An analysis method for time ordered data processing of Dark Matter experiments

The analysis of the time ordered data of Dark Matter experiments is becoming more and more challenging with the increase of sensitivity in the ongoing and forthcoming projects. Combined with the well-known level of background events, this leads to a rather high level of pile-up in the data. Ionization, scintillation as well as bolometric signals present common features in their acquisition timeline: low frequency baselines, random gaussian noise, parasitic noise and signal characterized by well-defined peaks. In particular, in the case of long-lasting signals such as bolometric ones, the pile-up of events may lead to an inaccurate reconstruction of the physical signal (misidentification as well as fake events). We present a general method to detect and extract signals in noisy data with a high pile-up rate and qe show that events from few keV to hundreds of keV can be reconstructed in time ordered data presenting a high pile-up rate. This method is based on an iterative detection and fitting procedure combined with prior wavelet-based denoising of the data and baseline subtraction. {We have tested this method on simulated data of the MACHe3 prototype experiment and shown that the iterative fitting procedure allows us to recover the lowest energy events, of the order of a few keV, in the presence of background signals from a few to hundreds of keV. Finally we applied this method to the recent MACHe3 data to successfully measure the spectrum of conversion electrons from Co57 source and also the spectrum of the background cosmic muons

Reflexion M\"ossbauer analysis of the in situ oxidation products hydroxycarbonate green rust

The purpose of this study is to determine the nature of the oxidation products of FeII-III hydroxycarbonate FeII4FeIII2(OH)12CO3~3H2O (green rust GR(CO32-)) by using the miniaturised M\"ossbauer spectrometer MIMOS II. Two M\"ossbauer measurements methods are used: method (i) with green rust pastes coated with glycerol and spread into Plexiglas sample holders, and method (ii) with green rust pastes in the same sample holders but introduced into a gas-tight cell with a beryllium window under a continuous nitrogen flow. Method (ii) allows us to follow the continuous deprotonation of GR(CO32-) into the fully ferric deprotonated form FeIII6O4(OH)8CO3~3H2O by adding the correct amount of H2O2, without any further oxidation or degradation of the samples

Estimation of the oceanic pCO₂ in the North Atlantic from VOS lines in-situ measurements: parameters needed to generate seasonally mean maps

Automated instruments on board Volunteer Observing Ships (VOS) have provided high-frequency pCO₂ measurements over basin-wide regions for a decade or so. In order to estimate regional air-sea CO₂ fluxes, it is necessary to interpolate between in-situ measurements to obtain maps of the marine pCO₂. Such an interpolation remains, however, a difficult task because VOS lines are too distant from each other to capture the high pCO₂ variability. Relevant physical parameters available at large scale are thus necessary to serve as a guide to estimate the pCO₂ values between the VOS lines. Satellites do not measure pCO₂ but they give access to parameters related to the processes that control its variability, such as sea surface temperature (SST). In this paper we developed a method to compute pCO₂ maps using satellite data (SST and CHL, the chlorophyll concentration), combined with a climatology of the mixed-layer depth (MLD). Using 15 401 measurements of surface pCO₂ acquired in the North Atlantic between UK and Jamaica, between June 1994 and August 1995, we show that the parameterization of pCO₂ as a function of SST, CHL and MLD yields more realistic pCO₂ values than parameterizations that have been widely used in the past, based on SST, latitude, longitude or SST only. This parameterization was then used to generate seasonal maps of pCO₂ over the North Atlantic. Results show that our approach yields the best marine pCO₂ estimates, both in terms of absolute accuracy, when compared with an independent data set, and of geographical patterns, when compared to the climatology of Takahashi et al. (2002). This suggests that monitoring the seasonal variability of pCO₂ over basin-wide regions is possible, provided that sufficient VOS lines are available

Experiences of aiding autobiographical memory using the sensecam

Human memory is a dynamic system that makes accessible certain memories of events based on a hierarchy of information, arguably driven by personal significance. Not all events are remembered, but those that are tend to be more psychologically relevant. In contrast, lifelogging is the process of automatically recording aspects of one's life in digital form without loss of information. In this article we share our experiences in designing computer-based solutions to assist people review their visual lifelogs and address this contrast. The technical basis for our work is automatically segmenting visual lifelogs into events, allowing event similarity and event importance to be computed, ideas that are motivated by cognitive science considerations of how human memory works and can be assisted. Our work has been based on visual lifelogs gathered by dozens of people, some of them with collections spanning multiple years. In this review article we summarize a series of studies that have led to the development of a browser that is based on human memory systems and discuss the inherent tension in storing large amounts of data but making the most relevant material the most accessible

X-ray Crystallographic Characterization of the Co(II)-substituted Tris-bound Form of the Aminopeptidase from \u3cem\u3eAeromonas proteolytica\u3c/em\u3e

The X-ray crystal structure of the Co(II)-loaded form of the aminopeptidase from Aeromonas proteolytica ([CoCo(AAP)]) was solved to 2.2 Å resolution. [CoCo(AAP)] folds into an α/β globular domain with a twisted β-sheet hydrophobic core sandwiched between α-helices, identical to [ZnZn(AAP)]. Co(II) binding to AAP does not introduce any major conformational changes to the overall protein structure and the amino acid residues ligated to the dicobalt(II) cluster in [CoCo(AAP)] are the same as those in the native Zn(II)-loaded structure with only minor perturbations in bond lengths. The Co(II)–Co(II) distance is 3.3 Å. Tris(hydroxymethyl)aminomethane (Tris) coordinates to the dinuclear Co(II) active site of AAP with one of the Tris hydroxyl oxygen atoms (O4) forming a single oxygen atom bridge between the two Co(II) ions. This is the only Tris atom coordinated to the metals with Co1–O and Co2–O bonds distances of 2.2 and 1.9 Å, respectively. Each of the Co(II) ions resides in a distorted trigonal bipyramidal geometry. This important structure bridges the gap between previous structural and spectroscopic studies performed on AAP and is discussed in this context

MACHe3, a prototype for non-baryonic dark matter search: KeV event detection and multicell correlation

Superfluid He3 at ultra-low temperatures (100 microKelvins) is a sensitive medium for the bolometric detection of particles. MACHe3 (MAtrix of Cells of Helium 3) is a project for non-baryonic dark matter search using He3 as a sensitive medium. Simulations made on a high granularity detector show a very good rejection to background signals. A multicell prototype including 3 bolometers has been developed to allow correlations between the cells for background event discrimination. One of the cells contains a low activity Co57 source providing conversion electrons of 7.3 and 13.6 keV to confirm the detection of low energy events. First results on the multicell prototype are presented. A detection threshold of 1 keV has been achieved. The detection of low energy conversion electrons coming from the Co57 source is highlighted as well as the cosmic muon spectrum measurement. The possibility to reject background events by using the correlation among the cells is demonstrated from the simultaneous detection of muons in different cells

Modelling soil dynamics and the effect of nitrogen levels on potato yield function

Non-Peer ReviewedCrop yield is maximized when optimal levels of nutrients, water, and other inputs are available to the crop and the influence of disease and weeds has been minimized. While each crop has differing responses to nutrient availability, modelling soil dynamics and the effect of nitrogen levels on potato yield is very important. The objective of this study was to model several environmental components of potato yield function including soil characteristics and organic matter content, soil nitrogen, temperature component, moisture component, solum and nitrogen mineralization, nitrogen fertilizer, and nitrogen sufficiency. The interaction of these components with moisture availability and nitrogen sufficiency was shown to impact potato yield