Proposal for an International Molybdenum Isotope Measurement Standard and Data Representation

Molybdenum isotopes are increasingly widely applied in Earth Sciences. They are primarily used to investigate the oxygenation of Earth's ocean and atmosphere. However, more and more fields of application are being developed, such as magmatic and hydrothermal processes, planetary sciences or the tracking of environmental pollution. Here, we present a proposal for a unifying presentation of Mo isotope ratios in the studies of mass-dependent isotope fractionation. We suggest that the δ98/95Mo of the NIST SRM 3134 be defined as +0.25‰. The rationale is that the vast majority of published data are presented relative to reference materials that are similar, but not identical, and that are all slightly lighter than NIST SRM 3134. Our proposed data presentation allows a direct first-order comparison of almost all old data with future work while referring to an international measurement standard. In particular, canonical δ98/95Mo values such as +2.3‰ for seawater and −0.7‰ for marine Fe–Mn precipitates can be kept for discussion. As recent publications show that the ocean molybdenum isotope signature is homogeneous, the IAPSO ocean water standard or any other open ocean water sample is suggested as a secondary measurement standard, with a defined δ98/95Mo value of +2.34 ± 0.10‰ (2s). Les isotopes du molybdène (Mo) sont de plus en plus largement utilisés dans les sciences de la Terre. Ils sont principalement utilisés pour étudier l'oxygénation de l'océan et de l'atmosphère de la Terre. Cependant, de plus en plus de domaines d'application sont en cours de développement, tels que ceux concernant les processus magmatiques et hydrothermaux, les sciences planétaires ou encore le suivi de la pollution environnementale. Ici, nous présentons une proposition de présentation unifiée des rapports isotopiques du Mo dans les études du fractionnement isotopique dépendant de la masse. Nous suggérons que le δ98/95Mo du NIST SRM 3134 soit définit comme étant égal à +0.25 ‰. La raison est que la grande majorité des données publiées sont présentés par rapport à des matériaux de référence qui sont similaires, mais pas identiques, et qui sont tous légèrement plus léger que le NIST SRM 3134. Notre proposition de présentation des données permet une comparaison directe au premier ordre de presque toutes les anciennes données avec les travaux futurs en se référant à un standard international. En particulier, les valeurs canoniques du δ98/95Mo comme celle de +2,3 ‰ pour l'eau de mer et de -0,7 ‰ pour les précipités de Fe-Mn marins peuvent être conservés pour la discussion. Comme les publications récentes montrent que la signature isotopique moyenne du molybdène de l'océan est homogène, le standard de l'eau océanique IAPSO ou tout autre échantillon d'eau provenant de l'océan ouvert sont proposé comme standards secondaires, avec une valeur définie du δ98/95 Mo de 2.34 ± 0.10 ‰ (2s).

Combining Wireless Sensor Networks and Machine Learning for Flash Flood Nowcasting

This paper addresses an investigation with machine learning (ML) classification techniques to assist in the problem of flash flood now casting. We have been attempting to build a Wireless Sensor Network (WSN) to collect measurements from a river located in an urban area. The machine learning classification methods were investigated with the aim of allowing flash flood now casting, which in turn allows the WSN to give alerts to the local population. We have evaluated several types of ML taking account of the different now casting stages (i.e. Number of future time steps to forecast). We have also evaluated different data representation to be used as input of the ML techniques. The results show that different data representation can lead to results significantly better for different stages of now casting.

The importance of ship log data: reconstructing North Atlantic, European and Mediterranean sea level pressure fields back to 1750

Local to regional climate anomalies are to a large extent determined by the state of the atmospheric circulation. The knowledge of large-scale sea level pressure (SLP) variations in former times is therefore crucial when addressing past climate changes across Europe and the Mediterranean. However, currently available SLP reconstructions lack data from the ocean, particularly in the pre-1850 period. Here we present a new statistically-derived 5° × 5° resolved gridded seasonal SLP dataset covering the eastern North Atlantic, Europe and the Mediterranean area (40°W–50°E; 20°N–70°N) back to 1750 using terrestrial instrumental pressure series and marine wind information from ship logbooks. For the period 1750–1850, the new SLP reconstruction provides a more accurate representation of the strength of the winter westerlies as well as the location and variability of the Azores High than currently available multiproxy pressure field reconstructions. These findings strongly support the potential of ship logbooks as an important source to determine past circulation variations especially for the pre-1850 period. This new dataset can be further used for dynamical studies relating large-scale atmospheric circulation to temperature and precipitation variability over the Mediterranean and Eurasia, for the comparison with outputs from GCMs as well as for detection and attribution studies.

