Automatic quality control in clinical (1) H MRSI of brain cancer.

MRSI grids frequently show spectra with poor quality, mainly because of the high sensitivity of MRS to field inhomogeneities. These poor quality spectra are prone to quantification and/or interpretation errors that can have a significant impact on the clinical use of spectroscopic data. Therefore, quality control of the spectra should always precede their clinical use. When performed manually, quality assessment of MRSI spectra is not only a tedious and time-consuming task, but is also affected by human subjectivity. Consequently, automatic, fast and reliable methods for spectral quality assessment are of utmost interest. In this article, we present a new random forest-based method for automatic quality assessment of (1) H MRSI brain spectra, which uses a new set of MRS signal features. The random forest classifier was trained on spectra from 40 MRSI grids that were classified as acceptable or non-acceptable by two expert spectroscopists. To account for the effects of intra-rater reliability, each spectrum was rated for quality three times by each rater. The automatic method classified these spectra with an area under the curve (AUC) of 0.976. Furthermore, in the subset of spectra containing only the cases that were classified every time in the same way by the spectroscopists, an AUC of 0.998 was obtained. Feature importance for the classification was also evaluated. Frequency domain skewness and kurtosis, as well as time domain signal-to-noise ratios (SNRs) in the ranges 50-75 ms and 75-100 ms, were the most important features. Given that the method is able to assess a whole MRSI grid faster than a spectroscopist (approximately 3 s versus approximately 3 min), and without loss of accuracy (agreement between classifier trained with just one session and any of the other labelling sessions, 89.88%; agreement between any two labelling sessions, 89.03%), the authors suggest its implementation in the clinical routine. The method presented in this article was implemented in jMRUI's SpectrIm plugin. Copyright © 2016 John Wiley & Sons, Ltd.

Geochemistry, physical properties, diatom abundance and datums of ODP Site 186-1150 and Hole 186-1151A

Detection of climate response to orbital forcing during Cenozoic long-term global cooling is a key to understanding the behavior of Earth's icehouse climate. Sedimentary rhythm, which is a rhythmic or cyclic variation in the sequence of sediments and sedimentary rocks, is useful for quantitative reconstruction of Earth's evolution during geological time. In this study, we attempt to (1) identify sources of natural gamma ray (NGR) emissions of core recovered during Ocean Drilling Program (ODP) Leg 186 by analyses of physical properties, major element concentrations, diatom abundances, and total organic carbon contents, (2) integrate whole-core NGR intensity of recovered core with wireline logging NGR measurements in order to construct a continuous sedimentary sequence, and (3) discuss changes in the NGR signal in the time domain. This attempt gives us preliminary information to discuss climate stability in relation to orbital forcing thorough geologic time. NGR values are obtained mainly by indirectly measuring the amount of terrigenous minerals including potassium and related elements in the sediments. NGR intensity is also affected by high porosity, which in these sediments was related to the amount of diatom valves. NGR signals might be a proxy of the intensity of the East Asian monsoon off Sanriku. A continuous sedimentary record was constructed by integration of the whole-core NGR intensity measured in sediments obtained from the drilled holes with that measured directly in the borehole by wireline logging, then using a stratigraphic age model to convert to a time series covering 1.3-9.7 Ma with a short break at ~5 Ma. High sedimentation rate (H) stages were identified in the sequence, related to intervals of low-amplitude precession and eccentricity variations. The transition of the dominant periodicities through the four H stages may correlate to major shifts in the climate system, including the onset of major Northern Hemisphere glaciation, the initial stage of the East Asian monsoon intensification, and the onset of the East Asian monsoon with uplift of the Himalayas and the Tibetan Plateau.

