same time, we identified unique spatio-temporal diffusion modalities and nano-environment organization for each channel subunit. These findings improve our understanding of KCNQ1-KCNE2 channel function and suggest strategies for elucidating the subunit stoichiometry and forces directing localization and diffusion of ion channel complexes in general.

SPATIO-TEMPORAL CHARACTERIZATION of litter at a touristic sandy beach in south Brazil

2021 ◽  
pp. 116927
Author(s):  
Bruna de Ramos ◽  
Melanie Vianna Alencar ◽  
Fábio Lameiro Rodrigues ◽  
Ana Luzia de Figueiredo Lacerda ◽  
Maíra Carneiro Proietti
Keyword(s):  
Sandy Beach ◽  
Spatio Temporal ◽  
South Brazil

scholarly journals A data acquisition setup for data driven acoustic design

2021 ◽  
pp. 1351010X2098690
Author(s):  
Romana Rust ◽  
Achilleas Xydis ◽  
Kurt Heutschi ◽  
Nathanael Perraudin ◽  
Gonzalo Casas ◽  
...  
Keyword(s):  
Data Acquisition ◽  
Interdisciplinary Approach ◽  
Computational Design ◽  
Surface Structures ◽  
Future Research ◽  
Data Set ◽  
Process Measures ◽  
First Results ◽  
Spatio Temporal ◽  
Automated Data Acquisition

In this paper, we present a novel interdisciplinary approach to study the relationship between diffusive surface structures and their acoustic performance. Using computational design, surface structures are iteratively generated and 3D printed at 1:10 model scale. They originate from different fabrication typologies and are designed to have acoustic diffusion and absorption effects. An automated robotic process measures the impulse responses of these surfaces by positioning a microphone and a speaker at multiple locations. The collected data serves two purposes: first, as an exploratory catalogue of different spatio-temporal-acoustic scenarios and second, as data set for predicting the acoustic response of digitally designed surface geometries using machine learning. In this paper, we present the automated data acquisition setup, the data processing and the computational generation of diffusive surface structures. We describe first results of comparative studies of measured surface panels and conclude with steps of future research.

App2Vec: Context-Aware Application Usage Prediction

2021 ◽  
Vol 15 (6) ◽  
pp. 1-21
Author(s):  
Huandong Wang ◽  
Yong Li ◽  
Mu Du ◽  
Zhenhui Li ◽  
Depeng Jin
Keyword(s):  
Dirichlet Process ◽  
Service Providers ◽  
State Of The Art ◽  
Representation Learning ◽  
Context Aware ◽  
Challenging Problem ◽  
Performance Gap ◽  
Bayesian Mixture Model ◽  
Bayesian Mixture ◽  
Spatio Temporal

Both app developers and service providers have strong motivations to understand when and where certain apps are used by users. However, it has been a challenging problem due to the highly skewed and noisy app usage data. Moreover, apps are regarded as independent items in existing studies, which fail to capture the hidden semantics in app usage traces. In this article, we propose App2Vec, a powerful representation learning model to learn the semantic embedding of apps with the consideration of spatio-temporal context. Based on the obtained semantic embeddings, we develop a probabilistic model based on the Bayesian mixture model and Dirichlet process to capture when , where , and what semantics of apps are used to predict the future usage. We evaluate our model using two different app usage datasets, which involve over 1.7 million users and 2,000+ apps. Evaluation results show that our proposed App2Vec algorithm outperforms the state-of-the-art algorithms in app usage prediction with a performance gap of over 17.0%.

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