Miracle-dz/UniFAR-FTUs huggingface dataset:
Heterogeneous sulfate production in the remote marine environment: Cloud processing and sea‐salt particle contributions

Heterogeneous sulfate production in the remote marine boundary layer is studied by combining measurements collected during the first Southern Hemisphere marine Aerosol Characterization Experiment (ACE 1) with two numerical models: one simulating heterogeneous sulfate production in sea-salt aerosol water (SSAW) and the other simulating cloud processing. The models calculate oxidation of SO2 by O3 and H2O2 via aqueous-phase reactions both in SSAW and in cloud droplets. Model calculations indicate that as much as 50–75% of the observed non-sea-salt (NSS) sulfate in particles in the ambient diameter size range of 0.9–16 μm during the ACE 1 measurement period is due to production in SSAW, with cloud processing producing the remainder. The initial alkalinity of the wind-generated sea-salt aerosols can strongly influence sulfate production. Changing the effective alkalinity of SSAW from a value typical of seawater to a value based on the measurements taken at Cape Grim results in a better match to the observed NSS sulfate size distribution with up to 75% of the predicted supermicrometer NSS sulfate being due to heterogeneous conversion in SSAW. The average rates of removal of sulfate due to dry and wet deposition for the 0.4–16 μm size range are 38 and 14 ng m−3 d−1 respectively.
Numerical modelling of earthquake cycles based on Navier-Stokes equations with Viscoelastic-plasticity rheology

Visco-elastic-plastic modelling approaches for long-term tectonic deformation assume that co-seismic fault displacement can be integrated over 1,000s-10,000s years (tens of earthquake cycles) with the appropriate failure law, and that short-timescale fluctuations in the stress field due to individual earthquakes have no effect on long-term behavior. Models of the earthquake rupture process generally assume that the tectonic (long-range) stress field or kinematic boundary conditions are steady over the course of multiple earthquake cycles. In this study, we develop a numerical framework that embeds earthquake rupture dynamics into a long-term tectonic deformation model by adding inertial terms and using highly adaptive time-stepping that can capture deformation at plate-motion rates as well as individual earthquakes. We reproduce benchmarks at the earthquake timescale to demonstrate the effectiveness of our approach. We then discuss how these high-resolution models degrade if the time-step cannot capture the rupture process accurately and, from this, infer when it is important to consider coupling of the two timescales and the level of accuracy required. To build upon these benchmarks, we undertake a generic study of a thrust fault in the crust with a prescribed geometry. We find that lower crustal rheology affects the periodic time of characteristic earthquake cycles and the inter-seismic, free-surface deformation rate. In particular, the relaxation of the surface of a cratonic region (with a relatively strong lower crust) has a characteristic double-peaked uplift profile that persists for thousands of years after a major slip event. This pattern might be diagnostic of active faults in cratonic regions.
Relational concept analysis for circular link key extraction

for dissemination) A link key extraction procedure in case of circular dependencies is presented. It uses relational concept analysis and extends the procedure of Deliverable 1.1. This leads to investigate more closely the semantics of relational concept analysis which is given in terms of fixed points. Extracting all fixed points may offer more link key candidates to consider.
Water supply at Los Alamos during 1991

This report summarizes production and aquifer conditions for water wells in the Los Alamos, Guaje, and Pajarito Well Fields . The wells supply all of the potable water used for municipal and some industrial purposes in Los Alamos County and the Los Alamos National Laboratory. The spring gallery in Water Canyon supplies nonpotable water for industrial use while the rest of the nonpotable water supply used for irrigation is surface water from the Guaje and Los Alamos Reservoirs. Included is a section on the chemical and radiochemical quality of water from the supply wells, gallery in Water Canyon and the reservoirs in Guaje and Los Alamos Canyons. A section on the quality of water with reference to compliance with state and federal regulations is included in the report.
Enhanced ocean temperature forecast skills through 3‐D super‐ensemble multi‐model fusion