Calculation Methodology and Fabrication Procedures for Particle Accelerator Strip-Line Kickers: Application to the CTF3 Combiner Ring Extraction Kicker and TL2 Tail Clippers

A particle accelerator is any device that, using electromagnetic fields, is able to communicate energy to charged particles (typically electrons or ionized atoms), accelerating and/or energizing them up to the required level for its purpose. The applications of particle accelerators are countless, beginning in a common TV CRT, passing through medical X-ray devices, and ending in large ion colliders utilized to find the smallest details of the matter. Among the other engineering applications, the ion implantation devices to obtain better semiconductors and materials of amazing properties are included. Materials supporting irradiation for future nuclear fusion plants are also benefited from particle accelerators. There are many devices in a particle accelerator required for its correct operation. The most important are the particle sources, the guiding, focalizing and correcting magnets, the radiofrequency accelerating cavities, the fast deflection devices, the beam diagnostic mechanisms and the particle detectors. Most of the fast particle deflection devices have been built historically by using copper coils and ferrite cores which could effectuate a relatively fast magnetic deflection, but needed large voltages and currents to counteract the high coil inductance in a response in the microseconds range. Various beam stability considerations and the new range of energies and sizes of present time accelerators and their rings require new devices featuring an improved wakefield behaviour and faster response (in the nanoseconds range). This can only be achieved by an electromagnetic deflection device based on a transmission line. The electromagnetic deflection device (strip-line kicker) produces a transverse displacement on the particle beam travelling close to the speed of light, in order to extract the particles to another experiment or to inject them into a different accelerator. The deflection is carried out by the means of two short, opposite phase pulses. The diversion of the particles is exerted by the integrated Lorentz force of the electromagnetic field travelling along the kicker. This Thesis deals with a detailed calculation, manufacturing and test methodology for strip-line kicker devices. The methodology is then applied to two real cases which are fully designed, built, tested and finally installed in the CTF3 accelerator facility at CERN (Geneva). Analytical and numerical calculations, both in 2D and 3D, are detailed starting from the basic specifications in order to obtain a conceptual design. Time domain and frequency domain calculations are developed in the process using different FDM and FEM codes. The following concepts among others are analyzed: scattering parameters, resonating high order modes, the wakefields, etc. Several contributions are presented in the calculation process dealing specifically with strip-line kicker devices fed by electromagnetic pulses. Materials and components typically used for the fabrication of these devices are analyzed in the manufacturing section. Mechanical supports and connexions of electrodes are also detailed, presenting some interesting contributions on these concepts. The electromagnetic and vacuum tests are then analyzed. These tests are required to ensure that the manufactured devices fulfil the specifications. Finally, and only from the analytical point of view, the strip-line kickers are studied together with a pulsed power supply based on solid state power switches (MOSFETs). The solid state technology applied to pulsed power supplies is introduced and several circuit topologies are modelled and simulated to obtain fast and good flat-top pulses.

A Fluctuation-Dissipation Model for Electrical Noise

This paper shows that today’s modelling of electrical noise as coming from noisy resistances is a non sense one contradicting their nature as systems bearing an electrical noise. We present a new model for electrical noise that including Johnson and Nyquist work also agrees with the Quantum Mechanical description of noisy systems done by Callen and Welton, where electrical energy fluctuates and is dissipated with time. By the two currents the Admittance function links in frequency domain with their common voltage, this new model shows the connection Cause-Effect that exists between Fluctuation and Dissipation of energy in time domain. In spite of its radical departure from today’s belief on electrical noise in resistors, this Complex model for electrical noise is obtained from Nyquist result by basic concepts of Circuit Theory and Thermo- dynamics that also apply to capacitors and inductors.

Using the Spectrum Analyzer as an Educational Tool for Mobile Communications

Application of the spectrum analyzer for illustrating several concepts associated with mobile communications is discussed. Specifically, two groups of observable features are described. First, time variation and frequency selectivity of multipath propagation can be revealed by carrying out simple measurements on commercial-network GSM and UMTS signals. Second, the main time-domain and frequency-domain features of GSM and UMTS radio signals can be observed. This constitutes a valuable tool for teaching mobile communication courses.