Statistical analysis of multichannel scalp field data

High density spatial and temporal sampling of EEG data enhances the quality of results of electrophysiological experiments. Because EEG sources typically produce widespread electric fields (see Chapter 3) and operate at frequencies well below the sampling rate, increasing the number of electrodes and time samples will not necessarily increase the number of observed processes, but mainly increase the accuracy of the representation of these processes. This is namely the case when inverse solutions are computed. As a consequence, increasing the sampling in space and time increases the redundancy of the data (in space, because electrodes are correlated due to volume conduction, and time, because neighboring time points are correlated), while the degrees of freedom of the data change only little. This has to be taken into account when statistical inferences are to be made from the data. However, in many ERP studies, the intrinsic correlation structure of the data has been disregarded. Often, some electrodes or groups of electrodes are a priori selected as the analysis entity and considered as repeated (within subject) measures that are analyzed using standard univariate statistics. The increased spatial resolution obtained with more electrodes is thus poorly represented by the resulting statistics. In addition, the assumptions made (e.g. in terms of what constitutes a repeated measure) are not supported by what we know about the properties of EEG data. From the point of view of physics (see Chapter 3), the natural “atomic” analysis entity of EEG and ERP data is the scalp electric field

An analysis of variance type method to describe and compare steady states in clinical data

Identifying and comparing different steady states is an important task for clinical decision making. Data from unequal sources, comprising diverse patient status information, have to be interpreted. In order to compare results an expressive representation is the key. In this contribution we suggest a criterion to calculate a context-sensitive value based on variance analysis and discuss its advantages and limitations referring to a clinical data example obtained during anesthesia. Different drug plasma target levels of the anesthetic propofol were preset to reach and maintain clinically desirable steady state conditions with target controlled infusion (TCI). At the same time systolic blood pressure was monitored, depth of anesthesia was recorded using the bispectral index (BIS) and propofol plasma concentrations were determined in venous blood samples. The presented analysis of variance (ANOVA) is used to quantify how accurately steady states can be monitored and compared using the three methods of measurement.

Preservation and representation of human bones and it's importance for anthropological Analysis - an introduction

This paper presents problems arising from the lack of standardized methods for recording skeletal remains. Using practical examples it is shown how preservation and representation of bones can distort observations and how this can be reduced by systematic data acquisition.

A Concept of Semantics Extraction from Web Data by Induction of Fuzzy Ontologies

Traditionally, ontologies describe knowledge representation in a denotational, formalized, and deductive way. In addition, in this paper, we propose a semiotic, inductive, and approximate approach to ontology creation. We define a conceptual framework, a semantics extraction algorithm, and a first proof of concept applying the algorithm to a small set of Wikipedia documents. Intended as an extension to the prevailing top-down ontologies, we introduce an inductive fuzzy grassroots ontology, which organizes itself organically from existing natural language Web content. Using inductive and approximate reasoning to reflect the natural way in which knowledge is processed, the ontology’s bottom-up build process creates emergent semantics learned from the Web. By this means, the ontology acts as a hub for computing with words described in natural language. For Web users, the structural semantics are visualized as inductive fuzzy cognitive maps, allowing an initial form of intelligence amplification. Eventually, we present an implementation of our inductive fuzzy grassroots ontology Thus,this paper contributes an algorithm for the extraction of fuzzy grassroots ontologies from Web data by inductive fuzzy classification.