An innovative multi‐model fusion technique is proposed to improve short‐term ocean temperature forecasts: the three‐dimensional super‐ensemble. In this method, a Kalman Filter is used to adjust three‐dimensional model weights over a past learning period, allowing to give more importance to recent observations, and take into account spatially varying model skills. The predictive performance is evaluated against SST analyses, CTD casts and gliders tracks collected during the Ligurian Sea Cal/Val 2008 experiment. Statistical results not only show a very significant bias reduction of this multi‐model forecast in comparison with the individual models, their ensemble mean and a single‐weight‐per‐model version of the super‐ensemble, but also the improvement of other pattern‐related skills. In a 48‐h forecast experiment, and with respect to the ensemble mean, surface and subsurface root‐mean‐square differences with observations are reduced by 57% and 35% respectively, making this new technique a suitable non‐intrusive post‐processing method for multi‐model operational forecasting systems.
The Real Effects of Financial Constraints: Evidence from a Financial Crisis

We survey 1,050 CFOs in the U.S., Europe, and Asia to assess whether their firms are credit constrained during the global credit crisis of 2008. We study whether corporate spending plans differ conditional on this measure of financial constraint. Our evidence indicates that constrained firms planned deeper cuts in tech spending, employment, and capital spending. Constrained firms also burned through more cash, drew more heavily on lines of credit for fear banks would restrict access in the future, and sold more assets to fund their operations. We also find that the inability to borrow externally causes many firms to bypass attractive investment opportunities, with 86% of constrained U.S. CFOs saying their investment in attractive projects was restricted during the credit crisis of 2008. More than half of the respondents say they will cancel or postpone their planned investment. Our results also hold in Europe and Asia, and in many cases are stronger in those economies.
Understanding adult lifelong learning participation as a layered problem

ABSTRACT This paper discusses the layered nature of lifelong learning participation, bringing together fragmented insights in why adults do or do not participate in lifelong learning activities. The paper will discuss the roles and responsibilities of individual adults, education and training providers and countries’ social education policies, often labelled as the micro-, meso- and macro-level. The aim of this work is to add a new model to the knowledge base that attempts to integrate separate insights at the three different levels. Apart from discussing the relevance of the micro-, meso- and macro-level, together with a comprehensive model, the paper provides some recommendations for future research in the area of adult lifelong learning participation, such as the adoption of multilevel models, the need for more data linkage and the desire for more diversification of research in terms of geographical spread and types of educational activities adults can undertake.
CARIBIC aircraft measurements of Eyjafjallajökull volcanic clouds in April/May 2010

Abstract. The Civil Aircraft for the Regular Investigation of the Atmosphere Based on an Instrument Container (CARIBIC) project investigates physical and chemical processes in the Earth's atmosphere using a Lufthansa Airbus long-distance passenger aircraft. After the beginning of the explosive eruption of the Eyjafjallajokull volcano on Iceland on 14 April 2010, the first CARIBIC volcano-specific measurement flight was carried out over the Baltic Sea and Southern Sweden on 20 April. Two more flights followed: one over Ireland and the Irish Sea on 16 May and the other over the Norwegian Sea on 19 May 2010. During these three special mission flights the CARIBIC container proved its merits as a comprehensive flying laboratory. The elemental composition of particles collected over the Baltic Sea during the first flight (20 April) indicated the presence of volcanic ash. Over Northern Ireland and the Irish Sea (16 May), the DOAS system detected SO2 and BrO co-located with volcanic ash particles that increased the aerosol optical depth. Over the Norwegian Sea (19 May), the optical particle counter detected a strong increase of particles larger than 400 nm diameter in a region where ash clouds were predicted by aerosol dispersion models. Aerosol particle samples collected over the Irish Sea and the Norwegian Sea showed large relative enhancements of the elements silicon, iron, titanium and calcium. Non-methane hydrocarbon concentrations in whole air samples collected on 16 and 19 May 2010 showed a pattern of removal of several hydrocarbons that is typical for chlorine chemistry in the volcanic clouds. Comparisons of measured ash concentrations and simulations with the FLEXPART dispersion model demonstrate the difficulty of detailed volcanic ash dispersion modelling due to the large variability of the volcanic cloud sources, extent and patchiness as well as the thin ash layers formed in the volcanic clouds.
UPCommons Portal del coneixement obert de la UPC