Revisiting the Classics to recover the Physical Sense in electrical noise

This paper shows a physically cogent model for electrical noise in resistors that has been obtained from Thermodynamical reasons. This new model derived from the works of Johnson and Nyquist also agrees with the Quantum model for noisy systems handled by Callen and Welton in 1951, thus unifying these two Physical viewpoints. This new model is a Complex or 2-D noise model based on an Admittance that considers both Fluctuation and Dissipation of electrical energy to excel the Real or 1-D model in use that only considers Dissipation. By the two orthogonal currents linked with a common voltage noise by an Admittance function, the new model is shown in frequency domain. Its use in time domain allows to see the pitfall behind a paradox of Statistical Mechanics about systems considered as energy-conserving and deterministic on the microscale that are dissipative and unpredictable on the macroscale and also shows how to use properly the Fluctuation-Dissipation Theorem.

Optimization of a label-free biosensor vertically characterized based on a periodic lattice of high aspect ratio SU-8 nano-pillars with a simplified 2D theoretical model

We have recently demonstrated a biosensor based on a lattice of SU8 pillars on a 1 μm SiO2/Si wafer by measuring vertically reflectivity as a function of wavelength. The biodetection has been proven with the combination of Bovine Serum Albumin (BSA) protein and its antibody (antiBSA). A BSA layer is attached to the pillars; the biorecognition of antiBSA involves a shift in the reflectivity curve, related with the concentration of antiBSA. A detection limit in the order of 2 ng/ml is achieved for a rhombic lattice of pillars with a lattice parameter (a) of 800 nm, a height (h) of 420 nm and a diameter(d) of 200 nm. These results correlate with calculations using 3D-finite difference time domain method. A 2D simplified model is proposed, consisting of a multilayer model where the pillars are turned into a 420 nm layer with an effective refractive index obtained by using Beam Propagation Method (BPM) algorithm. Results provided by this model are in good correlation with experimental data, reaching a reduction in time from one day to 15 minutes, giving a fast but accurate tool to optimize the design and maximizing sensitivity, and allows analyzing the influence of different variables (diameter, height and lattice parameter). Sensitivity is obtained for a variety of configurations, reaching a limit of detection under 1 ng/ml. Optimum design is not only chosen because of its sensitivity but also its feasibility, both from fabrication (limited by aspect ratio and proximity of the pillars) and fluidic point of view. (© 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)

Simulation Model for Sea Clutter in Airborne Radars

This paper presents the architecture and the methods used to dynamically simulate the sea backscatter of an airborne radar operating in a medium repetition frequency mode (MPRF). It offers a method of generating a sea backscatter signal which fulfills the intensity statistics of real clutter in time domain, spatial correlation and local Doppler spectrum of real data. Three antenna channels (sum, guard and difference) and their cross-correlation properties are simulated. The objective of this clutter generator is to serve as the signal source for the simulation of complex airborne pulsed radar signal processors

A Light-Weight On-Chip Monitoring Network for Dynamic Adaptation and Calibration

Current nanometer technologies suffer within-die parameter uncertainties, varying workload conditions, aging, and temperature effects that cause a serious reduction on yield and performance. In this scenario, monitoring, calibration, and dynamic adaptation become essential, demanding systems with a collection of multi purpose monitors and exposing the need for light-weight monitoring networks. This paper presents a new monitoring network paradigm able to perform an early prioritization of the information. This is achieved by the introduction of a new hierarchy level, the threshing level. Targeting it, we propose a time-domain signaling scheme over a single-wire that minimizes the network switching activity as well as the routing requirements. To validate our approach, we make a thorough analysis of the architectural trade-offs and expose two complete monitoring systems that suppose an area improvement of 40% and a power reduction of three orders of magnitude compared to previous works.