Sparse representation based action and gesture recognition

In this paper we present a solution to the problem of action and gesture recognition using sparse representations. The dictionary is modelled as a simple concatenation of features computed for each action or gesture class from the training data, and test data is classified by finding sparse representation of the test video features over this dictionary. Our method does not impose any explicit training procedure on the dictionary. We experiment our model with two kinds of features, by projecting (i) Gait Energy Images (GEIs) and (ii) Motion-descriptors, to a lower dimension using Random projection. Experiments have shown 100% recognition rate on standard datasets and are compared to the results obtained with widely used SVM classifier.

Volcanic forcing for climate modeling: a new microphysics-based data set covering years 1600–present

As the understanding and representation of the impacts of volcanic eruptions on climate have improved in the last decades, uncertainties in the stratospheric aerosol forcing from large eruptions are now linked not only to visible optical depth estimates on a global scale but also to details on the size, latitude and altitude distributions of the stratospheric aerosols. Based on our understanding of these uncertainties, we propose a new model-based approach to generating a volcanic forcing for general circulation model (GCM) and chemistry–climate model (CCM) simulations. This new volcanic forcing, covering the 1600–present period, uses an aerosol microphysical model to provide a realistic, physically consistent treatment of the stratospheric sulfate aerosols. Twenty-six eruptions were modeled individually using the latest available ice cores aerosol mass estimates and historical data on the latitude and date of eruptions. The evolution of aerosol spatial and size distribution after the sulfur dioxide discharge are hence characterized for each volcanic eruption. Large variations are seen in hemispheric partitioning and size distributions in relation to location/date of eruptions and injected SO2 masses. Results for recent eruptions show reasonable agreement with observations. By providing these new estimates of spatial distributions of shortwave and long-wave radiative perturbations, this volcanic forcing may help to better constrain the climate model responses to volcanic eruptions in the 1600–present period. The final data set consists of 3-D values (with constant longitude) of spectrally resolved extinction coefficients, single scattering albedos and asymmetry factors calculated for different wavelength bands upon request. Surface area densities for heterogeneous chemistry are also provided.

Mind the gap: Do proportional electoral systems foster a more equal representation of women and men, poor and rich?

Female gender and low income are two markers for groups that have been historically disadvantaged within most societies. The study explores two research questions related to their political representation: (1) ‘Are parties biased towards the ideological preferences of male and rich citizens?’; and (2) ‘Does the proportionality of the electoral system moderate the degree of under-representation of women and poor citizens in the party system?’ A multilevel analysis of survey data from 24 parliamentary democracies indicates that there is some bias against those with low income and, at a much smaller rate, women. This has systemic consequences for the quality of representation, as the preferences of the complementary groups differ. The proportionality of the electoral system influences the degree of under-representation: specifically, larger district magnitudes help in closing the considerable gap between rich and poor.

More Money, Fewer Problems? Cross-Level Effects of Economic Deprivation on Political Representation

While equal political representation of all citizens is a fundamental democratic goal, it is hampered empirically in a multitude of ways. This study examines how the societal level of economic inequality affects the representation of relatively poor citizens by parties and governments. Using CSES survey data for citizens’ policy preferences and expert placements of political parties, empirical evidence is found that in economically more unequal societies, the party system represents the preferences of relatively poor citizens worse than in more equal societies. This moderating effect of economic equality is also found for policy congruence between citizens and governments, albeit slightly less clear-cut.

Knowledge representation through graphs

Due to the increasing amount of data, knowledge aggregation, representation and reasoning are highly important for companies. In this paper, knowledge aggregation is presented as the first step. In the sequel, successful knowledge representation, for instance through graphs, enables knowledge-based reasoning. There exist various forms of knowledge representation through graphs; some of which allow to handle uncertainty and imprecision by invoking the technology of fuzzy sets. The paper provides an overview of different types of graphs stressing their relationships and their essential features.

Loyal to the Game? Strategic Policy Representation in Mixed Electoral Systems

In Germany's compensatory mixed electoral system, alternative electoral routes lead into parliament. We study the relationship between candidates' electoral situations across both tiers and policy representation, fully accounting for candidate, party and district preferences in a multi-actor constellation and the exact electoral incentives for candidates to represent either the party or the district. The results (2009 Bundestag election data) yield evidence of an interactive effect of closeness of the district race and list safety on candidates' positioning between their party and constituency.