Excitable lasers that mimic neuronal activity can be building blocks of ultra-fast neuro-inspired information processing systems, which can revolutionize the ﬁelds of optical signal processing, optical computing and artiﬁcial intelligence. To implement such photonic neurons, we must ﬁrst identify low-cost and energy-eﬃcient lasers whose excitable dynamics mimics neuronal dynamics. Here we conduct an experimental study of the dynamics of a diode laser with optical feedback from an external cavity. We focus on the response of the laser when is under weak periodic perturbations that are implemented via direct modulation of the laser pump current. We consider sinusoidal and pulsed waveforms. The dynamics of the laser intensity is compared with the dynamics of the membrane potential of a neuron, which is simulated with the FitzHugh-Nagumo (FHN) model. The analysis of the statistics of the time intervals between dropouts of the laser intensity (optical spikes) and of the time intervals between the neuron’s action potentials (or spikes) unveils similarities, and also diﬀerences. The analysis of the spike rate reveals a variation with the amplitude and with the frequency of the external signal that is similar for both, the laser and the FHN neuron. Therefore, in terms of the spike rate, the laser response to a weak periodic signal mimics the response of a FHN neuron, and thus diode lasers with optical feedback can be used to implement photonic neurons. A drawback of this implementation is the length of the feedback cavity, which prevents on-chip integration.
Automated error matching system using machine learning anddata clustering Evaluating unsupervised learningmethods for categorizing error types , capturing bugs , and detecting outliers

For large and complex software systems, it is a time-consuming process to manually inspect error logs produced from the test suites of such systems. Whether it is for identifying abnormal faults, or finding bugs; it is a process that limits development progress, and requires experience. An automated solution for such processes could potentially lead to efficient fault identification and bug reporting, while also enabling developers to spend more time on improving system functionality. Three unsupervised clustering algorithms are evaluated for the task, HDBSCAN, DBSCAN, and X-Means. In addition, HDBSCAN, DBSCAN and an LSTM-based autoencoder are evaluated for outlier detection. The dataset consists of error logs produced from a robotic test system. These logs are cleaned and pre-processed using stopword removal, stemming, term frequency-inverse document frequency (tf-idf) and singular value decomposition (SVD). Two domain experts are tasked with evaluating the results produced from clustering and outlier detection. Results indicate that X-Means outperform the other clustering algorithms when tasked with automatically categorizing error types, and capturing bugs. Furthermore, none of the outlier detection methods yielded sufficient results. However, it was found that X-Means’s clusters with a size of one data point yielded an accurate representation of outliers occurring in the error log dataset. Conclusively, the domain experts deemed X-means to be a helpful tool for categorizing error types, capturing bugs, and detecting outliers.
University of Birmingham Hemispheric asymmetry of globus pallidus relates to alpha modulation in reward-related attentional tasks

•Users may freely distribute the URL that is used to identify this publication. •Users may download and/or print one copy of the publication from the University of Birmingham research portal for the purpose of private study or non-commercial research. •User may use extracts from the document in line with the concept of ‘fair dealing’ under the Copyright, Designs and Patents Act 1988 (? ) •Users may not further distribute the material nor use it for the purposes of commercial gain.
Evidence for positive selection in the superoxide dismutase (Sod) region of Drosophila

