River inflow and salinity changes in the Caspian Sea during the last 5500 years

Pollen, spores and dinoflagellate cysts have been analysed on three sediment cores (1.8–1.4 m-long) taken from the south and middle basins of the Caspian Sea. A chronology available for one of the cores is based on calibrated radiocarbon dates (ca 5.5–0.8 cal. ka BP). The pollen and spores assemblages indicate fluctuations between steppe and desert. In addition there are some outstanding zones with a bias introduced by strong river inflow. The dinocyst assemblages change between slightly brackish (abundance of Pyxidinopsis psilata and Spiniferites cruciformis) and more brackish (dominance of Impagidinium caspienense) conditions. During the second part of the Holocene, important flow modifications of the Uzboy River and the Volga River as well as salinity changes of the Caspian Sea, causing sea-level fluctuations, have been reconstructed. A major change is suggested at ca 4 cal. ka BP with the end of a high level phase in the south basin. Amongst other hypotheses, this could be caused by the end of a late and abundant flow of the Uzboy River (now defunct), carrying to the Caspian Sea either meltwater from higher latitudes or water from the Amu-Daria. A similar, later clear phase of water inflow has also been observed from 2.1 to 1.7 cal. ka BP in the south basin and probably also in the north of the middle basin

Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support

<p>Abstract</p> <p>Background</p> <p>Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved.</p> <p>Method</p> <p>This paper introduces a new hybrid methodology <it>Expert-based Cooperative Analysis </it>(EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by <it>EbCA-Data Envelopment Analysis (EbCA-DEA)</it>, and 2) Case-mix of schizophrenia based on functional dependency using <it>Clustering Based on Rules (ClBR)</it>. In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases.</p> <p>Results</p> <p>EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here <it>Implicit Knowledg </it>-IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases.</p> <p>Discussion</p> <p>This paper presents EbCA and shows the convenience of completing classical data analysis with PEK as a mean to extract relevant knowledge in complex health domains. One of the major benefits of EbCA is iterative elicitation of IK.. Both explicit and tacit or implicit expert knowledge are critical to guide the scientific analysis of very complex decisional problems as those found in health system research.</p

Subtraction of temperature induced phase noise in the LISA frequency band

Temperature fluctuations are expected to be one of the limiting factors for gravitational wave detectors in the very low frequency range. Here we report the characterisation of this noise source in the LISA Pathfinder optical bench and propose a method to remove its contribution from the data. Our results show that temperature fluctuations are indeed limiting our measurement below one millihertz, and that their subtraction leads to a factor 5.6 (15 dB) reduction in the noise level at the lower end of the LISA measurement band 10^{-4} Hz, which increases to 20.2 (26 dB) at even lower frequencies, i.e., 1.5x10^{-5} Hz. The method presented here can be applied to the subtraction of other noise sources in gravitational wave detectors in the general situation where multiple sensors are used to characterise the noise source.Comment: 8 pages, 6 figure

Technical report: Optimization of the harvest stage for reducing cooking banana postharvest losses: a multi-criteria approach targeting matooke end-product.