Dynamic Analysis of high Speed Railway Traffic Loads on Ballasted Track

This paper reports the studies carried out to develop and calibrate the optimal models for the objectives of this work. In particular, quarter bogie model for vehicle, rail-wheel contact with Lagrangian multiplier method, 2D spatial discretization were selected as the optimal decisions. Furthermore, the 3D model of coupled vehicle-track also has been developed to contrast the results obtained in the 2D model. The calculations were carried out in the time domain and envelopes of relevant results were obtained for several track profiles and speed ranges. Distributed elevation irregularities were generated based on power spectral density (PSD) distributions. The results obtained include the wheel-rail contact forces, forces transmitted to the bogie by primary suspension. The latter loads are relevant for the purpose of evaluating the performance of the infrastructure

Determination of suitable irrigation lengths and intervals using capacitance humidity sensors for a sandy soil

production, during the summer of 2010. This farm is integrated at the Spanish research network for the sugar beet development (AIMCRA) which regarding irrigation, focuses on maximizing water saving and cost reduction. According to AIMCRA 0 s perspective for promoting irrigation best practices, it is essential to understand soil response to irrigation i.e. maximum irrigation length for each soil infiltration capacity. The Use of Humidity Sensors provides foundations to address soil 0 s behavior at the irrigation events and, therefore, to establish the boundaries regarding irrigation length and irrigation interval. In order to understand to what extent farmer 0 s performance at Tordesillas farm could have been potentially improved, this study aims to address suitable irrigation length and intervals for the given soil properties and evapotranspiration rates. In this sense, several humidity sensors were installed: (1) A Frequency Domain Reflectometry (FDR) EnviroScan Probe taking readings at 10, 20, 40 and 60cm depth and (2) different Time Domain Reflectometry (TDR) Echo 2 and Cr200 probes buried in a 50cm x 30cm x 50cm pit and placed along the walls at 10, 20, 30 and 40 cm depth. Moreover, in order to define soil properties, a textural analysis at the Tordesillas Farm was conducted. Also, data from the Tordesillas meteorological station was utilized.

On-chip Monitoring: A Light-Weight Interconnection Network Approach

Current nanometer technologies are subjected to several adverse effects that seriously impact the yield and performance of integrated circuits. Such is the case of within-die parameters uncertainties, varying workload conditions, aging, temperature, etc. Monitoring, calibration and dynamic adaptation have appeared as promising solutions to these issues and many kinds of monitors have been presented recently. In this scenario, where systems with hundreds of monitors of different types have been proposed, the need for light-weight monitoring networks has become essential. In this work we present a light-weight network architecture based on digitization resource sharing of nodes that require a time-to-digital conversion. Our proposal employs a single wire interface, shared among all the nodes in the network, and quantizes the time domain to perform the access multiplexing and transmit the information. It supposes a 16% improvement in area and power consumption compared to traditional approaches.

Statistical Machine Learning for Automatic Assessment of Physical Activity Intensity Using Multi-axial Accelerometry and Heart Rate

This work explores the automatic recognition of physical activity intensity patterns from multi-axial accelerometry and heart rate signals. Data collection was carried out in free-living conditions and in three controlled gymnasium circuits, for a total amount of 179.80 h of data divided into: sedentary situations (65.5%), light-to-moderate activity (17.6%) and vigorous exercise (16.9%). The proposed machine learning algorithms comprise the following steps: time-domain feature definition, standardization and PCA projection, unsupervised clustering (by k-means and GMM) and a HMM to account for long-term temporal trends. Performance was evaluated by 30 runs of a 10-fold cross-validation. Both k-means and GMM-based approaches yielded high overall accuracy (86.97% and 85.03%, respectively) and, given the imbalance of the dataset, meritorious F-measures (up to 77.88%) for non-sedentary cases. Classification errors tended to be concentrated around transients, what constrains their practical impact. Hence, we consider our proposal to be suitable for 24 h-based monitoring of physical activity in ambulatory scenarios and a first step towards intensity-specific energy expenditure estimators