DNA sequence variation in a 1410-bp region including the Cu,Zn Sod locus was examined in 41 homozygous lines of Drosophila melanogaster. Fourteen lines were from Barcelona, Spain, 25 were from California populations and the other two were from laboratory stocks. Two common electromorphs, SODS and SODF, are segregating in the populations. Our sample of 41 lines included 19 SodS and 22 SodF alleles (henceforward referred to as Slow and Fast alleles). All 19 Slow alleles were identical in sequence. Of the 22 Fast alleles sequenced, nine were identical in sequence and are referred to as the Fast A haplotypes. The Slow allele sequence differed from the Fast A haplotype at a single nucleotide site, the site that accounts for the amino acid difference between SODS and SODF. There were nine other haplotypes among the remaining 13 Fast alleles sequenced. The overall level of nucleotide diversity ( P) in this sample is not greatly different than that found at other loci in D. melanogaster. It is concluded that the Slow/Fast polymorphism is a recently arisen polymorphism, not an old balanced polymorphism. The large group of nearly identical haplotypes suggests that a recent mutation, at the Sod locus or tightly linked to it, has increased rapidly in frequency to around 5096, both in California and Spain. The application of a new statistical test demonstrates that the occurrence of such large numbers of haplotypes with so little variation among them is very unlikely under the usual equilibrium neutral model. We suggest that the high frequency of some haplotypes is due to natural selection at the Sod locus or at a tightly linked locus.
Geospatial modelling of metocean and environmental ancillary data for the oil spill probability assessment in SAR images

The confidence level of oil spill detections in satellite Synthetic Aperture Radar (SAR) imagery requires the analysis of many different factors. Unfortunately, oil slicks are not the only phenomena which can appear as a dark feature in a SAR image. These include a number of parameters like wind speed, currents, internal waves, upwelling sea areas, algae bloom, mixing water areas, et cetera. These phenomena are called look-alikes. The largest challenge in detecting oil spills in SAR images remains in the accurate discrimination between oil spills and look-alikes. This study introduces the vantages of using geospatial analysis of various metocean data (e.g. wind speed and direction, sea surface temperature, wave direction, ocean colour data) and environmental ancillary data (e.g. vessel traffic, port locations) as a supplementary information source for the oil spill probability assessment in SAR imagery. The analysed data exists in different formats with different value scales. In addition, the parameters of the metocean data analysis are not equally important for a reliability of oil spill detection. The weight of metocean parameters depends on the impact of natural phenomena on SAR systems (e.g. wind and currents have pro rata more influence on the probability than sea surface temperature and chlorophyll-a) and the area of interest (e.g. chlorophyll-a is a more important value for the Baltic Sea than for the Mediterranean Sea). The derived oil spill probability categorisation based on the weighted analysis of metocean environmental ancillary data could be a useful tool for authorities for an efficient planning of cost-intensive verification flights.
Seasonality of vegetation fires in Africa from remote sensing data and application to a global chemistry model

This paper sets out to show the potential use of remote sensing of active vegetation fires for continental- to global-scale modeling of biomass burning studies. It focuses on the analysis of the seasonality of vegetation fires for the African continent, as derived from NOAA-AVHRR-GAC-5km satellite data. These data are ideally suited for savanna fires, which constitute between 60 and 80% of the biomass burnt in Africa. Monthly counts of fire pixels, within 1° latitude × 1° longitude grid cells, over continental Africa have been calculated from November 1984 through October 1989. These 1° grid cells are summated to a 5° × 5° grid to enable comparison with previous studies and are analyzed at this resolution to show various features of the fire season. The analysis shows that previous attempts to characterize the seasonality of biomass burning have tended to underestimate the intensity of the peak months of burning or have predicted too long a fire season in certain areas. It also shows that there can be, for a given area, a temporal shift in the timing of the fire season from year to year. Such an interannual variability of fire seasonality makes satellite data more appropriate than statistical data for the modeling of atmospheric transport of vegetation fire products and the comparison with experimental measurements. Modeled values of black carbon mass concentration from a global transport model (MOGUNTIA), using the seasonality of biomass burning as an independent variable, are compared with measurements taken at Amsterdam Island (38°30′S, 77°30′E) and Lamto, Ivory Coast (6°N, 5°W). Although 5-year averaged satellite data were used, the seasonality as derived from satellite data determined in this paper gives modeled values of black carbon mass concentration that are in good agreement with the measurements.
Investigation of Data Quality Assurance across IoT Protocol Stack for V2I Interactions