This report presents results of RTB-ENDURE sub-output 1.3; ‘Determining appropriate harvest time for the cooking bananas with intrinsic long shelf-life using physical, chemical and sensory attributes’ of the cooking banana business case’s Output 1, entitled “Increased access of farmers to cooking banana varieties with preferred quality attributes and intrinsic long shelf life traits”. The worked aimed at reducing postharvest losses for cooking banana while modulating harvest stage for green life extension. The originality of this investigation was to evaluate the putative impact of fruit stage of harvest onto its potential storage life and eating quality. The optimal harvest stage was evaluated by coupling three antagonist parameters, namely fruit diameter, green life, and eating quality, to optimize harvest stage of the variety Kibuzi in specific edapho-climatic conditions of Rakai and Isingiro districts in southwestern Uganda. A temperature record was considered in both sites between flowering and harvest. The interval between flowering and harvest (IFH) of Kibuzi banana variety was used as a quantitative explanatory variable, and the site location (Rakai at 1270 masl vs Isingiro at 1440 masl) was used as a qualitative one. Since the sites were at different altitudes, two Tynitag temperature data loggers were installed to record temperatures. Fruits size, dry matter, fruit firmness, total soluble solids, titratable acidity and sensory attributes were recorded at four harvest stages: 112, 126, 138, 152 days and 111, 125, 137, 151 days after flowering. The evolution of three parameters; diameter of fruit, green life and overall acceptability of the end-product - Matooke - were simulated for 110 to 155 days range, leading to the identification of a range of optimal harvest ages for variety Kibuzi in Rakai at between 133 to 142 days and 133 to 150 days for Isingiro. The prediction of the optimal harvest stage will remain only valid for the two locations without taking into account thermal sum for establishing a strong relationship between fruit age in degree.days and green life. Given the respective altitudes at Rakai and Isingiro, it implies that the two edapho-climatic conditions were not so different in terms of on field temperature. With some more diverse thermal conditions in the experimental sites (lowland vs highland with at least 3°C needed between sites), the thermal sum concept will be even more precise for the prediction of the optimal harvest stage for bananas, regardless the location site (lowland, highland, with hot or cool local conditions). Such original multi-criteria approach (agro-morphological, physiological traits, and end-product sensory attributes) was relevant for the prediction of the optimal harvest stage, in order to reduce banana postharvest losses during transport and until Matooke preparation by end-users. Such innovative methodology can be applied to some other banana culinary recipes and end-uses

Ergodic and non-ergodic clustering of inertial particles

We compute the fractal dimension of clusters of inertial particles in mixing flows at finite values of Kubo (Ku) and Stokes (St) numbers, by a new series expansion in Ku. At small St, the theory includes clustering by Maxey's non-ergodic 'centrifuge' effect. In the limit of St to infinity and Ku to zero (so that Ku^2 St remains finite) it explains clustering in terms of ergodic 'multiplicative amplification'. In this limit, the theory is consistent with the asymptotic perturbation series in [Duncan et al., Phys. Rev. Lett. 95 (2005) 240602]. The new theory allows to analyse how the two clustering mechanisms compete at finite values of St and Ku. For particles suspended in two-dimensional random Gaussian incompressible flows, the theory yields excellent results for Ku < 0.2 for arbitrary values of St; the ergodic mechanism is found to contribute significantly unless St is very small. For higher values of Ku the new series is likely to require resummation. But numerical simulations show that for Ku ~ St ~ 1 too, ergodic 'multiplicative amplification' makes a substantial contribution to the observed clustering.Comment: 4 pages, 2 figure

Evolutionary computation and case-based reasoning interoperation in IEDSS through GESCONDA

Peer ReviewedPostprint (author’s final draft

Implementation of sub-nanosecond time-to-digital convertor in field-programmable gate array: applications to time-of-flight analysis in muon radiography

International audienceTime-of-flight (tof) techniques are standard techniques in high energy physics to determine particles propagation directions. Since particles velocities are generally close to c, the speed of light, and detectors typical dimensions at the meter level, the state-of-the-art tof techniques should reach sub-nanosecond timing resolution. Among the various techniques already available, the recently developed ring oscillator TDC ones, implemented in low cost FPGA, feature a very interesting figure of merit since a very good timing performance may be achieved with limited processing ressources. This issue is relevant for applications where unmanned sensors should have the lowest possible power consumption. Actually this article describes in details the application of this kind of tof technique to muon tomography of geological bodies. Muon tomography aims at measuring density variations and absolute densities through the detection of atmospheric muons flux's attenuation, due to the presence of matter. When the measured fluxes become very low, an identified source of noise comes from backwards propagating particles hitting the detector in a direction pointing to the geological body. The separation between through-going and backward-going particles, on the basis of the tof information is therefore a key parameter for the tomography analysis and subsequent previsions

Detection of Phase Jumps of Free Core Nutation of the Earth and their Concurrence with Geomagnetic Jerks

We detected phase jumps of the Free Core Nutation (FCN) of the Earth directly from the analysis of the Very Long Baseline Interferometer (VLBI) observation of the Earth rotation for the period 1984-2003 by applying the Weighted Wavelet Z-Transform (WWZ) method and the Short-time Periodogram with the Gabor function (SPG) method. During the period, the FCN had two significant phase jumps in 1992 and 1998. These epochs coincide with the reported occurrence of geomagnetic jerks.Comment: 8 pages, 4 figure