Detection of ice core particles via deep neural networks

Insoluble particles in ice cores record signatures of past climate parameters like vegetation, volcanic activity or aridity. Their analytical detection depends on intensive bench microscopy investigation and requires dedicated sample preparation steps. Both are laborious, require in-depth knowledge and often restrict sampling strategies. To help overcome these limitations, we present a framework based on Flow Imaging Microscopy coupled to a deep neural network for autonomous image classification of ice core particles. We train the network to classify 7 commonly found classes: mineral dust, felsic and basaltic volcanic ash (tephra), three species of pollen (Corylus avellana, Quercus robur, Quercus suber) and contamination particles that may be introduced onto the ice core surface during core handling operations. The trained network achieves 96.8 % classification accuracy at test time. We present the system’s potentials and limitations with respect to the detection of mineral dust, pollen grains and tephra shards, using both controlled materials and real ice core samples. The methodology requires little sample material, is non destructive, fully reproducible and does not require any sample preparation step. The presented framework can bolster research in the field, by cutting down processing time, supporting human-operated microscopy and further unlocking the paleoclimate potential of ice core records by providing the opportunity to identify an array of ice core particles. Suggestions for an improved system to be deployed within a continuous flow analysis workflow are also presented

Binary Black Hole Mergers in the first Advanced LIGO Observing Run

The first observational run of the Advanced LIGO detectors, from September 12, 2015 to January 19, 2016, saw the first detections of gravitational waves from binary black hole mergers. In this paper we present full results from a search for binary black hole merger signals with total masses up to $100 M_\odot$ and detailed implications from our observations of these systems. Our search, based on general-relativistic models of gravitational wave signals from binary black hole systems, unambiguously identified two signals, GW150914 and GW151226, with a significance of greater than $5\sigma$ over the observing period. It also identified a third possible signal, LVT151012, with substantially lower significance, which has a 87% probability of being of astrophysical origin. We provide detailed estimates of the parameters of the observed systems. Both GW150914 and GW151226 provide an unprecedented opportunity to study the two-body motion of a compact-object binary in the large velocity, highly nonlinear regime. We do not observe any deviations from general relativity, and place improved empirical bounds on several high-order post-Newtonian coefficients. From our observations we infer stellar-mass binary black hole merger rates lying in the range $9-240 \mathrm{Gpc}^{-3} \mathrm{yr}^{-1}$. These observations are beginning to inform astrophysical predictions of binary black hole formation rates, and indicate that future observing runs of the Advanced detector network will yield many more gravitational wave detections

Künstliches feedback für oberschenkelamputierte; theoretische Analyse - Artificial feedback for transfemoral amputees: Theoretical analysis

Dieser Beitrag untersucht auf Basis von Modellen der menschlichen Wahrnehmung den Einfluss künstlichen sensorischen Feedbacks auf posturale Kontrolle und Gangsymmetrie von Oberschenkelamputierten. In der Standphase wird ein vereinfachtes, statisches neuromechanisches Modell verwendet, in der Schwungphase ein Erweitertes Kalman-Filter, das dynamische Effekte berücksichtigt. Die Simulation lässt den Schluss zu, dass Rückmeldung des Fußdruckpunktes während der Standphase die Wahrnehmung verbessern könnte, künstliches Feedback während der Schwungphase jedoch nicht von Vorteil ist. Eine klinische Fallstudie wäre nötig, um die in der Simulation beobachteten Effekte sensorischen Feedbacks in der praktischen Anwendung mit Amputierten zu uberprufenBiomechanical EngineeringMechanical, Maritime and Materials Engineerin

DEVELOPMENT OF A CHEMICALLY MODIFIED ELECTRODE BASED ON CARBON PASTE AND FUNCTIONALIZED SILICA-GEL FOR PRECONCENTRATION AND VOLTAMMETRIC DETERMINATION OF MERCURY(II)

A mercury-sensitive chemically modified electrode (CME) based on modified silica gel-containing carbon paste was developed. The functional group attached to the silica gel surface was 3-(2-thiobenzimidazolyl)propyl, which is able to complex mercury ions. This electrode was applied to the determination of mercury(II) ions in aqueous solution. The mercury was chemically preconcentrated on the CME prior to voltammetric determination by anodic stripping in the differential-pulse mode. A calibration graph covering the concentration range from 0.08 to 2 mg l-1 was constructed. The precision for six determinations of 0.122 and 0.312 mg l-1 Hg(II) was 3.2 and 2.9% (relative standard deviation), respectively. The detection limit for a 5-min preconcentration period was 0.013 mg l-1. A study for foreign ions was also made

A model for agent mobility and interaction.

As information infrastructure move towards open systems where agents come and go, new facilities are required so that these agents can take advantage of each other's functionalities. We need agent systems that can provide to newcomer agents a place and the right agent to interact with. Such functionality must cope with high rate of agent entrance, with high load of agents, with vanishing agents or nodes in the agent system. Given these requirements, agents are constantly facing a problem of deciding where to go and with whom to work with. These two decisions, pertaining to mobility and interaction, have been singled out as fundamental for every agent system. We present an algorithm targeted at these two decisions while it fulfils the aforementioned requirements

Contributions to adaptable agent societies.

The adoption of agents as utile companions faces the problem of conciliating the development of complex and intelligent functionalities with the requirements of autonomy mobility and adaptability. Our main focus will be on the agents adaptability. A hybrid agent architecture approach is proposed where a static component, which resides at the user's host and includes most of the intelligence and decision support capabilities, is complemented by a mobile component that is aimed at interacting with other agents. Some adaptation strategies, based on classical and fuzzy methodologies, are also discussed using as background scenario a trading market competitive environment with buyer and seller agents interacting in it