Networking protocols have undergone significant developments and adaptations to cater for unique communication needs within the IoT paradigm. However, meeting these requirements in the context of vehicle-to-infrastructure (V2I) communications becomes a multidimensional problem due to factors like high mobility, intermittent connectivity, rapidly changing topologies, and an increased number of nodes. Thus, examining these protocols based on their characteristics and comparative analyses from the literature has shown that there is still room for improvement, particularly in ensuring efficiency in V2I interactions. This study aims to investigate the most viable network protocols for V2I communications, focusing on ensuring data quality (DQ) across the first three layers of the IoT protocol stack. This presents an improved understanding of the performance of network protocols in V2I communication. The findings of this paper showed that although each protocol offers unique strengths when evaluated against the identified dimensions of DQ, a cross-layer protocol fusion may be necessary to meet specific DQ dimensions. With the complexities and specific demands of V2I communications, it’s clear that no single protocol from our tri-layered perspective can solely fulfil all IP-based communication requirements given that the V2I communication landscape is teeming with heterogeneity, where a mixture of protocols is required to address unique communication demands.
Tolkningsbara ämnesmodeller baserade på ankarord

Topic models are useful tools for exploring large data sets of textual content by exposing a generative process from which the text was produced. Anchor-based topic models utilize a separability assumption, known as the anchor word assumption, to define a set of algorithms with provable guarantees which recover the underlying topics with a run time practically independent of corpus size. Each topic is assumed to contain a word which rarely occurs in other topics, know as the topic’s anchor word. A number of extensions to the initial algorithms, and enhancements made to tangential models, have been proposed which improve the intrinsic characteristics of the model making them more interpretable by humans. This thesis evaluates improvements to human interpretability due to: low-dimensional word embeddings in combination with a regularized objective function, automatic topic merging through anchor words, and utilizing word embeddings to synthetically increase corpus density. The aim is to find an anchor-based topic modeling approach which produces human interpretable results. Results show that anchor words are viable vehicles for automatic topic merging, and that using word embeddings significantly improves the original anchor method across all measured metrics. Combining lowdimensional embeddings and a regularized objective results in computational downsides with small or no improvements to the metrics measured.
Changes in composition and activity of soil microbial communities in peach and kiwifruit Mediterranean orchards under an innovative management system

The aim of this work was to evaluate the effects of 2 soil management systems, so called ‘innovative’ (INN) and ‘conventional’ (CON), on genetic and metabolic diversity of soil microbial communities of peach and kiwifruit orchards. INN system included minimum tillage, organic matter inputs from compost and cover crops, winter pruning, and adequate irrigation and fertilisation. CON system was characterised by conventional tillage, zero organic input, empirical pruning, strong chemical fertilisation, and excessive irrigation. After 4 years of treatments, soil samples were collected in different orchard sites. In peach and kiwifruit INN orchards, average fruit yields were significantly higher than in CON. INN orchards had a significantly higher total number of bacteria. The patterns of denaturing gradient gel electrophoresis of bacterial 16S rDNA/RNA from peach orchard showed differences between soils under drip emitters and along the inter-rows, whereas those from kiwifruit orchard clearly distinguished between INN and CON for both bacteria (16S rRNA) and fungi (18S rDNA/RNA). Shannon’s substrate diversity index, evaluated by Biolog® metabolic assay, was affected by soil treatment in peach orchard and by soil depth in kiwifruit orchard. Principal component analysis of Biolog® values clearly discriminated INN and CON soils of both orchards. The results revealed qualitative and quantitative changes of soil microbial communities in response to an innovative and sustainable soil management.